Combining local data and scientific models to prioritize conservation for European ground squirrel and safeguard grassland habitats

Combining local data and scientific models to prioritize conservation for European ground squirrel and safeguard grassland habitats | 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 Combining local data and scientific models to prioritize conservation for European ground squirrel and safeguard grassland habitats Tijana Nikolić Lugonja, Rogier Pouwels, Maja Arok, Dimitrije Radišić, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4822522/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Jan, 2025 Read the published version in Landscape Ecology → Version 1 posted 13 You are reading this latest preprint version Abstract Context Promoting habitat networks of natural grasslands within agricultural landscapes is crucial to supporting biodiversity and protecting endangered grassland species. Understanding the degree of fragmentation of these habitat networks assists in better elucidating their value to the grassland network. However, natural grassland characteristics in intensively used landscapes often need to be more adequately documented, which hinders effective grassland biodiversity conservation. Objectives We combined local data and modeling to identify conservation priorities for natural grasslands through assessing population and habitat patch characteristics for European Ground Squirrel ( Spermophilus citellus , EGS), a keystone grassland specialist, in agricultural settings. Methods We used available information with presence/absence data and two spatially explicit models (LARCH and Circuitscape) to assess the potential of the current landscape in northern Serbia to protect the EGS. We applied the LARCH model to indicate potential habitat networks for the EGS and Circuitscape to assess connectivity of areas within and between these networks and identify areas of interventions that will serve as corridors between networks after restoration work. Together with the presence/absence data, this is used to set priorities for conservation actions for each network. Results We identified the presence of 15 habitat networks. The networks differ in connectivity, size, capacity, and sustainability to support local EGS populations. Conclusions The results revealed areas on which spatial adaptation measures and actions should be deployed to accommodate the long-term survival of EGS. In addition, the findings help the conservation of (semi)natural grassland and future land planning in terms of sustainable land use in an agricultural setting. EGS grasslands connectivity LARCH conservation monitoring data Circuitscape Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Increased food production in agricultural areas (especially during the second half of the 20th century) often results in habitat degradation, fragmentation and loss, requiring conservation actions to protect species inhabiting the remaining (semi)natural habitats, e.g., grasslands. Often the focus of these conservation actions is to use the remnant fragments and isolated sites as a foundation for developing regional green networks within which measures and actions may be deployed, albeit with limited resources (Green et al. 2018). Establishing a network of well-connected sites allows individuals of species to access food and water, find mates, conquer new potential habitats and exchange individuals with other populations (Hilty et al. 2020 ; Unnithan Kumar and Cushman 2022 ). In the long term, a stable habitat network also offers species the chance to shift their ranges as an attempt to adapt to climate change (Heller and Zavaleta 2009 ; Hannah 2011 ; Littlefield et al. 2019 ). However, network-level habitat connectivity rarely guides plans of conservation actions and measures (Jalkanen et al. 2020 ). Recent research emphasizes the imperative to augment wildlife sites in terms of size, quality, connectivity, and quantity (Lawton et al. 2010; Hodgson et al. 2011 ). Since stochastic events are more damaging for small and isolated populations, increasing population size by enlarging habitat patches (“bigger”), increasing their quality (“better”), connecting them with other patches using corridors (“joined”) and even creating new habitats through restoration actions (“more”) should work in favor of increasing the resilience of the habitat network and boosting metapopulation dynamics, crucial for fighting global changes (Isaac et al. 2018). Therefore, it is evident that habitat patch quality, size, and density, as well as the matrix in between the habitat patches must be considered when designing conservation strategies of species (Hanski and Ovaskainen 2000 ; Fahrig 2003 ; Opdam et al. 2003 ; Fahrig 2011; Didham et al. 2012 ; Rybicki and Hanski 2013 ; Synes et al. 2020 ). Scattered within a heavily used agricultural landscape of central and south-eastern Europe, lives the endangered European ground squirrel ( Spermophilus citellus L. 1766, EGS). Due to agricultural use, land abandonment, urbanization, and increasing road networks, the distribution of this species has declined in Serbia and across its range. As a result, it currently holds the status of strictly protected in the Serbian legislature (Official Gazette R. Serbia 2010), is listed in Annex II of the Habitats Directive and Annex IV of the Species Directive, and Appendix II of the Bern Convention, and has been categorized as endangered (EN) on the IUCN red list of species (Council Directive 92/43/EEC; Council of Europe 1979; Hegyeli 2020 ). The iconic grassland inhabitant requires precise management actions. As it is a keystone species of (semi)natural grasslands, its disappearance from these areas negatively impacts broader grassland communities (Lindtner et al. 2018 , 2020 ). EGS is a small herbivore mammal (Rodentia: Sciuridae) with a functional role in improving soil structure, nutrient cycling, and maintaining plant community composition (Lindtner et al 2020 ). Its presence influences the abundance of other animal populations as it is an essential link between different trophic levels; and since individuals can alter habitats and regulate resources, EGS is considered a terrestrial ecosystem engineer (Lindtner et al. 2018 ; 2019 ; 2020 ). Therefore, we consider it a reliable indicator and model organism for conserving natural grassland ecosystems. EGS remains in habitat patches in northern Serbia within a primarily agricultural landscape. Assessing habitat and landscape-level conditions and patterns can be significant, given the long-term downward trend in the distribution of grasslands and the adverse effects of this loss on the broad natural grassland community within the agricultural landscapes (Marini et al. 2019 ). For example, grassland habitat capacity and surrounding landscape heterogeneity showed environment-induced changes in small mammals’ local population distribution or demography (Nikolić et al., 2019 ; 2020 ). Available evidence indicates that the agricultural matrix may impede or facilitate the movement of individuals (Fahrig et al. 2011 ; Vasudev et al. 2015 , Keeley et al. 2021 ), suggesting that structural and functional connectivity of grassland patches affects population viability and the long-term survival of targeted populations. Intensive population monitoring and comprehensive analysis of EGS habitat distribution could help prioritize conservation initiatives of natural grasslands within the agricultural landscape (Nikolić et al. 2019 ). For a ground-dwelling species like EGS, knowledge of landscape permeability and habitat connectivity is essential. Usually, this is acquired by including exact or estimated population data in a multi-scale, multi-level hierarchical modeling framework (McGarigal et al. 2016 ; Zeller et al. 2016 ; 2017 ). In these cases, spatially explicit models and keystone species data are relevant for choosing the most effective planning strategy for conservation, improving habitat quality, increasing quantity, and/or restoring connectivity (Hodgson et al. 2010; Marjakangas et al. 2023 ). This study aimed to assess the viability of current populations of EGS in northern Serbia and determine the connectivity of natural grassland habitats to prioritize conservation measures and actions. The study's findings and recommendations could help inform conservation efforts and management strategies to support the viability of EGS populations and enhance the overall conservation of natural grassland habitats in northern Serbia. Thus, the investigation aimed to (1) establish the locations of connected grassland habitat clusters (habitat networks), (2) assess dispersal connectivity within and between these networks and identify areas of “interventions” which will serves as corridors after restoration work (3) use the presence/absence data to determine the differences among these networks and prioritize conservation measures. To achieve these objectives, we applied a framework (Fig. 1 ) that combined local knowledge of EGS habitat preferences and dispersal capacity (Ćosić et al. 2013 ; Nikolić et al. 2019 ), two scientific models, and monitoring data (Nikolić et al. 2019 ). The models were used to assess the potential viability of the populations within the ecological networks and the connectivity within and between these networks. The monitoring data was further used to prioritize conservation measures such as improving quality or connectivity within or between the networks. Materials and methods Study area The study was conducted in Vojvodina, an autonomous province in the northernmost part of Serbia with a total area of 21 506 km 2 . Only about 6% of the area is under some form of protection (Puzović et al. 2015 ) and vast areas are designated for intensive agricultural production. EGS occupies 2.3% of the study area and its distribution has rapidly declined in the last few decades (Nikolić et al. 2019 ). As a result of the large-scale conversion of natural grasslands into arable land in Vojvodina during the second half of the 20th century, most local EGS populations are restricted to small remnant grassland patches inside a predominantly agricultural matrix (Nikolić et al. 2019 ). The number of occupied and abandoned patches (Fig. 1 ) varies across different spatial scales, reflecting the species’ response to the declining landscape heterogeneity (Fahrig et al. 2011 ). Overview of modelling framework We used a three-step framework to identify the conservation priorities in grassland habitat distribution for EGS (Fig. 2 ). In the first step, we identified the potential ecological networks for EGS. The ecological networks were determined based on the dispersal capacity of EGS and the potential viability of these networks was based on the habitat quality of the patches, the configuration of these networks and the presence of so-called potential key patches (Verboom et al. 2001 ). For this step, the model LARCH was used (Opdam et al. 2003 , Verboom and Pouwels 2004 ). As the LARCH model indicates potential habitat networks based on species' dispersal capacity, it overestimates the connectivity between patches for ground-dwelling species such as EGS. Therefore, the potential viability of these networks is met when connectivity between patches is not a problem. In the second step, we developed resistance maps for EGS and identified areas with weak connectivity within the ecological networks. We also determined