Habitat Suitability Map Research Articles

Economic mapping and assessment of Cymodocea nodosa meadows as nursery grounds for commercially important fish species. A case study in the Canary Islands

Cymodocea nodosa seagrass meadows provide several socio-economically ecosystem services, including nurseries for numerous species of commercial interest. These seagrasses are experiencing a worldwide decline, with global loss rates approaching 5% per year, mainly related to coastal human activities. Cymodocea nodosa, the predominant seagrass in the Canary Archipelago (Spain), is also exposed to these threats, which could lead to habitat loss or even local disappearance. In this case study, we estimated the potential economic value of Cymodocea nodosa seagrass meadows for local fisheries at an archipelago scale. Habitat suitability maps were constructed using MAXENT 3.4.1, a software for modelling species distributions by applying a maximum entropy machine-learning method, from a set of environmental variables and presence and background records extracted from historical cartographies. This model allows characterising and assessing the C. nodosa habitat suitability, overcoming the implicit complexity derived from seasonal changes in this species highly dynamic meadows and using it as a first step for the mapping and assessment of ecosystem services. In a second step, value transfer methodologies were used, along with published economic valuations of commercially-interesting fish species related to C. nodosa meadows. We estimate that the potential monetary value of these species can add up to more than 3 million euros per year for the entire Archipelago. The simplicity of the proposed methodology facilitates its repeatability in other similar regions, using freely available data and hence, being suitable for data-scarce scenarios.

Food and habitats requirements of the Eurasian Scops Owl (Otus scops) in Switzerland revealed by very high‐resolution multi‐scale models

In Europe, agricultural practices have progressively evolved towards high productivity leading either to the intensification of productive and accessible areas or to the abandonment of less profitable sites. Both processes have led to the degradation of semi‐natural habitats like extensive grasslands, threatening species such as the Eurasian Scops Owl Otus scops that rely on extensively managed agricultural landscapes. In this work, we aimed to assess the habitat preferences of the Scops Owl using habitat suitability models combined with a multi‐scale approach. We generated a set of multi‐scale predictors, considering both biotic and abiotic variables, built on two newly developed vegetation management and orthopteran abundance models. To select the variables to incorporate in a ‘best multi‐scale model’, we chose the best spatial scale for each variable using univariate models and by calculating their relative importance through multi‐model inference. Next, we built ensembles of small models (ESMs) at 10 different scales from 50 to 1000 m, and an additional model with each variable at its best scale (‘best multi‐scale model’). The latter performed better than most of the other ESMs and allowed the creation of a high‐resolution habitat suitability map for the species. Scops Owls showed a preference for dry sites with extensive and well‐structured habitats with 30–40% bush cover, and relied strongly on semi‐extensive grasslands covering at least 30% of the surface within 300 m of the territory centre and with high orthopteran availability near the centre (50‐m radius), revealing a need for good foraging grounds near the nest. At a larger spatial scale within a radius of 1000 m, the habitat suitability of Scops Owls was negatively related to forest cover. The resulting ESM predictions provide valuable tools for conservation planning, highlighting sites in need of particular conservation efforts together with offering estimates of the percentage of habitat types and necessary prey abundance that could be used as targets in future management plans to ensure the persistence of the population.

Predicting the potential habitat of Russian-Olive (Elaeagnus angustifolia) in urban landscapes

Russian-olive (Elaeagnus angustifolia) is a species native to southern Europe and central and eastern Asia. This species plays an important role in urban landscape design because of its rapid growth, resistance in harsh climates and tolerance to human-caused pressure. Understanding its potential dispersal and restricting parameters are the first steps toward the sustainable use of this species. Here, we used Species Distribution Models to predict the potential distribution of Russian-olive in Iran climate and estimate the possible limiting factors for its spread. Our results highlighted the importance of environmental variables including climatic factors, soil, and lithology in the distribution of this species throughout the country. According to these results, suitable habitats for Russian-olive are located in the north of Iran along the Alborz and Koppeh-Dagh mountain ranges. Therefore, the suitable habitats for this species are limited to only nine percent of the country. A habitat suitability map can be used to evaluate future developments in urban areas and predict the dispersal range of Russian-olive in Iran. Our results show that Russian-olive can be used to create new green spaces in urban climates in the northern regions of Iran.

