These files provide the full spatial data and group lists needed to replicate all analyses in "The Spatial Properties of Radical Environmental Organizations in the UK: Do or Die!"

Despite the ubiquity of coastal infrastructure, it is unclear what factors drive its placement, particularly for water access infrastructure (WAI) that facilitates entry to coastal ecosystems such as docks, piers, and boat landings. The placement of WAI has both ecological and social dimensions, and certain segments of coastal populations may have differential access to water. In this study, we employed an environmental justice framework to assess how public and private WAI in South Carolina, USA is distributed with respect to race and income. Using publicly available data from state agencies and the US Census Bureau, we mapped the distribution of these structures across the 301 km of the South Carolina coast. Using spatially explicit analyses with high resolution, we found that census block groups with lower income contain more public WAI, but racial composition has no effect. On the other hand, private docks showed the opposite trends, as the abundance of docks is significantly, positively correlated with census block groups that have greater percentages of White residents, while income has no effect. Under a "need-based" model of equity, we argue that WAI are not equitably distributed in South Carolina and constitute an environmental justice issue. We contend that the racially unequal distribution of docks is likely a consequence of the legacy of Black land loss, especially of waterfront property, throughout the coastal Southeast over the past half-century. Knowledge of racially inequitable distribution of WAI can guide public policy to rectify this imbalance and support advocacy organizations working to promote public water access. Our work also points to the importance of considering race in ecological research, as the spatial distribution of coastal infrastructure both directly affects ecosystems through the structures themselves and regulates which groups access water and what activities they can engage in at those sites.

Metacommunities are dynamic systems, but the influence of time independently of environmental change in their configuration has been rarely considered. In temporary ponds, strong temporal effects are expected to influence their metacommunity structure, even in relatively constant environments such as tropical habitats. We therefore expect that time as an independent factor could modulate tropical pond metacommunities, which would be also less affected by niche-related processes than by dispersal-related processes. In addition, good dispersers should be more environmentally structured than bad dispersers, which should be more spatially structured. Finally, the relevance of temporal effects should vary among organisms with different generation times. To test these hypotheses, we surveyed 30 temporary ponds along the dry tropical region of western Costa Rica and Nicaragua at three different moments of their hydroperiod: shortly after the infilling of the water bodies, at the middle of the hydroperiod and just before desiccation. We obtained data on 56 environmental variables and used geographic coordinates to build spatial variables (Moran Eigenvector Maps). We collected biological samples and estimated the specific abundance of phytoplankton, zooplankton and benthic invertebrates. To evaluate the relative role of environmental, spatial and temporal (sequential sampling season) effects for metacommunity organization, we used variation partitioning with distance-based redundancy analyses for each group of organisms. The inclusion of time in the analysis highlighted that pure temporal effects explained part of metacommunity variance in almost every group, being as important as spatial or even environmental effects for some groups of organisms. In contrast to the assumed low environmental constraints in tropical areas (i.e., high and stable temperatures), we found strong environmental effects. Passive dispersers were more influenced by environmental factors than active ones. We also found a positive relationship between the body size of the different groups of organisms and the magnitude of the temporal effects, interpreted as related to generation time. Finally, when analyzing each sampling period separately, we found differences in the relative role of environment and space at different sampling periods, showing that snapshot surveys may not be representative of highly dynamic metacommunities.

The data represent web-scraping of hyperlinks from a selection of environmental stewardship organizations that were identified in the 2017 NYC Stewardship Mapping and Assessment Project (STEW-MAP) (USDA 2017). There are two data sets: 1) the original scrape containing all hyperlinks within the websites and associated attribute values (see "README" file); 2) a cleaned and reduced dataset formatted for network analysis. For dataset 1: Organizations were selected from from the 2017 NYC Stewardship Mapping and Assessment Project (STEW-MAP) (USDA 2017), a publicly available, spatial data set about environmental stewardship organizations working in New York City, USA (N = 719). To create a smaller and more manageable sample to analyze, all organizations that intersected (i.e., worked entirely within or overlapped) the NYC borough of Staten Island were selected for a geographically bounded sample. Only organizations with working websites and that the web scraper could access were retained for the study (n = 78). The websites were scraped between 09 and 17 June 2020 to a maximum search depth of ten using the snaWeb package (version 1.0.1, Stockton 2020) in the R computational language environment (R Core Team 2020). For dataset 2: The complete scrape results were cleaned, reduced, and formatted as a standard edge-array (node1, node2, edge attribute) for network analysis. See "READ ME" file for further details. References: R Core Team. (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Version 4.0.3. Stockton, T. (2020). snaWeb Package: An R package for finding and building social networks for a website, version 1.0.1. USDA Forest Service. (2017). Stewardship Mapping and Assessment Project (STEW-MAP). New York City Data Set. Available online at https://www.nrs.fs.fed.us/STEW-MAP/data/. This dataset is associated with the following publication: Sayles, J., R. Furey, and M. Ten Brink. How deep to dig: effects of web-scraping search depth on hyperlink network analysis of environmental stewardship organizations. Applied Network Science. Springer Nature, New York, NY, 7: 36, (2022).