the potential connectivity between the networks to identify locations for corridors. For this step, the model Circuitscape was used (McRea et al. 2008; 2009). This provided information on which network lacks connectivity and where areas are located that could connect different networks. Finally, in step three, we combined the information from the models with monitoring data to distinguish between different categories of ecological networks and prioritize conservation measures for EGS in northern Serbia. Ecological network of European ground squirrel habitats For the present study, the map of 195 identified potential habitat patches provided by Nikolić et al. ( 2019 ) was adopted along with researchers’ field data and experience. We used the land use type to determine the main habitat suitability and four additional criteria as correction factors (see details in Supplementary file section S1.1). The total score for habitat quality in the patch was based on all five criteria (Table S1 ). The full list of scores and locations of the mapped habitat patches is available in Table S2. The habitat map was input for LARCH to assess the habitat patch capacity and determine the habitat networks of EGS. A dispersion capacity of 5 km for ESG was adopted from Nikolić et al. ( 2019 ). Sometimes EGS can disperse further, which is important for genetic exchange. However, these rare events should be neglected for metapopulation dynamics, and dispersal distance in LARCH is set at a distance that includes 90% of all dispersal events (Opdam et al. 2003 ). LARCH estimates the potential number of reproductive units (RUs) in every patch based on the habitat quality and size of the patches (Verboom and Pouwels 2004 ). For small mammals, a patch of one ha with the highest quality index is expected to potentially accommodate at least 5 RUs. The obtained results can be used to identify key patches (KPs). A key patch is defined as a patch large enough to contain a population with an extinction chance of less than 5% in 100 years, given an immigration rate of 1 individual per generation (Verboom et al. 2001 ). These patches act as sources within ecological networks and are often occupied when the species is present in that specific ecological network (Verboom et al. 2001 ). The threshold for short-lived mammals of 100 RUs was used in this study to identify key habitat patches (Verboom et al. 2001 , Verboom and Pouwels 2004 ). As individuals live in small colonies with a female biased sex ratio that are more sensitive to local extinction due to disturbances compared to species that reproduce as pair, we used 500 RUs as a threshold for a viable network for EGS instead of the standard of 200 RUs that is used for small rodents like voles (Verboom and Pouwels 2004 ). Assessing connectivity within and between ecological networks We used different methods for assessing the connectivity within- and between-ecological networks dispersal. We differentiated between the connectivity assessments to 1) identify patches within the networks that could be situated beyond the range of key patches, thereby posing potential risks for occupation and 2) to pinpoint potential corridors between ecological networks. For the connectivity within ecological networks, we assessed the connectivity between key patches to other patches in the ecological network as key patches act as sources and an ecological network is more stable when patches are well connected to key patches (Vos et al. 2007 ). We followed the variation in landscape patterns and their impact on EGS habitat cohesion at previously tested scales found by Nikolić et al. ( 2019 ). We assumed that the movement of individuals within the network is constrained by the quality of habitat and its surroundings. The characteristic of the habitat is defined in table S1 and for the quality of the surroundings we used information from Nikolić et al. ( 2019 ; 2020 ). For the assessment of the connectivity between ecological networks we assessed the connectivity between all patches as potential gene flow between networks is determined by all patches in the landscape. We assumed that dispersal of individuals is mainly determined by the type of land use, elevation and water courses between networks and not by detailed information within the networks (Mateo-Sánchez et al. 2015 ). We used Circuitscape (v 4.0; McRea et al. 2009) to identify the area of the highest landscape permeability (between networks) and the potential movement trajectories of individuals within the habitat networks (within networks). Circuitscape uses circuit theory and resistance (or conductance) surfaces to predict connectivity between nodes (source), whereas high current intensity between them identifies areas and paths potentially crucial for patterns of animal movement (McRae et al. 2008 ; 2009 ). Thus, we developed species-specific baseline maps of landscape permeability and habitat connectivity for EGS in the lowland area of Vojvodina. We employed the resistance-by-distance method between mapped EGS patches (source–network nodes) to develop between and within network connectivity models. All 195 patches from the dataset Nikolić et al. ( 2019 ) were used as input for assessing connectivity between networks and key patches generated by the LARCH model for assessing connectivity within networks. We generated a “current density” surface within the study area to assess between networks connectivity with the developed resistance raster and mapped habitat patches (see details in Supplementary file section S2.1). This model estimates connectivity across every possible movement trajectory among every pair of locations (mapped patches) in the so-called pairwise mode. To generate potential movement maps of individuals within habitat networks, we used the resistance surface, key populations as source nodes, and all other mapped patches as ground nodes - the locations individuals dispersed into (see details in Supplementary file section S2.2). This way, the “current” surface is estimated based on a 1:1 iteration between source and ground nodes, where we set source nodes to have a current value of 1 and ground nodes to have a current value of 0. Prioritizing conservation measures for each network We combined information from the LARCH analyses and the Circuitscape analyses with monitoring data to choose which main conservation strategy (Hodgson et al. 2010) or combination of strategies might be needed to improve the viability of population networks of EGS in northern Serbia. We distinguished between; current measures are sufficient, improve habitat quality of patches, restore more patches within network, improve connectivity within network and connect to other (viable) networks. For currently unoccupied networks it could be considered not to invest in further conservation efforts and use resources for improving still occupied networks that are not viable. Ecological networks with weak connectivity and potential areas for connecting ecological networks were used to indicate those areas that should be improved to enhance the dispersal of EGS within and between networks. Results Viability of habitat networks of EGS All habitat patches cover a combined area of 2586 ha in Vojvodina. Within the Banat region, 12.8% of the patches are of excellent or sound quality, while only 1% of the patches in Bačka and Srem are in this category (Supplementary file section S1.2; Table S2, Fig. S1 ). LARCH defined 15 potential habitat networks. Six of these networks have habitat patches big enough to sustain populations with more than 100 reproductive individuals (i.e., key populations; Fig. 3a). The number of key patches within those six networks vary (Table 1 ). Five networks, with ID_2, 4, 5, 8, and 13, are considered potentially viable (Table 1 ). One network, with ID_9, contains only one key patch, while the total network is large enough for approximately 350 RU. Table 1 LARCH modeling results for the fifteen habitat networks. Names are based on the location within the regions of the potential populations within the habitat networks (see also Fig. 3a, b) Network ID Name # Patches # Key patches Average quality Sum RU Viability 1 Small South Banat 5 0 0.45 84 no 2 Fruška gora 27 2 0.74 1012 yes 3 Farkaždin 1 0 0.00 0 no 4 Lok 5 2 0.65 607 yes 5 Greater South Banat 96 22 0.72 9187 yes (strongly) 6 Begejci 1 0 0.75 14 no 7 Gakovo 3 0 0.33 2 no 8 Central Banat 32 19 0.73 6885 yes (strongly) 9 Tomislavci 12 1 0.33 364 no 10 Bačko Dušanovo 1 0 0.50 4 no 11 Aleksa Šantić 1 0 1.00 23 no 12 Aradac 3 0 0.50 35 no 13 Trešnjevac 3 1 0.83 805 yes 14 Bikovo 3 0 0.67 98 no 15 Srpski Krstur 2 0 0.38 41 no Connectivity within and between ecological networks The ecological networks with the highest viability are the best-connected ones (Fig. 3b, Table 1 ). Of all the networks with more than ten patches, network 8 shows the highest connectivity (Fig. 4a, b). Network 5 is also well connected for most of the patches. Of all the viable networks, network 2 shows the lowest connectivity and many patches are not well connected with the more stable key patches. Prioritization of conservation measures Comparing the LARCH results and the monitoring data showed that potentially viable population networks and key patches provide a good base for protecting EGS. The results show that 93% of all key patches and 54% of others are occupied. Also, 66% of all patches are occupied in viable networks, and in non-viable networks, only 38%. The only patch occupied in network 9 was, in fact, the key patch. When the current network only has a few patches and these are all abandoned, they may be considered as a lost cause. Alternatively, they may be given a low priority as large efforts are probably needed; networks with ID 1, 3, 6, 7, 10, and 15. When resources are scarce, priority should be given to currently occupied patches at risk if they are not viable or have connectivity gaps. Based on the analyses, we conclude that two networks (5 and 8) need no further conservation measures. However, connecting them with the surrounding non-viable networks will improve overall networks sustainability. The analyses showed that the third viable network (2) lacks connectivity. It can be restored by improving the permeability within the network or by restoring more patches (Table 2 ). This will improve the gene flow in these networks’ total population of EGS. The analyses also show that in the northern part of Vojvodina, several small networks contain occupied key patches that are not viable; networks with IDs 9, and 13 and occupied networks without key patches; networks with IDs 11, 12 and 13. These networks are at risk of becoming abandoned as they are isolated. Connecting these networks with other one another or with network with ID 8 will improve the stability of the total EGS population in the northern part of Vojvodina. Table 2 Overview of networks and preferred conservation measures based on the LARCH and Circuitscape results, and monitoring data. Connectivity within networks is assessed as high when large parts of the network have a high connectivity, moderate when some parts of the network have a high connectivity, low when none of the network has a high connectivity (Fig. 3a) and it is not assessed when the network consist of one habitat patch. Connectivity between networks is assessed as high when a potential corridor, regardless the distance, to another network is all high, it is assessed moderate when