Habitat suitability mapping of the black coral Leiopathes glaberrima to support conservation of vulnerable marine ecosystems

The black coral Leiopathes glaberrima is an important habitat forming species that supports benthic biodiversity. Due to its high sensitivity to fishing activities, it has been classified as indicator of Vulnerable Marine Ecosystems (VMEs). However, the information on its habitat selection and large-scale spatial distribution in the Mediterranean Sea is poor. In this study a thorough literature review on the occurrence of L. glaberrima across the Mediterranean Sea was undertaken. Predictive modelling was carried out to produce the first continuous map of L. glaberrima suitable habitat in the central sector of the Mediterranean Sea. MaxEnt modeling was used to predict L. glaberrima probability of presence as a function of seven environmental predictors (bathymetry, slope, aspect North–South and East–West, kinetic energy due to currents at the seabed, seabed habitat types and sea bottom temperature). Our results show that bathymetry, slope and aspect are the most important factors driving L. glaberrima spatial distribution, while in less extent the other environmental variables. This study adds relevant information on the spatial distribution of vulnerable deep water corals in relation to the environmental factors in the Mediterranean Sea. It provides an important background for marine spatial planning especially for prioritizing areas for the conservation of VMEs.

Species distribution modeling and environmental suitability of the Southern crested newt, Triturus karelinii (Strauch, 1870) (Amphibia: Caudata) in Iran

The southern crested newt, Triturus karelinii (Strauch, 1870), is a newt endemic to the Ponto-Caspian region. We evaluate the potential distribution of this species and identify the most important environmental factors that determine the distribution of this species in Iran. Forty-four presence points and seven environmental variables were used to model the distribution range. Species distribution modeling was perform using the Maximum Entropy algorithm (MaxEnt). Precipitation of the warmest quarter, with 68.60% contribution, and altitude, with 13.70% contribution, were the most important factors determining the distribution of the species. According to our habitat suitability map, the Golestan, Mazandaran, Guilan, and Ardabil provinces are determined as possessing suitable habitat for the species, while the central and southern regions of Iran do not possess suitable habitats, associated with insufficient rainfall.

Distribution modelling of the garden dormouse Eliomys quercinus (Linnaeus, 1766) with novel climate change indicators

The garden dormouse Eliomys quercinus has been declining in both abundance and range since the mid-twentieth century. The eastern edge of its range has contracted from the Ural Mountains to eastern Germany. Habitat loss and fragmentation has been the most supported theory to explain the observed decline. Climate change has been implicated in declines of other terrestrial mammals, but not investigated for E. quercinus. To better understand the factors influencing the distribution of this species and to map habitat suitability for E. quercinus across Europe, we created a Maxent species distribution model. Among the main environmental variables used for the modelling, two novel climate change indicator variables were produced to indicate the degree of climate change between the early twentieth century and the present. Areas of high suitability were mapped, and variable importance estimated using jackknife tests and variable contribution metrics. The climate change indicators outperformed many conventional variables, which could indicate that climate change is a factor behind the current distribution of E. quercinus. We also analysed the land use types where presence points of E. quercinus were located and whether they were in areas of “high nature value farmland”. Over 30% of all spatially filtered presence points corresponded to high nature value farmland areas. Our results could indicate a role for changing climate (particularly in temperature) in the range decline E. quercinus, and for high nature value farmland practices in conserving this species. Field studies and improved monitoring for this species are recommended to confirm both possible findings.

Mapping habitat suitability for Asiatic black bear and red panda in Makalu Barun National Park of Nepal from Maxent and GARP models