Ecoregions for the Mississippi Alluvial Plain were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and non-government organizations that are responsible for different types of resources within the same geographical areas (Omernik and others, 2000). The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). This product is part of a collaborative effort primarily between USEPA Region VII, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), Mississippi Department of Environmental Quality, Arkansas Department of Environmental Quality, Arkansas Multi-Agency Wetland Planning Team (MAWPT), U.S. Army Corps of Engineers (USACE), U.S. Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS), U.S. Department of Interior - Fish and Wildlife Service (USFWS), and U.S. Department of Interior - U.S. Geological Survey (USGS) - Earth Resources Observation Systems (EROS) Data Center. The project is associated with an interagency effort to develop a common framework of ecological regions. Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies that have been used to develop the most common ecoregion-type frameworks, including those developed by the U.S. Department of Agriculture - Forest Service (USFS) (Bailey and others, 1994), the USEPA (Omernik, 1987, 1995), and the NRCS (United States Department of Agriculture - Soil Conservation Service, 1981). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in the Mississippi Alluvial Plain, where agreement can be reached among multiple resource management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation. Literature cited: Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103. Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38. U.S. Environmental Protection Agency. 2011. Level III and IV ecoregions of the continental United States. U.S. EPA, National Health and Environmental Effects Research Laboratory, Corvallis, Oregon, Map scale 1:3,000,000. Available online at: https://res1wwwd-o-tepad-o-tgov.vcapture.xyz/eco-research/level-iii-and-iv-ecoregions-continental-united-states. Comments and questions regarding Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.gov

Aim: The influences of environmental and spatial processes on species composition have been at the center of metacommunity ecology. Conversely, the relative importance of these processes for species co-occurrences and taxonomic similarity has remained poorly understood. We hypothesized that at a subcontinental scale, shared environmental preference would be the major driver of co-occurrences across species groups. In contrast, co-occurrences due to shared dispersal history were more likely in dispersal-limited taxa. Finally, we tested whether taxa co-occurring due to similar responses to environmental and spatial processes were more taxonomically similar than expected by chance. Location: The conterminous United States Time Period: 1993-2019 Major taxa studied: Stream diatoms, insects, and fish Methods: We generated co-occurrence networks and developed methodology to determine the proportions of nodes and edges explained by pure environment alone (after accounting for space), pure space alone (after accounting for the environment), pure environment and pure space together, and spatially structured environment. Taxonomic similarity of taxa co-occurring because of environmental and/or spatial controls or because of unmeasured processes was compared to that of a null model. Results: Pure environment alone, spatially structured environment, and pure environment and pure space together explained the greatest proportion of nodes and edges in the co-occurrence networks of diatom species and genera, and insect genera. Conversely, pure environment and pure space together best explained the nodes and edges in the co-occurrence network of fish species and genera. Co-occurring taxa were more closely related than the random expectation in all 30 cases. Main Conclusions: The environment controlled co-occurrences of all groups, while the influence of space was the strongest in fish, the most dispersal-limited group in our study. All co-occurring taxa were more taxonomically related than expected by chance due to environmental or spatial overlap or unaccounted factors. Methods We obtained data from Passy et al., (2023), including diatoms, insects, and fish, collected from, respectively, 1698, 1700, and 1700 stream sites across the conterminous United States (Fig. S1). Sites were compiled from both the National Water-Quality Assessment (NAWQA) program of the US Geological Survey and the National Rivers and Streams Assessment (NRSA) of the US Environmental Protection Agency, which used similar collection methods (Moulton II et al., 2002; US Environmental Protection Agency, 2013). Streams were sampled between 1993 and 2019, with the majority of samples collected between 2007 and 2010. Diatoms and insects were collected from a predetermined area of substrate from May to September. Fish were sampled throughout the year using backpack electrofishing and seining. Community data consisted of counts of species or a lower taxonomic category in diatoms and fish, but genera in insects. To standardize the sampling effort, diatom counts were sampled down to 400 cells, and the insect and fish counts, to 100 individuals. We accounted for differences in taxonomic resolution by examining all datasets at a genus level in addition to the species level for diatoms and fish. We selected our 1698-1700 sites from larger datasets of 2278 diatom, 2270 insect, and 2296 fish samples, ensuring similar environmental conditions, a minimum pairwise distance between any two sites of 1 km, and comparable average pairwise distance among datasets (1522, 1497, and 1491 km, respectively), which we provide here. Pairwise distances between all sites were calculated in km using the ‘distm’ function in the R package ‘geosphere’ (Hijmans et al., 2019). Each site had available physicochemical data on pH, specific conductance (µS/cm), water temperature (C°), nitrate (NO3, µg/L), and total phosphorous (TP, µg/L) from NAWQA or NRSA. Elevation (m) was obtained from the WorldClim database (Fick & Hijmans, 2017) and used to calculate slope (% grade), averaged across a 5 km buffer around each site with the package ‘raster’ (Hijmans et al., 2020). There were 19 climatic variables that described temperature and precipitation minima, maxima, averages, ranges, and seasonality across a 5 km buffer around each site (WorldClim V1.4) (Hijmans et al., 2005). Environmental variables were ln-transformed if normality was improved. The slope was arcsine square root-transformed. All variables were standardized (mean = 0, standard deviation = 1). We also assembled higher-order taxa for each metacommunity, consisting of phylum, class, order, family, genus, species, subspecies, variety, and form for diatoms; phylum, class, order, family, and genus for insects, and finally, phylum, class, order, family, genus, and species for fish.

Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). Data Download: https://app.fw.ky.gov/kfwis/kygeonet/ecoregion2012.zip Literature cited: Bailey, R.G., Avers, P.E., King, T., and McNab, W.H., eds., 1994, Ecoregions and subregions of the United States (map): Washington, D.C., USFS, scale 1:7,500,000.Bryce, S.A., Omernik, J.M., and Larsen, D.P., 1999, Ecoregions—a geographic framework to guide risk characterization and ecosystem management: Environmental Practice, v. 1, no. 3, p. 141-155.Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Griffith, G., Omernik, J., Azevedo, S., 1998, Ecoregions of Tennessee (text, map, summary tables, and photographs): Reston, Virginia, U.S. Geological Survey, map scale 1:940,000.McMahon, G., Gregonis, S.M., Waltman, S.W., Omernik, J.M., Thorson, T.D., Freeouf, J.A., Rorick, A.H., and Keys, J.E., 2001, Developing a spatial framework of common ecological regions for the conterminous United States: Environmental Management, v. 28, no. 3, p. 293-316.Omernik, J.M., 1987, Ecoregions of the conterminous United States (map supplement): Annals of the Association of American Geographers, v. 77, p. 118-125, scale 1:7,500,000.Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103.Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38.U.S. Department of Agriculture–Soil Conservation Service, 198, Land resource regions and major land resource areas of the United States: Agriculture Handbook 296, 156 p.U.S. Environmental Protection Agency, 2002, Level III ecoregions of the continental United States (revision of Omernik, 1987): Corvallis, Oregon, USEPA–National Health and Environmental Effects Research Laboratory, Map M-1, various scales.Wiken, E., 1986, Terrestrial ecozones of Canada: Ottawa, Environment Canada, Ecological Land Classification Series no. 19, 26 p.Woods, A.J., Omernik, J.M., Brockman, C.S., Gerber, T.D., Hosteter, W.D., and Azevedo, S.H., 1998, Ecoregions of Indiana and Ohio: Reston, USGS, map scale 1:500,000Comments and questions regarding the Level III and IV Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.govThis was first downloaded by KDFWR in 2005 for the State Wildlife Action Plan and then updated in 2012 again to reflect an updated national shapefile. Kentucky Department of Fish and Wildlife Resources downloaded first the Kentucky Data set https://www.epa.gov/eco-research/ecoregion-download-files-state-region-4#pane-15 , but saw that the boundary did match well the Kentucky state boundary maintained by KY Geonet. We then downloaded the national data set obtained from https://www.epa.gov/eco-research/level-iii-and-iv-ecoregions-continental-united-statesand intersected to the KY DGI state boundary, For those slivers assigned to unexpected ecoregions (55d Pre-Wisconsinan Drift Plains, 67h Southern Sandstone Ridges, 71m Northern Shawnee Hills, 71n Southern Shawnee Hills, 73c St. Francis Lowlands) we merged to the geographically nearest polygon so that the ecoregions found in this dataset match that in the poster Ecoregions of Kentucky.