a potential corridor is partly high and low when it shows no clear potential corridor (Fig. 3b). Netw. ID Name Average quality Patches % Occupied Key patch Viability Connectivity within networks Connectivity between networks Cons. measures* Conservation measures (Hodgson et al. 2010) 1 Small South Banat 0.45 5 0 no no low high 1 and 4 improve quality and connect to 5; or no further conservation efforts 2 Fruška gora 0.74 27 78 yes yes low moderate 2 and 3 improve connectivity within the network and restore more patches within the network 3 Farkaždin 0.00 1 0 no no - high 1 and 4 improve quality and connect to 5; or no further conservation efforts 4 Lok 0.65 5 100 yes yes moderate moderate 2 and 3 improve connectivity within the network and restore more patches within the network 5 Greater South Banat 0.72 96 61 yes yes (strongly) moderate high 0 preserve current status of the network 6 Begejci 0.75 1 0 no no - low 4 connect to 8; or no further conservation efforts 7 Gakovo 0.33 3 0 no no low low 1 and 4 improve quality and connect to one large network with ID's 9-149; or no further conservation efforts 8 Central Banat 0.73 32 69 yes yes (strongly) high high 0 preserve current status of the network 9 Tomislavci 0.33 12 8 yes no low low 1, 2 and 4 improve quality, restore more patches and make one large network with ID's 9–14 10 Bačko Dušanovo 0.50 1 0 no no - low 1 and 4 improve quality and make one large network with ID's 9–14; or no further conservation efforts 11 Aleksa Šantić 1.00 1 100 no no - low 2 and 4 make one large network with ID's 9–14 12 Aradac 0.50 3 100 no no low high 1 and 4 improve quality and make one large network with ID's 9–14 and/or connect to 8 13 Trešnjevac 0.83 3 67 yes yes moderate high 4 make one large network with ID's 9–14 14 Bikovo 0.67 3 100 no no low low 4 make one large network with ID's 9–14 15 Srpski Krstur 0.38 2 0 no no low moderate 1 and 4 connect to one large network with ID's 9–14; or no further conservation efforts * 0 = current measures are sufficient, 1 = improve quality of patches, 2 = restore more patches within network, 3 = improve connectivity within network and 4 = connect to other networks (with ID's) Discussion Combining the results from LARCH and Circuitscape with the monitoring data from Nikolić et al. ( 2019 ) provides a good overview of potential conservation measures for each network. Although Circuitscape analyses show that the connectivity of some viable networks might need improvements (Table 2 ) certain discrepancies should be noted, as connectivity between network areas identified by the “circuit” method is significantly larger than expected based on within-network connectivity (Fig. 3a, b; Table 2 ). The connectivity results provide insight into the potential improvement zones for restoration measures to improve natural grassland cover and enhance the likelihood of long-term survival of EGS and grassland species in the study area. Thus, spatial plans should include an increase in habitat surface area, habitat density, and habitat quality (Verboom and Pouwels 2004 ; Bierwagen 2007 ; Kalarus and Novicki 2015; Van Teeffelen et al. 2015 ; Albert et al. 2017 ; Benedek and Sîrbu 2018 ; Benedek et al. 2021 ; Barão et al. 2022 ). The study confirmed that between-network and within-network connectivity is poor in the majority of identified habitat networks located north within our study landscape (i.e., all situated north of the ID_8 network). In this area, we should perform landscape-level conservation planning to increase the percentage distribution and density of natural grassland habitats and habitat-level measures to ensure adequate habitat management and improve the presence of transitional habitats. This approach would enable viable networks at the regional level in the most efficient way (Jackson and Fahrig 2012 ; Chen et al. 2023 ). The results yielded by this study, along with the produced maps, provide an example of where good spatial governance could support EGS and other natural grassland species and ecosystems. Even though criticized, the species-specific network approach in highly modified agricultural areas is suitable since the complexity of its application is neutralized with biodiversity localized in the remaining semi-natural parts of the landscape (Jalkanen et al. 2020 ). For example, the identified KP in this study needs connections to all local populations by improving surrounding grassland habitat network links (e.g., to secure connections between the identified KP and other populations in the different parts of the network ID_2). Similarly, connecting the KP with other mapped but abandoned habitat patches by increasing the amount of habitat along with improving the quality by establishing regular habitat management (mowing or grazing) could potentially ensure the stability of such network. Sometimes translocation of individuals to those abandoned habitats might be necessary as some networks are isolated (e.g., in the network ID_9). Management of the sustainable network links is crucial when considering network cases such as the viability in the ID_2 network, which depends much more on the environment than on stochastic demographic processes (Ćosić 2015 ), highlighting the importance of spatial factors in the preservation efforts aimed at this part of the studied landscape. Furthermore, connecting isolated habitats characterized by medium-size capacity and populations with sufficiently large densities embodied in moderately permeable landscapes (e.g., ID_4) by steppingstone grassland corridors will increase the viability of populations within the network (Howell et al. 2018 ; Mims et al. 2023 ; Mohammadpour et al. 2023 ; Kim et al. 2024 ). Finally, improving grassland habitat density within the sustainable network in its impermeable parts (e.g., KP and other habitats in network ID_5) would positively affect abandoned habitats within the adjusted unsustainable ones (habitats in network ID_1, whose capacity needs improving). This comprehensive strategy would also enhance the local as well as the regional population’s resilience to the predicted increase in the frequency of extreme weather events because more extensive and more stable populations have a better chance of survival (Coetzee 2017 ; Frankham et al. 2017 ; Ashrafzadeh et al. 2020 ). Transitional habitats that individuals use during dispersal differ significantly from those suitable for life and reproduction (Pulliam 2000 ; Cushman et al. 2013 ). In the present study, areas with only one or two inhabited or abandoned habitats (ID_3, ID_6, ID_7, ID_10, and ID_15) are essential for connectivity between networks and the connection of regional populations in the landscape. Furthermore, in improving the connections, we should simultaneously improve habitat and landscape characteristics (Howell et al. 2018 ; Fahrig 2019 ). Promoting connectivity between networks is relevant since even a few immigrants can establish gene flow between populations. This assertion supports the findings reported by Ćosić et al. ( 2013 ), indicating no genetic bottlenecks for EGS in Vojvodina in the recent past. As shown by available evidence, changes in land use can potentially prompt EGS to leave unsuitable areas. For example, Nikolić et al. ( 2019 ) have established that, compared to the historical prevalence of EGS populations in Vojvodina, they have recently moved east and south, where they currently thrive in the most significant numbers. Researchers used the LARCH model in several studies to estimate the viability of populations on several dispersion scales (Van der Sluis et al. 2003 ; 2005 ; 2009 ; Pazúrová et al. 2018 ). The model relies on ecologically evaluated landscape indices (habitat suitability and capacity, dispersion, and population size) from the perspective of an analyzed species or group of species. The previous practice has shown that habitat capacity is a sensitive model parameter (Verboom et al. 2001 ; Verboom and Pouwels 2004 ; Regolin et al. 2021 ). For this reason, we conducted additional field research to evaluate the habitat capacity values yielded by the LARCH model. Moreover, even smaller areas can support more extensive and stable populations in these habitats, as shown by genetic analyses (Ćosić et al. 2013 ), indicating that combining model output with local knowledge improves the robustness of the results. For our research, the evaluation of habitat quality might even be further enhanced via quantitative methods such as analysis of satellite images and vegetation indices. In the present study, for EGS - a grassland habitat specialist, we evaluated spatial connectivity within and between the habitat network scale to provide an overview of all connectivity links and potential corridors (McRae et al. 2008 ; Zeller et al. 2012 ). The scale of this spatial variation has already provided insights for natural grassland restoration and the proposal for designation of some regions of Vojvodina as designated ecological zones for protecting grassland ecosystems (Nikolić et al. 2019 ). Information related to the permeability of certain landscape areas is helpful to identify areas in which one should direct investments to promote grassland connectivity. For example, in their study, Ćosić et al. ( 2013 ) demonstrated that historically, the Danube is a barrier between populations. Still, the Tisza River is not. This assertion is confirmed by establishing the Vojvodina landscape matrix permeability. In addition, our analysis aids in identifying parts of functionally unlinked areas within and between networks, representing areas at which to focus revitalization measures of the grassland cover to support EGS viability and grassland biodiversity. However, our findings are insufficient for determining how common EGS movements are, as the assessment of habitat connectivity within the heterogeneous matrix depends not only on individual traits but also on the available empirical data on the movement of individuals (Zeller et al. 2012 ; 2014 ). Therefore, the main limitation of the present study stems from the need for more information. Future research should focus on telemetry studies, landscape genetics analyses, and obtaining improved habitat maps (e.g., EUNIS level IV). Findings yielded by such investigations would significantly improve the current knowledge of the movement of EGS individuals through the landscape matrix and the response of individuals and populations to changes in land use. This information might help to improve parameters for dispersal capacity and permeability values of the landscape. This knowledge might be helpful in prioritizing the conservation measures needed in the northern part of the region where networks need to be connected to protect currently occupied networks, like networks ID_9 and 11–14. In conclusion, conservation measures at the regional level could yield results quickly, establishing sustainable habitat networks capable of buffering climate change in the long term (Beier et al. 2008 ; Albert et al. 2017 ; Keeley et al. 2021 ). The implementation of active measures related to land use designation for agricultural activities and restoration of natural grassland habitats need to consider the ownership structure of parcels or the inclusion of the private sector into conservation initiatives (Waldron et al. 2020 ). Moreover, when planning designated areas, a comparative analysis of people's societal and economic needs that depend on the targeted