Habitat evaluation is essential for managing wildlife populations and formulating conservation policies. With the rise of innovative powerful statistical techniques in partnership with Remote Sensing, GIS and GPS techniques, spatially explicit species distribution modeling (SDM) has rapidly grown in conservation biology. These models can help us to study habitat suitability at the scale of the species range, and are particularly useful for examining the overlapping habitat between sympatric species. Species presence points collected through field GPS observations, in conjunction with 13 different topographic, vegetation related, anthropogenic, and bioclimatic variables, as well as a land cover map with seven classification categories created by support vector machine (SVM) were used to implement Maxent and GARP ecological niche models. With the resulting ecological niche models, the suitable habitat for asiatic black bear (Ursus thibetanus) and red panda (Ailurus fulgens) in Nepal Makalu Barun National Park (MBNP) was predicted. All of the predictor variables were extracted from freely available remote sensing and publicly shared government data resources. The modeled results were validated by using an independent dataset. Analysis of the regularized training gain showed that the three most important environmental variables for habitat suitability were distance to settlement, elevation, and mean annual temperature. The habitat suitability modeling accuracy, characterized by the mean area under curve, was moderate for both species when GARP was used (0.791 for black bear and 0.786 for red panda), but was moderate for black bear (0.857), and high for red panda (0.920) when Maxent was used. The suitable habitat estimated by Maxent for black bear and red panda was 716 km2 and 343 km2 respectively, while the suitable area determined by GARP was 1074 km2 and 714 km2 respectively. Maxent predicted that the overlapping area was 83% of the red panda habitat and 40% of the black bear habitat, while GARP estimated 88% of the red panda habitat and 58% of the black bear habitat overlapped. The results of land cover exhibited that barren land covered the highest percentage of area in MBNP (36.0%) followed by forest (32.6%). Of the suitable habitat, both models indicated forest as the most preferred land cover for both species (63.7% for black bear and 61.6% for red panda from Maxent; 59.9% black bear and 58.8% for red panda from GARP). Maxent outperformed GARP in terms of habitat suitability modeling. The black bear showed higher habitat selectivity than red panda. We suggest that proper management should be given to the overlapping habitats in the buffer zone. For remote and inaccessible regions, the proposed methods are promising tools for wildlife management and conservation, deserving further popularization.

Role of Maximum Entropy and Citizen Science to Study Habitat Suitability of Jacobin Cuckoo in Different Climate Change Scenarios

Recent advancements in spatial modelling and mapping methods have opened up new horizons for monitoring the migration of bird species, which have been altered due to the climate change. The rise of citizen science has also aided the spatiotemporal data collection with associated attributes. The biodiversity data from citizen observatories can be employed in machine learning algorithms for predicting suitable environmental conditions for species’ survival and their future migration behaviours. In this study, different environmental variables effective in birds’ migrations were analysed, and their habitat suitability was assessed for future understanding of their responses in different climate change scenarios. The Jacobin cuckoo (Clamator jacobinus) was selected as the subject species, since their arrival to India has been traditionally considered as a sign for the start of the Indian monsoon season. For suitability predictions in current and future scenarios, maximum entropy (Maxent) modelling was carried out with environmental variables and species occurrences observed in India and Africa. For modelling, the correlation test was performed on the environmental variables (bioclimatic, precipitation, minimum temperature, maximum temperature, precipitation, wind and elevation). The results showed that precipitation-related variables played a significant role in suitability, and through reclassified habitat suitability maps, it was observed that the suitable areas of India and Africa might decrease in future climatic scenarios (SSPs 2.6, 4.5, 7.0 and 8.5) of 2030 and 2050. In addition, the suitability and unsuitability areas were calculated (in km2) to observe the subtle changes in the ecosystem. Such climate change studies can support biodiversity research and improve the agricultural economy.

Evaluation of environmental factors affecting the quality of Codonopsis pilosula based on chromatographic fingerprint and MaxEnt model

The quality control of Traditional Chinese medicine (TCM) is rather challenging owing to the diversity and complexity of chemical components, which fluctuate with geographic origin and growth environment. In this study, a comprehensive strategy based on ultra-high performance chromatographic (UPLC) fingerprint technique and MaxEnt model was proposed to evaluate the effects of environmental factors on the quality of Codonopsis pilosula. An UPLC analytical method was developed and validated by precision, repeatability and stability, and then applied to analyze 91 sets of samples collected from different sites of Dingxi district, Gansu province, China (one of the geo-authentic producing areas of Codonopsis pilosula). With a similarity evaluation software, a standard UPLC fingerprint was obtained and 23 common peaks were found out. The MaxEnt model was established based on the principle of maximum entropy and its accuracy was evaluated by the receiver operating characteristic (ROC) curve and the area under the curve (AUC). Based on the UPLC fingerprint and MaxEnt model, the potential habitat suitability distribution of Codonopsis pilosula in Dingxi district was obtained, and the correlation model between ecological factors and chemical components was established. With the spatial analysis function of ArcGIS, the quality zoning map of Codonopsis pilosula was further drawn integrating the above distribution map of potential habitat suitability and the correlation model. The research results could provide a reference for the selection of planting area and the production regionalization of an herbal medicine.

