Effects of scattered trees on pond ecosystems: experimental evidence from a biodiversity hotspot

Effects of scattered trees on pond ecosystems: experimental evidence from a biodiversity hotspot | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of scattered trees on pond ecosystems: experimental evidence from a biodiversity hotspot Beatriz Moreira Ferreira, João Luiz Caires-Souza, Vinicius Neres-Lima, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7429547/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Human-driven landscape modifications threaten pond ecosystems worldwide. The conversion of landscapes from forests to pastures can have significant impacts on pond biodiversity and ecosystem processes. Scattered trees are common elements in deforested landscapes and represent keystone structures because they increase biodiversity. Moreover, scattered trees are often associated with ponds, potentially affecting their structure and function. Here, we experimentally investigated how pond ecosystems respond to different landscape elements, including scattered trees. We built an experimental set of 12 ponds in a pasture area with three treatments: ponds near the edge of a continuous forest, those under the canopy of a scattered tree and those in the open pasture. To test the effects of the treatments on the biotic and abiotic characteristics of the ponds, we quantified water temperature, oxygen, dissolved nutrients (NO₃⁻, NH₄⁺, and PO₄³⁻), turbidity, conductivity, allochthonous organic material and phytoplanktonic chlorophyll. Scattered-tree ponds presented relatively high concentrations of dissolved NH₄⁺ and PO₄³⁻, as well as relatively high levels of phytoplanktonic chlorophyll. Edge ponds presented relatively high levels of allochthonous organic material and conductivity, whereas open-pasture ponds presented relatively high temperatures, oxygen concentrations and NO₃⁻ concentrations. Our results provide evidence that landscape elements can have diverse effects on pond ecosystems. Although we expected scattered-tree ponds to resemble edge ponds by buffering the impact of the pasture, the presence of a single scattered tree created a distinct and novel environment. Scattered trees associated with ponds thus represent important elements that contribute to increasing ecological heterogeneity in deforested landscapes. abiotic and biotic factors small waterbodies isolated tree pasture landscape Atlantic forest Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Ponds are common ecosystems worldwide, both in natural and human-modified landscapes. Because of their small size, ponds have a strong relationship with their terrestrial surroundings (Schneider et al. 2002 ). Compared with open ponds, riparian vegetation provides allochthonous organic matter and shade, reducing light intensity, temperature, dissolved oxygen and primary production within ponds (Schiesari 2006 ). The integrity of aquatic–terrestrial connections is essential for the functioning of aquatic systems, especially small systems, including ponds (Schneider et al. 2002 ). The energy flux between aquatic and terrestrial environments is reciprocal: terrestrial areas contribute energy to ponds through allochthonous organic matter, whereas ponds export energy via emergent organisms (Schneider et al. 2002 ; Earl and Semlitsch 2012 ), that is, aquatic species that complete part of their life cycle in water and then transition to the terrestrial environment (e.g., adult insects and amphibians). Owing to their significant contribution to terrestrial nutrient dynamics through these emergent organisms, ponds can be considered biogeochemical hotspots (Capps et al. 2014 ). Compared with larger systems, small ponds play a disproportionately important role in nutrient dynamics at local, regional, and global scales—not only as breeding sites for various organisms but also as sources and sinks of greenhouse gases (Capps et al. 2014 ; Holgerson and Raymond 2016 ). However, the link between aquatic and terrestrial systems can be sensitive to abiotic factors, such as temperature, where relatively high water temperatures can alter nutrient and energy fluxes between ecosystems (Yvon-Durocher et al. 2011 ; Nash et al. 2021 ). Ponds are among the most threatened systems among freshwater ecosystems (De Meester et al. 2005 ). The destruction of habitats has resulted in the degradation and elimination of ponds at alarming rates (Blaustein and Schwartz S. 2001). Owing to their shallowness and, sometimes, temporary nature, ponds are highly vulnerable to anthropogenic actions, such as water extraction, or, during dry periods, may be drained or buried for agricultural use (Calhoun et al. 2017 ). The loss of vegetation cover around ponds resulting from human activities, such as agriculture and raising cattle, triggers a cascade of alterations in ecosystem characteristics and processes occurring within these environments (Foley et al. 2005 ; Strayer and Dudgeon 2010 ; Dala-Corte et al. 2020 ). However, ponds can still contribute disproportionately to biodiversity, even in human-modified landscapes (Davies et al. 2007 ; De Marco et al. 2014 ; Hill et al. 2017 ). For example, ponds located in a modified landscape in the Brazilian Cerrado increase beta diversity despite their small size (De Marco et al. 2014 ). Urban ponds are also important sites for maintaining biodiversity in modified landscapes, with urban ponds showing high taxonomic richness but a different composition from nonurban ponds (Hill et al. 2017 ). In human-modified landscapes, natural ponds are extinguished, whereas artificial ponds are created for many purposes, such as water management, recreation and irrigation (2008). There is still controversy about how well an artificial pond can mimic a natural pond (Pechmann et al. 2001 ; Brown et al. 2012 ; Apinda Legnouo et al. 2014 ; Kolozsvary and Holgerson 2016 ). Artificial ponds may present different biotic and abiotic characteristics than natural ponds do, with differences in hydroperiod, canopy cover, dissolved phosphorus, pH, conductivity, temperature, chlorophyll, vegetation and macroinvertebrates (Kolozsvary and Holgerson 2016 ). However, the creation of artificial ponds is still important for the mitigation of wetland loss and for the conservation of many species, especially those that depend on water for reproduction (Pechmann et al. 2001 ; Brand and Snodgrass 2009 ; Simaika et al. 2016 ). Additionally, a variety of terrestrial species rely on pond systems for food, water and habitat (Nummi et al. 2011 ; Lewis-Phillips et al. 2020 ). Many studies have shown that a landscape with a pond network (the so-called “pondscape”) is extremely important for species that use these sites as stepping stones to cross agricultural areas between forest fragments, for example (De Marco et al. 2014 ; Simaika et al. 2016 ; Calhoun et al. 2017 ; Deacon et al. 2018 ). It is important to consider methods to manage the terrestrial area around a pondscape to protect pond ecosystems and biota amid the increase in agriculture and cattle raising. In a pondscape, the different landscape elements associated with ponds (e.g., forest fragments, types of plantations, trees, lakes and rivers) can have a significant effect on pond ecosystems. Ponds occurring in pastures and other human-impacted ecosystems can be associated with scattered trees (or isolated trees) left after deforestation to provide shade for cattle. Scattered trees provide a range of ecosystem services that benefit farmers, such as fruit provisioning, shading for cattle, carbon sequestration and nitrogen cycle regulation (Manning et al. 2006 ; Hartel et al. 2017 ; Cuni Sanchez and Lindsell 2017 ). These trees are considered “keystone structures” in the landscape because of their disproportionate effect on the ecosystem relative to their small area of occupancy (Manning et al. 2006 ; Fischer et al. 2010 ). For example, scattered trees increase landscape connectivity, act as a regeneration core, resting site, and shelter for species that cross a matrix with unfavorable conditions (e.g., forest species crossing open areas), and provide a local microclimate with lower temperature and luminosity and higher humidity, among other benefits (Manning et al. 2006 ). However, there is little information on how scattered trees affect pond ecosystems. To our knowledge, no experimental studies have tested the effects of landscape elements on pond ecosystems. Experimental studies are highly important for providing robust ecological evidence by controlling for multiple confounding factors. Additionally, pond ecosystems are relatively simple systems suitable for replication in experimental approaches (De Meester et al. 2005 ). There is a need to clarify many questions regarding pond ecology, many of which were pointed out by Hill and colleagues (Hill et al. 2021 ). The present study unifies ecosystem ecology and landscape ecology to understand whether management strategies can help reduce anthropogenic impacts on ponds. We experimentally evaluated the effects of landscape elements on pond ecosystem characteristics. To do so, we built 12 experimental ponds in a pasture matrix surrounded by forest in a fragmented landscape of the Atlantic Forest, which is a top-ranked biodiversity hotspot globally (Myers et al. 2000 ). Ponds were built in pasture areas under three different landscape contexts (treatments): 1) near the edge of a continuous forest (hereafter “edge ponds”), 2) in open pasture (hereafter “pasture ponds”) and 3) under the canopy of scattered trees (hereafter “scattered-tree ponds”). We expected scattered-tree ponds and edge ponds to have similar characteristics due to their tree cover, with higher allochthonous material biomass and conductivity and lower temperature, oxygen, dissolved nutrients, turbidity, and chlorophyll than did pasture ponds. We thus expected scattered trees to act as environmental buffers. In this way, scattered trees, as well as the forest edge, buffer the effect of pasture by diminishing the runoff of terrestrial nutrients and soil and providing a local microclimate with a lower temperature. The input of leaf litter from scattered trees and edge ponds leads to increased conductivity. Nevertheless, pasture ponds are more affected by the absence of tree cover, which favors increases in temperature and phytoplanktonic chlorophyll. Pasture ponds are more susceptible to soil runoff, which increases turbidity and dissolved nutrients. Methods 1. Study area and experimental design The study was