Habitat-based forage productivity and grazing dynamics in a heterogeneous wetland system

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However, their spatially heterogeneous structure and seasonal hydrological dynamics present challenges for the sustainable management of grazing, particularly in long-standing free-grazing systems. Objectives: This study aimed to evaluate forage production and grazing dynamics in the habitat-based Kızılırmak Delta wetland, providing management-oriented information for the sustainable use of wetlands under free-grazing conditions. Methods: Research was conducted in four different habitat classes between 2022 and 2023: permanent wet meadows, coastal dunes/sandy grasslands, grazed permanent pastures and seasonally flooded pastures. Grazing occurred naturally under long-standing free-range conditions, with no experimental intervention on the animals. Botanical composition, plant species richness and plant quality grade were determined each year prior to the initial harvest. Dry matter yield, grazing capacity, grazing area per buffalo and grazing grade were calculated monthly throughout the grazing season. The data were analysed using analysis of variance (ANOVA), and spatiotemporal patterns were visualised using hierarchical clustering heatmaps. Key results: Significant habitat-related differences were identified in terms of botanical composition, species richness and plant quality grade (P ≤ 0.01). Seasonally flooded pastures exhibited the highest average dry matter yield (9.23 t/ha), grazing capacity (3,100 head) and lowest grazing area per buffalo (1.20 ha/head). Monthly analyses revealed strong seasonal variability: the highest forage availability occurred at the start of the grazing season in accessible habitats. Heatmap analyses clearly distinguished between habitat classes based on productivity and grazing indicators. Conclusion: Forage production and grazing pressure in the Kızılırmak Delta are primarily driven by habitat characteristics and seasonal hydrological processes. Implications and impacts: Habitat-based, hydrologically sensitive grazing management can increase grazing efficiency while preserving the integrity of the ecosystem in open-grazed wetland systems, thus supporting both sustainable livestock production and wetland conservation. wetland grazing management grazing capacity water buffalo habitat Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Highlights Habitat-based analysis revealed strong spatial heterogeneity in forage productivity within the Kızılırmak Delta wetland. Seasonally flooded pastures showed the highest dry matter yield and grazing capacity despite their limited surface area. Monthly assessments demonstrated pronounced seasonal shifts in forage availability driven by hydrological dynamics. Grazing capacity and area per buffalo varied substantially among habitat types, indicating different management thresholds. Habitat-oriented and hydrology-aware grazing strategies can enhance precision management in wetland grazing systems. IMPACT This study makes a contribution to precision agriculture by quantifying forage productivity and grazing pressure indicators within a heterogeneous wetland system on a habitat-specific basis. This provides spatially explicit information to support data-driven pasture planning and land use decisions. By linking hydrological variability with forage availability, the results inform adaptive, site-specific management strategies that enhance the efficiency with which resources are used while maintaining the integrity of the ecosystem. Introduction Wetlands occupy only 3–5% of the Earth’s terrestrial surface (Niu et al., 2024 ). Despite this limited coverage, they serve critical ecological functions in regulating regional climates, supplying water resources, sustaining biodiversity, and providing habitats for endemic and endangered species (Sterner et al., 2020 ; Bai et al., 2020 ; Leonardi and Dai, 2022 ; Mei et al., 2024 ; Bu et al., 2025 ). Functioning as transitional zones between terrestrial and aquatic systems, wetlands offer breeding, feeding, and growth opportunities for diverse wildlife species (Yağmur et al., 2019 ; Jafarzadeh et al., 2022 ). They are integral to global Earth surface processes—such as the atmosphere and hydrosphere—and remain highly sensitive to environmental change and anthropogenic pressures (Li et al., 2021 ; Bai and Wang, 2024 ). The ecological services of wetlands are wide-ranging, encompassing erosion control, flood regulation, pollution reduction, climate moderation, wastewater treatment, biodiversity conservation, groundwater recharge, and wildlife support (Mahdianpari et al., 2020; Cui et al., 2021 ; Guo et al., 2021 ; Zivec et al., 2023 ). Owing to this multitude of benefits, wetlands are often described as the “kidneys of nature” (Mahdavi et al., 2018 ). Nevertheless, recent assessments by the United Nations Environment Programme and the Ramsar Convention indicate that nearly 35% of global wetlands have been lost over the past five decades, posing a severe threat to biodiversity (Convention on Wetlands, 2021 ). In Turkey, wetlands are regarded as strategic ecosystems for sustaining livestock production. Their rich vegetation and high productivity support multiple levels of the food chain and contribute substantially to rural economies through forage yield and grazing capacity (Gül, 2020 ). The Kızılırmak Delta, one of Turkey’s largest and most ecologically significant wetland systems, exemplifies this multifunctionality. The approximately 56,000-hectare Kızılırmak delta wetlands, located along the Black Sea coast, have Ramsar site status, with around 11,000 hectares designated as wetlands of international ecological importance (Demirkalp et al., 2010 ). In 2016, the wetlands were added to the UNESCO World Heritage Sites tentative list ( http://whc.unesco.org/en/tentativelists/6125/ ). Hosting around 354 bird species—more than half of Turkey’s avifauna—it serves as a critical refuge for migratory and resident waterfowl. Simultaneously, its expansive pastures and reedbeds provide a vital forage base for the region’s traditional water buffalo husbandry (Anon, 2021). The ecological functioning of the Kızılırmak Delta is governed not only by its overall extent, but also by pronounced habitat heterogeneity driven by hydrological gradients and soil moisture regimes. Within the delta, grazing landscapes consist of multiple heterogeneous habitat types that differ markedly in terms of vegetation structure, forage productivity and seasonal accessibility ((Boz, 2025 ; Uzun et al. 2024 ; Sürmen, 2021 ). These include permanent wet meadows characterised by persistently high soil moisture; coastal dunes and sandy grasslands with low water-holding capacity; long-grazed permanent pastures shaped by sustained grazing pressure; and seasonally flooded pastures that only become accessible after the water recedes in summer (Yavuz, 2011 ). This differentiation of habitats plays a decisive role in determining the spatial patterns of forage availability, grazing intensity and ecological resilience within the delta. Water buffaloes ( Bubalus bubalis ) are particularly well adapted to wetland environments due to their physiological characteristics, including thicker skin and fewer sweat glands compared to cattle, which limit their heat tolerance (Sambraus and Spannl-Flor, 2005 ). Consequently, wetlands offer a favorable habitat for these animals (Krawczynski et al., 2008 ). Historically, buffalo husbandry has been central to the cultural identity of the Kızılırmak Delta. Although national buffalo numbers have declined since the 1980s, the delta remains a stronghold for the species. Yılmaz and Kara ( 2019 ) underscore the delta’s pivotal role in ensuring the future of buffalo farming in Turkey, emphasizing the importance of aligning livestock sustainability with wetland management strategies. Beyond their role in food production, buffaloes act as ecological engineers in shaping wetland habitats. Their grazing and wallowing activities reduce dense reed stands, thereby creating feeding and nesting opportunities for waterfowl (Anonymous, 2021 ). This interaction exemplifies a reciprocal ecological relationship in which livestock activity supports biodiversity while benefiting from wetland forage resources. In particular, the non-selective grazing behavior of buffaloes promotes a balanced distribution of legumes and grasses, thereby sustaining plant diversity (Fürész et al., 2023). However, the ecological outcomes of grazing are strongly influenced by the specific characteristics of the habitat in question. In hydrologically dynamic habitats, such as seasonally flooded pastures, forage production and grazing capacity can increase rapidly following the recession of water. In contrast, structurally fragile habitats, such as coastal dunes and sandy grasslands, are more susceptible to degradation under sustained grazing pressure ((Rüzgar and Gümü, 2025; Arıman et al. 2024 ; Berndt et al. 2019 ). This spatial variability highlights the importance of evaluating grazing impacts and forage productivity within a habitat-based framework, rather than treating wetlands as uniform grazing systems. Moderate buffalo grazing contributes to ecosystem biodiversity by reducing vegetation density. However, overgrazing can lead to soil erosion and biodiversity loss, highlighting the need for careful pasture management (Altıntaş et al., 2018 ). Therefore, sustainable grazing plans and collaborative pasture management practices are critical to balancing livestock productivity with biodiversity conservation. Forage yield is a key indicator of pasture conditions, use, and environmental assessment (Ali et al., 2016 ). Accordingly, accurate assessment of pasture productivity and carrying capacity is vital for sustainable livestock management and should be prioritized by both policymakers and farmers (Liu et al., 2023 ; Morais et al., 2025 ). This study addresses the existing knowledge gap by providing a habitat-based assessment of forage production and grazing dynamics in the Kızılırmak Delta. Through the joint analysis of dry matter yield, grazing capacity, grazing area per buffalo and grazing intensity across four ecologically distinct wetland habitats under long-established free-grazing conditions, the study provides a fresh perspective on the regulation of grazing systems in complex wetland landscapes by hydrological variability and habitat structure. The findings provide evidence that can inform the development of adaptive, habitat-specific grazing strategies that reconcile forage use with the conservation of wetland ecosystem integrity. Materials and methods Study area This study was conducted between 2022 and 2023 in the Kızılırmak Delta Wetland, located in Samsun Province in northern Turkey. The approximate central coordinates of the study area are 41°65′07″ N latitude and 36°07′47″ E longitude. Spanning approximately 11,000 hectares, the delta is an extensive wetland complex comprising coastal zones, river channels, lakes, reed beds, marshes, natural meadows, rangelands, floodplain forests, dune systems and surrounding agricultural lands. Due to its significant ecological value and biodiversity, the Kızılırmak Delta has been designated a Wetland of International Importance under the Ramsar Convention (Figure 1). Between April and November each year, approximately 7.000-10.000 water buffalo owned by local farmers graze freely across the delta. The area available for grazing is estimated to be around 2.500 hectares. In the present study, the movements of the buffalo and the intensity of grazing were not experimentally controlled or manipulated. Instead, all measurements were conducted under existing free-ranging grazing conditions in order to realistically reflect the forage production potential of the delta under current management practices. Sampling sites were classified into four main ecological units based on hydrological conditions and dominant vegetation. A. Permanent Wet Grasslands: These grasslands are characterised by consistently high soil moisture and surface water in some areas for a significant portion of the year. They are typically associated with hydromorphic soils. The vegetation consists of dense grassland communities with a variety of moisture-tolerant grasses and legumes. These habitats provide high biomass production and remain suitable for grazing over extended periods, particularly during the summer months. B. Coastal Dunes/Sandy Grasslands: These habitats are located between the coastal zone and adjacent lakes, and are characterised by sandy soils with a low water-holding capacity. The vegetation is generally made up of short, mostly annual species with ruderal characteristics, resulting in relatively low forage productivity. From a grazing perspective, coastal dunes and sandy grasslands are considered relatively fragile ecosystems with limited carrying capacity. C. Grazed permanent pastures: These encompass areas that have been subjected to regular grazing over many years, exhibiting moderate soil moisture conditions and vegetation characteristics. Plant communities are dominated by grass and legume species that can tolerate grazing, reflecting a relatively stable balance between forage production and utilisation under prolonged grazing pressure. D. Seasonally flooded pastures: These habitats are partially or fully submerged during spring and the early part of summer. As the water recedes from midsummer onwards, the land becomes accessible for grazing. After the waters have receded, the vegetation is typically dominated by Paspalum species, and these habitats demonstrate high forage production potential during the summer. Seasonally flooded pastures are among the most dynamic and productive components of the grazing system in the delta. Each ecological unit comprised multiple sampling sites, and the total area represented by each habitat class is summarized in Table 1. Representative field photographs of each ecological unit are provided in Figure 2 to facilitate visual interpretation of landscape-level differences among habitat types. Climate Characteristic The Kızılırmak Delta Wetland has a "semi-humid" climate, according to the classification compiled by the National Directorate General of Meteorogy (MGM) and based on the Thornthwaite