The Habitat Suitability Analysis was built using ArcGIS Pro's ModelBuilder tool. This program does not have an option to save the model's inputs as a relative file path. As a result, the model may not run because it's searching for each layer's original file path. If this happens, we have included a file titled Habitat_Suitability_Analysis_Script that outlines the processes we used to build the model. This submission contains three folders and three supplemental files. The folder titled "Data" includes all of the raw data and data input in the Habitat Suitability Analysis. The folder titled "Scripts" describes the steps to build the Habitat Suitability Analysis model in ArcGIS Pro. The Results folder contains the Habitat Suitability Analysis model and the data that was input into the model. The supplemental files are a file titled "Dryad_Folder_Contents" which describes the contents of every folder in this submission, and a file titled "Habitat_Suitability_Analysis_README" which contain...

To address the global challenge of reducing greenhouse gas emissions contributing to climate change, it is essential to explore innovative, renewable, and sustainable energy solutions. Bioenergy, derived from biological sources, plays a vital role by providing renewable options for heat, electricity, and vehicle fuel. Biofuels from food crops like sugarcane and cassava demonstrate the potential of agricultural products for energy generation, while jatropha is cultivated primarily for oil. This learning activity focuses on land suitability mapping for these selected crops in Florida, incorporating criteria such as temperature, rainfall, soil type, soil pH, and topography. The analysis evaluates the land requirements of food and energy crops within the Food-Energy-Water (FEW) nexus framework, addressing potential land-use conflicts. Geographic Information Systems (GIS) are employed to identify optimal regions for energy crop cultivation, promoting sustainable practices that balance food security, water conservation, and renewable energy production. The modules are developed and designed for undergraduate students, particularly those enrolled in any of courses such as environmental science, GIS, natural resource management, agricultural science and remote sensing. Students will apply GIS and remote sensing techniques to analyze interactions among food, energy, and water resources, focusing on resilient crops. The activity incorporates the 4DEE framework – Core Ecological Concepts, Ecological Practices, Human-Environment Interactions, and Cross-Cutting Themes to enhance understanding of the FEW nexus. Through hands-on projects addressing real-world ecological challenges, students will develop critical skills in geospatial data analysis, data interpretation, and ethical considerations, preparing them for sustainable resource management. Likewise on part of the instructors, the activity is designed for those with intermediate to advanced GIS expertise, particularly in ArcGIS Pro and Google Earth Engine for spatial analysis and a basic understanding and application of the Food-Energy-Water (FEW) Nexus to guide students in making informed land-use decisions that support sustainable development goals.

Basemap natural color RGB image.Produced from ESA’s Sentinel-2 A/B imagery, 10 meter resolution Satellite Derive Bathymetry (SDB) is a highly accurate, extremely cost effective bathymetry product that can be produced in clear shallow water regions. The surface in this web scene was calibrated and validated using nautical charts as a survey planning surface to demonstrate shoal points and "no-go" areas.TCarta is a leading global provider of innovative hydrospatial products and Earth observation analysis services. TCarta GIS professionals, hydrographers, and developers provide solutions for onshore and offshore geospatial applications from engineering to environmental monitoring and beyond.TCarta’s primary focus is on providing affordability and accessibility of data and analytics utilizing cutting edge technology and approaches to best serve our clients where traditional methods fail with proven integrity of services and professional practices in a changing and dynamic world.USES: Satellite Derived Bathymetry (SDB) is a lower cost alternative to marine surveys and much higher resolution than ETOPO and GEBCO datasets. Coastal Engineering: Floating Solar Facilities: Suitability Analysis - Location siting using modern and accurate bathymetryWave modeling for construction planningMooring design & Cable routing to shore Offshore Wind Farms:Planning and AppraisalEnvironmental Impact assessmentsMooring design & Cable routingSite characterization Fiber Optic Cable Route Planning:Protecting marine life sanctuariesDecrease distance Aquaculture:Site selectionMonitoringFlow prediction Dredging:Measuring materialMonitoring Water Quality Monitoring:Chlorophyll IndexSediment flowNatural Disasters:Inundation modellingEnvironmental Compliance monitoring.TOOLS: ArcGIS PRO add-in and toolboxDELIVERABLES: GIS ready raster and vector formats, typically as GeoTiff, ASCII data with xyzu(where u represents Uncertainty of Z value) files in map projection coordinates (WGS84) with metadata. Other formats are available upon request like geodatabases, KML/KMZ, HDF, NetCDF