conducted in a fragmented landscape in Rio de Janeiro, Brazil. The experimental pond system is located in a pasture area surrounded by a private reserve called Reserva Ecológica de Guapiaçu, which comprises approximately 7,200 ha of Atlantic Forest (Almeida-Gomes and Rocha 2014 ). Native vegetation is classified as dense evergreen forest, and the climate has two different seasons: one relatively warm and wet and the other colder and drier (Vieira et al. 2009 ; Almeida-Gomes and Rocha 2014 ). The landscape where the experiment was conducted is a low-intensity pasture where cattle are semiconfined. In these types of pasture areas, it is common to find scattered trees with the purpose of providing shade for cattle (Manning et al. 2006 ). In 2016, we established a system of standardized experimental ponds to assess how different landscape elements influence pond ecosystems (Almeida-Gomes et al., 2025 , Caires-Souza et al. in prep). The study was conducted within a pasture area bordered by forest fragments of varying sizes. A total of 12 ponds were constructed with an excavator and assigned to three landscape treatments: four ponds situated in an open pasture located 20 m away from the nearest scattered tree (pasture ponds) (Fig. 1 a), four beneath scattered trees of the genus Ficus (scattered-tree ponds) (Fig. 1 b), and four located at the forest/pasture edge (edge ponds) (Fig. 1 c). Each pond measured approximately 3 m by 2.5 m at a depth of 0.5 m and was lined with a plastic tarp to retain rainwater. To prevent disturbance by cattle, all ponds were enclosed by a barbed wire fence and were spaced at least 50 meters apart. The edge ponds were positioned such that one side bordered the forest while the remaining three sides faced the pasture. Ponds placed under scattered trees were standardized using individuals from the genus Ficus , a group commonly found in tropical pastures that is known to contribute to forest restoration in human-modified landscapes (Cottee-Jones et al. 2016 ). Although some shrubs or small trees occasionally occurred nearby, these tree-treatment ponds were characterized by a single dominant Ficus tree that provided the main canopy structure. Statistical analysis confirmed that the distance to the forest edge did not differ significantly between the open pasture and scattered-tree treatments (Welch’s t test; T₃.₈₄ = -0.74; p = 0.50). All ponds were naturally filled with rainwater and naturally colonized by a range of organisms, including algae, macrophytes, invertebrates, and tadpoles. 2. Environmental variables We sampled the ponds monthly during the warmer and wet seasons for two years (November 2020–March 2021 and November 2021–March 2021–2022). To evaluate the effects of tree cover on pond characteristics, we measured the following parameters: temperature (°C), conductivity (µS/cm), turbidity (ppm), allochthonous material weight (g/m²), phytoplanktonic chlorophyll (µg/L), oxygen saturation (%) and dissolved nutrient concentration (Ammonium, Nitrate, and Soluble Reagent Phosphorus [SRP]). All parameters were recorded monthly at each pond during the anuran breeding season for 2 years. Each pond was sampled 8 times. We measured conductivity and turbidity with a multiparameter sonde (HANNA®) and temperature and oxygen saturation with a YSI-ProDSS. We collected phytoplanktonic chlorophyll from surface water (top 10 cm), filtered it through Whatman GF-D fiberglass filters, froze the samples, extracted it in 90% alcohol and analyzed it in the laboratory with a fluorometer (AQUAFLUOR®). We sampled the allochthonous material (leaves and branches) with a stove pipe (0.0314 m²), and the material was dried in an oven for 72 hours or until there was no weight difference. Samples for dissolved ammonium (NH 4 + ), nitrate (NO 3 ) and SRP determination were collected and frozen. The dissolved nutrients were analyzed via flow injection analysis according to the manufacturer’s instructions (FIAlab 2500, FIALab Instruments Inc., Seattle, WA, USA). 3. Statistical analysis All the environmental variables were standardized to a mean of “0” and a standard deviation of “1”, as they had different scales and units. We ran a Pearson correlation matrix for the raw data via the “cor” function in the R environment to understand the relationships among the variables. We calculated the mean of each variable per pond with the data sampled monthly through the breeding season for two years and then calculated a matrix of dissimilarity between ponds on the basis of Euclidean distances (Legendre and Legendre 2012 ). To test for differences in multivariate dispersions between the treatments (scattered tree, edge, and pasture) in relation to the limnological variables, we carried out a principal component analysis (PCA) with the “vegan” package (Oksanen 2007 ). We did not detect any effect of the different years of sampling in our data. To test whether the difference between treatments was significant, we ran a permutation test (PERMANOVA – 999 permutations) via the “Adonis” function from the “vegan” package (Oksanen 2007 ). We used the function “betadisper” from the “vegan” package to test the homogeneity of variances. All analyses were carried out in R software version 4.4.2 (R Core Team 2024 ). Results The limnological characteristics of the experimental ponds highly varied (Fig. 2 ). In terms of allochthonous material, edge ponds varied from 183.16 g/m² to 428.50 g/m², scattered-tree ponds varied from 72.86 g/m² to 387.03 g/m², and pasture ponds varied from 67.95 g/m² to 117.86 g/m² (Fig. 2 -A). The phytoplanktonic chlorophyll concentration ranged from 0.10 µg/L to 0.19 µg/L in edge ponds, 0.25 µg/L to 0.66 µg/L in scattered-tree ponds and 0.11 µg/L to 0.17 µg/L in pasture ponds (Fig. 2 -B). In terms of conductivity, edge ponds varied from 53.70 µS/cm to 112.46 µS/cm, scattered-tree ponds varied from 63.15 µS/cm to 99.95 µS/cm, and pasture ponds varied from 42.57 µS/cm to 74.73 µS/cm (Fig. 2 -C). The oxygen saturation percentage ranged from 11.13–53.41% in edge ponds, 9.18–26.27% in scattered-tree ponds and 26.45–101.47% in pasture ponds (Fig. 2 -D). The temperature varied from 24.74°C to 27.53°C in edge ponds, 23.90°C to 25.10°C in scattered-tree ponds and 25.42°C to 28.36°C in pasture ponds (Fig. 2 -E). In terms of turbidity, edge ponds varied from 8.53 ppm to 14.82 ppm, scattered trees varied from 7.21 ppm to 20.77 ppm, and pasture ponds varied from 12.04 ppm to 37.95 ppm (Fig. 2 -F). The pond dissolved NO 3 concentration ranged from 17.64 µg/L to 34.66 µg/L in edge ponds, 25.71 µg/L to 134.45 µg/L in scattered-tree ponds and 24.00 µg/L to 115.12 µg/L in pasture ponds (Fig. 2 -G). The dissolved NH 4 + concentration ranged from 83.62 µg/L to 144.81 µg/L in edge ponds, 97.34 µg/L to 1000.78 µg/L in scattered-tree ponds and 57.88 µg/L to 142.98 µg/L in pasture ponds (Fig. 2 -H). The pond SRP concentrations ranged from 7.80 µg/L to 99.72 µg/L in edge ponds, 11.78 µg/L to 701.54 µg/L in scattered-tree ponds and 12.68 µg/L to 73.11 µg/L in pasture ponds (Fig. 2 -I). The first two axes of the PCA explained 59.5% of the total variability in the ponds’ biotic and abiotic characteristics (Fig. 3 ). The PCA separated the scattered-tree ponds from the pasture ponds along Axis 1, and edge ponds were separated from the other two groups along Axis 2 (Fig. 3 ). The first axis explains 42.3% of the variation and is associated with dissolved oxygen, SRP and NH 4 + concentrations; allochthonous material stock; and conductivity. The positive values correspond to ponds with higher dissolved oxygen, and the negative values correspond to ponds with lower dissolved oxygen but higher SRP and NH 4 + concentrations, allochthonous material stock, and conductivity. The second axis explains 17.2% of the variation and is associated with turbidity, SRP, and NH 4 + concentrations. Compared with other ponds, scattered-tree ponds tended to have higher SRP and NH 4 + concentrations and phytoplanktonic chlorophyll, whereas pasture ponds tended to have higher turbidity, dissolved oxygen, and lower conductivity. Edge ponds had lower turbidity and higher conductivity, as well as greater allochthonous material stock (Fig. 3 ). The biotic and abiotic characteristics differed significantly among the treatments (PERMANOVA; F (2,9) = 3.67, p < 0.01) (Fig. 3 ). However, edge ponds appeared to constitute an intermediate group, with some ponds presenting characteristics similar to those of scattered-tree ponds and others similar to those of pasture ponds. The group variances were marginally significantly different (BETADISPER; F (2,9) = 3.62, p = 0.07). A pairwise permutation test of the groups’ variance revealed a significant difference between the scattered-tree and edge ponds (observed p = 0.05, permuted p = 0.057) (Fig. 4 ). The Pearson correlation analysis revealed moderate positive correlations between dissolved oxygen and turbidity (r = 0.43), conductivity and allochthonous material stock (r = 0.44), and SRP concentration and phytoplanktonic chlorophyll (r = 0.47) (Fig. 5 ). There was a moderate negative correlation between allochthonous material stock and turbidity (r = -0.4) (Fig. 5 ). These findings indicate that ponds with higher turbidity are likely to have more dissolved oxygen but lower allochthonous material stocks (Fig. 2 ). Moreover, ponds with relatively high allochthonous material stocks tended to exhibit relatively high conductivity. There was a strong positive correlation between the NH4 + and SRP concentrations (r = 0.7) (Fig. 5 ). Ponds with high SRP concentrations also presented high NH 4 + concentrations and more phytoplanktonic chlorophyll (Fig. 2 ). Discussion In this study, we experimentally assessed the impact of landscape elements on pond biotic and abiotic characteristics, including the role of scattered trees in buffering human impacts on pond ecosystems. We expected scattered-tree ponds to present an ecosystem more similar to edge ponds, highlighting the role of scattered trees in buffering human impacts similar to the proximity of a forest patch. Indeed, pondscape elements (forest edges, pastures, and scattered trees) affect the biotic and abiotic characteristics of ponds. Our results show that the landscape context, particularly the presence of tree cover, is important in determining the abiotic characteristics of ponds. We expected pasture ponds to present high levels of dissolved nutrients, phytoplanktonic chlorophyll, temperature, oxygen, and turbidity. Moreover, we expected scattered trees and edge ponds to present high