Ecoregions for the Mississippi Alluvial Plain were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and non-government organizations that are responsible for different types of resources within the same geographical areas (Omernik and others, 2000). The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). This product is part of a collaborative effort primarily between USEPA Region VII, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), Mississippi Department of Environmental Quality, Arkansas Department of Environmental Quality, Arkansas Multi-Agency Wetland Planning Team (MAWPT), U.S. Army Corps of Engineers (USACE), U.S. Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS), U.S. Department of Interior - Fish and Wildlife Service (USFWS), and U.S. Department of Interior - U.S. Geological Survey (USGS) - Earth Resources Observation Systems (EROS) Data Center. The project is associated with an interagency effort to develop a common framework of ecological regions. Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies that have been used to develop the most common ecoregion-type frameworks, including those developed by the U.S. Department of Agriculture - Forest Service (USFS) (Bailey and others, 1994), the USEPA (Omernik, 1987, 1995), and the NRCS (United States Department of Agriculture - Soil Conservation Service, 1981). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in the Mississippi Alluvial Plain, where agreement can be reached among multiple resource management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation. Literature cited: Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103. Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38. U.S. Environmental Protection Agency. 2011. Level III and IV ecoregions of the continental United States. U.S. EPA, National Health and Environmental Effects Research Laboratory, Corvallis, Oregon, Map scale 1:3,000,000. Available online at: https://res1wwwd-o-tepad-o-tgov.vcapture.xyz/eco-research/level-iii-and-iv-ecoregions-continental-united-states. Comments and questions regarding Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.gov

Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). Literature cited: Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103. Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38. U.S. Environmental Protection Agency. 2011. Level III and IV ecoregions of the continental United States. U.S. EPA, National Health and Environmental Effects Research Laboratory, Corvallis, Oregon, Map scale 1:3,000,000. Available online at: http://www.epa.gov/wed/pages/ecoregions/level_iii_iv.htm. Comments and questions regarding Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.gov

Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). Literature cited: Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103. Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38. U.S. Environmental Protection Agency. 2011. Level III and IV ecoregions of the continental United States. U.S. EPA, National Health and Environmental Effects Research Laboratory, Corvallis, Oregon, Map scale 1:3,000,000. Available online at: https://www.epa.gov/eco-research/level-iii-and-iv-ecoregions-continental-united-states. Comments and questions regarding Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.gov

Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). Literature cited: Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103. Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38. Comments and questions regarding Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.gov