landscape is mandatory. In this context, the spatial approach can be precious, as it facilitates collaboration among different sectors and interest groups on strategic planning (Keeley et al. 2019 ; Hilty et al. 2020 ). Finally, even though this study only focused on the European ground squirrel as a model organism, the conceptual and methodological approach we used and the results we obtained might be applied for other species and ecosystems to prioritize between conservation measures to improve habitat quality, increase habitat quantity or improve connectivity (i.e. Hodgson et al. 2010). Declarations Acknowledgements We would like to thank the European ground squirrel community, Bird Protection and Study Society of Serbia and local community for friendly advice during fieldwork campaign. Funding: This work has been supported by The Ministry of Science, Technological Development and innovation, Republic of Serbia, under Grant 2024: 451-03-66/2024-03/ 200358, The Rufford Foundation grant “Building a better future for European ground squirrel in Serbia” and H2020 project ANTARES (SGA-CSA. No. 739570). Competing Interests: The authors have no relevant financial or non-financial interests to disclose. Author Contributions: TNL, RP and W GW W, contributed to the study conception and design. Data collection and analysis were performed by TNL, MA, DR, DĆ and NĆ. The first draft of the manuscript was written by TNL, RP and MA and all authors commented on previous versions. All authors read and approved the final manuscript. Data Availability: The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. References Albert CH, Rayfield B, Dumitru M, Gonzalez A (2017) Applying network theory to prioritize multispecies habitat networks that are robust to climate and land‐use change. Cons Biol 31(6):1383-1396. https://doi.org/10.1111/cobi.12943 Ashrafzadeh MR, Khosravi R, Adibi MA, Taktehrani A, Wan HY, Cushman SA (2020) A multi-scale, multi-species approach for assessing effectiveness of habitat and connectivity conservation for endangered felids. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4822522","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":345966838,"identity":"ff4e245c-7bfa-4388-b3ac-8e99e340af7b","order_by":0,"name":"Tijana Nikolić Lugonja","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIie2PMUvDQBiGXylcli/tehDRvyAU7GCof+WOg7hIKHTN0OmyFLvWyb9yEshUdBWyGBz8AQURGtRLKaVgjjo63LMkHDzf+76Ax/Mf6UFsv4xwYgRiwY4ZdKDAKskflMM/AxTiaK/rAPV6kiHtU2HMa/ac9oO8fps0MUYL4yqmomWJKQu1MKKspoxWw+G9TnD60p3YbomIQeoBXRg5q6TmtywKZwU4d2yxKRv62itPVrl531DzDT5wFkuiUFslnLeKsYq47BEz4HAUK5BchXdcairbLWq7xR5RxHm3EixWqqKPWD7M1WP9mY3T8zyv19SMz1zFbE57q2Mp/X7a57hueTwej2fHD/A+VOPLbjtPAAAAAElFTkSuQmCC","orcid":"","institution":"University of Novi Sad","correspondingAuthor":true,"prefix":"","firstName":"Tijana","middleName":"Nikolić","lastName":"Lugonja","suffix":""},{"id":345966839,"identity":"d7c9e1fa-b64f-4edd-b188-863c331d3891","order_by":1,"name":"Rogier Pouwels","email":"","orcid":"","institution":"Wageningen University and Research","correspondingAuthor":false,"prefix":"","firstName":"Rogier","middleName":"","lastName":"Pouwels","suffix":""},{"id":345966840,"identity":"7fb46455-f1c9-4361-810c-79d353f3eb58","order_by":2,"name":"Maja Arok","email":"","orcid":"","institution":"University of Novi Sad","correspondingAuthor":false,"prefix":"","firstName":"Maja","middleName":"","lastName":"Arok","suffix":""},{"id":345966841,"identity":"a3e36031-c996-4c05-bd46-8bec1bf3afce","order_by":3,"name":"Dimitrije Radišić","email":"","orcid":"","institution":"University of Novi Sad","correspondingAuthor":false,"prefix":"","firstName":"Dimitrije","middleName":"","lastName":"Radišić","suffix":""},{"id":345966842,"identity":"84ef05cf-3d8a-4660-afba-77fab5fd9b82","order_by":4,"name":"Nada Ćosić","email":"","orcid":"","institution":"University of Belgrade","correspondingAuthor":false,"prefix":"","firstName":"Nada","middleName":"","lastName":"Ćosić","suffix":""},{"id":345966843,"identity":"f38fa540-2d84-4176-984f-fde73145f35e","order_by":5,"name":"Duško Ćirović","email":"","orcid":"","institution":"University of Belgrade","correspondingAuthor":false,"prefix":"","firstName":"Duško","middleName":"","lastName":"Ćirović","suffix":""},{"id":345966844,"identity":"553181de-09f5-4531-b64f-808e3aa18208","order_by":6,"name":"Wieger GW Wamelink","email":"","orcid":"","institution":"Wageningen University and Research","correspondingAuthor":false,"prefix":"","firstName":"Wieger","middleName":"GW","lastName":"Wamelink","suffix":""}],"badges":[],"createdAt":"2024-07-29 13:51:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4822522/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4822522/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10980-024-02037-1","type":"published","date":"2025-01-12T15:57:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63479199,"identity":"ca579195-4308-4973-88a4-d6daa09968f3","added_by":"auto","created_at":"2024-08-28 14:36:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":18511375,"visible":true,"origin":"","legend":"\u003cp\u003eHabitat occupancy of the patches defined by Nikolić et al. (2019) (abon p – abandoned; occ p – occupied). In the upper right: the geographic position of Serbia and Vojvodina (in the purple circle)\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-4822522/v1/ffe4be3a55ec94c6f2368e4a.png"},{"id":63479856,"identity":"5c947c43-033b-41c6-a7af-d461165dec8b","added_by":"auto","created_at":"2024-08-28 14:44:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":79427,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the three steps used to identify and prioritize conservation measures for EGS\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4822522/v1/efcc2629c505373777e94988.png"},{"id":63479197,"identity":"10941410-c708-4a46-8df5-857b3b6312b2","added_by":"auto","created_at":"2024-08-28 14:36:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":33455097,"visible":true,"origin":"","legend":"\u003cp\u003eThe location of key patches (a) and the viability of the 15 habitat networks (b)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4822522/v1/6a07e7683a9f36c52c7a74e7.png"},{"id":63479200,"identity":"451c5e2d-bbcc-4a18-a9c7-762c472531cf","added_by":"auto","created_at":"2024-08-28 14:36:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":23675911,"visible":true,"origin":"","legend":"\u003cp\u003eThe location of key patches (a) and the viability of the 15 habitat networks (b)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4822522/v1/1cb523260c73e88fabb335ff.png"},{"id":73694343,"identity":"91a088e0-c2ce-4d02-8e69-7604b4a0f087","added_by":"auto","created_at":"2025-01-13 16:13:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":121716835,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4822522/v1/47c946ae-58d3-4107-a5a9-f193ac522a41.pdf"},{"id":63479194,"identity":"ee2fd359-0b70-40ff-bb33-b24bea06218c","added_by":"auto","created_at":"2024-08-28 14:36:24","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":472683,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixConsEGSRMT.docx","url":"https://assets-eu.researchsquare.com/files/rs-4822522/v1/121a31bab38ea3ca603af51e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Combining local data and scientific models to prioritize conservation for European ground squirrel and safeguard grassland habitats","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIncreased food production in agricultural areas (especially during the second half of the 20th century) often results in habitat degradation, fragmentation and loss, requiring conservation actions to protect species inhabiting the remaining (semi)natural habitats, e.g., grasslands. Often the focus of these conservation actions is to use the remnant fragments and isolated sites as a foundation for developing regional green networks within which measures and actions may be deployed, albeit with limited resources (Green et al. 2018). Establishing a network of well-connected sites allows individuals of species to access food and water, find mates, conquer new potential habitats and exchange individuals with other populations (Hilty et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Unnithan Kumar and Cushman \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the long term, a stable habitat network also offers species the chance to shift their ranges as an attempt to adapt to climate change (Heller and Zavaleta \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Hannah \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Littlefield et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, network-level habitat connectivity rarely guides plans of conservation actions and measures (Jalkanen et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Recent research emphasizes the imperative to augment wildlife sites in terms of size, quality, connectivity, and quantity (Lawton et al. 2010; Hodgson et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Since stochastic events are more damaging for small and isolated populations, increasing population size by enlarging habitat patches (\u0026ldquo;bigger\u0026rdquo;), increasing their quality (\u0026ldquo;better\u0026rdquo;), connecting them with other patches using corridors (\u0026ldquo;joined\u0026rdquo;) and even creating new habitats through restoration actions (\u0026ldquo;more\u0026rdquo;) should work in favor of increasing the resilience of the habitat network and boosting metapopulation dynamics, crucial for fighting global changes (Isaac et al. 2018). Therefore, it is evident that habitat patch quality, size, and density, as well as the matrix in between the habitat patches must be considered when designing conservation strategies of species (Hanski and Ovaskainen \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Fahrig \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Opdam et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Fahrig 2011; Didham et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Rybicki and Hanski \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Synes et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eScattered within a heavily used agricultural landscape of central and south-eastern Europe, lives the endangered European ground squirrel (\u003cem\u003eSpermophilus citellus\u003c/em\u003e L. 1766, EGS). Due to agricultural use, land abandonment, urbanization, and increasing road networks, the distribution of this species has declined in Serbia and across its range. As a result, it currently holds the status of strictly protected in the Serbian legislature (Official Gazette R. Serbia 2010), is listed in Annex II of the Habitats Directive and Annex IV of the Species Directive, and Appendix II of the Bern Convention, and has been categorized as endangered (EN) on the IUCN red list of species (Council Directive 92/43/EEC; Council of Europe 1979; Hegyeli \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The iconic grassland inhabitant requires precise management actions. As it is a keystone species of (semi)natural grasslands, its disappearance from these areas negatively impacts broader grassland communities (Lindtner et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). EGS is a small herbivore mammal (Rodentia: Sciuridae) with a functional role in improving soil structure, nutrient cycling, and maintaining plant community composition (Lindtner et al \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Its presence influences the abundance of other animal populations as it is an essential link between different trophic levels; and since individuals can alter habitats and regulate resources, EGS is considered a terrestrial ecosystem engineer (Lindtner et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, we consider it a reliable indicator and model organism for conserving natural grassland ecosystems.