allochthonous material and conductivity and lower dissolved nutrients, phytoplanktonic chlorophyll, temperature, oxygen, and turbidity. However, our results revealed low levels of similarity between scattered-tree ponds and edge ponds (Fig. 4 ). Compared with edge ponds, scattered-tree ponds presented higher allochthonous material stocks, conductivities, NH 4 + and SRP concentrations, and phytoplanktonic chlorophyll contents. In contrast to what we expected, pasture ponds presented lower dissolved NH 4 + and SRP concentrations and phytoplanktonic chlorophyll than scattered-tree ponds did. In natural systems, ponds shaded by vegetation are known to have inputs of allochthonous material and to be more heterotrophic systems than are ponds without riparian forests, which receive less allochthonous input and have higher primary production (Rubbo et al. 2006 ). For this reason, we expected edge ponds to have characteristics more similar to those of naturally forested ponds with high allochthonous material input because of their proximity to the forest. However, edge ponds are still located within the pasture, and the relative position of the forest edge trees could have affected the quantity of litterfall directly into the pond. Leaf litter input is important for the maintenance of small aquatic systems because it provides energy to consumers directly, as a food source, and indirectly, by providing nutrients for primary production through the decomposition process (Earl and Semlitsch 2012 ; Holgerson et al. 2016 ). The input of leaf litter can increase the export of organisms to terrestrial ecosystems (Earl and Semlitsch 2012 ), and small ponds contribute disproportionately to terrestrial ecosystems by providing prey for many terrestrial species (e.g., amphibians and insects), thus increasing animal diversity in surrounding areas (Nummi et al. 2011 ; Rivera Vasconcelos et al. 2018 ; Lewis-Phillips et al. 2020 ; Zamora-Marín et al. 2021 ; Fehlinger et al. 2022 ). In this way, factors that affect leaf litter input, such as the presence of scattered trees or pond positioning relative to the nearest forest, could be important drivers determining a pond’s contribution to the terrestrial ecosystem. Moreover, the composition of leaf litter is also important for animal diversity, abundance, and fitness (Stephens et al. 2013 ). In our experimental system, we expected the scattered-tree and edge ponds to accumulate similar amounts of allochthonous material, but the composition of this material was different: while scattered-tree ponds receive leaf inputs from one tree species ( Ficus sp ., known to have recalcitrant leaves), edge ponds receive leaf inputs from a variety of species. This difference in leaf litter composition and diversity can affect pond ecosystems and community composition. The lack of leaf litter input can have even stronger effects on pond communities and their consequent ecosystem processes. For example, tadpoles bred in mesocosms with no leaf litter had much lower masses at metamorphosis and lower fitness (Rubbo et al. 2008 ; Stephens et al. 2013 ; Stoler et al. 2015 ). Pasture ponds, which lack tree cover and are more exposed to sunlight, are expected to present higher primary production with higher dissolved oxygen (Schiesari 2006 ; Rubbo et al. 2008 ). In this way, we expected the absence of canopy cover to increase primary production, increasing phytoplanktonic chlorophyll and dissolved oxygen in pasture ponds. This is because light and nutrients are important factors that limit primary production (Bourassa and Cattaneo 2000 ; Tromboni et al. 2019 ). Our results revealed that, compared with scattered-tree ponds, pasture ponds presented lower phytoplanktonic chlorophyll but high dissolved oxygen contents. Additionally, the scattered-tree ponds had more allochthonous material and higher phytoplanktonic chlorophyll but lower dissolved oxygen. Other studies have shown a negative correlation between leaf litter input and dissolved oxygen, which is consistent with our findings (Rubbo et al. 2006 ; Earl and Semlitsch 2013 ). This occurred because the increase in leaf litter input increases community respiration (Rubbo et al. 2008 ). However, in contrast to our findings, a negative relationship was also observed between leaf litter inputs and phytoplanktonic chlorophyll (Rubbo et al. 2006 ; Earl and Semlitsch 2013 ). This finding raises the question of the relationship between primary productivity and leaf litter in small ponds. Small covered ponds are often considered net heterotrophic systems with detrital-based food webs only because of low dissolved oxygen measurements. Nonetheless, a study conducted by Holgerson and colleagues ( 2016 ) revealed that leaf litter can be an important source of nutrients for algae, which can lead to higher algal quality and quantity than expected. In this way, shaded pond food webs can rely not only on leaf-litter fragments but also on leaf litter-derived algae (Schiesari et al. 2009 ; Taylor and Batzer 2010 ). In our study, the excess light in pasture ponds may have led to nutrient limitations for phytoplanktonic chlorophyll biomass, while scattered-tree ponds may have received enough light and nutrients to increase it. Because ponds are shallow systems, they are more susceptible to wind effects, which cause resuspension of the bottom nutrients, or to nutrients that come from an allochthonous source, which can cause shifting between states (Declerck et al. 2006 ). The presence of riparian vegetation, despite providing allochthonous nutrients and organic matter, protects the ponds from the wind effect and diminishes the input of nutrients and soil that comes with the runoff water. In general, forested ponds alternate between two states: clear water with macrophytes (mesotrophic) and turbid water with high chlorophyll concentrations (eutrophic) (Kuczyńska-Kippen et al. 2024 ). In contrast, pasture ponds are susceptible to increases in dissolved nutrients due to the close presence of cattle that search these spots to drink water, for example (Miller et al. 2010 ; Fierro et al. 2017 ). In this way, forested ponds are known to be mesotrophic to low eutrophic systems, whereas pasture ponds are expected to be hypereutrophic systems (Robin et al. 2014 ; Kuczyńska-Kippen et al. 2024 ). However, different from what we expected, the scattered-tree ponds presented the highest NH 4 + and SRP concentrations. The higher dissolved nutrient concentrations in the scattered-tree ponds may be due to the frequent presence of cattle searching for cooler, shaded areas. This could lead to an increase in manure close to scattered-tree ponds that could run into the ponds. These findings corroborate our results that revealed a moderate positive correlation between the dissolved SRP concentration and phytoplanktonic chlorophyll content. Our results revealed that pasture ponds presented greater turbidity than edge ponds and scattered-tree ponds did. We expected that turbidity would be correlated with chlorophyll, but this was not the case. Other studies have shown that pond turbidity can be related to the concentrations of dissolved chlorophyll, dissolved organic carbon, or sediment with silt (Declerck et al. 2006 ; Robin et al. 2014 ). Water transparency is expected to be affected by chlorophyll when it is above 30 µg. L -1 (Robin et al. 2014 ). Our ponds presented chlorophyll concentrations lower than 30 µg. L -1 , so turbidity can be related to other factors, such as sediment leached from the pasture. All the experimental ponds were located in a pasture area, and all the ponds were fenced to prevent cattle access. However, recent work has shown that fences can be ineffective in preventing the impact caused by cattle (Swartz et al. 2019 ). In pasture landscaped areas, cows act as geomorphic agents by increasing soil erosion, diminishing infiltration rates, and increasing the amount of runoff water to aquatic systems (Trimble and Mendel 1995 ; Declerck et al. 2006 ; Mcdowell and Wilcock 2009 ; O’Callaghan et al. 2019 ). We suspect that, because our ponds are located in a pasture area, the presence of scattered trees or ponds close to a forest edge was not enough for this vegetation to act as a filter to pasture nutrient runoff but was enough to lower soil leaching and pond turbidity. Turbidity is an important abiotic factor that can impact pond ecosystems and community structuring and can be used as an impact indicator (Declerck et al. 2006 ; Campbell et al. 2009 ; Akasaka et al. 2010 ). However, the impact of turbidity on pond communities is still controversial. For many taxa, high levels of turbidity can lead to lower species richness (Campbell et al. 2009 ; Akasaka et al. 2010 ). For example, turbidity can have a negative effect on tadpole species richness by decreasing development and survival rates (Wood and Richardson 2009 ). Nonetheless, turbidity can also improve tadpole camouflage to predators in this way, increasing tadpole richness (Gregory 1993 ; Tavares-Junior et al. 2020 ). Scattered trees associated with ponds could represent good breeding sites for many organisms with biphasic life cycles, e.g., anurans and insects. The presence of scattered trees increases species richness in pasture areas near these trees (Prevedello et al. 2018 ). A study conducted in the same experimental system revealed a treatment effect on adult anuran abundance, with higher abundance around edge ponds, followed by scattered-tree ponds and lower abundance around pasture ponds (Almeida-Gomes et al. 2025 )(Almeida-Gomes et al. 2025 ). Importantly, during our study, we found tadpoles of the species Aplastodiscus eugenioi , which is considered a near-threatened species (IUCN - Red list), in our edge ponds. This means that, despite the artificiality of these ponds, their presence in a pasture area created a new breeding environment for a threatened species. Many studies have shown the importance of pond ecosystem heterogeneity for tadpole community structuring (da Silva et al. 2012 ; Júnior and Rocha 2013 ; Tavares-Junior et al. 2020 ). The scattered-tree ponds presented the highest degree of ecosystem variability (Fig. 5 ), which indicates that the presence of a scattered tree can increase ecosystem heterogeneity. Ecosystem heterogeneity promotes species richness by providing diverse microhabitats, shelters, and food resources (Haddad and Prado 2005 ; Tavares-Junior et al. 2020 ; Fernández-Aláez et al. 2020 ). A study with macrophytes revealed that permanent ponds were more environmentally