method. According to the long-term average for the region, the total rainfall is 720 mm and the average temperature is 14.6 °C ( Figure 3 ). In the second year of the research, there was almost twice as much precipitation in the March-May and June-August periods compared to the first year. While the average temperature between January and March of the first year was 6.5 °C, this value was determined as 8.1 °C in the second year. Therefore, it was observed that there were significant differences in temperature and precipitation amounts between seasons and years. Data collection and analysis Botanical Composition The botanical composition was determined during the first week of June, which coincided with the flowering period of the plants in the three areas (excluding the Seasonally Flooded Pastures) in both years. The Seasonally Flooded Pastures were not subject to botanical composition determination during this period as they were flooded. Over the following months, this area became completely covered in Paspalum species. Botanical composition was determined according to the weight percentage of each plant species within the total composition. To determine dry matter yield, the harvested plants were separated by species, dried and weighed. Then, the weight of each species was divided by the total weight to determine its proportion in the botanical composition (Taşdelen and Yazıcı, 2022). Plant Quality Grade (PQG) The plant quality grade (PQG) of forage was determined to evaluate the overall quality of the grazing resources in the study area. The PQG was calculated as: Quality scores of plant species were obtained from Gökkuş et al. (2000), Babalık (2008), Aydın and Uzun (2002), and Karakuş (2014). Forage quality was categorized as: very good (8.1-10.0), good (7.1-8.0), moderate (4.1-6.0), poor (2.1-4.0), and very poor (0.0-2.0). The above-mentioned observations were made in both years only before the first harvest (in June) and in areas that remained continuously dry. Dry matter Yield In order to determine the forage production potential of the Kızılırmak Delta, 80 iron cages, each measuring 50 x 70 centimetres, were placed in grazing areas. Data were collected from 42 cages over a two-year period; some cages were excluded from the study due to damage or collapse. The cages were distributed as follows: 9 in permanent wet meadows, 9 in coastal dunes/sandy grasslands, 6 in grazed permanent pastures and 18 in seasonally flooded pastures. Forage harvesting was carried out using 0.12 m² (0.3 x 0.4 m) squares inside and outside the cages. Sampling began in June each year and was repeated at approximately 30-day intervals until November (six harvests per year). The harvested biomass was oven-dried at 105 °C until a constant weight was reached and then weighed to determine the dry matter yield (Töngel, 2018). To determine the degree of grazing in the grazed areas of the delta, grazing densities were calculated using in-cage and out-of-cage feed yield values (Figure 4). A grazing degree of ~50% indicates sustainable utilization, while up to 70% may be acceptable in areas with favorable precipitation (Aydın and Uzun, 2002). Accordingly, 70% was adopted as the threshold for appropriate grazing in this study. Grazing Capacity and Grazing Area per Buffalo: The grazing capacity (GC) and pasture area required per buffalo were estimated using the following formulas (Çaçan and Balkan, 2021): * In these calculations, grazing capacity was standardized using a cattle unit (CU) concept, where a 500-kg animal was defined as 1 CU for comparative purposes. In the Kızılırmak Delta, grazing is predominantly carried out by female water buffalo, with an average live body weight of approximately 375 kg, corresponding to 0.75 CU. Based on this average body weight, daily dry matter consumption was estimated as 9 kg DM per animal, assuming a utilization factor of 70%. Statistical Analysis The data obtained were analysed using the SAS 9.0 statistical software package. Prior to performing ANOVA, the data were tested for normality using the Shapiro–Wilk test and for homogeneity of variance using the Levene test. Once these assumptions had been confirmed, one-way ANOVA was applied. Statistical differences between all the means were determined using Duncan's multiple range test. Hierarchical heat mapping was performed using the RStudio software environment (4.4.2) (https://posit.co/products/open-source/rstudio/?sid=1/, accessed 10 October 2025). The heatmap package was used for heatmap visualisations. Results Botanical Composition In both study years, the botanical composition was determined during the first week of June, which coincided with the flowering period of the dominant plant species. A total of 115 plant species were identified in the habitats. The dominant species are given in Table 2, while all the other species are listed in Supplementary Table 1. Botanical composition could not be assessed in seasonally flooded pasture habitats during the measurement period, as these areas were completely submerged at the time of sampling. Over the following months, this habitat was almost entirely dominated by Paspalum species, which are the primary source of forage for grazing animals within the delta. Based on two-year averages, the proportions of legumes, grasses and forbs differed significantly between habitats (P ≤ 0.01; Table 3). The highest legume proportions were found in permanent wet meadows (29.78%) and grazed permanent pastures (26.56%), while significantly lower values were recorded in coastal dunes and sandy grasslands (18.53%). Similarly, grass proportions were highest in permanent wet meadows (55.78%) and grazed permanent pastures (55.59%), while coastal dunes and sandy grasslands had substantially lower grass cover (40.17%). Conversely, forb proportions were markedly higher in coastal dunes and sandy grasslands, accounting for 41.30% of the botanical composition. According to the combined analysis of variance, both year and habitat effects were statistically significant for legume, grass and forb proportions (P ≤ 0.01)(Table 3). Number of plants The number of plant species differed significantly among habitat types (P ≤ 0.01; Table 3). Based on two-year averages, the highest species richness was recorded in coastal dunes and sandy grasslands (27.83 species), while the lowest value was observed in permanent wet meadows (14.50 species). The results of the combined analysis indicated that year and habitat had a strong and significant effect on the number of plants (P ≤ 0.01), whereas the effects year × habitat interaction was not statistically significant (Table 3). Plant quality grade There was a significant difference in plant quality grade among habitat types (P ≤ 0.01; Table 3). Based on two-year mean values, the highest grade was observed in permanent wet meadows (6.04%), while the lowest was recorded in coastal dunes and sandy grasslands (3.88%). According to the combined analysis of variance, both year and habitat had a significant effect on plant quality grade (P ≤ 0.05), whereas the interaction between year and habitat was not statistically significant (Table 3). Dry matter yield Statistically significant differences in dry matter yield were observed at the P < 0.05 level for the years and months, and at the P < 0.01 level for the ecological unit and the ecological unit x month interaction (Table 4). Dry matter yield reached its maximum monthly value in June in all ecological units (except seasonally flooded pastures), decreased significantly from July onwards and remained at relatively low levels during the autumn months (Table 4). Based on two-year averages, seasonally flooded pastures had the highest total dry matter yield (9.23 t ha -1 ), followed by grazed permanent pastures (8.67 t ha -1 ) and permanent wet meadows (8.56 t ha -1 ). By contrast, the lowest dry matter yield (5.35 t ha⁻¹) was found in coastal dunes and sandy grasslands (Table 5). Dry matter yield peaked in June across all ecological units, then decreased substantially from July onwards, stabilising at lower, more uniform levels between August and November ( Figure 5). The hierarchical clustering heatmap (Figure 6) clearly shows a separation of seasonally flooded pastures from the other ecological units in terms of dry matter yield. Meanwhile, coastal dunes and sandy grasslands form a separate cluster characterised by consistently low yield values. Grazing capacity Grazing capacity was statistically significantly affected by year, month, ecological unit, and month x ecological unit interaction (Table 4). Monthly data showed that grazing capacity was at its maximum in June, declining gradually during the summer and autumn months (Table 4). The highest mean grazing capacity was recorded in seasonally flooded pastures (3.100 head), followed by coastal dunes and sandy grasslands (2.640 head) and grazed permanent pastures (1,888 head). Permanent wet meadows exhibited the lowest mean grazing capacity (496 head) (Table 5). Across all ecological units, grazing capacity peaked in June, decreasing progressively as the grazing season advanced to reach more limited levels in autumn (Figure 5). Hierarchical clustering revealed that seasonally flooded pastures formed a distinct, dominant cluster, whereas permanent wet meadows grouped separately due to their consistently lower grazing capacity values (Figure 6). Grazing area per buffalo The grazing area per buffalo differed significantly according to the year, month, ecological unit and year × month interaction (Table 4). On a monthly basis, the grazing area per buffalo was at its lowest in June, increasing towards its highest values in August and September (Table 4). Based on two-year averages, the smallest grazing area per buffalo was observed in seasonally flooded pastures (1.20 ha -1 per buffalo), followed by grazed permanent pastures (2.62 ha -1 per buffalo) and permanent wet meadows (2.76 ha -1 per buffalo). The largest grazing area requirement per buffalo was observed in coastal dunes and sandy grasslands (4.80 ha -1 per head) (Table 5). Across ecological units, the grazing area per buffalo reached its minimum in June and its maximum in August–September (Figure 5). Clustering analysis showed that coastal dunes and sandy grasslands were clearly separated by their high area requirements, whereas seasonally flooded pastures formed a distinct cluster characterised by low grazing area per buffalo values (Figure 6). Grazing Degree Grazing degree was strongly influenced by year, month, ecological unit and year × month interaction (Table 4). Monthly patterns indicated that grazing degree was highest in June and became more balanced toward late summer and autumn (Table 4). The highest mean grazing degree was recorded across ecological units in permanent wet meadows (70%) and grazed permanent pastures (69%). Seasonally flooded pastures exhibited intermediate grazing degree values (63%), while coastal dunes and sandy grasslands exhibited the lowest mean grazing degree (58%) (Table 5). Grazing degree peaked at the beginning of the grazing season, stabilising at lower, more uniform levels by late summer and autumn (Figure 5). Permanent wet meadows and grazed permanent pastures displayed similar clustering patterns, while coastal dunes and sandy grasslands formed a separate group characterised by consistently lower grazing degree values (Figure 6). Discussion The findings of this study demonstrate that the ecological functioning of the grazing system in the Kızılırmak Delta varies significantly between different habitats. The four main habitat types identified in the delta — permanent wet meadows, coastal dunes and sandy grasslands, grazed permanent pastures and seasonally flooded pastures — fulfil distinct ecological roles in terms of botanical composition, forage production and grazing potential. These results clearly indicate that wetlands should be managed as habitat-specific units with differing responses to grazing, rather than as homogeneous grazing landscapes. From a botanical perspective, although the proportion of legumes remained relatively high in permanent wet meadows, a general decline in legume abundance was observed across all habitats when two-year averages were considered. This pattern corroborates previous findings that legumes are among the most sensitive functional plant groups in wetland grasslands, particularly in response to grazing pressure and interannual climatic variability (Tegegn et al., 2010). Given legumes' well-established role in enhancing forage nutritive value and improving animal performance (Wolkaro & Tesfaye, 2025), the observed reduction in legume abundance could indicate a decline in forage quality in wetland grazing systems. By contrast, the growing dominance of grasses, particularly in seasonally flooded pastures and permanent wet meadows, is a result of the combined effects of habitat hydrology and the relatively indiscriminate grazing behaviour of water buffalo. Although grass dominance promotes biomass continuity and yield stability, it is also linked to a slight decline in forage quality compared to legume-rich pastures, due to generally lower crude protein content and digestibility (Wrobel et al., 2025). Similar patterns have been reported in wetland grazing systems in Hungary, where water buffalo grazing has promoted the growth of economically valuable grasses and legumes while suppressing invasive species (Fűrész et al., 2023). The results obtained from the Kızılırmak Delta are consistent with these observations, suggesting that, when habitat-specific conditions are taken into account, buffalo grazing can steer plant communities towards more balanced and functionally resilient assemblages. The results relating to rangeland quality grade revealed significant spatial variations between different habitats. Permanent wet meadows and seasonally flooded pastures consistently fell within the 'good' quality class in both study years, indicating a relatively sustainable balance between botanical composition and grazing pressure. Conversely, the lower rangeland quality grades observed in fragile habitats such as coastal dunes and sandy grasslands suggest these areas are more sensitive to soil limitations and combined stressors, including grazing pressure and seasonal drought. These findings suggest that rangeland quality grade is not