The Terrestrial 30x30 Conserved Areas map layer was developed by the CA Nature working group, providing a statewide perspective on areas managed for the protection or enhancement of biodiversity. Understanding the spatial distribution and extent of these durably protected and managed areas is a vital aspect of tracking and achieving the “30x30” goal of conserving 30% of California's lands and waters by 2030.Terrestrial and Freshwater Data• The California Protected Areas Database (CPAD), developed and managed by GreenInfo Network, is the most comprehensive collection of data on open space in California. CPAD data consists of Holdings, a single parcel or small group of parcels, such that the spatial features of CPAD correspond to ownership boundaries. • The California Conservation Easement Database (CCED), managed by GreenInfo Network, aggregates data on lands with easements. Conservation Easements are legally recorded interests in land in which a landholder sells or relinquishes certain development rights to their land in perpetuity. Easements are often used to ensure that lands remain as open space, either as working farm or ranch lands, or areas for biodiversity protection. Easement restrictions typically remain with the land through changes in ownership. • The Protected Areas Database of the United States (PAD-US), hosted by the United States Geological Survey (USGS), is developed in coordination with multiple federal, state, and non-governmental organization (NGO) partners. PAD-US, through the Gap Analysis Project (GAP), uses a numerical coding system in which GAP codes 1 and 2 correspond to management strategies with explicit emphasis on protection and enhancement of biodiversity. PAD-US is not specifically aligned to parcel boundaries and as such, boundaries represented within it may not align with other data sources. • Numerous datasets representing designated boundaries for entities such as National Parks and Monuments, Wild and Scenic Rivers, Wilderness Areas, and others, were downloaded from publicly available sources, typically hosted by the managing agency.Methodology1. CPAD and CCED represent the most accurate location and ownership information for parcels in California which contribute to the preservation of open space and cultural and biological resources.2. Superunits are collections of parcels (Holdings) within CPAD which share a name, manager, and access policy. Most Superunits are also managed with a generally consistent strategy for biodiversity conservation. Examples of Superunits include Yosemite National Park, Giant Sequoia National Monument, and Anza-Borrego Desert State Park. 3. Some Superunits, such as those owned and managed by the Bureau of Land Management, U.S. Forest Service, or National Park Service , are intersected by one or more designations, each of which may have a distinct management emphasis with regards to biodiversity. Examples of such designations are Wilderness Areas, Wild and Scenic Rivers, or National Monuments.4. CPAD Superunits and CCED easements were intersected with all designation boundary files to create the operative spatial units for conservation analysis, henceforth 'Conservation Units,' which make up the Terrestrial 30x30 Conserved Areas map layer. Each easement was functionally considered to be a Superunit. 5. Each Conservation Unit was intersected with the PAD-US dataset in order to determine the management emphasis with respect to biodiversity, i.e., the GAP code. Because PAD-US is national in scope and not specifically parcel aligned with California assessors' surveys, a direct spatial extraction of GAP codes from PAD-US would leave tens of thousands of GAP code data slivers within the 30x30 Conserved Areas map. Consequently, a generalizing approach was adopted, such that any Conservation Unit with greater than 80% areal overlap with a single GAP code was uniformly assigned that code. Additionally, the total area of GAP codes 1 and 2 were summed for the remaining uncoded Conservation Units. If this sum was greater than 80% of the unit area, the Conservation Unit was coded as GAP 2. 6. Subsequent to this stage of analysis, certain Conservation Units remained uncoded, either due to the lack of a single GAP code (or combined GAP codes 1&2) overlapping 80% of the area, or because the area was not sufficiently represented in the PAD-US dataset. 7. These uncoded Conservation Units were then broken down into their constituent, finer resolution Holdings, which were then analyzed according to the above workflow. 8. Areas remaining uncoded following the two-step process of coding at the Superunit and then Holding levels were assigned a GAP code of 4. This is consistent with the definition of GAP Code 4: areas unknown to have a biodiversity management focus. 9. Greater than 90% of all areas in the Terrestrial 30x30 Conserved Areas map layer were GAP coded at the level of CPAD Superunits intersected by designation boundaries, the coarsest land units of analysis. By adopting these coarser analytical units, the Terrestrial 30X30 Conserved Areas map layer avoids hundreds of thousands of spatial slivers that result from intersecting designations with smaller, more numerous parcel records. In most cases, individual parcels reflect the management scenario and GAP status of the umbrella Superunit and other spatially coincident designations.Tracking Conserved AreasThe total acreage of conserved areas will increase as California works towards its 30x30 goal. Some changes will be due to shifts in legal protection designations or management status of specific lands and waters. However, shifts may also result from new data representing improvements in our understanding of existing biodiversity conservation efforts. The California Nature Project is expected to generate a great deal of excitement regarding the state's trajectory towards achieving the 30x30 goal. We also expect it to spark discussion about how to shape that trajectory, and how to strategize and optimize outcomes. We encourage landowners, managers, and stakeholders to investigate how their lands are represented in the Terrestrial 30X30 Conserved Areas Map Layer. This can be accomplished by using the Conserved Areas Explorer web application, developed by the CA Nature working group. Users can zoom into the locations they understand best and share their expertise with us to improve the data representing the status of conservation efforts at these sites. The Conserved Areas Explorer presents a tremendous opportunity to strengthen our existing data infrastructure and the channels of communication between land stewards and data curators, encouraging the transfer of knowledge and improving the quality of data. CPAD, CCED, and PAD-US are built from the ground up. Data is derived from available parcel information and submissions from those who own and manage the land. So better data starts with you. Do boundary lines require updating? Is the GAP code inconsistent with a Holding’s conservation status? If land under your care can be better represented in the Terrestrial 30X30 Conserved Areas map layer, please use this link to initiate a review. The results of these reviews will inform updates to the California Protected Areas Database, California Conservation Easement Database, and PAD-US as appropriate for incorporation into future updates to CA Nature and tracking progress to 30x30.