Geo spatial approach for tiger habitat suitability mapping: A case study of Bandhavgarh national park, Madhya Pradesh, India

In the present study, evaluation of Tiger (Panthera tigris tigris) and their prey species (Chital & Sambar) habitat was carried out in Bandhavgarh National park by using remote sensing, ground and other ancillary data and these data sources were integrated with GIS using multi-criteria analysis (MCA) model. For the modeling, several variables in the dataset viz., forest cover density, slope, altitude, road, water body, settlement and drainage were used as independent variables in the analysis. All these data sets were considered as input data for developing the model. Expert views and field experience were considered while allotting values to variables for MCA analysis to generate final weight. The result indicated that Sal, mixed Sal, miscellaneous forest, plantation, grassland, agriculture and scrub land are the major land use/land cover types and majority of the study area is covered under forest. The habitat parameters have tremendous impact over the habitat utilization and suitability pattern of Tiger, Chital & Sambar in Bandhavgarh National Park. From this study most suitable habitat for Tiger in BNP is 1264.01 km² which is 56.48% of the total geographical area of the national park while 531.22 km² area comes under moderately suitable for tiger which is 23.74% of the total geographical area of the national park. The results pointed out that 80% of national park has been found to be high to moderately suitable for Tiger habitat. The result have been found to be an important input as baseline information for population modeling and natural resource management in the national park.

Bottom Communities and Abiotic Factors: Analysis of Statistical Relationship Using the Instability Index and Virtual Species Distribution

Statistical procedures for quantifying the relationships between the community structure and abiotic variables start with selecting a minimum set of uncorrelated environmental factors that determine the ecological conditions essential for each of the species. This is especially important when constructing models of spatial distribution of species which are key to ecology of communities and conservation of nature. The aim of the study is to explore whether some applications of information theory can be used to rank environmental factors with respect to their contribution to the formation of the ecological structure of aquatic communities. We consider the applicability of the instability index, which is a special case of the Kullback-Leibler entropy divergence and reflects the information gain from the displacement of a particular realization of a random variable relative to its mean value. Using of instability indices allows to reduce multidimensional data sets on species structure of communities and abiotic factors to lower dimension sets of commensurate standardized variables and to explore the relationships between the latter. The initial data we used were the results of the long-term (1990–2019) hydrobiological survey of benthic communities in small and medium-sized rivers in the Middle and Lower Volga regions. We consider the indices of instability calculated for each of 147 taxa of macrozoobenthos and 8 geophysical and hydrochemical indicators. Based on these data, we constructed random forest regression models and calculated potential weights of environmental factors that determine ecological preferences of species. The most significant explanatory variables were used to construct distribution maps of «virtual species», which were compared with the corresponding empirical data. A habitat suitability map of chironomids (Diptera, Chironomidae), the Prodiamesinae subfamily, is presented. Instability indices can be effectively used for exploratory analysis of various ecosystems, e. g. ranking habitats according to the degree of environmental instability and / or species associations, selecting the most informative abiotic variables that determine the population density of the taxa, etc.

Reducing persecution is more effective for restoring large carnivores than restoring their prey.

Large carnivores are currently disappearing from many world regions because of habitat loss, prey depletion, and persecution. Ensuring large carnivore persistence requires safeguarding and sometimes facilitating the expansion of their populations. Understanding which conservation strategies, such as reducing persecution or restoring prey, are most effective to help carnivores to reclaim their former ranges is therefore important. Here, we systematically explored such alternative strategies for the endangered Persian leopard (Panthera pardus saxicolor) in the Caucasus. We combined a rule-based habitat suitability map and a spatially explicit leopard population model to identify potential leopard subpopulations (i.e., breeding patches), and to test the effect of different levels of persecution reduction and prey restoration on leopard population viability across the entire Caucasus ecoregion and northern Iran (about 737,000km2 ). We identified substantial areas of potentially suitable leopard habitat (~120,000km2 ), most of which is currently unoccupied. Our model revealed that leopards could potentially recolonize these patches and increase to a population of >1,000 individuals in 100yr, but only in scenarios of medium to high persecution reduction and prey restoration. Overall, reducing persecution had a more pronounced effect on leopard metapopulation viability than prey restoration: Without conservation strategies to reduce persecution, leopards went extinct from the Caucasus in all scenarios tested. Our study highlights the importance of persecution reduction in small populations, which should hence be prioritized when resources for conservation are limited. We show how individual-based, spatially explicit metapopulation models can help in quantifying the recolonization potential of large carnivores in unoccupied habitat, designing adequate conservation strategies to foster such recolonizations, and anticipating the long-term prospects of carnivore populations under alternative scenarios. Our study also outlines how data scarcity, which is typical for threatened range-expanding species, can be overcome with a rule-based habitat map. For Persian leopards, our projections clearly suggest that there is a large potential for a viable metapopulation in the Caucasus, but only if major conservation actions are taken towards reducing persecution and restoring prey.