solely dependent on stocking density, but is also heavily influenced by micro-ecological conditions and the inherent characteristics of the habitat (Niu et al., 2025). The results regarding number of plants further emphasise the critical role of habitat heterogeneity in maintaining biodiversity within wetland ecosystems. The higher species richness observed in permanent wet meadows and grazed permanent pastures highlights the structural complexity and ecological resilience of these habitats. However, greater species richness does not necessarily equate to increased functional stability or rangeland balance. As has been reported in other wetland and rangeland ecosystems, the relationship between number of plants and ecosystem functioning is not linear (Li et al., 2024; Eldridge et al., 2016; Zhang et al., 2025). Selective grazing by water buffalo, favouring graminoids and legumes while less palatable species persist within the community, is a key mechanism that may explain why species richness remains relatively high in certain habitats (Tsiobani et al., 2019). Clear differences were observed among habitat classes in terms of dry matter yield, grazing capacity and grazing area per buffalo. Although seasonally flooded pastures occupy a relatively small surface area, they were found to be the habitat class with the lowest grazing area per buffalo due to their high dry matter yield and grazing capacity. In contrast, habitats such as coastal dunes and sandy grasslands had lower production intensity, requiring substantially more grazing area per animal. These findings are consistent with previous studies demonstrating that grazing efficiency in wetlands is largely governed by the hydrological regime (Vega et al., 2022; Zhuo et al., 2024). Perrino et al. (2021) reported that changes in the water regime directly influence pasture productivity in Mediterranean wetlands, emphasising that appropriate stocking levels can support both habitat conservation and high forage yields. However, O’Dea et al. (2022) observed that hydrological alterations in certain wetland ecosystems can result in higher animal densities, which may have adverse effects on plant communities. The results from the Kızılırmak Delta suggest that these contrasting processes must be considered together when evaluating grazing management in wetlands. The grazing degree results further suggest that the overall grazing pressure within the delta remained within sustainable limits. Values ranging between 30% and 84% indicate that the existing grazing system is not entirely uncontrolled, with most habitats classified as 'light' to 'moderate'. However, the relatively high grazing degrees observed in seasonally flooded pastures highlight the intensive use of these habitats by water buffalo. This pattern is consistent with the known tendency of buffalo to utilise areas close to water sources and newly emerged, palatable vegetation following flood recession (Tsiobani et al., 2019; Centeri, 2022). In wetland ecosystems, water buffalo were identified as the dominant grazers, with horses and wild boar contributing at a secondary level (Mihaliou & Massaro, 2021). The rapid exploitation of high-quality green forage that becomes available during the summer period can be attributed to the elevated grazing levels in habitats where floodwaters recede. These findings suggest that the hydrological regime not only regulates forage production, but also significantly influences the spatial distribution of animals and grazing patterns across the landscape. Overall, if managed without consideration of habitat-specific differences, the grazing system in the Kızılırmak Delta may pose ecological risks. However, a habitat-based management approach that explicitly incorporates hydrological processes and adjusts grazing intensity according to ecological carrying capacity would enable high forage production to be maintained while conserving the integrity of the wetland ecosystem. In this respect, the present study provides robust scientific evidence to inform the effective and sustainable management of water buffalo grazing in wetlands. Conclusion This study demonstrates that the wetland rangelands of the Kızılırmak Delta have the potential to support both livestock production and biodiversity conservation, provided that grazing activities are managed in harmony with natural ecological and hydrological processes. The spatial and temporal variations observed in vegetation structure, dry matter production, grazing capacity and grazing pressure were shaped by the combined effects of habitat characteristics, seasonal hydrological dynamics and interannual climatic variability. The findings emphasise the importance of maintaining hydrological heterogeneity and adjusting grazing intensity according to the ecological carrying capacity of individual habitats. Despite their relatively limited surface area, seasonally flooded pastures emerged as key components of the system by providing high forage production and grazing efficiency. In contrast, more fragile habitats, such as coastal dunes and sandy grasslands, require cautious, low-intensity grazing strategies to prevent ecological degradation. When planned and monitored appropriately, water buffalo grazing can contribute to developing productive, resilient and functionally integrated wetland rangeland systems without compromising ecosystem integrity. In this context, integrating sustainable grazing strategies with conservation-oriented wetland management is essential for achieving long-term ecological and socio-economic benefits in multifunctional wetland landscapes such as the Kızılırmak Delta. Declarations Author contributions SA: conceptualization, methodology, formal analysis, investigation, data curation, writing – original draft preparation, visualization, project administration. EE and KEY: conceptualization, methodology, writing – review and editing, and supervision. MG: formal analysis, investigation, data curation, writing – review and editing, and visualization. All authors contributed to the article and approved the submitted version. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Acknowledgments We would like to thank AKS planning and engineering company for their support in carrying out this study. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References Ali I, Cawkwell F, Dwyer E, Barrett B and Green S (2016). Satellite remote sensing of grasslands: from observation to management. J. Plant Ecol. 9, 649–671. doi: 10.1093/jpe/rtw005 Altıntaş G, Altıntaş A, Çakmak E, and Demir O (2018) A research on sustainability in the Iimproved Pastures: Case of Sivas-Amasya-Tokat. 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Sci. 11:989214. doi: 10.3389/fenvs.2023.989214 Tables Table 1. Ecological classification of study sites Ecological units Number of cages Grazing area (ha) Hydrological characters A-Permanent wet meadows 9 17+33+15 High water table B-Coastal dunes / sandy grasslands 9 81+147+318 Low moisture C-Grazed permanent pastures 6 35+120 Fluctuating moisture D-Seasonally flooded pastures 18 105+123+76+ 59+30+292 Seasonal flooding Table 2. Dominant plant species identified in different habitats in the Kızılırmak Delta Wetland. Plant species Families Habitats A B C D Lolium perenn e L. Poaceae + + Paspalum distichum L. Poaceae + + + Poa pratensis L. Poaceae + + Agrostis stolonifera L. Poaceae + + Briza minor L. Poaceae + + Catapodium rigidum (L.) C.E.Hubb. Poaceae + + Cynodon dactylon (L.) Pers. var. dactylon Poaceae + + Hordeum murinum L. Poaceae + + Lotus corniculatus L. var. tenuifolius Fabaceae + Medicago lupulina L. Fabaceae + Medicago minima (L.) Bartal. var. minima Fabaceae + + Trifolium campestre Schreb Fabaceae + + Trifolium repens L. var. repens Fabaceae + + Trifolium resupinatum L. var. resupinatum Fabaceae + + + Trifolium pratense L. var. pratense Fabaceae + + Medicago polymorpha L. Fabaceae + + + Ranunculus marginatus d’Urv. Ranunculaceae + + Rubus caesius L. Rosaceae + Eryngium maritimum L. Apiaceae + + Muscari armeniacum Leichtlin ex Baker Apiaceae + + Salvia verbenaca L. Lamiaceae + Verbascum sinuatum L. var. sinuatum Scrophulariaceae + + Sambucus ebulus L. Adoxaceae + Salicornia europaea L. Amaranthaceae + + Bellis perennis L. Asteraceae + + Centaurea iberica Trev. ex Sprengel Asteraceae + Cichorium intybus L. Asteraceae + Senecio vulgari s L. Asteraceae + Taraxacum macrolepium Schischk Asteraceae + + + Achillea millefolium L. subsp. millefolium Asteraceae + + Cynara cardunculu s L. Asteraceae + Convolvulus arvensis L. Convolvulaceae + + Carex acutiformis Ehrh. Cyperaceae + + Cyperus capitatus Vand. Cyperaceae + Euphorbia helioscopia L. subsp. helioscopia Euphorbiaceae + Juncus acutus L. subsp. acutus Juncaceae + + + + Juncus inflexus L. subsp. inflexus Juncaceae + + + + Juncus littoralis C.A.Mey. Juncaceae + + + + Table 3. The botanical composition, number of plants and quality grade of the wetland in the Kızılırmak Delta (average over two years). Ecological unit (eu) Botanical composition (%) Number of plant Plant quality grade (%) Legume Grass Forb A 29.78±6.23 a 55.78±8.67 a 14.44±3.20 b 14.50±2.11 b 6.04±0.26 a B 18.53±2.40 b 40.17±5.60 b 41.30±6.72 a 27.83±6.97 a 3.88±0.92 c C 26.56±2.04 a 55.59±2.96 a 17.75±4.39 b 26.00±5.77 a 5.17±0.22 b mean 24.55±6.91B 49.98±10.39A 25.47±13.48B 22.38±8.30 5.01±1.13 year(y) ** ** ns * * eu ** ** ** ** ** y x eu ns ns ns ns ns Data are presented as the mean ± standard deviation (SD). Different letters indicate significant differences at * p ≤ 0.05, ** p ≤ 0.01 level within one parameter. (ns) non-significant. Table 4. Dry matter yield, grazing capacity, grazing area per buffalo, and grazing degree of the Kızılırmak Delta Wetland (average over two years). June July August September October November Dry matter yield (t ha) A 4.42±0.85 a 1.50±0.27 a 0.44±0.11 bc 0.66±0.13 bc 0.97±0.13 b 0.87±0.11 b B 2.75±0.58 b 0.97±0.14 c 0.25±0.04 c 0.34±0.07 c 0.55±0.05 c 0.50±0.05 c C 4.05±0.23 a 1.33±0.16 b 0.61±0.25 b 0.82±0.35 b 0.96±0.30 b 0.91±0.30 b D - 1.66±0.30 a 2.05±0.60 a 2.30±0.84 a 1.80±0.65 a 1.42±0.51 a mean 3.70±0.99A 1.43±0.36B 1.11±0.92DE 1.32±1.03BC 1.23±0.84D 1.03±0.50E year:* , ecological unit:**, month:*, ecological unit x month: **; *P < 0.05 and **P < 0.01 Grazing capacity (head) A 250±103 c 85±35 b 24±9 b 36±12 b 53±15 b 47±14 b B 1379±1006a 473±310 a 123±79 b 157±98 b 266±166 b 244±157 b C 825±490 b 278±176 ab 147±118 b 201±163 b 224±170 b 213±163 b D - 550±534 a 666±683 a 781±796 a 615±641 a 489±506 a mean 817±827A 395±425B 338±535B 405±620B 364±488B 302±386B year:* ecological unit:** month:* ecological unit x month: **; *P < 0.05 and **P < 0.01 Grazing area per buffalo (ha head) A 0.09±0.02 b 0.27±0.05bc 0.94±0.24 b 0.60±0.11 b 0.41±0.05 b 0.45±0.06 b B 0.15±0.03 a 0.41±0.07 a 1.56±0.26 a 1.20±0.27 a 0.71±0.06 a 0.78±0.07 a C 0.09±0.05 b 0.30±0.03 b 0.76±0.32 c 0.56±0.24 b 0.45±0.14 b 0.47±0.15 b D - 0.23±0.04 c 0.21±0.08 d 0.19±0.07 c 0.25±0.10 c 0.31±0.12 c mean 0.11±0.03F 0.29±0.07E 0.73±0.55A 0.55±0.41B 0.41±0.19D 0.46±0.20C year:** ecological unit:** month:* ecological unit x month: **; *P < 0.05 and **P < 0.01 Grazing degree (%) A 82±1.75 a 66±2.98 a 40±11.5 c 46±4.13 c 53±2.72 b 65±2.40 a B 65±5.80 b 58±6.44 b 50±9.48 b 30±8.16 b 48±5.85 c 53±5.43 c C 82±0.89 a 66±5.77 a 46±14.03 b 54±8.18 b 56±6.56 ab 59±11.83 b D - 56±6.05 b 67±3.92 a 76±1.95 a 58±6.67 a 53±6.55 c mean 76±9.21A 60±6.89B 54±13.24D 56±18.95C 54±6.96D 57±8.35C year:** ecological unit:** month:* ecological unit x month: **; *P < 0.05 and **P < 0.01 Data are presented as the mean ± standard deviation (SD). Different letters indicate significant differences at * p ≤ 0.05, ** p ≤ 0.01 level within one parameter. Table 5. Total dry matter yield, grazing capacity, grazing area per buffalo, and grazing degree of the Kızılırmak Delta wetland (average over two years). Ecological Unit (eu) Dry matter yield Grazing capacity Grazing area per buffalo Grazing degree A 8.56±1.49 a 496±194 b 2.76±0.45 b 0.70±0.01 a B 5.35±0.84 b 2640±1854 a 4.80±0.59 a 0.58±0.04 c C 8.67±1.46 a 1888±1340 ab 2.62±0.90 b 0.69±0.01 a D 9.23±2.72 a 3100±3194 a 1.20±0.37 c 0.63±0.02 b mean 8.24±2.51 2270±2473 2.51±1.47 0.65±0.05 year (y) * * * ** eu ** ** ** ** y x eu ns ns ns ns Data are presented as the mean ± standard deviation (SD). Different letters indicate significant differences at * p ≤ 0.05, ** p ≤ 0.01 level within one parameter. (ns) non-significant. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8647170","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":581773693,"identity":"c0934253-cb1e-4b59-b4ab-848136ed14aa","order_by":0,"name":"Sebahattin Albayrak","email":"data:image/png;base64,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","orcid":"","institution":"Ondokuz Mayıs University","correspondingAuthor":true,"prefix":"","firstName":"Sebahattin","middleName":"","lastName":"Albayrak","suffix":""},{"id":581773694,"identity":"adf2ca10-4949-4b95-8620-a73954927bf2","order_by":1,"name":"Emire Elmas","email":"","orcid":"","institution":"Sinop University","correspondingAuthor":false,"prefix":"","firstName":"Emire","middleName":"","lastName":"Elmas","suffix":""},{"id":581773695,"identity":"c1639329-cd39-4cef-89da-30de4f8805f5","order_by":2,"name":"Kiraz Erciyas Yavuz","email":"","orcid":"","institution":"Ondokuz Mayıs University","correspondingAuthor":false,"prefix":"","firstName":"Kiraz","middleName":"Erciyas","lastName":"Yavuz","suffix":""},{"id":581773696,"identity":"63923695-aa38-486e-8ebc-a4dc888d89f5","order_by":3,"name":"Mustafa Güler","email":"","orcid":"","institution":"Ondokuz Mayıs University","correspondingAuthor":false,"prefix":"","firstName":"Mustafa","middleName":"","lastName":"Güler","suffix":""}],"badges":[],"createdAt":"2026-01-20 09:19:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8647170/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8647170/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101486547,"identity":"f9c353b5-9fe5-42c5-a42f-4aad1d6cf603","added_by":"auto","created_at":"2026-01-30 09:14:58","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":896458,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study area in the Kızılırmak Delta wetland (northern Türkiye).