heterogeneous, leading to greater macrophyte diversity (Fernández-Aláez et al. 2020 ). Our results revealed that the presence of scattered trees diminished pond turbidity and provided diverse food resources, i.e., leaf litter and algae. These characteristics, associated with the lower temperature due to the microclimate promoted by the scattered trees, could enhance the community diversity and species richness of ponds. In this sense, scattered trees are good landscape elements for the management of pasture landscapes not only to promote the conservation of terrestrial animals but also for the conservation of pond ecosystems and their associated biodiversity. In conclusion, all three landscape elements (proximity to forest edges, scattered trees, and open pastures) differentially affected the ecosystem characteristics of the experimental ponds. Scattered trees did not mimic the presence of the edge forest as we expected, but they presented high habitat heterogeneity, which could be beneficial to organisms using ponds as breeding sites. Our results revealed that scattered trees did not buffer the pasture effect on pond ecosystems as we expected, and scattered-tree ponds presented high levels of dissolved nutrients, suspended chlorophyll, and allochthonous material and lower temperatures, dissolved oxygen concentrations and turbidity. However, the presence of scattered trees created a more heterogeneous pondscape and provided more heterogeneity for pond ecosystems, which could increase pond biological diversity (Almeida-Gomes et al. 2025 ) and thus represent an important landscape element for the conservation of ponds in fragmented landscapes. Nonetheless, it is still necessary to understand the effects of scattered trees on pond community structure and ecosystem processes. Declarations Fundings: JLdCS, BM-F, and VNL received scholarships from CAPES (Finance Code 001). VN-L and EZ were also supported by FAPERJ (E-26/210.060/2024, E-26/201.286/2021, E-26/211.078/2019, E-26/203.213/2017), and EZ received additional support from UERJ Prociência and CNPq (Bolsa PQ 304792/2022-5). Funding was also provided by FUNBIO (to JLdCS) and PELD-MCF (CNPq 442349/2020-3). Competing interests: The authors declare that have no competing financial or non-financial interest that could have influenced the work reported in this paper. Author Contributions: All authors contributed to the study conception and design. Data collection and material preparation: Beatriz Moreira Ferreira and João Luiz de Caires Souza; Data analysis: Beatriz Moreira Ferreira and Vinicius Neres Lima; Writing—original draft: Beatriz Moreira Ferreira; Writing—review and editing: Beatriz Moreira Ferreira, Jayme Prevedello, João Luiz de Caires Souza, Vinicius Neres Lima and Eugenia Zandonà. All authors read and approved the final manuscript. Acknowledgments We thank the Reserva Ecológica de Guapiaçu (REGUA) for logistical support. We are especially grateful to all who assisted with fieldwork and the construction and maintenance of the experimental ponds, including Orlando M. Vogelbacher, Júlia E. da Silva, Jefferson R. Amaral, Leticia B. da Silva, Bruna S. da Silva, Karoline E.F. Lacerda, Leticia Castro, Kauan N. Fonseca, Cecília L. Silva, Vitor N.T.B. Júnior, Maurício de A. Gomes, Caio H.G. Barcellos, Marcus V. Vieira, João Gabriel Pannunzio, and Pedro Paulo da S. Ferreira. Data Availability: Data supporting the findings of this study are available from the corresponding author on reasonable request. References Akasaka M, Takamura N, Mitsuhashi H, Kadono Y (2010) Effects of land use on aquatic macrophyte diversity and water quality of ponds. 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Hydrobiologia 848:1623–1638. https://doi.org/10.1007/S10750-021-04552-7/FIGURES/5 (2008) The Pond Manifesto Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7429547","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":509290743,"identity":"4bb2b0da-d52a-40e1-ab3b-8cb9a3d14c1b","order_by":0,"name":"Beatriz Moreira Ferreira","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-4239-2201","institution":"Universidade do Estado do Rio de Janeiro","correspondingAuthor":true,"prefix":"","firstName":"Beatriz","middleName":"Moreira","lastName":"Ferreira","suffix":""},{"id":509290744,"identity":"1ae7207c-1fec-4b55-b98e-c49eee0e77c5","order_by":1,"name":"João Luiz Caires-Souza","email":"","orcid":"","institution":"Universidade do Estado do Rio de Janeiro","correspondingAuthor":false,"prefix":"","firstName":"João","middleName":"Luiz","lastName":"Caires-Souza","suffix":""},{"id":509290745,"identity":"3ef9844f-5c6a-4041-b77c-792be5582242","order_by":2,"name":"Vinicius Neres-Lima","email":"","orcid":"","institution":"Universidade do Estado do Rio de Janeiro","correspondingAuthor":false,"prefix":"","firstName":"Vinicius","middleName":"","lastName":"Neres-Lima","suffix":""},{"id":509290746,"identity":"83c2c5ae-cc41-4eff-b538-1d3e6fdb10da","order_by":3,"name":"Jayme A. 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A) Allochthonous material (g.m\u003csup\u003e-\u003c/sup\u003e²); B) Phytoplanktonic chlorophyll (μg. L\u003csup\u003e-1\u003c/sup\u003e); C) Conductivity (µS.cm\u003csup\u003e-1\u003c/sup\u003e); D) Oxygen (%); E) Temperature (°C); F) Turbidity (ppm); G) Ammonium (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e\u003csub\u003e \u003c/sub\u003eµg. L\u003csup\u003e-1\u003c/sup\u003e); H) Soluble Reactive Phosphorus (SRP µg. L\u003csup\u003e-1\u003c/sup\u003e); I) Nitrate (NO\u003csub\u003e3\u003c/sub\u003e µg.L\u003csup\u003e-1\u003c/sup\u003e). The colors represent different treatments: blue– edge ponds (left box); pink– pasture ponds (middle box); yellow– scattered-tree ponds (right box)\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7429547/v1/2dbe738bac300d98af37316a.png"},{"id":90854507,"identity":"14947ad6-5614-4ee0-bdbc-da9132af824f","added_by":"auto","created_at":"2025-09-09 04:13:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":140180,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) showing the groups (colorful ellipses) and the biotic and abiotic variables of the 12 ponds. Dim1 represented 42.3% (oxygen, SRP and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, allochthonous material and conductivity), and Dim 2 represented 17.2% (turbidity, SRP and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e) of the total variability. The ellipses correspond to 65% of the variation. The numbers correspond to pond IDs, where 1, 6, 15, and 17 are pasture ponds; 2, 3, 13, and 14 are scattered-tree ponds; and 12, 16, 18, and 19 are edge ponds\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7429547/v1/ea231c66a1fee801f6a24359.png"},{"id":90854618,"identity":"9e9d26a7-5f4f-4be5-a747-dcfc4713e045","added_by":"auto","created_at":"2025-09-09 04:21:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":29399,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplot of the distance to the centroid representing the variance in the biotic and abiotic characteristics of each pond type (Edge ponds, Pasture ponds and Scattered-tree ponds)\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7429547/v1/7224276cba17b00763b94456.png"},{"id":90854620,"identity":"6a1bf0ed-f587-4a59-b2c9-ec0caa41a726","added_by":"auto","created_at":"2025-09-09 04:21:04","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":93386,"visible":true,"origin":"","legend":"\u003cp\u003eMatrix showing the results of the Pearson correlation between the environmental variables (conductivity (uS), dissolved NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+ \u003c/sup\u003e(NH4+ (µg. L\u003csup\u003e-1\u003c/sup\u003e), SRP (PO4 (µg. L\u003csup\u003e-1\u003c/sup\u003e), dissolved NO\u003csub\u003e3 \u003c/sub\u003e(NO3 (µg. L\u003csup\u003e-1\u003c/sup\u003e), oxygen (O\u003csub\u003e2 \u003c/sub\u003e%), allochthonous organic material (g.m\u003csup\u003e-\u003c/sup\u003e²), turbidity (ppm), and phytoplankton chlorophyll (mg.L\u003csup\u003e-1\u003c/sup\u003e)). The empty boxes represent nonsignificant correlations. The correlation gradient color shows negative correlation values (Pearson’s r) in blue, noncorrelations in white and positive correlations in red\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7429547/v1/2b5ca71d27bc36d642c96c9a.png"},{"id":93812079,"identity":"4a97fb22-5d9e-49a7-8941-361a32760f8a","added_by":"auto","created_at":"2025-10-17 20:36:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1229199,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7429547/v1/242a2500-7054-44a4-8975-e1f2795e1186.pdf"}],"financialInterests":"","formattedTitle":"Effects of scattered trees on pond ecosystems: experimental evidence from a biodiversity hotspot","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePonds are common ecosystems worldwide, both in natural and human-modified landscapes. Because of their small size, ponds have a strong relationship with their terrestrial surroundings (Schneider et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Compared with open ponds, riparian vegetation provides allochthonous organic matter and shade, reducing light intensity, temperature, dissolved oxygen and primary production within ponds (Schiesari \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The integrity of aquatic–terrestrial connections is essential for the functioning of aquatic systems, especially small systems, including ponds (Schneider et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The energy flux between aquatic and terrestrial environments is reciprocal: terrestrial areas contribute energy to ponds through allochthonous organic matter, whereas ponds export energy via emergent organisms (Schneider et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Earl and Semlitsch \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), that is, aquatic species that complete part of their life cycle in water and then transition to the terrestrial environment (e.g., adult insects and amphibians). Owing to their significant contribution to terrestrial nutrient dynamics through these emergent organisms, ponds can be considered biogeochemical hotspots (Capps et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Compared with larger systems, small ponds play a disproportionately important role in nutrient dynamics at local, regional, and global scales—not only as breeding sites for various organisms but also as sources and sinks of greenhouse gases (Capps et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Holgerson and Raymond \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, the link between aquatic and terrestrial systems can be sensitive to abiotic factors, such as temperature, where relatively high water temperatures can alter nutrient and energy fluxes between ecosystems (Yvon-Durocher et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Nash et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePonds are among the most threatened systems among freshwater ecosystems (De Meester et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The destruction of habitats has resulted in the degradation and elimination of ponds at alarming rates (Blaustein and Schwartz S. 2001). Owing to their shallowness and, sometimes, temporary nature, ponds are highly vulnerable to anthropogenic actions, such as water extraction, or, during dry periods, may be drained or buried for agricultural use (Calhoun et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The loss of vegetation cover around ponds resulting from human activities, such as agriculture and raising cattle, triggers a cascade of alterations in ecosystem characteristics and processes occurring within these environments (Foley et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Strayer and Dudgeon \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Dala-Corte et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, ponds can still contribute disproportionately to biodiversity, even in human-modified landscapes (Davies et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; De Marco et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Hill et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). For example, ponds located in a modified landscape in the Brazilian Cerrado increase beta diversity despite their small size (De Marco et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Urban ponds are also important sites for maintaining biodiversity in modified landscapes, with urban ponds showing high taxonomic richness but a different composition from nonurban ponds (Hill et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn human-modified landscapes, natural ponds are extinguished, whereas artificial ponds are created for many purposes, such as water management, recreation and irrigation (2008). There is still controversy about how well an artificial pond can mimic a natural pond (Pechmann et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Brown et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Apinda Legnouo et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kolozsvary and Holgerson \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Artificial ponds may present different biotic and abiotic characteristics than natural ponds do, with differences in hydroperiod, canopy cover, dissolved phosphorus, pH, conductivity, temperature, chlorophyll, vegetation and macroinvertebrates (Kolozsvary and Holgerson \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, the creation of artificial ponds is still important for the mitigation of wetland loss and for the conservation of many species, especially those that depend on water for reproduction (Pechmann et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Brand and Snodgrass \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Simaika et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Additionally, a variety of terrestrial species rely on pond systems for food, water and habitat (Nummi et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Lewis-Phillips et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Many studies have shown that a landscape with a pond network (the so-called “pondscape”) is extremely important for species that use these sites as stepping stones to cross agricultural areas between forest fragments, for example (De Marco et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Simaika et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Calhoun et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Deacon et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). It is important to consider methods to manage the terrestrial area around a pondscape to protect pond ecosystems and biota amid the increase in agriculture and cattle raising.\u003c/p\u003e\u003cp\u003eIn a pondscape, the different landscape elements associated with ponds (e.g., forest fragments, types of plantations, trees, lakes and rivers) can have a significant effect on pond ecosystems. Ponds occurring in pastures and other human-impacted ecosystems can be associated with scattered trees (or isolated trees) left after deforestation to provide shade for cattle. Scattered trees provide a range of ecosystem services that benefit farmers, such as fruit provisioning, shading for cattle, carbon sequestration and nitrogen cycle regulation (Manning et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Hartel et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cuni Sanchez and Lindsell \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These trees are considered “keystone structures” in the landscape because of their disproportionate effect on the ecosystem relative to their small area of occupancy (Manning et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Fischer et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). For example, scattered trees increase landscape connectivity, act as a regeneration core, resting site, and shelter for species that cross a matrix with unfavorable conditions (e.g., forest species crossing open areas), and provide a local microclimate with lower temperature and luminosity and higher humidity, among other benefits (Manning et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). However, there is little information on how scattered trees affect pond ecosystems. To our knowledge, no experimental studies have tested the effects of landscape elements on pond ecosystems. Experimental studies are highly important for providing robust ecological evidence by controlling for multiple confounding factors. Additionally, pond ecosystems are relatively simple systems suitable for replication in experimental approaches (De Meester et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThere is a need to clarify many questions regarding pond ecology, many of which were pointed out by Hill and colleagues (Hill et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The present study unifies ecosystem ecology and landscape ecology to understand whether management strategies can help reduce anthropogenic impacts on ponds. We experimentally evaluated the effects of landscape elements on pond ecosystem characteristics. To do so, we built 12 experimental ponds in a pasture matrix surrounded by forest in a fragmented landscape of the Atlantic Forest, which is a top-ranked biodiversity hotspot globally (Myers et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Ponds were built in pasture areas under three different landscape contexts (treatments): 1) near the edge of a continuous forest (hereafter “edge ponds”), 2) in open pasture (hereafter “pasture ponds”) and 3) under the canopy of scattered trees (hereafter “scattered-tree ponds”). We expected scattered-tree ponds and edge ponds to have similar characteristics due to their tree cover, with higher allochthonous material biomass and conductivity and lower temperature, oxygen, dissolved nutrients, turbidity, and chlorophyll than did pasture ponds. We thus expected scattered trees to act as environmental buffers. In this way, scattered trees, as well as the forest edge, buffer the effect of pasture by diminishing the runoff of terrestrial nutrients and soil and providing a local microclimate with a lower temperature. The input of leaf litter from scattered trees and edge ponds leads to increased conductivity. Nevertheless, pasture ponds are more affected by the absence of tree cover, which favors increases in temperature and phytoplanktonic chlorophyll. Pasture ponds are more susceptible to soil runoff, which increases turbidity and dissolved nutrients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e1. Study area and experimental design\u003c/p\u003e\u003cp\u003eThe study was conducted in a fragmented landscape in Rio de Janeiro, Brazil. The experimental pond system is located in a pasture area surrounded by a private reserve called Reserva Ecológica de Guapiaçu, which comprises approximately 7,200 ha of Atlantic Forest (Almeida-Gomes and Rocha \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Native vegetation is classified as dense evergreen forest, and the climate has two different seasons: one relatively warm and wet and the other colder and drier (Vieira et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Almeida-Gomes and Rocha \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The landscape where the experiment was conducted is a low-intensity pasture where cattle are semiconfined. In these types of pasture areas, it is common to find scattered trees with the purpose of providing shade for cattle (Manning et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn 2016, we established a system of standardized experimental ponds to assess how different landscape elements influence pond ecosystems (Almeida-Gomes et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e, Caires-Souza et al. in prep). The study was conducted within a pasture area bordered by forest fragments of varying sizes. A total of 12 ponds were constructed with an excavator and assigned to three landscape treatments: four ponds situated in an open pasture located 20 m away from the nearest scattered tree (pasture ponds) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea), four beneath scattered trees of the genus Ficus (scattered-tree ponds) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb), and four located at the forest/pasture edge (edge ponds) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Each pond measured approximately 3 m by 2.5 m at a depth of 0.5 m and was lined with a plastic tarp to retain rainwater. To prevent disturbance by cattle, all ponds were enclosed by a barbed wire fence and were spaced at least 50 meters apart. The edge ponds were positioned such that one side bordered the forest while the remaining three sides faced the pasture. Ponds placed under scattered trees were standardized using individuals from the genus \u003cem\u003eFicus\u003c/em\u003e, a group commonly found in tropical pastures that is known to contribute to forest restoration in human-modified landscapes (Cottee-Jones et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Although some shrubs or small trees occasionally occurred nearby, these tree-treatment ponds were characterized by a single dominant \u003cem\u003eFicus\u003c/em\u003e tree that provided the main canopy structure. Statistical analysis confirmed that the distance to the forest edge did not differ significantly between the open pasture and scattered-tree treatments (Welch’s t test; T₃.