The Terrestrial 30x30 Conserved Areas map layer was developed by the CA Nature working group, providing a statewide perspective on areas managed for the protection or enhancement of biodiversity. Understanding the spatial distribution and extent of these durably protected and managed areas is a vital aspect of tracking and achieving the “30x30” goal of conserving 30% of California's lands and waters by 2030.Terrestrial and Freshwater Data• The California Protected Areas Database (CPAD), developed and managed by GreenInfo Network, is the most comprehensive collection of data on open space in California. CPAD data consists of Holdings, a single parcel or small group of parcels which comprise the spatial features of CPAD, generally corresponding to ownership boundaries. • The California Conservation Easement Database (CCED), managed by GreenInfo Network, aggregates data on lands with easements. Conservation Easements are legally recorded interests in land in which a landholder sells or relinquishes certain development rights to their land in perpetuity. Easements are often used to ensure that lands remain as open space, either as working farm or ranch lands, or areas for biodiversity protection. Easement restrictions typically remain with the land through changes in ownership. •The Protected Areas Database of the United States (PAD-US), hosted by the United States Geological Survey (USGS), is developed in coordination with multiple federal, state, and non-governmental organization (NGO) partners. PAD-US, through the Gap Analysis Project (GAP), uses a numerical coding system in which GAP codes 1 and 2 correspond to management strategies with explicit emphasis on protection and enhancement of biodiversity. PAD-US is not specifically aligned to parcel boundaries and as such, boundaries represented within it may not align with other data sources. • Numerous datasets representing designated boundaries for entities such as National Parks and Monuments, Wild and Scenic Rivers, Wilderness Areas, and others, were downloaded from publicly available sources, typically hosted by the managing agency.Methodology1.CPAD and CCED represent the most accurate location and ownership information for parcels in California which contribute to the preservation of open space and cultural and biological resources.2. Superunits are collections of parcels (Holdings) within CPAD which share a name, manager, and access policy. Most Superunits are also managed with a generally consistent strategy for biodiversity conservation. Examples of Superunits include Yosemite National Park, Giant Sequoia National Monument, and Anza-Borrego Desert State Park. 3. Some Superunits, such as those owned and managed by the Bureau of Land Management, U.S. Forest Service, or National Park Service , are intersected by one or more designations, each of which may have a distinct management emphasis with regards to biodiversity. Examples of such designations are Wilderness Areas, Wild and Scenic Rivers, or National Monuments.4. CPAD Superunits and CCED easements were intersected with all designation boundary files to create the operative spatial units for conservation analysis, henceforth 'Conservation Units,' which make up the Terrestrial 30x30 Conserved Areas map layer. Each easement was functionally considered to be a Superunit. 5. Each Conservation Unit was intersected with the PAD-US dataset in order to determine the management emphasis with respect to biodiversity, i.e., the GAP code. Because PAD-US is national in scope and not specifically parcel aligned with California assessors' surveys, a direct spatial extraction of GAP codes from PAD-US would leave tens of thousands of GAP code data slivers within the 30x30 Conserved Areas map. Consequently, a generalizing approach was adopted, such that any Conservation Unit with greater than 80% areal overlap with a single GAP code was uniformly assigned that code. Additionally, the total area of GAP codes 1 and 2 were summed for the remaining uncoded Conservation Units. If this sum was greater than 80% of the unit area, the Conservation Unit was coded as GAP 2. 6.Subsequent to this stage of analysis, certain Conservation Units remained uncoded, either due to the lack of a single GAP code (or combined GAP codes 1&2) overlapping 80% of the area, or because the area was not sufficiently represented in the PAD-US dataset. 7.These uncoded Conservation Units were then broken down into their constituent, finer resolution Holdings, which were then analyzed according to the above workflow. 8. Areas remaining uncoded following the two-step process of coding at the Superunit and then Holding levels were assigned a GAP code of 4. This is consistent with the definition of GAP Code 4: areas unknown to have a biodiversity management focus. 9. Greater than 90% of all areas in the Terrestrial 30x30 Conserved Areas map layer were GAP coded at the level of CPAD Superunits intersected by designation boundaries, the coarsest land units of analysis. By adopting these coarser analytical units, the Terrestrial 30X30 Conserved Areas map layer avoids hundreds of thousands of spatial slivers that result from intersecting designations with smaller, more numerous parcel records. In most cases, individual parcels reflect the management scenario and GAP status of the umbrella Superunit and other spatially coincident designations.10. PAD-US is a principal data source for understanding the spatial distribution of GAP coded lands, but it is national in scope, and may not always be the most current source of data with respect to California holdings. GreenInfo Network, which develops and maintains the CPAD and CCED datasets, has taken a lead role in establishing communication with land stewards across California in order to make GAP attribution of these lands as current and accurate as possible. The tabular attribution of these datasets is analyzed in addition to PAD-US in order to understand whether a holding may be considered conserved. Tracking Conserved Areas The total acreage of conserved areas will increase as California works towards its 30x30 goal. Some changes will be due to shifts in legal protection designations or management status of specific lands and waters. However, shifts may also result from new data representing improvements in our understanding of existing biodiversity conservation efforts. The California Nature Project is expected to generate a great deal of excitement regarding the state's trajectory towards achieving the 30x30 goal. We also expect it to spark discussion about how to shape that trajectory, and how to strategize and optimize outcomes. We encourage landowners, managers, and stakeholders to investigate how their lands are represented in the Terrestrial 30X30 Conserved Areas Map Layer. This can be accomplished by using the Conserved Areas Explorer web application, developed by the CA Nature working group. Users can zoom into the locations they understand best and share their expertise with us to improve the data representing the status of conservation efforts at these sites. The Conserved Areas Explorer presents a tremendous opportunity to strengthen our existing data infrastructure and the channels of communication between land stewards and data curators, encouraging the transfer of knowledge and improving the quality of data. CPAD, CCED, and PAD-US are built from the ground up. Data is derived from available parcel information and submissions from those who own and manage the land. So better data starts with you. Do boundary lines require updating? Is the GAP code inconsistent with a Holding’s conservation status? If land under your care can be better represented in the Terrestrial 30X30 Conserved Areas map layer, please use this link to initiate a review.The results of these reviews will inform updates to the California Protected Areas Database, California Conservation Easement Database, and PAD-US as appropriate for incorporation into future updates to CA Nature and tracking progress to 30x30.