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8647170/v1/665a6b6615891d99c9d53fcc.jpeg"},{"id":101486550,"identity":"bf49d97c-aa43-4d48-a2f8-ffd02c051a24","added_by":"auto","created_at":"2026-01-30 09:14:58","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1238813,"visible":true,"origin":"","legend":"\u003cp\u003eFour different habitats are shown in the images: permanent wet meadows, coastal dunes/sandy grasslands, grazed permanent pastures, and seasonally flooded pastures.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8647170/v1/f9cf02efa26aad5462b12d54.jpeg"},{"id":101486553,"identity":"4d2d3549-4352-49e9-aa5a-2fe45ad40dbb","added_by":"auto","created_at":"2026-01-30 09:14:58","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":105821,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly precipitation totals (left) and monthly mean air temperature (right) for 2022 and 2023, compared with long-term climatic normals for the Kızılırmak Delta region. Bars indicate precipitation (mm), and lines indicate temperature (°C).\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8647170/v1/84608763845f5b30211f609f.jpeg"},{"id":101752471,"identity":"cfae8240-12b7-444c-9994-2042655e9881","added_by":"auto","created_at":"2026-02-03 10:27:41","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":525712,"visible":true,"origin":"","legend":"\u003cp\u003eGeneral view of the vegetation inside and outside the cage\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8647170/v1/4566bef5c5fe5780bd5558f5.jpeg"},{"id":101486552,"identity":"6aa408ed-7e93-4b3a-9fb9-1afeedbbe45c","added_by":"auto","created_at":"2026-01-30 09:14:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":149739,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly dynamics of dry matter yield, grazing capacity, grazing area per buffalo, and grazing degree across ecological units (two-year mean).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8647170/v1/6e63e1359372c7998315fb94.png"},{"id":101486551,"identity":"12218093-c641-4ce1-8da1-014eaecd9b11","added_by":"auto","created_at":"2026-01-30 09:14:58","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":70456,"visible":true,"origin":"","legend":"\u003cp\u003eEcological-unit–based comparison of grazing productivity indicators in the Kızılırmak Delta (two-year mean).\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8647170/v1/9e3208f260e25103e985612b.png"},{"id":101756369,"identity":"01b6c4df-b0db-4839-ab53-f6a3607e54f0","added_by":"auto","created_at":"2026-02-03 10:57:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4058374,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8647170/v1/20d02495-d341-49a9-901d-5e2164f492cd.pdf"},{"id":101486548,"identity":"f550c144-becc-4c92-bed6-ca6eb5f0f3eb","added_by":"auto","created_at":"2026-01-30 09:14:58","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":48556,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-8647170/v1/52c8f8d6dbea643bc28e17e2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Habitat-based forage productivity and grazing dynamics in a heterogeneous wetland system","fulltext":[{"header":"Highlights","content":"\u003cp\u003eHabitat-based analysis revealed strong spatial heterogeneity in forage productivity within the Kızılırmak Delta wetland.\u003c/p\u003e\u003cp\u003eSeasonally flooded pastures showed the highest dry matter yield and grazing capacity despite their limited surface area.\u003c/p\u003e\u003cp\u003eMonthly assessments demonstrated pronounced seasonal shifts in forage availability driven by hydrological dynamics.\u003c/p\u003e\u003cp\u003eGrazing capacity and area per buffalo varied substantially among habitat types, indicating different management thresholds.\u003c/p\u003e\u003cp\u003eHabitat-oriented and hydrology-aware grazing strategies can enhance precision management in wetland grazing systems.\u003c/p\u003e\u003cp\u003eIMPACT\u003c/p\u003e\u003cp\u003eThis study makes a contribution to precision agriculture by quantifying forage productivity and grazing pressure indicators within a heterogeneous wetland system on a habitat-specific basis. This provides spatially explicit information to support data-driven pasture planning and land use decisions. By linking hydrological variability with forage availability, the results inform adaptive, site-specific management strategies that enhance the efficiency with which resources are used while maintaining the integrity of the ecosystem.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eWetlands occupy only 3\u0026ndash;5% of the Earth\u0026rsquo;s terrestrial surface (Niu et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Despite this limited coverage, they serve critical ecological functions in regulating regional climates, supplying water resources, sustaining biodiversity, and providing habitats for endemic and endangered species (Sterner et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bai et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Leonardi and Dai, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mei et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Bu et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Functioning as transitional zones between terrestrial and aquatic systems, wetlands offer breeding, feeding, and growth opportunities for diverse wildlife species (Yağmur et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jafarzadeh et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). They are integral to global Earth surface processes\u0026mdash;such as the atmosphere and hydrosphere\u0026mdash;and remain highly sensitive to environmental change and anthropogenic pressures (Li et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bai and Wang, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The ecological services of wetlands are wide-ranging, encompassing erosion control, flood regulation, pollution reduction, climate moderation, wastewater treatment, biodiversity conservation, groundwater recharge, and wildlife support (Mahdianpari et al., 2020; Cui et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Guo et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zivec et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Owing to this multitude of benefits, wetlands are often described as the \u0026ldquo;kidneys of nature\u0026rdquo; (Mahdavi et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Nevertheless, recent assessments by the United Nations Environment Programme and the Ramsar Convention indicate that nearly 35% of global wetlands have been lost over the past five decades, posing a severe threat to biodiversity (Convention on Wetlands, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Turkey, wetlands are regarded as strategic ecosystems for sustaining livestock production. Their rich vegetation and high productivity support multiple levels of the food chain and contribute substantially to rural economies through forage yield and grazing capacity (G\u0026uuml;l, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The Kızılırmak Delta, one of Turkey\u0026rsquo;s largest and most ecologically significant wetland systems, exemplifies this multifunctionality. The approximately 56,000-hectare Kızılırmak delta wetlands, located along the Black Sea coast, have Ramsar site status, with around 11,000 hectares designated as wetlands of international ecological importance (Demirkalp et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In 2016, the wetlands were added to the UNESCO World Heritage Sites tentative list (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://whc.unesco.org/en/tentativelists/6125/\u003c/span\u003e\u003cspan address=\"http://whc.unesco.org/en/tentativelists/6125/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Hosting around 354 bird species\u0026mdash;more than half of Turkey\u0026rsquo;s avifauna\u0026mdash;it serves as a critical refuge for migratory and resident waterfowl. Simultaneously, its expansive pastures and reedbeds provide a vital forage base for the region\u0026rsquo;s traditional water buffalo husbandry (Anon, 2021). The ecological functioning of the Kızılırmak Delta is governed not only by its overall extent, but also by pronounced habitat heterogeneity driven by hydrological gradients and soil moisture regimes. Within the delta, grazing landscapes consist of multiple heterogeneous habitat types that differ markedly in terms of vegetation structure, forage productivity and seasonal accessibility ((Boz, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Uzun et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; S\u0026uuml;rmen, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These include permanent wet meadows characterised by persistently high soil moisture; coastal dunes and sandy grasslands with low water-holding capacity; long-grazed permanent pastures shaped by sustained grazing pressure; and seasonally flooded pastures that only become accessible after the water recedes in summer (Yavuz, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This differentiation of habitats plays a decisive role in determining the spatial patterns of forage availability, grazing intensity and ecological resilience within the delta.\u003c/p\u003e \u003cp\u003eWater buffaloes (\u003cem\u003eBubalus bubalis\u003c/em\u003e) are particularly well adapted to wetland environments due to their physiological characteristics, including thicker skin and fewer sweat glands compared to cattle, which limit their heat tolerance (Sambraus and Spannl-Flor, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Consequently, wetlands offer a favorable habitat for these animals (Krawczynski et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Historically, buffalo husbandry has been central to the cultural identity of the Kızılırmak Delta. Although national buffalo numbers have declined since the 1980s, the delta remains a stronghold for the species. Yılmaz and Kara (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) underscore the delta\u0026rsquo;s pivotal role in ensuring the future of buffalo farming in Turkey, emphasizing the importance of aligning livestock sustainability with wetland management strategies. Beyond their role in food production, buffaloes act as ecological engineers in shaping wetland habitats. Their grazing and wallowing activities reduce dense reed stands, thereby creating feeding and nesting opportunities for waterfowl (Anonymous, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This interaction exemplifies a reciprocal ecological relationship in which livestock activity supports biodiversity while benefiting from wetland forage resources. In particular, the non-selective grazing behavior of buffaloes promotes a balanced distribution of legumes and grasses, thereby sustaining plant diversity (F\u0026uuml;r\u0026eacute;sz et al., 2023). However, the ecological outcomes of grazing are strongly influenced by the specific characteristics of the habitat in question. In hydrologically dynamic habitats, such as seasonally flooded pastures, forage production and grazing capacity can increase rapidly following the recession of water. In contrast, structurally fragile habitats, such as coastal dunes and sandy grasslands, are more susceptible to degradation under sustained grazing pressure ((R\u0026uuml;zgar and G\u0026uuml;m\u0026uuml;, 2025; Arıman et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Berndt et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This spatial variability highlights the importance of evaluating grazing impacts and forage productivity within a habitat-based framework, rather than treating wetlands as uniform grazing systems.\u003c/p\u003e \u003cp\u003eModerate buffalo grazing contributes to ecosystem biodiversity by reducing vegetation density. However, overgrazing can lead to soil erosion and biodiversity loss, highlighting the need for careful pasture management (Altıntaş et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, sustainable grazing plans and collaborative pasture management practices are critical to balancing livestock productivity with biodiversity conservation. Forage yield is a key indicator of pasture conditions, use, and environmental assessment (Ali et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Accordingly, accurate assessment of pasture productivity and carrying capacity is vital for sustainable livestock management and should be prioritized by both policymakers and farmers (Liu et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Morais et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study addresses the existing knowledge gap by providing a habitat-based assessment of forage production and grazing dynamics in the Kızılırmak Delta. Through the joint analysis of dry matter yield, grazing capacity, grazing area per buffalo and grazing intensity across four ecologically distinct wetland habitats under long-established free-grazing conditions, the study provides a fresh perspective on the regulation of grazing systems in complex wetland landscapes by hydrological variability and habitat structure. The findings provide evidence that can inform the development of adaptive, habitat-specific grazing strategies that reconcile forage use with the conservation of wetland ecosystem integrity.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eStudy area\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted between 2022 and 2023 in the Kızılırmak Delta Wetland, located in Samsun Province in northern Turkey. The approximate central coordinates of the study area are 41\u0026deg;65\u0026prime;07\u0026Prime; N latitude and 36\u0026deg;07\u0026prime;47\u0026Prime; E longitude. Spanning approximately 11,000 hectares, the delta is an extensive wetland complex comprising coastal zones, river channels, lakes, reed beds, marshes, natural meadows, rangelands, floodplain forests, dune systems and surrounding agricultural lands. Due to its significant ecological value and biodiversity, the Kızılırmak Delta has been designated a Wetland of International Importance under the Ramsar Convention (Figure 1).