Produced from ESA’s Sentinel-2 A/B imagery, 10 meter resolution Satellite Derive Bathymetry (SDB) is a highly accurate, extremely cost effective bathymetry product that can be produced in clear shallow water regions. The surface in this web scene was calibrated and validated using nautical charts as a survey planning surface to demonstrate shoal points and "no-go" areas.TCarta is a leading global provider of innovative hydrospatial products and Earth observation analysis services. TCarta GIS professionals, hydrographers, and developers provide solutions for onshore and offshore geospatial applications from engineering to environmental monitoring and beyond.TCarta’s primary focus is on providing affordability and accessibility of data and analytics utilizing cutting edge technology and approaches to best serve our clients where traditional methods fail with proven integrity of services and professional practices in a changing and dynamic world.USES: Satellite Derived Bathymetry (SDB) is a lower cost alternative to marine surveys and much higher resolution than ETOPO and GEBCO datasets. Coastal Engineering: Floating Solar Facilities: Suitability Analysis - Location siting using modern and accurate bathymetryWave modeling for construction planningMooring design & Cable routing to shore Offshore Wind Farms:Planning and AppraisalEnvironmental Impact assessmentsMooring design & Cable routingSite characterization Fiber Optic Cable Route Planning:Protecting marine life sanctuariesDecrease distance Aquaculture:Site selectionMonitoringFlow prediction Dredging:Measuring materialMonitoring Water Quality Monitoring:Chlorophyll IndexSediment flowNatural Disasters:Inundation modellingEnvironmental Compliance monitoring.TOOLS: ArcGIS PRO add-in and toolboxDELIVERABLES: GIS ready raster and vector formats, typically as GeoTiff, ASCII data with xyzu(where u represents Uncertainty of Z value) files in map projection coordinates (WGS84) with metadata. Other formats are available upon request like geodatabases, KML/KMZ, HDF, NetCDFContact Sales@tcarta.com..

Bathymetry of Bowden Harbor Jamaica as a vector tile map service.Produced from ESA’s Sentinel-2 A/B imagery, 10 meter resolution Satellite Derive Bathymetry (SDB) is a highly accurate, extremely cost effective bathymetry product that can be produced in clear shallow water regions. The surface in this web scene was calibrated and validated using nautical charts as a survey planning surface to demonstrate shoal points and "no-go" areas.TCarta is a leading global provider of innovative hydrospatial products and Earth observation analysis services. TCarta GIS professionals, hydrographers, and developers provide solutions for onshore and offshore geospatial applications from engineering to environmental monitoring and beyond.TCarta’s primary focus is on providing affordability and accessibility of data and analytics utilizing cutting edge technology and approaches to best serve our clients where traditional methods fail with proven integrity of services and professional practices in a changing and dynamic world.USES: Satellite Derived Bathymetry (SDB) is a lower cost alternative to marine surveys and much higher resolution than ETOPO and GEBCO datasets. Coastal Engineering: Floating Solar Facilities: Suitability Analysis - Location siting using modern and accurate bathymetryWave modeling for construction planningMooring design & Cable routing to shore Offshore Wind Farms:Planning and AppraisalEnvironmental Impact assessmentsMooring design & Cable routingSite characterization Fiber Optic Cable Route Planning:Protecting marine life sanctuariesDecrease distance Aquaculture:Site selectionMonitoringFlow prediction Dredging:Measuring materialMonitoring Water Quality Monitoring:Chlorophyll IndexSediment flowNatural Disasters:Inundation modellingEnvironmental Compliance monitoring.TOOLS: ArcGIS PRO add-in and toolboxDELIVERABLES: GIS ready raster and vector formats, typically as GeoTiff, ASCII data with xyzu(where u represents Uncertainty of Z value) files in map projection coordinates (WGS84) with metadata. Other formats are available upon request like geodatabases, KML/KMZ, HDF, NetCDFContact Sales@tcarta.com..