₈₄ = -0.74; p = 0.50). All ponds were naturally filled with rainwater and naturally colonized by a range of organisms, including algae, macrophytes, invertebrates, and tadpoles.\u003c/p\u003e\u003cp\u003e2. Environmental variables\u003c/p\u003e\u003cp\u003eWe sampled the ponds monthly during the warmer and wet seasons for two years (November 2020–March 2021 and November 2021–March 2021–2022). To evaluate the effects of tree cover on pond characteristics, we measured the following parameters: temperature (°C), conductivity (µS/cm), turbidity (ppm), allochthonous material weight (g/m²), phytoplanktonic chlorophyll (µg/L), oxygen saturation (%) and dissolved nutrient concentration (Ammonium, Nitrate, and Soluble Reagent Phosphorus [SRP]). All parameters were recorded monthly at each pond during the anuran breeding season for 2 years. Each pond was sampled 8 times. We measured conductivity and turbidity with a multiparameter sonde (HANNA®) and temperature and oxygen saturation with a YSI-ProDSS. We collected phytoplanktonic chlorophyll from surface water (top 10 cm), filtered it through Whatman GF-D fiberglass filters, froze the samples, extracted it in 90% alcohol and analyzed it in the laboratory with a fluorometer (AQUAFLUOR®). We sampled the allochthonous material (leaves and branches) with a stove pipe (0.0314 m²), and the material was dried in an oven for 72 hours or until there was no weight difference. Samples for dissolved ammonium (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e), nitrate (NO\u003csub\u003e3\u003c/sub\u003e) and SRP determination were collected and frozen. The dissolved nutrients were analyzed via flow injection analysis according to the manufacturer’s instructions (FIAlab 2500, FIALab Instruments Inc., Seattle, WA, USA).\u003c/p\u003e\u003cp\u003e3. Statistical analysis\u003c/p\u003e\u003cp\u003eAll the environmental variables were standardized to a mean of “0” and a standard deviation of “1”, as they had different scales and units. We ran a \u003cem\u003ePearson\u003c/em\u003e correlation matrix for the raw data via the “cor” function in the R environment to understand the relationships among the variables. We calculated the mean of each variable per pond with the data sampled monthly through the breeding season for two years and then calculated a matrix of dissimilarity between ponds on the basis of Euclidean distances (Legendre and Legendre \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). To test for differences in multivariate dispersions between the treatments (scattered tree, edge, and pasture) in relation to the limnological variables, we carried out a principal component analysis (PCA) with the “vegan” package (Oksanen \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). We did not detect any effect of the different years of sampling in our data. To test whether the difference between treatments was significant, we ran a permutation test (PERMANOVA – 999 permutations) via the “Adonis” function from the “vegan” package (Oksanen \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). We used the function “betadisper” from the “vegan” package to test the homogeneity of variances. All analyses were carried out in R software version 4.4.2 (R Core Team \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe limnological characteristics of the experimental ponds highly varied (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In terms of allochthonous material, edge ponds varied from 183.16 g/m\u0026sup2; to 428.50 g/m\u0026sup2;, scattered-tree ponds varied from 72.86 g/m\u0026sup2; to 387.03 g/m\u0026sup2;, and pasture ponds varied from 67.95 g/m\u0026sup2; to 117.86 g/m\u0026sup2; (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-A). The phytoplanktonic chlorophyll concentration ranged from 0.10 \u0026micro;g/L to 0.19 \u0026micro;g/L in edge ponds, 0.25 \u0026micro;g/L to 0.66 \u0026micro;g/L in scattered-tree ponds and 0.11 \u0026micro;g/L to 0.17 \u0026micro;g/L in pasture ponds (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-B). In terms of conductivity, edge ponds varied from 53.70 \u0026micro;S/cm to 112.46 \u0026micro;S/cm, scattered-tree ponds varied from 63.15 \u0026micro;S/cm to 99.95 \u0026micro;S/cm, and pasture ponds varied from 42.57 \u0026micro;S/cm to 74.73 \u0026micro;S/cm (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-C). The oxygen saturation percentage ranged from 11.13\u0026ndash;53.41% in edge ponds, 9.18\u0026ndash;26.27% in scattered-tree ponds and 26.45\u0026ndash;101.47% in pasture ponds (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-D). The temperature varied from 24.74\u0026deg;C to 27.53\u0026deg;C in edge ponds, 23.90\u0026deg;C to 25.10\u0026deg;C in scattered-tree ponds and 25.42\u0026deg;C to 28.36\u0026deg;C in pasture ponds (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-E). In terms of turbidity, edge ponds varied from 8.53 ppm to 14.82 ppm, scattered trees varied from 7.21 ppm to 20.77 ppm, and pasture ponds varied from 12.04 ppm to 37.95 ppm (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-F). The pond dissolved NO\u003csub\u003e3\u003c/sub\u003e concentration ranged from 17.64 \u0026micro;g/L to 34.66 \u0026micro;g/L in edge ponds, 25.71 \u0026micro;g/L to 134.45 \u0026micro;g/L in scattered-tree ponds and 24.00 \u0026micro;g/L to 115.12 \u0026micro;g/L in pasture ponds (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-G). The dissolved NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e concentration ranged from 83.62 \u0026micro;g/L to 144.81 \u0026micro;g/L in edge ponds, 97.34 \u0026micro;g/L to 1000.78 \u0026micro;g/L in scattered-tree ponds and 57.88 \u0026micro;g/L to 142.98 \u0026micro;g/L in pasture ponds (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-H). The pond SRP concentrations ranged from 7.80 \u0026micro;g/L to 99.72 \u0026micro;g/L in edge ponds, 11.78 \u0026micro;g/L to 701.54 \u0026micro;g/L in scattered-tree ponds and 12.68 \u0026micro;g/L to 73.11 \u0026micro;g/L in pasture ponds (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-I).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe first two axes of the PCA explained 59.5% of the total variability in the ponds\u0026rsquo; biotic and abiotic characteristics (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The PCA separated the scattered-tree ponds from the pasture ponds along Axis 1, and edge ponds were separated from the other two groups along Axis 2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The first axis explains 42.3% of the variation and is associated with dissolved oxygen, SRP and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e concentrations; allochthonous material stock; and conductivity. The positive values correspond to ponds with higher dissolved oxygen, and the negative values correspond to ponds with lower dissolved oxygen but higher SRP and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e concentrations, allochthonous material stock, and conductivity. The second axis explains 17.2% of the variation and is associated with turbidity, SRP, and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e concentrations. Compared with other ponds, scattered-tree ponds tended to have higher SRP and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e concentrations and phytoplanktonic chlorophyll, whereas pasture ponds tended to have higher turbidity, dissolved oxygen, and lower conductivity. Edge ponds had lower turbidity and higher conductivity, as well as greater allochthonous material stock (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe biotic and abiotic characteristics differed significantly among the treatments (PERMANOVA; F\u003csub\u003e(2,9)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;3.67, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, edge ponds appeared to constitute an intermediate group, with some ponds presenting characteristics similar to those of scattered-tree ponds and others similar to those of pasture ponds. The group variances were marginally significantly different (BETADISPER; F\u003csub\u003e(2,9)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;3.62, p\u0026thinsp;=\u0026thinsp;0.07). A pairwise permutation test of the groups\u0026rsquo; variance revealed a significant difference between the scattered-tree and edge ponds (observed p\u0026thinsp;=\u0026thinsp;0.05, permuted p\u0026thinsp;=\u0026thinsp;0.057) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe \u003cem\u003ePearson\u003c/em\u003e correlation analysis revealed moderate positive correlations between dissolved oxygen and turbidity (r\u0026thinsp;=\u0026thinsp;0.43), conductivity and allochthonous material stock (r\u0026thinsp;=\u0026thinsp;0.44), and SRP concentration and phytoplanktonic chlorophyll (r\u0026thinsp;=\u0026thinsp;0.47) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). There was a moderate negative correlation between allochthonous material stock and turbidity (r = -0.4) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These findings indicate that ponds with higher turbidity are likely to have more dissolved oxygen but lower allochthonous material stocks (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Moreover, ponds with relatively high allochthonous material stocks tended to exhibit relatively high conductivity. There was a strong positive correlation between the NH4\u0026thinsp;+\u0026thinsp;and SRP concentrations (r\u0026thinsp;=\u0026thinsp;0.7) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Ponds with high SRP concentrations also presented high NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e concentrations and more phytoplanktonic chlorophyll (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we experimentally assessed the impact of landscape elements on pond biotic and abiotic characteristics, including the role of scattered trees in buffering human impacts on pond ecosystems. We expected scattered-tree ponds to present an ecosystem more similar to edge ponds, highlighting the role of scattered trees in buffering human impacts similar to the proximity of a forest patch. Indeed, pondscape elements (forest edges, pastures, and scattered trees) affect the biotic and abiotic characteristics of ponds. Our results show that the landscape context, particularly the presence of tree cover, is important in determining the abiotic characteristics of ponds. We expected pasture ponds to present high levels of dissolved nutrients, phytoplanktonic chlorophyll, temperature, oxygen, and turbidity. Moreover, we expected scattered trees and edge ponds to present high allochthonous material and conductivity and lower dissolved nutrients, phytoplanktonic chlorophyll, temperature, oxygen, and turbidity. However, our results revealed low levels of similarity between scattered-tree ponds and edge ponds (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Compared with edge ponds, scattered-tree ponds presented higher allochthonous material stocks, conductivities, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and SRP concentrations, and phytoplanktonic chlorophyll contents. In contrast to what we expected, pasture ponds presented lower dissolved NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and SRP concentrations and phytoplanktonic chlorophyll than scattered-tree ponds did.