\u003c/p\u003e\n\u003cp\u003eBetween April and November each year, approximately 7.000-10.000 water buffalo owned by local farmers graze freely across the delta. The area available for grazing is estimated to be around 2.500 hectares. In the present study, the movements of the buffalo and the intensity of grazing were not experimentally controlled or manipulated. Instead, all measurements were conducted under existing free-ranging grazing conditions in order to realistically reflect the forage production potential of the delta under current management practices. Sampling sites were classified into four main ecological units based on hydrological conditions and dominant vegetation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA. Permanent Wet Grasslands: These grasslands are characterised by consistently high soil moisture and surface water in some areas for a significant portion of the year. They are typically associated with hydromorphic soils. The vegetation consists of dense grassland communities with a variety of moisture-tolerant grasses and legumes. These habitats provide high biomass production and remain suitable for grazing over extended periods, particularly during the summer months.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eB. Coastal Dunes/Sandy Grasslands: These habitats are located between the coastal zone and adjacent lakes, and are characterised by sandy soils with a low water-holding capacity. The vegetation is generally made up of short, mostly annual species with ruderal characteristics, resulting in relatively low forage productivity. From a grazing perspective, coastal dunes and sandy grasslands are considered relatively fragile ecosystems with limited carrying capacity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eC. Grazed permanent pastures: These encompass areas that have been subjected to regular grazing over many years, exhibiting moderate soil moisture conditions and vegetation characteristics. Plant communities are dominated by grass and legume species that can tolerate grazing, reflecting a relatively stable balance between forage production and utilisation under prolonged grazing pressure.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eD. Seasonally flooded pastures: These habitats are partially or fully submerged during spring and the early part of summer. As the water recedes from midsummer onwards, the land becomes accessible for grazing. After the waters have receded, the vegetation is typically dominated by \u003cem\u003ePaspalum\u003c/em\u003e species, and these habitats demonstrate high forage production potential during the summer. Seasonally flooded pastures are among the most dynamic and productive components of the grazing system in the delta.\u003c/p\u003e\n\u003cp\u003eEach ecological unit comprised multiple sampling sites, and the total area represented by each habitat class is summarized in Table 1. Representative field photographs of each ecological unit are provided in Figure 2 to facilitate visual interpretation of landscape-level differences among habitat types.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClimate Characteristic\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Kızılırmak Delta Wetland has a \u0026quot;semi-humid\u0026quot; climate, according to the classification compiled by the National Directorate General of Meteorogy (MGM) and based on the Thornthwaite method. According to the long-term average for the region, the total rainfall is 720 mm and the average temperature is 14.6 \u0026deg;C \u003cstrong\u003e(\u003c/strong\u003eFigure 3\u003cstrong\u003e).\u003c/strong\u003e In the second year of the research, there was almost twice as much precipitation in the March-May and June-August periods compared to the first year. While the average temperature between January and March of the first year was 6.5 \u0026deg;C, this value was determined as 8.1 \u0026deg;C in the second year. Therefore, it was observed that there were significant differences in temperature and precipitation amounts between seasons and years.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBotanical Composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe botanical composition was determined during the first week of June, which coincided with the flowering period of the plants in the three areas (excluding the Seasonally Flooded Pastures) in both years. The Seasonally Flooded Pastures were not subject to botanical composition determination during this period as they were flooded. Over the following months, this area became completely covered in Paspalum species. Botanical composition was determined according to the weight percentage of each plant species within the total composition. To determine dry matter yield, the harvested plants were separated by species, dried and weighed. Then, the weight of each species was divided by the total weight to determine its proportion in the botanical composition (Taşdelen and Yazıcı, 2022).\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlant Quality Grade (PQG)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe plant quality grade (PQG) of forage was determined to evaluate the overall quality of the grazing resources in the study area. The PQG was calculated as:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003eQuality scores of plant species were obtained from G\u0026ouml;kkuş et al. (2000), Babalık (2008), Aydın and Uzun (2002), and Karakuş (2014). Forage quality was categorized as: very good (8.1-10.0), good (7.1-8.0), moderate (4.1-6.0), poor (2.1-4.0), and very poor (0.0-2.0).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe above-mentioned observations were made in both years only before the first harvest (in June) and in areas that remained continuously dry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDry matter Yield\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn order to determine the forage production potential of the Kızılırmak Delta, 80 iron cages, each measuring 50 x 70 centimetres, were placed in grazing areas. Data were collected from 42 cages over a two-year period; some cages were excluded from the study due to damage or collapse. The cages were distributed as follows: 9 in permanent wet meadows, 9 in coastal dunes/sandy grasslands, 6 in grazed permanent pastures and 18 in seasonally flooded pastures. Forage harvesting was carried out using 0.12 m\u0026sup2; (0.3 x 0.4 m) squares inside and outside the cages. Sampling began in June each year and was repeated at approximately 30-day intervals until November (six harvests per year). The harvested biomass was oven-dried at 105 \u0026deg;C until a constant weight was reached and then weighed to determine the dry matter yield (T\u0026ouml;ngel, 2018). To determine the degree of grazing in the grazed areas of the delta, grazing densities were calculated using in-cage and out-of-cage feed yield values (Figure 4).\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eA grazing degree of ~50% indicates sustainable utilization, while up to 70% may be acceptable in areas with favorable precipitation (Aydın and Uzun, 2002). Accordingly, 70% was adopted as the threshold for appropriate grazing in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrazing Capacity and Grazing Area per Buffalo:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe grazing capacity (GC) and pasture area required per buffalo were estimated using the following formulas (\u0026Ccedil;a\u0026ccedil;an and Balkan, 2021):\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e* In these calculations, grazing capacity was standardized using a cattle unit (CU) concept, where a 500-kg animal was defined as 1 CU for comparative purposes. In the Kızılırmak Delta, grazing is predominantly carried out by female water buffalo, with an average live body weight of approximately 375 kg, corresponding to 0.75 CU. Based on this average body weight, daily dry matter consumption was estimated as 9 kg DM per animal, assuming a utilization factor of 70%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data obtained were analysed using the SAS 9.0 statistical software package. Prior to performing ANOVA, the data were tested for normality using the Shapiro\u0026ndash;Wilk test and for homogeneity of variance using the Levene test. Once these assumptions had been confirmed, one-way ANOVA was applied. Statistical differences between all the means were determined using Duncan\u0026apos;s multiple range test. Hierarchical heat mapping was performed using the RStudio software environment (4.4.2) (https://posit.co/products/open-source/rstudio/?sid=1/, accessed 10 October 2025). The heatmap package was used for heatmap visualisations.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBotanical Composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn both study years, the botanical composition was determined during the first week of June, which coincided with the flowering period of the dominant plant species. A total of 115 plant species were identified in the habitats. The dominant species are given in Table 2, while all the other species are listed in Supplementary Table 1. Botanical composition could not be assessed in seasonally flooded pasture habitats during the measurement period, as these areas were completely submerged at the time of sampling. Over the following months, this habitat was almost entirely dominated by \u003cem\u003ePaspalum\u003c/em\u003e species, which are the primary source of forage for grazing animals within the delta. Based on two-year averages, the proportions of legumes, grasses and forbs differed significantly between habitats (P ≤ 0.01; Table 3). The highest legume proportions were found in permanent wet meadows (29.78%) and grazed permanent pastures (26.56%), while significantly lower values were recorded in coastal dunes and sandy grasslands (18.53%). Similarly, grass proportions were highest in permanent wet meadows (55.78%) and grazed permanent pastures (55.59%), while coastal dunes and sandy grasslands had substantially lower grass cover (40.17%). Conversely, forb proportions were markedly higher in coastal dunes and sandy grasslands, accounting for 41.30% of the botanical composition. According to the combined analysis of variance, both year and habitat effects were statistically significant for legume, grass and forb proportions (P ≤ 0.01)(Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNumber of plants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe number of plant species differed significantly among habitat types (P ≤ 0.01; Table 3). Based on two-year averages, the highest species richness was recorded in coastal dunes and sandy grasslands (27.83 species), while the lowest value was observed in permanent wet meadows (14.50 species). The results of the combined analysis indicated that year and habitat had a strong and significant effect on the number of plants (P ≤ 0.01), whereas the effects year × habitat interaction was not statistically significant (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlant quality grade\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was a significant difference in plant quality grade among habitat types (P ≤ 0.01; Table 3). Based on two-year mean values, the highest grade was observed in permanent wet meadows (6.04%), while the lowest was recorded in coastal dunes and sandy grasslands (3.88%). According to the combined analysis of variance, both year and habitat had a significant effect on plant quality grade (P ≤ 0.05), whereas the interaction between year and habitat was not statistically significant (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDry matter yield\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistically significant differences in dry matter yield were observed at the P \u0026lt; 0.05 level for the years and months, and at the P \u0026lt; 0.01 level for the ecological unit and the ecological unit x month interaction (Table 4). Dry matter yield reached its maximum monthly value in June in all ecological units (except seasonally flooded pastures), decreased significantly from July onwards and remained at relatively low levels during the autumn months (Table 4). Based on two-year averages, seasonally flooded pastures had the highest total dry matter yield (9.23 t ha\u003csup\u003e-1\u003c/sup\u003e), followed by grazed permanent pastures (8.67 t ha\u003csup\u003e-1\u003c/sup\u003e) and permanent wet meadows (8.56 t ha\u003csup\u003e-1\u003c/sup\u003e). By contrast, the lowest dry matter yield (5.35 t ha⁻¹) was found in coastal dunes and sandy grasslands (Table 5). Dry matter yield peaked in June across all ecological units, then decreased substantially from July onwards, stabilising at lower, more uniform levels between August and November \u003cstrong\u003e(\u003c/strong\u003eFigure 5). The hierarchical clustering heatmap (Figure 6) clearly shows a separation of seasonally flooded pastures from the other ecological units in terms of dry matter yield. Meanwhile, coastal dunes and sandy grasslands form a separate cluster characterised by consistently low yield values.