Many species show range expansions or contractions due to climate-change-induced changes in habitat suitability. In cold climates, many species that are limited by snow are showing range expansions due to reduced winter severity. The European polecat (Mustela putorius) occurs over large parts of Europe with its northern range limit in southern Fennoscandia. However, it is to date unknown what factors limit polecat distribution. We thus investigated whether climate or land-use variables are more important in determining the habitat suitability for polecats in Sweden. We hypothesized that 1) climatic factors, especially the yearly number of snow days, drive habitat suitability for polecats, and that, 2) as the number of snow days is predicted to decline in the near future, habitat suitability in northern Sweden will increase. We used a combination of sightings data and a selection of national maps of environmental factors to test these hypotheses using MaxEnt models. We also used maps of future climate predictions (2021–2050 and 2063–2098) to predict future habitat suitability. The number of snow days was the most important factor, negatively determining habitat suitability for polecats, as expected. Consequently, the predictions showed an increase in suitable habitat both in the current distribution range and in northern Sweden, especially along the coast of the Baltic Sea. Our results suggest that the polecat distribution is limited by snow and that reduced snow cover will likely result in a northward range expansion. However, the exact mechanisms for how snow limits polecats are still poorly understood. Consequently, we expect the Scandinavian polecat population to increase in numbers, in contrast to many populations elsewhere in Europe, where numbers are declining. Due to polecat predation, the expansion of the species might have cascading effects on other wildlife populations. Methods Polecat sightings data To determine the distribution and habitat suitability of polecats in Sweden, we used sightings data of polecats gathered by volunteers and documented to the Swedish Species Information Centre between 1960 and 2020 (Figure 1; Swedish Species Information Centre 2020). We validated data at the edge of the distribution by contacting the person that reported the sighting, and removed data points if there was uncertainty about the sighting, we also removed data that was categorized as roadkill. As a result, we discarded 44 of the 425 sightings before analysis. Due to an increase of popularity of the sightings platform, the majority of sightings (78%) used in the analyses was from the period 2010–2020. Description of covariates We used nine covariates distributed over four different categories to test our hypotheses (Table 1). We included these covariates based on habitat and diet preferences of the polecat found in previous studies All parameters were rasterized and aggregated to 1-km2 grid cells over the whole of Sweden in ArcGis Pro version 2.6.0

Land cover and soil moisture

We selected several land-cover types and an index of soil moisture from the ungeneralised version of the National Land Cover Database (NMD) Sweden. This project provides a land cover map for the whole of Sweden divided into 24 different land-cover types, as well as a measure of soil moisture as a spectrum from dry to wet soil. We reclassified 17 of the 24 land-cover types into three different groups: coniferous forest, deciduous forest and open landscapes (Table S1.1). We selected these three groups for ease of analysis and due to previous studies showing that polecats selected or avoided these land-cover types at small spatial scales. Polecats were found to avoid coniferous forest (Baghli and Verhagen 2005, Zabala et al. 2005), select for deciduous forest (Jedrzejewski et al. 1993, Baghli et al. 2005), and use landscapes that were characterised by a variety of open habitat and forest (Blandford 1987, Lodé 1993, 2000a, Baghli et al. 2005). Furthermore, we used soil moisture as a variable that could further distinguish areas that would be wet during part of the year, which could result in increased amphibian populations, which are an important part of the polecat’s diet (Lodé 1993, 1997, 2000b, Hammershøj et al. 2004, Malecha and Antczak 2013). After reclassification, we determined the proportion of surface covered by each land-cover group, as well as the average soil moisture index, for each 1-km2 grid cell. Table S1.1: The landcover type clusters and which variables are merged from the original landcover data.