\u003c/p\u003e\u003cp\u003eIn natural systems, ponds shaded by vegetation are known to have inputs of allochthonous material and to be more heterotrophic systems than are ponds without riparian forests, which receive less allochthonous input and have higher primary production (Rubbo et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). For this reason, we expected edge ponds to have characteristics more similar to those of naturally forested ponds with high allochthonous material input because of their proximity to the forest. However, edge ponds are still located within the pasture, and the relative position of the forest edge trees could have affected the quantity of litterfall directly into the pond. Leaf litter input is important for the maintenance of small aquatic systems because it provides energy to consumers directly, as a food source, and indirectly, by providing nutrients for primary production through the decomposition process (Earl and Semlitsch \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Holgerson et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The input of leaf litter can increase the export of organisms to terrestrial ecosystems (Earl and Semlitsch \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and small ponds contribute disproportionately to terrestrial ecosystems by providing prey for many terrestrial species (e.g., amphibians and insects), thus increasing animal diversity in surrounding areas (Nummi et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Rivera Vasconcelos et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lewis-Phillips et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zamora-Mar\u0026iacute;n et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Fehlinger et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this way, factors that affect leaf litter input, such as the presence of scattered trees or pond positioning relative to the nearest forest, could be important drivers determining a pond\u0026rsquo;s contribution to the terrestrial ecosystem. Moreover, the composition of leaf litter is also important for animal diversity, abundance, and fitness (Stephens et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In our experimental system, we expected the scattered-tree and edge ponds to accumulate similar amounts of allochthonous material, but the composition of this material was different: while scattered-tree ponds receive leaf inputs from one tree species (\u003cem\u003eFicus sp\u003c/em\u003e., known to have recalcitrant leaves), edge ponds receive leaf inputs from a variety of species. This difference in leaf litter composition and diversity can affect pond ecosystems and community composition. The lack of leaf litter input can have even stronger effects on pond communities and their consequent ecosystem processes. For example, tadpoles bred in mesocosms with no leaf litter had much lower masses at metamorphosis and lower fitness (Rubbo et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Stephens et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Stoler et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePasture ponds, which lack tree cover and are more exposed to sunlight, are expected to present higher primary production with higher dissolved oxygen (Schiesari \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Rubbo et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In this way, we expected the absence of canopy cover to increase primary production, increasing phytoplanktonic chlorophyll and dissolved oxygen in pasture ponds. This is because light and nutrients are important factors that limit primary production (Bourassa and Cattaneo \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Tromboni et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Our results revealed that, compared with scattered-tree ponds, pasture ponds presented lower phytoplanktonic chlorophyll but high dissolved oxygen contents. Additionally, the scattered-tree ponds had more allochthonous material and higher phytoplanktonic chlorophyll but lower dissolved oxygen. Other studies have shown a negative correlation between leaf litter input and dissolved oxygen, which is consistent with our findings (Rubbo et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Earl and Semlitsch \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This occurred because the increase in leaf litter input increases community respiration (Rubbo et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). However, in contrast to our findings, a negative relationship was also observed between leaf litter inputs and phytoplanktonic chlorophyll (Rubbo et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Earl and Semlitsch \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This finding raises the question of the relationship between primary productivity and leaf litter in small ponds. Small covered ponds are often considered net heterotrophic systems with detrital-based food webs only because of low dissolved oxygen measurements. Nonetheless, a study conducted by Holgerson and colleagues (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) revealed that leaf litter can be an important source of nutrients for algae, which can lead to higher algal quality and quantity than expected. In this way, shaded pond food webs can rely not only on leaf-litter fragments but also on leaf litter-derived algae (Schiesari et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Taylor and Batzer \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In our study, the excess light in pasture ponds may have led to nutrient limitations for phytoplanktonic chlorophyll biomass, while scattered-tree ponds may have received enough light and nutrients to increase it.\u003c/p\u003e\u003cp\u003eBecause ponds are shallow systems, they are more susceptible to wind effects, which cause resuspension of the bottom nutrients, or to nutrients that come from an allochthonous source, which can cause shifting between states (Declerck et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The presence of riparian vegetation, despite providing allochthonous nutrients and organic matter, protects the ponds from the wind effect and diminishes the input of nutrients and soil that comes with the runoff water. In general, forested ponds alternate between two states: clear water with macrophytes (mesotrophic) and turbid water with high chlorophyll concentrations (eutrophic) (Kuczyńska-Kippen et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In contrast, pasture ponds are susceptible to increases in dissolved nutrients due to the close presence of cattle that search these spots to drink water, for example (Miller et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Fierro et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In this way, forested ponds are known to be mesotrophic to low eutrophic systems, whereas pasture ponds are expected to be hypereutrophic systems (Robin et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kuczyńska-Kippen et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, different from what we expected, the scattered-tree ponds presented the highest NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and SRP concentrations. The higher dissolved nutrient concentrations in the scattered-tree ponds may be due to the frequent presence of cattle searching for cooler, shaded areas. This could lead to an increase in manure close to scattered-tree ponds that could run into the ponds. These findings corroborate our results that revealed a moderate positive correlation between the dissolved SRP concentration and phytoplanktonic chlorophyll content.\u003c/p\u003e\u003cp\u003eOur results revealed that pasture ponds presented greater turbidity than edge ponds and scattered-tree ponds did. We expected that turbidity would be correlated with chlorophyll, but this was not the case. Other studies have shown that pond turbidity can be related to the concentrations of dissolved chlorophyll, dissolved organic carbon, or sediment with silt (Declerck et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Robin et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Water transparency is expected to be affected by chlorophyll when it is above 30 \u0026micro;g. L\u003csup\u003e-1\u003c/sup\u003e (Robin et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Our ponds presented chlorophyll concentrations lower than 30 \u0026micro;g. L\u003csup\u003e-1\u003c/sup\u003e, so turbidity can be related to other factors, such as sediment leached from the pasture. All the experimental ponds were located in a pasture area, and all the ponds were fenced to prevent cattle access. However, recent work has shown that fences can be ineffective in preventing the impact caused by cattle (Swartz et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In pasture landscaped areas, cows act as geomorphic agents by increasing soil erosion, diminishing infiltration rates, and increasing the amount of runoff water to aquatic systems (Trimble and Mendel \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Declerck et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Mcdowell and Wilcock \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; O\u0026rsquo;Callaghan et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). We