\u003c/p\u003e \u003cp\u003eEGS remains in habitat patches in northern Serbia within a primarily agricultural landscape. Assessing habitat and landscape-level conditions and patterns can be significant, given the long-term downward trend in the distribution of grasslands and the adverse effects of this loss on the broad natural grassland community within the agricultural landscapes (Marini et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For example, grassland habitat capacity and surrounding landscape heterogeneity showed environment-induced changes in small mammals\u0026rsquo; local population distribution or demography (Nikolić et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Available evidence indicates that the agricultural matrix may impede or facilitate the movement of individuals (Fahrig et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Vasudev et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Keeley et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), suggesting that structural and functional connectivity of grassland patches affects population viability and the long-term survival of targeted populations. Intensive population monitoring and comprehensive analysis of EGS habitat distribution could help prioritize conservation initiatives of natural grasslands within the agricultural landscape (Nikolić et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For a ground-dwelling species like EGS, knowledge of landscape permeability and habitat connectivity is essential. Usually, this is acquired by including exact or estimated population data in a multi-scale, multi-level hierarchical modeling framework (McGarigal et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Zeller et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In these cases, spatially explicit models and keystone species data are relevant for choosing the most effective planning strategy for conservation, improving habitat quality, increasing quantity, and/or restoring connectivity (Hodgson et al. 2010; Marjakangas et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study aimed to assess the viability of current populations of EGS in northern Serbia and determine the connectivity of natural grassland habitats to prioritize conservation measures and actions. The study's findings and recommendations could help inform conservation efforts and management strategies to support the viability of EGS populations and enhance the overall conservation of natural grassland habitats in northern Serbia. Thus, the investigation aimed to (1) establish the locations of connected grassland habitat clusters (habitat networks), (2) assess dispersal connectivity within and between these networks and identify areas of \u0026ldquo;interventions\u0026rdquo; which will serves as corridors after restoration work (3) use the presence/absence data to determine the differences among these networks and prioritize conservation measures. To achieve these objectives, we applied a framework (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) that combined local knowledge of EGS habitat preferences and dispersal capacity (Ćosić et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Nikolić et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), two scientific models, and monitoring data (Nikolić et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The models were used to assess the potential viability of the populations within the ecological networks and the connectivity within and between these networks. The monitoring data was further used to prioritize conservation measures such as improving quality or connectivity within or between the networks.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area\u003c/h2\u003e \u003cp\u003eThe study was conducted in Vojvodina, an autonomous province in the northernmost part of Serbia with a total area of 21 506 km\u003csup\u003e2\u003c/sup\u003e. Only about 6% of the area is under some form of protection (Puzović et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and vast areas are designated for intensive agricultural production. EGS occupies 2.3% of the study area and its distribution has rapidly declined in the last few decades (Nikolić et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). As a result of the large-scale conversion of natural grasslands into arable land in Vojvodina during the second half of the 20th century, most local EGS populations are restricted to small remnant grassland patches inside a predominantly agricultural matrix (Nikolić et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The number of occupied and abandoned patches (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) varies across different spatial scales, reflecting the species\u0026rsquo; response to the declining landscape heterogeneity (Fahrig et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOverview of modelling framework\u003c/h2\u003e \u003cp\u003eWe used a three-step framework to identify the conservation priorities in grassland habitat distribution for EGS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In the first step, we identified the potential ecological networks for EGS. The ecological networks were determined based on the dispersal capacity of EGS and the potential viability of these networks was based on the habitat quality of the patches, the configuration of these networks and the presence of so-called potential key patches (Verboom et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). For this step, the model LARCH was used (Opdam et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, Verboom and Pouwels \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). As the LARCH model indicates potential habitat networks based on species' dispersal capacity, it overestimates the connectivity between patches for ground-dwelling species such as EGS. Therefore, the potential viability of these networks is met when connectivity between patches is not a problem. In the second step, we developed resistance maps for EGS and identified areas with weak connectivity within the ecological networks. We also determined the potential connectivity between the networks to identify locations for corridors. For this step, the model Circuitscape was used (McRea et al. 2008; 2009). This provided information on which network lacks connectivity and where areas are located that could connect different networks. Finally, in step three, we combined the information from the models with monitoring data to distinguish between different categories of ecological networks and prioritize conservation measures for EGS in northern Serbia.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eEcological network of European ground squirrel habitats\u003c/h2\u003e \u003cp\u003eFor the present study, the map of 195 identified potential habitat patches provided by Nikolić et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) was adopted along with researchers\u0026rsquo; field data and experience. We used the land use type to determine the main habitat suitability and four additional criteria as correction factors (see details in Supplementary file section S1.1). The total score for habitat quality in the patch was based on all five criteria (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The full list of scores and locations of the mapped habitat patches is available in Table S2.\u003c/p\u003e \u003cp\u003eThe habitat map was input for LARCH to assess the habitat patch capacity and determine the habitat networks of EGS. A dispersion capacity of 5 km for ESG was adopted from Nikolić et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Sometimes EGS can disperse further, which is important for genetic exchange. However, these rare events should be neglected for metapopulation dynamics, and dispersal distance in LARCH is set at a distance that includes 90% of all dispersal events (Opdam et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). LARCH estimates the potential number of reproductive units (RUs) in every patch based on the habitat quality and size of the patches (Verboom and Pouwels \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). For small mammals, a patch of one ha with the highest quality index is expected to potentially accommodate at least 5 RUs. The obtained results can be used to identify key patches (KPs). A key patch is defined as a patch large enough to contain a population with an extinction chance of less than 5% in 100 years, given an immigration rate of 1 individual per generation (Verboom et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). These patches act as sources within ecological networks and are often occupied when the species is present in that specific ecological network (Verboom et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The threshold for short-lived mammals of 100 RUs was used in this study to identify key habitat patches (Verboom et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2001\u003c/span\u003e, Verboom and Pouwels \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). As individuals live in small colonies with a female biased sex ratio that are more sensitive to local extinction due to disturbances compared to species that reproduce as pair, we used 500 RUs as a threshold for a viable network for EGS instead of the standard of 200 RUs that is used for small rodents like voles (Verboom and Pouwels \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eAssessing connectivity within and between ecological networks\u003c/h2\u003e \u003cp\u003eWe used different methods for assessing the connectivity within- and between-ecological networks dispersal. We differentiated between the connectivity assessments to 1) identify patches within the networks that could be situated beyond the range of key patches, thereby posing potential risks for occupation and 2) to pinpoint potential corridors between ecological networks. For the connectivity within ecological networks, we assessed the connectivity between key patches to other patches in the ecological network as key patches act as sources and an ecological network is more stable when patches are well connected to key patches (Vos et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). We followed the variation in landscape patterns and their impact on EGS habitat cohesion at previously tested scales found by Nikolić et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). We assumed that the movement of individuals within the network is constrained by the quality of habitat and its surroundings. The characteristic of the habitat is defined in table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and for the quality of the surroundings we used information from Nikolić et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). For the assessment of the connectivity between ecological networks we assessed the connectivity between all patches as potential gene flow between networks is determined by all patches in the landscape. We assumed that dispersal of individuals is mainly determined by the type of land use, elevation and water courses between networks and not by detailed information within the networks (Mateo-S\u0026aacute;nchez et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe used Circuitscape (v 4.0; McRea et al. 2009) to identify the area of the highest landscape permeability (between networks) and the potential movement trajectories of individuals within the habitat networks (within networks). Circuitscape uses circuit theory and resistance (or conductance) surfaces to predict connectivity between nodes (source), whereas high current intensity between them identifies areas and paths potentially crucial for patterns of animal movement (McRae et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Thus, we developed species-specific baseline maps of landscape permeability and habitat connectivity for EGS in the lowland area of Vojvodina. We employed the resistance-by-distance method between mapped EGS patches (source\u0026ndash;network nodes) to develop between and within network connectivity models. All 195 patches from the dataset Nikolić et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) were used as input for assessing connectivity between networks and key patches generated by the LARCH model for assessing connectivity within networks.