Understanding the spatial scales at which environmental factors drive species richness patterns is a major challenge in ecology. Due to the trade-off between spatial grain and extent, studies tend to focus on a single spatial scale, and the effects of multiple environmental variables operating across spatial scales on the pattern of local species richness have rarely been investigated. Here, we related variation in local species richness of ground beetles, landbirds, and small mammals to variation in vegetation structure and topography, regional climate, biome diversity, and glaciation history for 27 sites across the USA at two different spatial grains. We studied the relative influence of broad-scale (landscape) environmental conditions using variables estimated at the site level (climate, productivity, biome diversity, and glacial era ice cover) and fine-scale (local) environmental conditions using variables estimated at the plot level (topography and vegetation structure) to explain local species richness. We also examined whether plot-level factors scale up to drive continental scale richness patterns. We used Bayesian hierarchical models and quantified the amount of variance in observed richness that was explained by environmental factors at different spatial scales. For all three animal groups, our models explained much of the variation in local species richness (85-89%), but site-level variables explained a greater proportion of richness variance than plot-level variables. Temperature was the most important site-level predictor for explaining variance in landbirds and ground beetles richness. Some aspects of vegetation structure were the main plot-level predictors of landbird richness. Environmental predictors generally had poor explanatory power for small mammal richness, while glacial era ice cover was the most important site-level predictor. Relationships between plot-level factors and richness varied greatly among geographical regions and spatial grains, and most relationships did not hold when predictors were scaled up to continental scale. Our results suggest that the factors that determine richness may be highly dependent on spatial grain, geography, and animal group. We demonstrate that instead of artificially manipulating the resolution to study multi-scale effects, a hierarchical approach that uses fine grain data at broad extents could help solve the issue of scale selection in environment-richness studies. Methods

We estimated landbird richness at the plot level using the NEON dataset of breeding bird point counts (Carrasco et al. 2022: National Ecological Observatory Network 2016a). Birds associated with terrestrial habitats were sampled during the breeding season using point counts performed by one or more expert observers who recorded all species seen or heard within a 125 m radius during a 6-minute period. To allow comparison across plots with different number of point counts, we only used the central point count for plots with multiple point counts. To standardise the sampling effort among plots, we aggregated data from two survey dates for each plot, carried out during the years 2016, 2017 or 2018, which resulted in 192 plots across 25 NEON sites for our analysis (Carrasco et al. 2022: Supplementary Material Table S1). We selected survey dates based on their temporal proximity to the available lidar data (for calculating topographical and vegetation structure indices).