Mapping the Habitat Suitability of West Nile Virus Vectors in Southern Quebec and Eastern Ontario, Canada, with Species Distribution Modeling and Satellite Earth Observation Data

Transmission of vector-borne diseases (VBDs) relies on the presence of their vectors. Good knowledge of their habitat distribution could inform of their presence and then the potential transmission risk. In Canada, West Nile virus (WNV), a VBD transmitted by mosquitoes of the Culex genus to birds, humans, and other mammals, was first reported in 2002. Since then, human cases have been reported every year. To reduce the health burden of the disease and to guide the vector control efforts, this work aims to provide a map of habitat suitability of the main vectors of WNV, Culex pipiens-restuans, in southern Quebec and eastern Ontario at 30 m spatial resolution. Landsat 8-OTI/TIRS images were combined with existing geographical data to characterize vegetated and paved areas in urban and peri-urban areas and to create a land use land cover map related to environmental determinants of Culex pipiens-restuans. Landscape metrics were calculated to characterize the neighborhood environment. They were used with 1008 presence sites of the vectors to build species distribution models with Maxent, a model based on the maximum entropy principle, and to predict habitat suitability for Culex pipiens-restuans in the study area. The performance of the models was very good, with a mean area under the curve of 0.92 and a continuous Boyce index of 0.97. A habitat suitability map of the whole study area was created for Culex pipiens-restuans. The resulting map and environment analysis highlight the importance of the edge of vegetation and mixed or paved areas for the bio-ecology of Culex pipiens-restuans.

Habitat Suitability Assessment of Wintering Herbivorous Anseriformes in Poyang Lake, China

To design a good conservation strategy for herbivorous Anseriformes wintering in Poyang Lake, knowledge of habitat suitability is essential. Therefore, this study aimed to assess the habitat suitability of herbivorous Anseriformes of China’s Poyang Lake. Landsat images with a resolution of 30 m downloaded from the United States Geological Survey, and other ancillary data were used. The ENVI 5.3 software and ArcGIS 10.2 software were used for preprocessing, classifying the satellite image, and mapping habitat suitability. The study reveals that land cover types were divided into vegetation, mudflats, water, and sand. Similarly, the study area’s habitats were also divided into unsuitable, fair, good, and best grades. However, the distribution of the habitat suitability for each grade reveals significant spatial variations. For instance, vegetation indicated the areas with the best habitat grade, followed by mudflats, and these areas cover (47.93%, 2015 and 55.78%, 2019) the majority of the study area. The unsuitable grades cover the smallest areas (0.48%) of the lake. Similarly, this study results showed a slight change in habitat suitability areas. Therefore, this study highlighted that Poyang Lake has valuable importance for the conservation of herbivorous Anseriformes. Extending the years of study and including some ecological variables from different stopovers could improve the results.

Genetic diversity of Horvath’s Rock Lizard meets current environmental restrictions

The Horvath’s rock lizard Iberolacerta horvathi (Mehely, 1904) is an understudied lacertid species, which is geographically isolated from its congeners and currently classified as Near Threatened under IUCN red listing criteria. Due to its limited distribution and narrow environmental preferences, we expect that the species had been affected by past climatic oscillations. By combining all available data on species occurrences and our own records, we produced an updated distribution map. We used ecological niche models to identify the current environmental factors underlying the species range and developed a habitat suitability map. We sequenced one mitochondrial and one nuclear marker to characterize the distribution of the genetic variability and infer the historical demography of the species. The habitat suitability map identified areas where targeted field searches should be prioritized, as well as unsuitable habitats coinciding with likely barriers to gene flow. We found considerable genetic variability suggesting that the species probably survived the Pleistocene glaciations in at least two main refugia, one in the South and the other in the central/northern portion of its distribution. While southern populations show a moderate demographic decrease starting at the onset of the Eemian interglacial, the northern populations underwent an expansion during Late Pleistocene. We provide a revised species distribution and a first characterization of its genetic variability across its distribution to guide conservation priorities for this endemic and spatially restricted species.