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrazing capacity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGrazing capacity was statistically significantly affected by year, month, ecological unit, and month x ecological unit interaction (Table 4). Monthly data showed that grazing capacity was at its maximum in June, declining gradually during the summer and autumn months (Table 4). The highest mean grazing capacity was recorded in seasonally flooded pastures (3.100 head), followed by coastal dunes and sandy grasslands (2.640 head) and grazed permanent pastures (1,888 head). Permanent wet meadows exhibited the lowest mean grazing capacity (496 head) (Table 5). Across all ecological units, grazing capacity peaked in June, decreasing progressively as the grazing season advanced to reach more limited levels in autumn (Figure 5). Hierarchical clustering revealed that seasonally flooded pastures formed a distinct, dominant cluster, whereas permanent wet meadows grouped separately due to their consistently lower grazing capacity values (Figure 6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrazing area per buffalo\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe grazing area per buffalo differed significantly according to the year, month, ecological unit and year × month interaction (Table 4). On a monthly basis, the grazing area per buffalo was at its lowest in June, increasing towards its highest values in August and September (Table 4). Based on two-year averages, the smallest grazing area per buffalo was observed in seasonally flooded pastures (1.20 ha\u003csup\u003e-1\u003c/sup\u003e\u0026nbsp; per buffalo), followed by grazed permanent pastures (2.62 ha\u003csup\u003e-1\u003c/sup\u003e per buffalo) and permanent wet meadows (2.76 ha\u003csup\u003e-1\u003c/sup\u003e per buffalo). The largest grazing area requirement per buffalo was observed in coastal dunes and sandy grasslands (4.80 ha\u003csup\u003e-1\u003c/sup\u003e\u0026nbsp; per head) (Table 5). Across ecological units, the grazing area per buffalo reached its minimum in June and its maximum in August–September (Figure 5). Clustering analysis showed that coastal dunes and sandy grasslands were clearly separated by their high area requirements, whereas seasonally flooded pastures formed a distinct cluster characterised by low grazing area per buffalo values (Figure 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrazing Degree\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGrazing degree was strongly influenced by year, month, ecological unit and year × month interaction (Table 4). Monthly patterns indicated that grazing degree was highest in June and became more balanced toward late summer and autumn (Table 4). The highest mean grazing degree was recorded across ecological units in permanent wet meadows (70%) and grazed permanent pastures (69%). Seasonally flooded pastures exhibited intermediate grazing degree values (63%), while coastal dunes and sandy grasslands exhibited the lowest mean grazing degree (58%) (Table 5). Grazing degree peaked at the beginning of the grazing season, stabilising at lower, more uniform levels by late summer and autumn (Figure 5). Permanent wet meadows and grazed permanent pastures displayed similar clustering patterns, while coastal dunes and sandy grasslands formed a separate group characterised by consistently lower grazing degree values (Figure 6).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of this study demonstrate that the ecological functioning of the grazing system in the Kızılırmak Delta varies significantly between different habitats. The four main habitat types identified in the delta — permanent wet meadows, coastal dunes and sandy grasslands, grazed permanent pastures and seasonally flooded pastures — fulfil distinct ecological roles in terms of botanical composition, forage production and grazing potential. These results clearly indicate that wetlands should be managed as habitat-specific units with differing responses to grazing, rather than as homogeneous grazing landscapes.\u003c/p\u003e\n\u003cp\u003eFrom a botanical perspective, although the proportion of legumes remained relatively high in permanent wet meadows, a general decline in legume abundance was observed across all habitats when two-year averages were considered. This pattern corroborates previous findings that legumes are among the most sensitive functional plant groups in wetland grasslands, particularly in response to grazing pressure and interannual climatic variability (Tegegn et al., 2010). Given legumes' well-established role in enhancing forage nutritive value and improving animal performance (Wolkaro \u0026amp; Tesfaye, 2025), the observed reduction in legume abundance could indicate a decline in forage quality in wetland grazing systems. By contrast, the growing dominance of grasses, particularly in seasonally flooded pastures and permanent wet meadows, is a result of the combined effects of habitat hydrology and the relatively indiscriminate grazing behaviour of water buffalo. Although grass dominance promotes biomass continuity and yield stability, it is also linked to a slight decline in forage quality compared to legume-rich pastures, due to generally lower crude protein content and digestibility (Wrobel et al., 2025). Similar patterns have been reported in wetland grazing systems in Hungary, where water buffalo grazing has promoted the growth of economically valuable grasses and legumes while suppressing invasive species (Fűrész et al., 2023). The results obtained from the Kızılırmak Delta are consistent with these observations, suggesting that, when habitat-specific conditions are taken into account, buffalo grazing can steer plant communities towards more balanced and functionally resilient assemblages.\u003c/p\u003e\n\u003cp\u003eThe results relating to rangeland quality grade revealed significant spatial variations between different habitats. Permanent wet meadows and seasonally flooded pastures consistently fell within the 'good' quality class in both study years, indicating a relatively sustainable balance between botanical composition and grazing pressure. Conversely, the lower rangeland quality grades observed in fragile habitats such as coastal dunes and sandy grasslands suggest these areas are more sensitive to soil limitations and combined stressors, including grazing pressure and seasonal drought. These findings suggest that rangeland quality grade is not solely dependent on stocking density, but is also heavily influenced by micro-ecological conditions and the inherent characteristics of the habitat (Niu et al., 2025).\u003c/p\u003e\n\u003cp\u003eThe results regarding number of plants further emphasise the critical role of habitat heterogeneity in maintaining biodiversity within wetland ecosystems. The higher species richness observed in permanent wet meadows and grazed permanent pastures highlights the structural complexity and ecological resilience of these habitats. However, greater species richness does not necessarily equate to increased functional stability or rangeland balance. As has been reported in other wetland and rangeland ecosystems, the relationship between number of plants and ecosystem functioning is not linear (Li et al., 2024; Eldridge et al., 2016; Zhang et al., 2025). Selective grazing by water buffalo, favouring graminoids and legumes while less palatable species persist within the community, is a key mechanism that may explain why species richness remains relatively high in certain habitats (Tsiobani et al., 2019).\u003c/p\u003e\n\u003cp\u003eClear differences were observed among habitat classes in terms of dry matter yield, grazing capacity and grazing area per buffalo. Although seasonally flooded pastures occupy a relatively small surface area, they were found to be the habitat class with the lowest grazing area per buffalo due to their high dry matter yield and grazing capacity. In contrast, habitats such as coastal dunes and sandy grasslands had lower production intensity, requiring substantially more grazing area per animal. These findings are consistent with previous studies demonstrating that grazing efficiency in wetlands is largely governed by the hydrological regime (Vega et al., 2022; Zhuo et al., 2024). Perrino et al. (2021) reported that changes in the water regime directly influence pasture productivity in Mediterranean wetlands, emphasising that appropriate stocking levels can support both habitat conservation and high forage yields. However, O’Dea et al. (2022) observed that hydrological alterations in certain wetland ecosystems can result in higher animal densities, which may have adverse effects on plant communities. The results from the Kızılırmak Delta suggest that these contrasting processes must be considered together when evaluating grazing management in wetlands.\u003c/p\u003e\n\u003cp\u003eThe grazing degree results further suggest that the overall grazing pressure within the delta remained within sustainable limits. Values ranging between 30% and 84% indicate that the existing grazing system is not entirely uncontrolled, with most habitats classified as 'light' to 'moderate'. However, the relatively high grazing degrees observed in seasonally flooded pastures highlight the intensive use of these habitats by water buffalo. This pattern is consistent with the known tendency of buffalo to utilise areas close to water sources and newly emerged, palatable vegetation following flood recession (Tsiobani et al., 2019; Centeri, 2022). In wetland ecosystems, water buffalo were identified as the dominant grazers, with horses and wild boar contributing at a secondary level (Mihaliou \u0026amp; Massaro, 2021). The rapid exploitation of high-quality green forage that becomes available during the summer period can be attributed to the elevated grazing levels in habitats where floodwaters recede. These findings suggest that the hydrological regime not only regulates forage production, but also significantly influences the spatial distribution of animals and grazing patterns across the landscape.\u003c/p\u003e\n\u003cp\u003eOverall, if managed without consideration of habitat-specific differences, the grazing system in the Kızılırmak Delta may pose ecological risks. However, a habitat-based management approach that explicitly incorporates hydrological processes and adjusts grazing intensity according to ecological carrying capacity would enable high forage production to be maintained while conserving the integrity of the wetland ecosystem. In this respect, the present study provides robust scientific evidence to inform the effective and sustainable management of water buffalo grazing in wetlands.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that the wetland rangelands of the Kızılırmak Delta have the potential to support both livestock production and biodiversity conservation, provided that grazing activities are managed in harmony with natural ecological and hydrological processes. The spatial and temporal variations observed in vegetation structure, dry matter production, grazing capacity and grazing pressure were shaped by the combined effects of habitat characteristics, seasonal hydrological dynamics and interannual climatic variability. The findings emphasise the importance of maintaining hydrological heterogeneity and adjusting grazing intensity according to the ecological carrying capacity of individual habitats. Despite their relatively limited surface area, seasonally flooded pastures emerged as key components of the system by providing high forage production and grazing efficiency. In contrast, more fragile habitats, such as coastal dunes and sandy grasslands, require cautious, low-intensity grazing strategies to prevent ecological degradation. When planned and monitored appropriately, water buffalo grazing can contribute to developing productive, resilient and functionally integrated wetland rangeland systems without compromising ecosystem integrity. In this context, integrating sustainable grazing strategies with conservation-oriented wetland management is essential for achieving long-term ecological and socio-economic benefits in multifunctional wetland landscapes such as the Kızılırmak Delta.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSA: conceptualization, methodology, formal analysis, investigation, data curation, writing – original draft preparation, visualization, project administration. EE and KEY: conceptualization, methodology, writing – review and editing, and supervision. MG: formal analysis, investigation, data curation, writing – review and editing, and visualization. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank AKS planning and engineering company for their support in carrying out this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAli I, Cawkwell F, Dwyer E, Barrett B and Green S (2016). 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Turkish journak of Forestry. 23(2): 106 \u0026ndash; 115. https://doi.org/10.18182/tjf.1061956\u003c/li\u003e\n\u003cli\u003eTegegn A and Gebreyes LN (2010) Changes in plant species composition and diversity along a grazing gradient from livestock watering point in allaidege rangeland of north-eastern ethiopia rangelands\u003cstrong\u003e. \u003c/strong\u003eLivestock Research for Rural Development 23(9). https://www.researchgate.net/publication/286497710\u003c/li\u003e\n\u003cli\u003eT\u0026ouml;ngel \u0026Ouml; (2018) Determination of the Effects of Different Cutting Times on Botanical Composition, Hay Yield and Nutritional Value in a Fertilized Bottom Pasture. Ondokuz Mayıs University, Institute of Science, PhD Thesis, Samsun. 742p.\u003c/li\u003e\n\u003cli\u003eTsiobani ET, Yiakoulaki MD, Menexes, G (2019) Seasonal variation in water buffaloes\u0026rsquo; diet grazing in wet grasslands in Northern Greece. Hacquetia. 18(2): 201-2012. DOI: 10.2478/hacq-2019-0004\u003c/li\u003e\n\u003cli\u003eUzun, A., Yavuz, KE., Karaer, F., Polat, N., Bakan, G., G\u0026uuml;rg\u0026ouml;ze1, S. (2024). Ecogeomorphological Investigation of Anthropogenic Changes in the Kızılırmak River Mouth, T\u0026uuml;rkiye. Wetlands, 44:83. https://doi.org/10.1007/s13157-024-01843-2\u003c/li\u003e\n\u003cli\u003eVega JA, Arellano-P\u0026acute;erez S, Alvarez-Gonz\u0026acute;alez JG, Fern\u0026acute;andez C, Jim\u0026acute;enez E, Fern\u0026acute;andez-Alonso JM and Ruiz-Gonz\u0026acute;alez AD (2022) Modelling aboveground biomass and fuel load components at stand level in shrub communities in NW Spain. For. Ecol. Manage. 505 https://doi.org/10.1016/j.foreco.2021.119926.\u003c/li\u003e\n\u003cli\u003eWolkaro T and Tesveye G (2025). Role of Forage Legumes in Enhancing Soil Fertility and Livestock Nutrition in Ethiopia . \u003cem\u003eAmerican Journal of Applied Scientific Research \u003c/em\u003e11(3): 145-151. https://doi.org/10.11648/j.ajasr.20251103.11\u003c/li\u003e\n\u003cli\u003eWrobel B, Zielewicz W and Paszkiewicz-Jasinska A (2025) Improving Forage Quality from Permanent Grasslands to Enhance Ruminant Productivity. Agriculture 5, 1438. https://doi.org/10.3390/agriculture15131438\u003c/li\u003e\n\u003cli\u003eYağmur N, Musaoğlu N and Taşkın G (2019) Detection of shallow water area with machine learning algorithms. ISPRS Geospatial Week 2019 At: Enschede, The Netherlands. 10.5194/isprs-archives-XLII-2-W13-1269-2019\u003c/li\u003e\n\u003cli\u003eYavuz KE (2011) An important natural area: Kizilirmak delta. https://www.researchgate.net/publication/343295177\u003c/li\u003e\n\u003cli\u003eYılmaz A and Kara MA (2019) Status and Future of Water Buffalo Husbandry in the World and Turkey. Turk J Agric Res 2019, 6(3): 356-363. doi: 10.19159/tutad.598629\u003c/li\u003e\n\u003cli\u003eZhang X, Chen S, Yao P, Han J and Jin R (2025) Knowledge Structure and Evolution ofWetland Plant Diversity Research: Visual Exploration Based on CiteSpace. Biology 14, 781. https://doi.org/10.3390/biology14070781 \u003c/li\u003e\n\u003cli\u003eZhuo W, Wu N, Shi R, Liu P, Zhan Xing Fu C and Cui Y (2024) Aboveground biomass retrieval of wetland vegetation at the species level using UAV hyperspectral imagery and machine learning. Ecological Indicators 166. 