Cluster of land-cover types

Land-cover type number as presented in the NMD

Coniferous forest

111 (Pine forest not on wetland), 112 (Spruce forest not on wetland), 113 (Mixed coniferous not on wetland), 121 (Pine forest on wetland), 122 (Spruce forest on wetland), 123 (Mixed coniferous on wetland)

Deciduous forest

115 (Deciduous forest not on wetland), 116 (Deciduous hardwood forest not on wetland), 117 (Deciduous forest with deciduous hardwood forest not on wetland), 125 (Deciduous forest on wetland), 126 (Deciduous hardwood forest on wetland), 127 (Deciduous with deciduous hardwood forest on wetland)

Open landscapes

2 (Open wetland), 3 (Arable land), 41 (Non-vegetated other open land), 42 (Vegetated other open land), 118 (Temporarily non-forest not on wetland), 128 (Temporarily non-forest on wetland)

Snow cover and Minimum winter temperature The Swedish Meteorological and Hydrological Institute provides snow cover data for Sweden as the average number of days with snow with a depth above 20mm. The data is provided in 4 time periods, including two future projections (P1=1961–1990, P2 = 1991–2013, P3 = 2021–2050, P4= 2069–2098; Swedish Meteorological and Hydrological Institute 2021). The future projections we included are based on the 4.5 RCP scenario(Thomson et al. 2011). We included these data as a previous study showed that polecats had more difficulty catching prey when there is snow on the ground (Weber 1989). The data consists of interpolated data from 200 weather stations with an average given per municipality. We have rasterized the data giving average values for cells crossing municipality boundaries. We used data averages per cell of P2 for model building, while we used averages of P3 and P4 per cell for model projections of future scenarios.

Human pressure

We used the human footprint index as published by NASA in 2018 as a measure of human pressure. We did this as previous studies have shown that polecats tend to select for areas with extensive human use (Sidorovich et al. 1996, Rondinini et al. 2006) while avoiding urban centres (Zabala et al. 2005). The dataset is based on the global human footprint between 1995 and 2004. The human footprint is an index based on population density, land-use, infrastructure (buildings, lights, land use/cover) and human access (roads, railways; Venter et al. 2018). This raster dataset is publicly available and has a resolution of 1 km2. We only clipped the dataset to the borders of Sweden. Water availability We used the Water & Wetness geo data from Copernicus (CLMS 2018) as a measure of water availability. We did this as previous studies showed that polecats select for riparian habitat (Baghli et al. 2005) as amphibians are an important part of their diet (Lodé 1993, 1997, 2000b, Hammershøj et al. 2004, Malecha and Antczak 2013). This dataset includes all waterways and waterbodies with a resolution of 10 m. We have outlined all waterbodies and then made a buffer of 30 meters around all waterlines to represent near-water (riparian) habitat. We then calculated the proportion of near-water habitat in each 1-km2 grid cell. Elevation We used elevation data from the Copernicus Land Monitoring Service - EU-DEM project. We did this as previous studies showed that polecats avoid high-elevation areas. The dataset is provided as a raster with a spatial resolution of 25 meters. We calculated the average elevation for each 1-km2 grid cell. Bias correction for sampling intensity Due to the nature of citizen science data, it is prone to come with a bias. This bias manifests itself mostly in a discrepancy in spatial sampling effort. To account for this bias, we created a density kernel (as recommended by Kramer-Schadt et al. 2013 and Morelle and Lejeune 2015 and in line with Rutten et al. 2019) based on all mustelid sightings (n = 25686) reported to the Swedish Species Information Centre between 1972 and 2021 (Swedish Species Information Centre 2020), except for the Eurasian badger (Meles meles), the wolverine (Gulo gulo) and the polecat. We excluded the badger and wolverine as we expect this species to be much easier to identify and see compared to the polecat and other mustelids. Furthermore, badger and wolverine have a limited distribution in Sweden, while all other species – Eurasian otter (Lutra lutra), pine marten (Martes martes), American mink (Neovison vison), stoat (Mustela erminea), and weasel (Mustela nivalis) – have a distribution that covers the whole of Sweden (Swedish Species Information Centre 2020). We created the kernel with the ‘Kernel Density’ function in ArcGIS Pro (Esri 2021) with the mustelid sighting coordinates and the 1 km2 raster grid used for the covariates. The use of this density kernel is based on the assumption that people reporting other mustelids would also report a polecat if they saw one, and thus that the distribution of mustelid sightings is representative of the distribution of potential polecat reporters.