\u003c/p\u003e \u003cp\u003eWe generated a \u0026ldquo;current density\u0026rdquo; surface within the study area to assess between networks connectivity with the developed resistance raster and mapped habitat patches (see details in Supplementary file section S2.1). This model estimates connectivity across every possible movement trajectory among every pair of locations (mapped patches) in the so-called pairwise mode. To generate potential movement maps of individuals within habitat networks, we used the resistance surface, key populations as source nodes, and all other mapped patches as ground nodes - the locations individuals dispersed into (see details in Supplementary file section S2.2). This way, the \u0026ldquo;current\u0026rdquo; surface is estimated based on a 1:1 iteration between source and ground nodes, where we set source nodes to have a current value of 1 and ground nodes to have a current value of 0.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePrioritizing conservation measures for each network\u003c/h2\u003e \u003cp\u003eWe combined information from the LARCH analyses and the Circuitscape analyses with monitoring data to choose which main conservation strategy (Hodgson et al. 2010) or combination of strategies might be needed to improve the viability of population networks of EGS in northern Serbia. We distinguished between; current measures are sufficient, improve habitat quality of patches, restore more patches within network, improve connectivity within network and connect to other (viable) networks. For currently unoccupied networks it could be considered not to invest in further conservation efforts and use resources for improving still occupied networks that are not viable. Ecological networks with weak connectivity and potential areas for connecting ecological networks were used to indicate those areas that should be improved to enhance the dispersal of EGS within and between networks.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eViability of habitat networks of EGS\u003c/h2\u003e\n \u003cp\u003eAll habitat patches cover a combined area of 2586 ha in Vojvodina. Within the Banat region, 12.8% of the patches are of excellent or sound quality, while only 1% of the patches in Bačka and Srem are in this category (Supplementary file section S1.2; Table S2, Fig. \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). LARCH defined 15 potential habitat networks. Six of these networks have habitat patches big enough to sustain populations with more than 100 reproductive individuals (i.e., key populations; Fig. 3a). The number of key patches within those six networks vary (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Five networks, with ID_2, 4, 5, 8, and 13, are considered potentially viable (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). One network, with ID_9, contains only one key patch, while the total network is large enough for approximately 350 RU.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLARCH modeling results for the fifteen habitat networks. Names are based on the location within the regions of the potential populations within the habitat networks (see also Fig.\u0026nbsp;3a, b)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNetwork ID\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eName\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e# Patches\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e# Key patches\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAverage quality\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSum RU\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eViability\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall South Banat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFru\u0026scaron;ka gora\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFarkaždin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLok\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGreater South Banat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes (strongly)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBegejci\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGakovo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral Banat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes (strongly)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTomislavci\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBačko Du\u0026scaron;anovo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAleksa \u0026Scaron;antić\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAradac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTre\u0026scaron;njevac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBikovo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSrpski Krstur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eConnectivity within and between ecological networks\u003c/h2\u003e\n \u003cp\u003eThe ecological networks with the highest viability are the best-connected ones (Fig. 3b, Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Of all the networks with more than ten patches, network 8 shows the highest connectivity (Fig.\u0026nbsp;4a, b). Network 5 is also well connected for most of the patches. Of all the viable networks, network 2 shows the lowest connectivity and many patches are not well connected with the more stable key patches.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003ePrioritization of conservation measures\u003c/h2\u003e\n \u003cp\u003eComparing the LARCH results and the monitoring data showed that potentially viable population networks and key patches provide a good base for protecting EGS. The results show that 93% of all key patches and 54% of others are occupied. Also, 66% of all patches are occupied in viable networks, and in non-viable networks, only 38%. The only patch occupied in network 9 was, in fact, the key patch. When the current network only has a few patches and these are all abandoned, they may be considered as a lost cause. Alternatively, they may be given a low priority as large efforts are probably needed; networks with ID 1, 3, 6, 7, 10, and 15. When resources are scarce, priority should be given to currently occupied patches at risk if they are not viable or have connectivity gaps. Based on the analyses, we conclude that two networks (5 and 8) need no further conservation measures. However, connecting them with the surrounding non-viable networks will improve overall networks sustainability. The analyses showed that the third viable network (2) lacks connectivity. It can be restored by improving the permeability within the network or by restoring more patches (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). This will improve the gene flow in these networks\u0026rsquo; total population of EGS. The analyses also show that in the northern part of Vojvodina, several small networks contain occupied key patches that are not viable; networks with IDs 9, and 13 and occupied networks without key patches; networks with IDs 11, 12 and 13. These networks are at risk of becoming abandoned as they are isolated. Connecting these networks with other one another or with network with ID 8 will improve the stability of the total EGS population in the northern part of Vojvodina.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOverview of networks and preferred conservation measures based on the LARCH and Circuitscape results, and monitoring data. Connectivity within networks is assessed as high when large parts of the network have a high connectivity, moderate when some parts of the network have a high connectivity, low when none of the network has a high connectivity (Fig.\u0026nbsp;3a) and it is not assessed when the network consist of one habitat patch. Connectivity between networks is assessed as high when a potential corridor, regardless the distance, to another network is all high, it is assessed moderate when a potential corridor is partly high and low when it shows no clear potential corridor (Fig.\u0026nbsp;3b).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNetw. ID\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eName\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAverage quality\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatches\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e% Occupied\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKey patch\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eViability\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConnectivity within networks\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConnectivity between networks\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCons. measures*\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConservation measures\u003c/p\u003e\n \u003cp\u003e(Hodgson et al. 2010)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall South Banat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 and 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eimprove quality and connect to 5; or no further conservation efforts\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFru\u0026scaron;ka gora\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 and 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eimprove connectivity within the network and restore more patches within the network\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFarkaždin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 and 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eimprove quality and connect to 5; or no further conservation efforts\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLok\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 and 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eimprove connectivity within the network and restore more patches within the network\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGreater South Banat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes (strongly)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epreserve current status of the