112365. https://doi.org/10.1016/j.ecolind.2024.112365\u003c/li\u003e\n\u003cli\u003eZivec P, Sheldon F and Capon SJ (2023) Natural regeneration of wetlands under climate change. Front. Environ. Sci. 11:989214. doi: 10.3389/fenvs.2023.989214\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Ecological classification of study sites\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEcological units\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of cages\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrazing area (ha)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHydrological characters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003eA-Permanent wet meadows\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e17+33+15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eHigh water table\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003eB-Coastal dunes / sandy grasslands\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e81+147+318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eLow moisture\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003eC-Grazed permanent pastures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e35+120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eFluctuating moisture\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003eD-Seasonally flooded pastures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e105+123+76+ 59+30+292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eSeasonal flooding\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2. Dominant plant species identified in different habitats in the Kızılırmak Delta Wetland.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlant species\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamilies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHabitats\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eLolium perenn\u003c/em\u003ee L.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePoaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003ePaspalum distichum L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePoaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003ePoa pratensis L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePoaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eAgrostis stolonifera L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePoaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eBriza minor L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePoaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eCatapodium rigidum\u0026nbsp;\u003c/em\u003e(L.) C.E.Hubb.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePoaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eCynodon dactylon\u0026nbsp;\u003c/em\u003e(L.) Pers. var. \u003cem\u003edactylon\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePoaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eHordeum murinum\u0026nbsp;\u003c/em\u003eL.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePoaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eLotus corniculatus\u0026nbsp;\u003c/em\u003eL. var. \u003cem\u003etenuifolius\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFabaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eMedicago lupulina L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFabaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eMedicago minima\u0026nbsp;\u003c/em\u003e(L.) Bartal. var. \u003cem\u003eminima\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFabaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eTrifolium campestre\u0026nbsp;\u003c/em\u003eSchreb\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFabaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eTrifolium repens\u0026nbsp;\u003c/em\u003eL. var. \u003cem\u003erepens\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFabaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eTrifolium resupinatum\u0026nbsp;\u003c/em\u003eL. var. \u003cem\u003eresupinatum\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFabaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eTrifolium pratense\u0026nbsp;\u003c/em\u003eL. var. \u003cem\u003epratense\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFabaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eMedicago polymorpha L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFabaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eRanunculus marginatus\u0026nbsp;\u003c/em\u003ed\u0026rsquo;Urv.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eRanunculaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eRubus caesius L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eRosaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eEryngium maritimum L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eApiaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eMuscari armeniacum\u0026nbsp;\u003c/em\u003eLeichtlin ex Baker\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eApiaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eSalvia verbenaca\u0026nbsp;\u003c/em\u003eL.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eLamiaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eVerbascum sinuatum\u0026nbsp;\u003c/em\u003eL. var. \u003cem\u003esinuatum\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eScrophulariaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eSambucus ebulus L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAdoxaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eSalicornia europaea\u0026nbsp;\u003c/em\u003eL.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAmaranthaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eBellis perennis L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAsteraceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eCentaurea iberica\u0026nbsp;\u003c/em\u003eTrev. ex Sprengel\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAsteraceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eCichorium intybus L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAsteraceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eSenecio vulgari\u003c/em\u003es L.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAsteraceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eTaraxacum macrolepium\u0026nbsp;\u003c/em\u003eSchischk\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAsteraceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eAchillea millefolium\u0026nbsp;\u003c/em\u003eL. subsp. \u003cem\u003emillefolium\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAsteraceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eCynara cardunculu\u003c/em\u003es L.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAsteraceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eConvolvulus arvensis L.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eConvolvulaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eCarex acutiformis\u0026nbsp;\u003c/em\u003eEhrh.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eCyperaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eCyperus capitatus\u0026nbsp;\u003c/em\u003eVand.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eCyperaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eEuphorbia helioscopia\u0026nbsp;\u003c/em\u003eL. subsp. \u003cem\u003ehelioscopia\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eEuphorbiaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eJuncus acutus\u0026nbsp;\u003c/em\u003eL. subsp. \u003cem\u003eacutus\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eJuncaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eJuncus inflexus\u0026nbsp;\u003c/em\u003eL. subsp. \u003cem\u003einflexus\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eJuncaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cem\u003eJuncus littoralis\u0026nbsp;\u003c/em\u003eC.A.Mey.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eJuncaceae\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 3. The botanical composition, number of plants and quality grade of the wetland in the Kızılırmak Delta (average over two years).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEcological unit (eu)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBotanical composition (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of plant\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlant quality grade (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLegume\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrass\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eForb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e29.78\u0026plusmn;6.23 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e55.78\u0026plusmn;8.67 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e14.44\u0026plusmn;3.20 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e14.50\u0026plusmn;2.11 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e6.04\u0026plusmn;0.26 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e18.53\u0026plusmn;2.40 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e40.17\u0026plusmn;5.60 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e41.30\u0026plusmn;6.72 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e27.83\u0026plusmn;6.97 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e3.88\u0026plusmn;0.92 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e26.56\u0026plusmn;2.04 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e55.59\u0026plusmn;2.96 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e17.75\u0026plusmn;4.39 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e26.00\u0026plusmn;5.77 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e5.17\u0026plusmn;0.22 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e24.55\u0026plusmn;6.91B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e49.98\u0026plusmn;10.39A\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e25.47\u0026plusmn;13.48B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e22.38\u0026plusmn;8.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e5.01\u0026plusmn;1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eyear(y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eeu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003ey x eu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as the mean \u0026plusmn; standard deviation (SD). Different letters indicate significant differences at * p \u0026le; 0.05, ** p \u0026le; 0.01 level within one parameter. (ns) non-significant.\u003c/p\u003e\n\u003cp\u003eTable 4. Dry matter yield, grazing capacity, grazing area per buffalo, and grazing degree of the Kızılırmak Delta Wetland (average over two years).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJune\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJuly\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAugust\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeptember\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOctober\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNovember\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 651px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDry matter yield (t ha)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e4.42\u0026plusmn;0.85 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.50\u0026plusmn;0.27 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.44\u0026plusmn;0.11 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.66\u0026plusmn;0.13 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.97\u0026plusmn;0.13 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.87\u0026plusmn;0.11 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2.75\u0026plusmn;0.58 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.97\u0026plusmn;0.14 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.25\u0026plusmn;0.04 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.34\u0026plusmn;0.07 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.55\u0026plusmn;0.05 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.50\u0026plusmn;0.05 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e4.05\u0026plusmn;0.23 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.33\u0026plusmn;0.16 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.61\u0026plusmn;0.25 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.82\u0026plusmn;0.35 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.96\u0026plusmn;0.30 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.91\u0026plusmn;0.30 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.66\u0026plusmn;0.30 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e2.05\u0026plusmn;0.60 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e2.30\u0026plusmn;0.84 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.80\u0026plusmn;0.65 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e1.42\u0026plusmn;0.51 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3.70\u0026plusmn;0.99A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.43\u0026plusmn;0.36B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1.11\u0026plusmn;0.92DE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1.32\u0026plusmn;1.03BC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.23\u0026plusmn;0.84D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e1.03\u0026plusmn;0.50E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 651px;\"\u003e\n \u003cp\u003eyear:* , ecological unit:**, month:*, ecological unit x month: \u0026nbsp;**; *P \u0026lt; 0.05 and **P \u0026lt; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 651px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrazing capacity (head)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e250\u0026plusmn;103 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e85\u0026plusmn;35 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e24\u0026plusmn;9 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e36\u0026plusmn;12 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e53\u0026plusmn;15 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e47\u0026plusmn;14 