Estimated footprint of shellfishing activities in Zostera noltei meadows in a northern Spain estuary: Lessons for management

Intertidal seagrasses often occupy areas of high ecological importance that are also targeted for human activities, such as shellfishing and leisure walking. These activities could affect the growth or survival of seagrass. The society at large lacks knowledge of the ecological relevance of seagrasses and their vulnerability, presenting an obstacle for their conservation. Here, the Oka estuary (Basque Country, N. Spain) is used as a case study to analyse the spatial extent of shellfishing activities in seagrass (Zostera noltei). This estuary holds 84% of the intertidal seagrass meadows present in the Basque Country and is visited during the year by professional and recreational shellfishers. Bait digging is legal year-round, and clam digging (by professionals only) from October to February. Human presence over 11 years averaged 17 people on the tidal flat in each daylight hours from August to October. Each professional shellfishing daily trip affected 7.4–21.6 m2 by fishing and 110–188 m2 by trampling in seagrass, but was substantially different between clam and bait (crustacean, worm) fishing. Scaling up this area to estimated annual number of shellfishers, 8–69% of the total seagrass area is trampled and 1–9% is dug per year. In comparison to a habitat suitability map for seagrass, 98% of trampling occurred within a very highly suitable area for seagrass presence (i.e., >90%). This pressure could adversely affect seagrass density and prevent the expansion of meadows into areas suitable for seagrass. Management of public impacts to seagrass in this estuary could occur through prohibition of some activities in seagrass and awareness campaigns among shellfishers and walkers.

Habitat Suitability Modeling and Mapping to Assess the Influence of Freshwater Withdrawals on Spatial Distributions and Population Numbers of Estuarine Species in the Lower Peace River and Charlotte Harbor, Florida

AbstractThe effects of potential reductions of freshwater inflow were evaluated for the lower Peace River and its largest tributary, lower Shell Creek, which flow into the Charlotte Harbor estuary in southwest Florida. Habitat suitability modeling (HSM) and mapping of fish and invertebrate species life stages were used to seasonally predict changes in spatial distributions and population numbers associated with simulated freshwater withdrawals. Seasonal salinity grids and temperature grids derived from values predicted by hydrodynamic modeling (2007–2014) were similar between baseline (i.e., flows not affected by water withdrawals) and minimum flows (flows associated with water withdrawals). Depth grids, bottom type grids, and seasonal dissolved oxygen grids were held constant between the two scenarios. Seasonal habitat suitability models were applied to 28 fish and invertebrate species life stages with affinities for low or moderate salinity. Salinity was the most significant factor in seasonal models for species life stages. The seasonal HSM maps produced showed that spatial distributions were similar between baseline and minimum flows for each species life stage. Most seasonal estimates of population numbers under minimum flows were less than the estimates for the baseline condition, indicating some effect on population numbers associated with flow reductions. Reductions in population numbers under minimum flows ranged from 0.3% to 21.0%, with 3 out of 28 seasonal comparisons indicating losses >15% and 12 comparisons indicating losses between 5% and 15%. Although other factors related to freshwater inflow can also influence species abundance and distribution, these results demonstrate how output from hydrodynamic modeling can be applied to HSM analyses and mapping to estimate spatial changes in habitat areas and population numbers for the life stages of selected fish and invertebrate species in relation to changes in salinity distributions, which can be used to identify areas of an estuary that are particularly susceptible to the effects of inflow reductions.