network\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBegejci\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003econnect to 8; or no further conservation efforts\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGakovo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 and 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eimprove quality and connect to one large network with ID\u0026apos;s 9-149; or no further conservation efforts\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral Banat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes (strongly)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epreserve current status of the network\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTomislavci\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1, 2 and 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eimprove quality, restore more patches and make one large network with ID\u0026apos;s 9\u0026ndash;14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBačko Du\u0026scaron;anovo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 and 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eimprove quality and make one large network with ID\u0026apos;s 9\u0026ndash;14; or no further conservation efforts\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAleksa \u0026Scaron;antić\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 and 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emake one large network with ID\u0026apos;s 9\u0026ndash;14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAradac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 and 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eimprove quality and make one large network with ID\u0026apos;s 9\u0026ndash;14 and/or connect to 8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTre\u0026scaron;njevac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emake one large network with ID\u0026apos;s 9\u0026ndash;14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBikovo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emake one large network with ID\u0026apos;s 9\u0026ndash;14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSrpski Krstur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 and 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003econnect to one large network with ID\u0026apos;s 9\u0026ndash;14;\u003c/p\u003e\n \u003cp\u003eor no further conservation efforts\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\"\u003e* 0\u0026thinsp;=\u0026thinsp;current measures are sufficient, 1\u0026thinsp;=\u0026thinsp;improve quality of patches, 2\u0026thinsp;=\u0026thinsp;restore more patches within network, 3\u0026thinsp;=\u0026thinsp;improve connectivity within network and 4\u0026thinsp;=\u0026thinsp;connect to other networks (with ID\u0026apos;s)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCombining the results from LARCH and Circuitscape with the monitoring data from Nikolić et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) provides a good overview of potential conservation measures for each network. Although Circuitscape analyses show that the connectivity of some viable networks might need improvements (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) certain discrepancies should be noted, as connectivity between network areas identified by the \u0026ldquo;circuit\u0026rdquo; method is significantly larger than expected based on within-network connectivity (Fig.\u0026nbsp;3a, b; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The connectivity results provide insight into the potential improvement zones for restoration measures to improve natural grassland cover and enhance the likelihood of long-term survival of EGS and grassland species in the study area. Thus, spatial plans should include an increase in habitat surface area, habitat density, and habitat quality (Verboom and Pouwels \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Bierwagen \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Kalarus and Novicki 2015; Van Teeffelen et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Albert et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Benedek and S\u0026icirc;rbu \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Benedek et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bar\u0026atilde;o et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The study confirmed that between-network and within-network connectivity is poor in the majority of identified habitat networks located north within our study landscape (i.e., all situated north of the ID_8 network). In this area, we should perform landscape-level conservation planning to increase the percentage distribution and density of natural grassland habitats and habitat-level measures to ensure adequate habitat management and improve the presence of transitional habitats. This approach would enable viable networks at the regional level in the most efficient way (Jackson and Fahrig \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The results yielded by this study, along with the produced maps, provide an example of where good spatial governance could support EGS and other natural grassland species and ecosystems.\u003c/p\u003e \u003cp\u003eEven though criticized, the species-specific network approach in highly modified agricultural areas is suitable since the complexity of its application is neutralized with biodiversity localized in the remaining semi-natural parts of the landscape (Jalkanen et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). For example, the identified KP in this study needs connections to all local populations by improving surrounding grassland habitat network links (e.g., to secure connections between the identified KP and other populations in the different parts of the network ID_2). Similarly, connecting the KP with other mapped but abandoned habitat patches by increasing the amount of habitat along with improving the quality by establishing regular habitat management (mowing or grazing) could potentially ensure the stability of such network. Sometimes translocation of individuals to those abandoned habitats might be necessary as some networks are isolated (e.g., in the network ID_9). Management of the sustainable network links is crucial when considering network cases such as the viability in the ID_2 network, which depends much more on the environment than on stochastic demographic processes (Ćosić \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), highlighting the importance of spatial factors in the preservation efforts aimed at this part of the studied landscape. Furthermore, connecting isolated habitats characterized by medium-size capacity and populations with sufficiently large densities embodied in moderately permeable landscapes (e.g., ID_4) by steppingstone grassland corridors will increase the viability of populations within the network (Howell et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mims et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Mohammadpour et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kim et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Finally, improving grassland habitat density within the sustainable network in its impermeable parts (e.g., KP and other habitats in network ID_5) would positively affect abandoned habitats within the adjusted unsustainable ones (habitats in network ID_1, whose capacity needs improving). This comprehensive strategy would also enhance the local as well as the regional population\u0026rsquo;s resilience to the predicted increase in the frequency of extreme weather events because more extensive and more stable populations have a better chance of survival (Coetzee \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Frankham et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ashrafzadeh et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTransitional habitats that individuals use during dispersal differ significantly from those suitable for life and reproduction (Pulliam \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Cushman et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In the present study, areas with only one or two inhabited or abandoned habitats (ID_3, ID_6, ID_7, ID_10, and ID_15) are essential for connectivity between networks and the connection of regional populations in the landscape. Furthermore, in improving the connections, we should simultaneously improve habitat and landscape characteristics (Howell et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fahrig \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Promoting connectivity between networks is relevant since even a few immigrants can establish gene flow between populations. This assertion supports the findings reported by Ćosić et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), indicating no genetic bottlenecks for EGS in Vojvodina in the recent past. As shown by available evidence, changes in land use can potentially prompt EGS to leave unsuitable areas. For example, Nikolić et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) have established that, compared to the historical prevalence of EGS populations in Vojvodina, they have recently moved east and south, where they currently thrive in the most significant numbers.\u003c/p\u003e \u003cp\u003eResearchers used the LARCH model in several studies to estimate the viability of populations on several dispersion scales (Van der Sluis et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Paz\u0026uacute;rov\u0026aacute; et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The model relies on ecologically evaluated landscape indices (habitat suitability and capacity, dispersion, and population size) from the perspective of an analyzed species or group of species. The previous practice has shown that habitat capacity is a sensitive model parameter (Verboom et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Verboom and Pouwels \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Regolin et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For this reason, we conducted additional field research to evaluate the habitat capacity values yielded by the LARCH model. Moreover, even smaller areas can support more extensive and stable populations in these habitats, as shown by genetic analyses (Ćosić et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), indicating that combining model output with local knowledge improves the robustness of the results. For our research, the evaluation of habitat quality might even be further enhanced via quantitative methods such as analysis of satellite images and vegetation indices.\u003c/p\u003e \u003cp\u003eIn the present study, for EGS - a grassland habitat specialist, we evaluated spatial connectivity within and between the habitat network scale to provide an overview of all connectivity links and potential corridors (McRae et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Zeller et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The scale of this spatial variation has already provided insights for natural grassland restoration and the proposal for designation of some regions of Vojvodina as designated ecological zones for protecting grassland ecosystems (Nikolić et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Information related to the permeability of certain landscape areas is helpful to identify areas in which one should direct investments to promote grassland connectivity. For example, in their study, Ćosić et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) demonstrated that historically, the Danube is a barrier between populations. Still, the Tisza River is not. This assertion is confirmed by establishing the Vojvodina landscape matrix permeability. In addition, our analysis aids in identifying parts of functionally unlinked areas within and between networks, representing areas at which to focus revitalization measures of the grassland cover to support EGS viability and grassland biodiversity.