This submission is from a master's group thesis project at The Bren School of Environmental Science & Management at the University of California, Santa Barbara, and contains the final written report and associated datasets. The graduate student researchers who completed this project include: Meghan Fletcher, Alyssa Kibbe, Grace Kumaishi, Anna Talken, and Nikole Vannest.

The California landscape has been fragmented by urban development, infrastructure, and agriculture. Maintaining connectivity between areas of wildlife habitat is important for the viability of many long-ranging species, such as the mountain lion (Puma concolor). Mountain lion populations are highly susceptible to habitat fragmentation, and face reduced access to resources and decreased genetic diversity. This study explores the habitat connectivity between the Jack and Laura Dangermond Preserve (JLDP), a 24,460 acre protected property owned by The Nature Conservancy (TNC), and neighboring protected areas to identify potential pathways of movement for mountain lions along the Central and Southern California coast. In this project, we: 1) determine regional connectivity and least cost paths between core habitats by modeling suitable mountain lion habitat, 2) estimate mountain lion habitat use and movement on JLDP by performing a site-level suitability and corridor analysis and 3) create a short film focused on highlighting our research, the role that JLDP plays in conservation, and the importance of habitat connectivity. The results of our project show that JLDP contains suitable habitat for mountain lions and may play a positive role in coastal connectivity. When considering the connectivity between JLDP and other regional protected areas, our analyses indicate that urbanized coastal regions act as barriers to mountain lions and contain pinch points that channelize movement. These results can guide TNC in developing management strategies for protecting mountain lions on JLDP and in the surrounding region.

Analyses were conducted using ArcGIS, Google Earth Engine, MaxENT, Circuitscape, and Omniscape. The project began in April 2021 and ended in June 2022. Methods Data was collected from open source data acquired using Google Earth Engine and Esri ArcOnline from the following sources: NASA, USGS, JPL-CalTech, Conservation Science Partners, CalFish, US Census and CalFire. It was processed using Esri ArcMap, ArcGIS Pro, Maxent, Omniscape via Jupyter Notebook and the Linkage Mapper Toolkit within ArcMap.

seafloor elevation bathymetry of Bowden Harbor, JamaicaProduced from ESA’s Sentinel-2 A/B imagery, 10 meter resolution Satellite Derive Bathymetry (SDB) is a highly accurate, extremely cost effective bathymetry product that can be produced in clear shallow water regions. The surface in this web scene was calibrated and validated using nautical charts as a survey planning surface to demonstrate shoal points and "no-go" areas.TCarta is a leading global provider of innovative hydrospatial products and Earth observation analysis services. TCarta GIS professionals, hydrographers, and developers provide solutions for onshore and offshore geospatial applications from engineering to environmental monitoring and beyond.TCarta’s primary focus is on providing affordability and accessibility of data and analytics utilizing cutting edge technology and approaches to best serve our clients where traditional methods fail with proven integrity of services and professional practices in a changing and dynamic world.USES: Satellite Derived Bathymetry (SDB) is a lower cost alternative to marine surveys and much higher resolution than ETOPO and GEBCO datasets. Coastal Engineering: Floating Solar Facilities: Suitability Analysis - Location siting using modern and accurate bathymetryWave modeling for construction planningMooring design & Cable routing to shore Offshore Wind Farms:Planning and AppraisalEnvironmental Impact assessmentsMooring design & Cable routingSite characterization Fiber Optic Cable Route Planning:Protecting marine life sanctuariesDecrease distance Aquaculture:Site selectionMonitoringFlow prediction Dredging:Measuring materialMonitoring Water Quality Monitoring:Chlorophyll IndexSediment flowNatural Disasters:Inundation modellingEnvironmental Compliance monitoring.TOOLS: ArcGIS PRO add-in and toolboxDELIVERABLES: GIS ready raster and vector formats, typically as GeoTiff, ASCII data with xyzu(where u represents Uncertainty of Z value) files in map projection coordinates (WGS84) with metadata. Other formats are available upon request like geodatabases, KML/KMZ, HDF, NetCDFContact Sales@tcarta.com..