suspect that, because our ponds are located in a pasture area, the presence of scattered trees or ponds close to a forest edge was not enough for this vegetation to act as a filter to pasture nutrient runoff but was enough to lower soil leaching and pond turbidity. Turbidity is an important abiotic factor that can impact pond ecosystems and community structuring and can be used as an impact indicator (Declerck et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Campbell et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Akasaka et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). However, the impact of turbidity on pond communities is still controversial. For many taxa, high levels of turbidity can lead to lower species richness (Campbell et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Akasaka et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). For example, turbidity can have a negative effect on tadpole species richness by decreasing development and survival rates (Wood and Richardson \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Nonetheless, turbidity can also improve tadpole camouflage to predators in this way, increasing tadpole richness (Gregory \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Tavares-Junior et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eScattered trees associated with ponds could represent good breeding sites for many organisms with biphasic life cycles, e.g., anurans and insects. The presence of scattered trees increases species richness in pasture areas near these trees (Prevedello et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). A study conducted in the same experimental system revealed a treatment effect on adult anuran abundance, with higher abundance around edge ponds, followed by scattered-tree ponds and lower abundance around pasture ponds (Almeida-Gomes et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)(Almeida-Gomes et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Importantly, during our study, we found tadpoles of the species \u003cem\u003eAplastodiscus eugenioi\u003c/em\u003e, which is considered a near-threatened species (IUCN - Red list), in our edge ponds. This means that, despite the artificiality of these ponds, their presence in a pasture area created a new breeding environment for a threatened species. Many studies have shown the importance of pond ecosystem heterogeneity for tadpole community structuring (da Silva et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; J\u0026uacute;nior and Rocha \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Tavares-Junior et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe scattered-tree ponds presented the highest degree of ecosystem variability (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), which indicates that the presence of a scattered tree can increase ecosystem heterogeneity. Ecosystem heterogeneity promotes species richness by providing diverse microhabitats, shelters, and food resources (Haddad and Prado \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Tavares-Junior et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fern\u0026aacute;ndez-Al\u0026aacute;ez et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A study with macrophytes revealed that permanent ponds were more environmentally heterogeneous, leading to greater macrophyte diversity (Fern\u0026aacute;ndez-Al\u0026aacute;ez et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Our results revealed that the presence of scattered trees diminished pond turbidity and provided diverse food resources, i.e., leaf litter and algae. These characteristics, associated with the lower temperature due to the microclimate promoted by the scattered trees, could enhance the community diversity and species richness of ponds. In this sense, scattered trees are good landscape elements for the management of pasture landscapes not only to promote the conservation of terrestrial animals but also for the conservation of pond ecosystems and their associated biodiversity.\u003c/p\u003e\u003cp\u003eIn conclusion, all three landscape elements (proximity to forest edges, scattered trees, and open pastures) differentially affected the ecosystem characteristics of the experimental ponds. Scattered trees did not mimic the presence of the edge forest as we expected, but they presented high habitat heterogeneity, which could be beneficial to organisms using ponds as breeding sites. Our results revealed that scattered trees did not buffer the pasture effect on pond ecosystems as we expected, and scattered-tree ponds presented high levels of dissolved nutrients, suspended chlorophyll, and allochthonous material and lower temperatures, dissolved oxygen concentrations and turbidity. However, the presence of scattered trees created a more heterogeneous pondscape and provided more heterogeneity for pond ecosystems, which could increase pond biological diversity (Almeida-Gomes et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and thus represent an important landscape element for the conservation of ponds in fragmented landscapes. Nonetheless, it is still necessary to understand the effects of scattered trees on pond community structure and ecosystem processes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFundings:\u003c/h2\u003e\n\u003cp\u003eJLdCS, BM-F, and VNL received scholarships from CAPES (Finance Code 001). VN-L and EZ were also supported by FAPERJ (E-26/210.060/2024, E-26/201.286/2021, E-26/211.078/2019, E-26/203.213/2017), and EZ received additional support from UERJ Proci\u0026ecirc;ncia and CNPq (Bolsa PQ 304792/2022-5). Funding was also provided by FUNBIO (to JLdCS) and PELD-MCF (CNPq 442349/2020-3).\u003c/p\u003e\n\u003ch2\u003eCompeting interests:\u003c/h2\u003e\n\u003cp\u003eThe authors declare that have no competing financial or non-financial interest that could have influenced the work reported in this paper.\u003c/p\u003e\n\u003ch2\u003eAuthor Contributions:\u003c/h2\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Data collection and material preparation: Beatriz Moreira Ferreira and Jo\u0026atilde;o Luiz de Caires Souza; Data analysis: Beatriz Moreira Ferreira and Vinicius Neres Lima; Writing\u0026mdash;original draft: Beatriz Moreira Ferreira; Writing\u0026mdash;review and editing: Beatriz Moreira Ferreira, Jayme Prevedello, Jo\u0026atilde;o Luiz de Caires Souza, Vinicius Neres Lima and Eugenia Zandon\u0026agrave;. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eWe thank the Reserva Ecol\u0026oacute;gica de Guapia\u0026ccedil;u (REGUA) for logistical support. We are especially grateful to all who assisted with fieldwork and the construction and maintenance of the experimental ponds, including Orlando M. Vogelbacher, J\u0026uacute;lia E. da Silva, Jefferson R. Amaral, Leticia B. da Silva, Bruna S. da Silva, Karoline E.F. Lacerda, Leticia Castro, Kauan N. Fonseca, Cec\u0026iacute;lia L. Silva, Vitor N.T.B. J\u0026uacute;nior, Maur\u0026iacute;cio de A. Gomes, Caio H.G. Barcellos, Marcus V. Vieira, Jo\u0026atilde;o Gabriel Pannunzio, and Pedro Paulo da S. Ferreira.\u003c/p\u003e\n\u003ch2\u003eData Availability:\u003c/h2\u003e\n\u003cp\u003eData supporting the findings of this study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkasaka M, Takamura N, Mitsuhashi H, Kadono Y (2010) Effects of land use on aquatic macrophyte diversity and water quality of ponds. 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Hydrobiologia 848:1623\u0026ndash;1638. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/S10750-021-04552-7/FIGURES/5\u003c/span\u003e\u003cspan address=\"10.1007/S10750-021-04552-7/FIGURES/5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008) The Pond Manifesto\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"abiotic and biotic factors, small waterbodies, isolated tree, pasture landscape, Atlantic forest","lastPublishedDoi":"10.21203/rs.3.rs-7429547/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7429547/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHuman-driven landscape modifications threaten pond ecosystems worldwide. The conversion of landscapes from forests to pastures can have significant impacts on pond biodiversity and ecosystem processes. Scattered trees are common elements in deforested landscapes and represent keystone structures because they increase biodiversity. Moreover, scattered trees are often associated with ponds, potentially affecting their structure and function. Here, we experimentally investigated how pond ecosystems respond to different landscape elements, including scattered trees. We built an experimental set of 12 ponds in a pasture area with three treatments: ponds near the edge of a continuous forest, those under the canopy of a scattered tree and those in the open pasture. To test the effects of the treatments on the biotic and abiotic characteristics of the ponds, we quantified water temperature, oxygen, dissolved nutrients (NO₃⁻, NH₄⁺, and PO₄\u0026sup3;⁻), turbidity, conductivity, allochthonous organic material and phytoplanktonic chlorophyll. Scattered-tree ponds presented relatively high concentrations of dissolved NH₄⁺ and PO₄\u0026sup3;⁻, as well as relatively high levels of phytoplanktonic chlorophyll. Edge ponds presented relatively high levels of allochthonous organic material and conductivity, whereas open-pasture ponds presented relatively high temperatures, oxygen concentrations and NO₃⁻ concentrations. Our results provide evidence that landscape elements can have diverse effects on pond ecosystems. Although we expected scattered-tree ponds to resemble edge ponds by buffering the impact of the pasture, the presence of a single scattered tree created a distinct and novel environment. Scattered trees associated with ponds thus represent important elements that contribute to increasing ecological heterogeneity in deforested landscapes.\u003c/p\u003e","manuscriptTitle":"Effects of scattered trees on pond ecosystems: experimental evidence from a biodiversity hotspot","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 04:12:59","doi":"10.21203/rs.3.rs-7429547/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7239cb3c-8826-4261-b22d-977789bb26e2","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-17T20:28:32+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-09 04:12:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7429547","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7429547","identity":"rs-7429547","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}