\u003c/p\u003e \u003cp\u003eHowever, our findings are insufficient for determining how common EGS movements are, as the assessment of habitat connectivity within the heterogeneous matrix depends not only on individual traits but also on the available empirical data on the movement of individuals (Zeller et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Therefore, the main limitation of the present study stems from the need for more information. Future research should focus on telemetry studies, landscape genetics analyses, and obtaining improved habitat maps (e.g., EUNIS level IV). Findings yielded by such investigations would significantly improve the current knowledge of the movement of EGS individuals through the landscape matrix and the response of individuals and populations to changes in land use. This information might help to improve parameters for dispersal capacity and permeability values of the landscape. This knowledge might be helpful in prioritizing the conservation measures needed in the northern part of the region where networks need to be connected to protect currently occupied networks, like networks ID_9 and 11\u0026ndash;14.\u003c/p\u003e \u003cp\u003eIn conclusion, conservation measures at the regional level could yield results quickly, establishing sustainable habitat networks capable of buffering climate change in the long term (Beier et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Albert et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Keeley et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The implementation of active measures related to land use designation for agricultural activities and restoration of natural grassland habitats need to consider the ownership structure of parcels or the inclusion of the private sector into conservation initiatives (Waldron et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Moreover, when planning designated areas, a comparative analysis of people's societal and economic needs that depend on the targeted landscape is mandatory. In this context, the spatial approach can be precious, as it facilitates collaboration among different sectors and interest groups on strategic planning (Keeley et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hilty et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Finally, even though this study only focused on the European ground squirrel as a model organism, the conceptual and methodological approach we used and the results we obtained might be applied for other species and ecosystems to prioritize between conservation measures to improve habitat quality, increase habitat quantity or improve connectivity (i.e. Hodgson et al. 2010).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e We would like to thank the European ground squirrel community, Bird Protection and Study Society of Serbia and local community for friendly advice during fieldwork campaign.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This work has been supported by The Ministry of Science, Technological Development and innovation, Republic of Serbia, under Grant 2024: 451-03-66/2024-03/ 200358, The Rufford Foundation grant “Building a better future for European ground squirrel in Serbia” and H2020 project ANTARES (SGA-CSA. No. 739570).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e The authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e TNL, RP and W GW W, contributed to the study conception and design. Data collection and analysis were performed by TNL, MA, DR, DĆ and NĆ. The first draft of the manuscript was written by TNL, RP and MA and all authors commented on previous versions. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAlbert CH, Rayfield B, Dumitru M, Gonzalez A (2017) Applying network theory to prioritize multispecies habitat networks that are robust to climate and land‐use change. Cons Biol 31(6):1383-1396. https://doi.org/10.1111/cobi.12943\u003c/li\u003e\n \u003cli\u003eAshrafzadeh MR, Khosravi R, Adibi MA, Taktehrani A, Wan HY, Cushman SA (2020) A multi-scale, multi-species approach for assessing effectiveness of habitat and connectivity conservation for endangered felids. 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Working paper analysing the economic implications of the proposed 30% target for areal protection in the draft post-2020 Global Biodiversity Framework.\u003c/li\u003e\n \u003cli\u003eZaharia G, Petrencu L, Baltag EŞ (2016) Site selection of European ground squirrels (\u003cem\u003eSpermophilus citellus\u003c/em\u003e) in Eastern Romania and how they are influenced by climate, relief, and vegetation. Turk J Zool\u003cem\u003e\u0026nbsp;\u003c/em\u003e40:917-924. https://doi.org/10.3906/zoo-1505-28\u003c/li\u003e\n \u003cli\u003eZeller KA, McGarigal K, Whiteley AR (2012) Estimating landscape resistance to movement: a review. Landsc Ecol 27:777-797. https://doi.org/10.1007/s10980-012-9737-0\u003c/li\u003e\n \u003cli\u003eZeller KA, McGarigal K, Beier P, Cushman SA, Vickers TW, Boyce WM (2014) Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state: pumas as a case study. Landsc Ecol 29:541-557. https://doi.org/10.1007/s10980-014-9991-4\u003c/li\u003e\n \u003cli\u003eZeller KA, McGarigal K, Cushman SA, Beier P, Vickers TW, Boyce WM (2016) Using step and path selection functions for estimating resistance to movement: pumas as a case study. Landsc Ecol, 31:1319-1335. https://doi.org/10.1007/s10980-015-0301-6\u003c/li\u003e\n \u003cli\u003eZeller KA, McGarigal K, Cushman SA, Beier P, Vickers TW, Boyce WM (2017) Sensitivity of resource selection and connectivity models to landscape definition. Landsc Ecol 32:835-855. https://doi.org/10.1007/s10980-017-0489-8\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"landscape-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"land","sideBox":"Learn more about [Landscape Ecology](https://www.springer.com/journal/10980)","snPcode":"10980","submissionUrl":"https://submission.nature.com/new-submission/10980/3","title":"Landscape Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"EGS, grasslands, connectivity, LARCH, conservation, monitoring data, Circuitscape","lastPublishedDoi":"10.21203/rs.3.rs-4822522/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4822522/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eContext\u003c/b\u003e\u003c/p\u003e \u003cp\u003ePromoting habitat networks of natural grasslands within agricultural landscapes is crucial to supporting biodiversity and protecting endangered grassland species. Understanding the degree of fragmentation of these habitat networks assists in better elucidating their value to the grassland network. However, natural grassland characteristics in intensively used landscapes often need to be more adequately documented, which hinders effective grassland biodiversity conservation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eObjectives\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe combined local data and modeling to identify conservation priorities for natural grasslands through assessing population and habitat patch characteristics for European Ground Squirrel (\u003cem\u003eSpermophilus citellus\u003c/em\u003e, EGS), a keystone grassland specialist, in agricultural settings.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe used available information with presence/absence data and two spatially explicit models (LARCH and Circuitscape) to assess the potential of the current landscape in northern Serbia to protect the EGS. We applied the LARCH model to indicate potential habitat networks for the EGS and Circuitscape to assess connectivity of areas within and between these networks and identify areas of interventions that will serve as corridors between networks after restoration work. Together with the presence/absence data, this is used to set priorities for conservation actions for each network.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe identified the presence of 15 habitat networks. The networks differ in connectivity, size, capacity, and sustainability to support local EGS populations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe results revealed areas on which spatial adaptation measures and actions should be deployed to accommodate the long-term survival of EGS. In addition, the findings help the conservation of (semi)natural grassland and future land planning in terms of sustainable land use in an agricultural setting.\u003c/p\u003e","manuscriptTitle":"Combining local data and scientific models to prioritize conservation for European ground squirrel and safeguard grassland habitats","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-28 14:36:19","doi":"10.21203/rs.3.rs-4822522/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-24T15:14:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-22T21:25:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-20T07:16:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-16T14:23:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"276643472558357720171826900785780306173","date":"2024-09-02T07:19:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187038191734149601219607569276333225104","date":"2024-09-01T22:25:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9363464411333295761845574279868354422","date":"2024-08-30T15:31:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-21T16:13:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"139278117608760180864784691334571950777","date":"2024-08-07T21:35:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-05T19:25:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-31T17:09:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-31T17:07:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Landscape Ecology","date":"2024-07-29T13:47:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"landscape-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"land","sideBox":"Learn more about [Landscape Ecology](https://www.springer.com/journal/10980)","snPcode":"10980","submissionUrl":"https://submission.nature.com/new-submission/10980/3","title":"Landscape Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6ae4b9cb-30ea-4652-8539-477669913417","owner":[],"postedDate":"August 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-13T16:06:30+00:00","versionOfRecord":{"articleIdentity":"rs-4822522","link":"https://doi.org/10.1007/s10980-024-02037-1","journal":{"identity":"landscape-ecology","isVorOnly":false,"title":"Landscape Ecology"},"publishedOn":"2025-01-12 15:57:36","publishedOnDateReadable":"January 12th, 2025"},"versionCreatedAt":"2024-08-28 14:36:19","video":"","vorDoi":"10.1007/s10980-024-02037-1","vorDoiUrl":"https://doi.org/10.1007/s10980-024-02037-1","workflowStages":[]},"version":"v1","identity":"rs-4822522","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4822522","identity":"rs-4822522","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}