Tile layer of Transects of Bowden Harbour Jamaica at Lowest Astronomical Tide.Produced from ESA’s Sentinel-2 A/B imagery, 10 meter resolution Satellite Derive Bathymetry (SDB) is a highly accurate, extremely cost effective bathymetry product that can be produced in clear shallow water regions. The surface in this web scene was calibrated and validated using nautical charts as a survey planning surface to demonstrate shoal points and "no-go" areas.TCarta is a leading global provider of innovative hydrospatial products and Earth observation analysis services. TCarta GIS professionals, hydrographers, and developers provide solutions for onshore and offshore geospatial applications from engineering to environmental monitoring and beyond.TCarta’s primary focus is on providing affordability and accessibility of data and analytics utilizing cutting edge technology and approaches to best serve our clients where traditional methods fail with proven integrity of services and professional practices in a changing and dynamic world.USES: Satellite Derived Bathymetry (SDB) is a lower cost alternative to marine surveys and much higher resolution than ETOPO and GEBCO datasets. Coastal Engineering: Floating Solar Facilities: Suitability Analysis - Location siting using modern and accurate bathymetryWave modeling for construction planningMooring design & Cable routing to shore Offshore Wind Farms:Planning and AppraisalEnvironmental Impact assessmentsMooring design & Cable routingSite characterization Fiber Optic Cable Route Planning:Protecting marine life sanctuariesDecrease distance Aquaculture:Site selectionMonitoringFlow prediction Dredging:Measuring materialMonitoring Water Quality Monitoring:Chlorophyll IndexSediment flowNatural Disasters:Inundation modellingEnvironmental Compliance monitoring.TOOLS: ArcGIS PRO add-in and toolboxDELIVERABLES: GIS ready raster and vector formats, typically as GeoTiff, ASCII data with xyzu(where u represents Uncertainty of Z value) files in map projection coordinates (WGS84) with metadata. Other formats are available upon request like geodatabases, KML/KMZ, HDF, NetCDFContact Sales@tcarta.com..

Shoal points are the shallow water points .Produced from ESA’s Sentinel-2 A/B imagery, 10 meter resolution Satellite Derive Bathymetry (SDB) is a highly accurate, extremely cost effective bathymetry product that can be produced in clear shallow water regions. The surface in this web scene was calibrated and validated using nautical charts as a survey planning surface to demonstrate shoal points and "no-go" areas.TCarta is a leading global provider of innovative hydrospatial products and Earth observation analysis services. TCarta GIS professionals, hydrographers, and developers provide solutions for onshore and offshore geospatial applications from engineering to environmental monitoring and beyond.TCarta’s primary focus is on providing affordability and accessibility of data and analytics utilizing cutting edge technology and approaches to best serve our clients where traditional methods fail with proven integrity of services and professional practices in a changing and dynamic world.USES: Satellite Derived Bathymetry (SDB) is a lower cost alternative to marine surveys and much higher resolution than ETOPO and GEBCO datasets. Coastal Engineering: Floating Solar Facilities: Suitability Analysis - Location siting using modern and accurate bathymetryWave modeling for construction planningMooring design & Cable routing to shore Offshore Wind Farms:Planning and AppraisalEnvironmental Impact assessmentsMooring design & Cable routingSite characterization Fiber Optic Cable Route Planning:Protecting marine life sanctuariesDecrease distance Aquaculture:Site selectionMonitoringFlow prediction Dredging:Measuring materialMonitoring Water Quality Monitoring:Chlorophyll IndexSediment flowNatural Disasters:Inundation modellingEnvironmental Compliance monitoring.TOOLS: ArcGIS PRO add-in and toolboxDELIVERABLES: GIS ready raster and vector formats, typically as GeoTiff, ASCII data with xyzu(where u represents Uncertainty of Z value) files in map projection coordinates (WGS84) with metadata. Other formats are available upon request like geodatabases, KML/KMZ, HDF, NetCDF