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1379\u0026plusmn;1006a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e473\u0026plusmn;310 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e123\u0026plusmn;79 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e157\u0026plusmn;98 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e266\u0026plusmn;166 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e244\u0026plusmn;157 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e825\u0026plusmn;490 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e278\u0026plusmn;176 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e147\u0026plusmn;118 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e201\u0026plusmn;163 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e224\u0026plusmn;170 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e213\u0026plusmn;163 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e550\u0026plusmn;534 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e666\u0026plusmn;683 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e781\u0026plusmn;796 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e615\u0026plusmn;641 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e489\u0026plusmn;506 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e817\u0026plusmn;827A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e395\u0026plusmn;425B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e338\u0026plusmn;535B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e405\u0026plusmn;620B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e364\u0026plusmn;488B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e302\u0026plusmn;386B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 651px;\"\u003e\n \u003cp\u003eyear:* ecological unit:** month:* ecological unit x month: \u0026nbsp;**; *P \u0026lt; 0.05 and **P \u0026lt; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 651px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrazing area per buffalo (ha head)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.09\u0026plusmn;0.02 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.27\u0026plusmn;0.05bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.94\u0026plusmn;0.24 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.60\u0026plusmn;0.11 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.41\u0026plusmn;0.05 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.45\u0026plusmn;0.06 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.15\u0026plusmn;0.03 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.41\u0026plusmn;0.07 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1.56\u0026plusmn;0.26 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1.20\u0026plusmn;0.27 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.71\u0026plusmn;0.06 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.78\u0026plusmn;0.07 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.09\u0026plusmn;0.05 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.30\u0026plusmn;0.03 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.76\u0026plusmn;0.32 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.56\u0026plusmn;0.24 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.45\u0026plusmn;0.14 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.47\u0026plusmn;0.15 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.23\u0026plusmn;0.04 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.21\u0026plusmn;0.08 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.19\u0026plusmn;0.07 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.25\u0026plusmn;0.10 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.31\u0026plusmn;0.12 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.11\u0026plusmn;0.03F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.29\u0026plusmn;0.07E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.73\u0026plusmn;0.55A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.55\u0026plusmn;0.41B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.41\u0026plusmn;0.19D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.46\u0026plusmn;0.20C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 651px;\"\u003e\n \u003cp\u003eyear:** ecological unit:** month:* ecological unit x month: \u0026nbsp;**; *P \u0026lt; 0.05 and **P \u0026lt; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 651px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrazing degree (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e82\u0026plusmn;1.75 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e66\u0026plusmn;2.98 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e40\u0026plusmn;11.5 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e46\u0026plusmn;4.13 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e53\u0026plusmn;2.72 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e65\u0026plusmn;2.40 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e65\u0026plusmn;5.80 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e58\u0026plusmn;6.44 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e50\u0026plusmn;9.48 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e30\u0026plusmn;8.16 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e48\u0026plusmn;5.85 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e53\u0026plusmn;5.43 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e82\u0026plusmn;0.89 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e66\u0026plusmn;5.77 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e46\u0026plusmn;14.03 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e54\u0026plusmn;8.18 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e56\u0026plusmn;6.56 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e59\u0026plusmn;11.83 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e56\u0026plusmn;6.05 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e67\u0026plusmn;3.92 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e76\u0026plusmn;1.95 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e58\u0026plusmn;6.67 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e53\u0026plusmn;6.55 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e76\u0026plusmn;9.21A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e60\u0026plusmn;6.89B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e54\u0026plusmn;13.24D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e56\u0026plusmn;18.95C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e54\u0026plusmn;6.96D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e57\u0026plusmn;8.35C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 651px;\"\u003e\n \u003cp\u003eyear:** ecological unit:** month:* ecological unit x month: \u0026nbsp;**; *P \u0026lt; 0.05 and **P \u0026lt; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as the mean \u0026plusmn; standard deviation (SD). Different letters indicate significant differences at * p \u0026le; 0.05, ** p \u0026le; 0.01 level within one parameter.\u003c/p\u003e\n\u003cp\u003eTable 5. Total dry matter yield, grazing capacity, grazing area per buffalo, and grazing degree of the Kızılırmak Delta wetland (average over two years).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEcological Unit\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(eu)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDry matter yield\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrazing capacity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrazing area per buffalo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrazing\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003edegree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e8.56\u0026plusmn;1.49 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e496\u0026plusmn;194 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e2.76\u0026plusmn;0.45 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.70\u0026plusmn;0.01 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e5.35\u0026plusmn;0.84 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e2640\u0026plusmn;1854 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e4.80\u0026plusmn;0.59 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.58\u0026plusmn;0.04 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e8.67\u0026plusmn;1.46 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e1888\u0026plusmn;1340 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e2.62\u0026plusmn;0.90 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.69\u0026plusmn;0.01 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e9.23\u0026plusmn;2.72 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e3100\u0026plusmn;3194 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e1.20\u0026plusmn;0.37 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.63\u0026plusmn;0.02 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e8.24\u0026plusmn;2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e2270\u0026plusmn;2473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e2.51\u0026plusmn;1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.65\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eyear (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eeu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003ey x eu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as the mean \u0026plusmn; standard deviation (SD). Different letters indicate significant differences at * p \u0026le; 0.05, ** p \u0026le; 0.01 level within one parameter. (ns) non-significant.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"wetlands-ecology-and-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wetl","sideBox":"Learn more about [Wetlands Ecology and Management](https://www.springer.com/journal/11273)","snPcode":"11273","submissionUrl":"https://submission.nature.com/new-submission/11273/3","title":"Wetlands Ecology and Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"wetland, grazing management, grazing capacity, water buffalo, habitat","lastPublishedDoi":"10.21203/rs.3.rs-8647170/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8647170/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eContext: Wetland pastures support both livestock production and biodiversity. However, their spatially heterogeneous structure and seasonal hydrological dynamics present challenges for the sustainable management of grazing, particularly in long-standing free-grazing systems.\u003c/p\u003e \u003cp\u003eObjectives: This study aimed to evaluate forage production and grazing dynamics in the habitat-based Kızılırmak Delta wetland, providing management-oriented information for the sustainable use of wetlands under free-grazing conditions.\u003c/p\u003e \u003cp\u003eMethods: Research was conducted in four different habitat classes between 2022 and 2023: permanent wet meadows, coastal dunes/sandy grasslands, grazed permanent pastures and seasonally flooded pastures. Grazing occurred naturally under long-standing free-range conditions, with no experimental intervention on the animals. Botanical composition, plant species richness and plant quality grade were determined each year prior to the initial harvest. Dry matter yield, grazing capacity, grazing area per buffalo and grazing grade were calculated monthly throughout the grazing season. The data were analysed using analysis of variance (ANOVA), and spatiotemporal patterns were visualised using hierarchical clustering heatmaps.\u003c/p\u003e \u003cp\u003eKey results: Significant habitat-related differences were identified in terms of botanical composition, species richness and plant quality grade (P\u0026thinsp;\u0026le;\u0026thinsp;0.01). Seasonally flooded pastures exhibited the highest average dry matter yield (9.23 t/ha), grazing capacity (3,100 head) and lowest grazing area per buffalo (1.20 ha/head). Monthly analyses revealed strong seasonal variability: the highest forage availability occurred at the start of the grazing season in accessible habitats. Heatmap analyses clearly distinguished between habitat classes based on productivity and grazing indicators.\u003c/p\u003e \u003cp\u003eConclusion: Forage production and grazing pressure in the Kızılırmak Delta are primarily driven by habitat characteristics and seasonal hydrological processes.\u003c/p\u003e \u003cp\u003eImplications and impacts: Habitat-based, hydrologically sensitive grazing management can increase grazing efficiency while preserving the integrity of the ecosystem in open-grazed wetland systems, thus supporting both sustainable livestock production and wetland conservation.\u003c/p\u003e","manuscriptTitle":"Habitat-based forage productivity and grazing dynamics in a heterogeneous wetland system","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-30 09:14:53","doi":"10.21203/rs.3.rs-8647170/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-17T11:37:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-13T13:45:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-06T21:14:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"111220316197180769315458623248591771661","date":"2026-02-02T15:30:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120643888920518826465108679055300837353","date":"2026-01-28T11:01:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-28T07:24:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-23T01:03:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-20T10:51:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Wetlands Ecology and Management","date":"2026-01-20T08:29:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"wetlands-ecology-and-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wetl","sideBox":"Learn more about [Wetlands Ecology and Management](https://www.springer.com/journal/11273)","snPcode":"11273","submissionUrl":"https://submission.nature.com/new-submission/11273/3","title":"Wetlands Ecology and Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8939bd1a-235e-4531-a786-44b8617bfc07","owner":[],"postedDate":"January 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T08:10:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-30 09:14:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8647170","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8647170","identity":"rs-8647170","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}