Evaluating population connectivity and targeting conservation action for an endangered cat

AbstractDispersal of animals among populations helps to increase genetic variability and population viability. The endangered ocelot (Leopardus pardalis) in south Texas persists in two small populations separated by 30 km and cutoff from populations in northeastern Mexico. Despite the relatively short distance separating the two south Texas populations, movement between them has been limited, leading researchers to believe landscape connectivity is poor in the region. We developed habitat suitability maps using remote sensing and GPS‐collared ocelots and ran connectivity analyses to assess current habitat linkages, important areas for conservation, and areas where connectivity could be improved through habitat restoration. First, we developed a resource selection function using random forest models and GPS data from ten ocelots collared at Laguna Atascosa National Wildlife Refuge combined with spatial layers derived from LiDAR and remotely sensed imagery. We then used these results as the basis for a cost surface layer. Using this layer, we examined habitat connectivity using least‐cost and circuit theory methods. We evaluated linkages by cost of movement, identified areas important for maintaining existing connectivity, and ranked areas where restoration would have the greatest benefit to connectivity. We found that core habitats within the two populations were relatively well connected but connectivity between the two populations was poor. By identifying areas currently important for connectivity and areas with the greatest benefit to ocelots if restored, these results will help inform land acquisition and restoration planning to improve ocelot conservation in south Texas.

Satellite-based habitat monitoring reveals long-term dynamics of deer habitat in response to forest disturbances.

Disturbances play a key role in driving forest ecosystem dynamics, but how disturbances shape wildlife habitat across space and time often remains unclear. A major reason for this is a lack of information about changes in habitat suitability across large areas and longer time periods. Here, we use a novel approach based on Landsat satellite image time series to map seasonal habitat suitability annually from 1986 to 2017. Our approach involves characterizing forest disturbance dynamics using Landsat-based metrics, harmonizing these metrics through a temporal segmentation algorithm, and then using them together with GPS telemetry data in habitat models. We apply this framework to assess how natural forest disturbances and post-disturbance salvage logging affect habitat suitability for two ungulates, roe deer (Capreolus capreolus) and red deer (Cervus elaphus), over 32yr in a Central European forest landscape. We found that red and roe deer differed in their response to forest disturbances. Habitat suitability for red deer consistently improved after disturbances, whereas the suitability of disturbed sites was more variable for roe deer depending on season (lower during winter than summer) and disturbance agent (lower in windthrow vs. bark-beetle-affected stands). Salvage logging altered the suitability of bark beetle-affected stands for deer, having negative effects on red deer and mixed effects on roe deer, but generally did not have clear effects on habitat suitability in windthrows. Our results highlight long-lasting legacy effects of forest disturbances on deer habitat. For example, bark beetle disturbances improved red deer habitat suitability for at least 25yr. The duration of disturbance impacts generally increased with elevation. Methodologically, our approach proved effective for improving the robustness of habitat reconstructions from Landsat time series: integrating multiyear telemetry data into single, multi-temporal habitat models improved model transferability in time. Likewise, temporally segmenting the Landsat-based metrics increased the temporal consistency of our habitat suitability maps. As the frequency of natural forest disturbances is increasing across the globe, their impacts on wildlife habitat should be considered in wildlife and forest management. Our approach offers a widely applicable method for monitoring habitat suitability changes caused by landscape dynamics such as forest disturbance.

Predicting Plant Communities in the Vicinity of Wheat Crops and Vineyards in Europe using Participatory Modeling

The risk assessment of pesticide use on non-target terrestrial plants is currently based on standardized greenhouse tests with a limited number of mostly crop plant species. Higher tier tests or assessments of any kind (e.g., field, semi-field, landscape studies) are not standardized. In this study we explored an approach to inform such a higher level by collecting datasets and information at European scale to characterize the vegetation communities that are likely to grow in the off-field areas of wheat and vine crops. The EUNIS (European Nature Information System) habitat classification was used to identify eight man-made habitats considered characteristic of the off-field areas in the European agricultural landscape. These habitats are spatially identified on the bases of a modelling process where vegetation plots, taken from the European Vegetation Archive, were used as observations and climate, soil, topographic, population density parameters and Remote Sensed Essential Biodiversity Variables as predictors. This modelling results in habitat suitability maps. The habitats are also described in terms of species frequencies and abundances, and to plant traits underlying possible vulnerability to pesticide exposure requested from the TRY plant trait database. Wheat and vine crop spatial data were derived from EUROSTAT and the QUICKScan methodology was used to combine all these data. We conclude that this method is helpful in reaching the objective as described in this paper. Its potential is that it can be extended probabilistically or linked to plant effect models.