We obtained data on ground beetles from the NEON’s Ground Beetles Sampled from Pitfall Traps dataset (Carrasco et al. 2022: National Ecological Observatory Network 2016c), which provides counts of ground beetles (Coleoptera: Carabidae). The NEON sampling protocol uses four pitfall traps (473 mL deli containers filled with 150 or 250 mL of propylene glycol) placed 20 m from the centre of the plot in the four cardinal directions. Sampling occurred in a two-week duration (i.e., a bout) during the growing season. We used 10 bouts per year in each plot in order to standardise the sampling efforts. Unlike for landbirds and small mammals, we only selected plots that were sampled in 2018 (n = 110 plots across 19 NEON sites; Carrasco et al. 2022: Supplementary Material Table S1). We made this decision because the number of traps per bout changed from four to three from 2018 on, and therefore using data from different years would have led to inconsistent sampling efforts. We aggregated taxa identified to species across the 10 bouts to calculate plot-level species richness. For specimens sent for taxonomic validation, we used the species ID assigned by the expert taxonomist. For ground beetles, we used lidar data that were collected temporally closest to 2018. We extracted data on small mammals from the NEON’s Small Mammal Box Trapping dataset (Carrasco et al. 2022: National Ecological Observatory Network 2016d). NEON defines a small mammal as any rodent that is nonvolant, nocturnally active, and an aboveground forager weighing 5-600 g (e.g., cricetids, heteromyds, small sciurids and murids, etc.). Mammals were sampled using box traps, which were configured in a 10 m x 10 m grid (totalling 100 box traps) in most plots. Only species classified as “targeted” by NEON’s box traps were used in our analyses. To standardise sampling efforts, we included four bouts (each bout constitutes three consecutive nights of trapping) per plot and year. We estimated species richness based on individuals identified to the species level for each plot and year (2016-2018). We excluded opportunistic captures of non-targeted species. Lastly, for statistical modelling we retained from each plot only data from the year closest to the year of the lidar data (n = 89 plots across 23 NEON sites; Carrasco et al. 2022: Supplementary Material Table S1).

For all three taxonomic groups, our plot-level species richness metric is equivalent to the species density metric described by Gotelli and Colwell (2011). We used the term richness in our paper because we combined multiple surveys for birds and sampling bouts for ground beetles and small mammals (each of which aggregates multiple traps), to maximise sampling completeness within each plot, while ensuring that the sampling effort is the same by using the same number of surveys and bouts across all plots within each taxonomic group. Despite these measures, sampling completeness may nevertheless differ across plots. We examined the correlation between our raw species richness metric and the estimated asymptotic richness (Carrasco et al. 2022: Chao et al. 2014) (calculated using the iNext package in R (Carrasco et al. 2022: Hsieh et al. 2016)) to assess if differences in sampling completeness might affect our analyses and results from section 2.4 below. We found moderate to high positive correlation (landbirds: Pearson r = 0.60; ground beetles: r = 0.93; small mammals: r = 0.99) between our richness metric and estimated asymptotic richness (Carrasco et al. 2022: Supplementary Material Figure S1), suggesting that differences in sampling completeness is unlikely to affect the main conclusionsofouranalysis,especially for ground beetles and small mammals. Detailed information on animal surveys and richness estimation methodology can be found in Carrasco et al. 2022: Supplementary Material Appendix S1.

Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). Literature cited: Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103. Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38. U.S. Environmental Protection Agency. 2011. Level III and IV ecoregions of the continental United States. U.S. EPA, National Health and Environmental Effects Research Laboratory, Corvallis, Oregon, Map scale 1:3,000,000. Available online at: https://www.epa.gov/eco-research/level-iii-and-iv-ecoregions-continental-united-states. Comments and questions regarding Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.gov

Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). Literature cited: Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103. Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38. U.S. Environmental Protection Agency. 2011. Level III and IV ecoregions of the continental United States. U.S. EPA, National Health and Environmental Effects Research Laboratory, Corvallis, Oregon, Map scale 1:3,000,000. Available online at: https://www.epa.gov/eco-research/level-iii-and-iv-ecoregions-continental-united-states. Comments and questions regarding Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.gov

Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). Literature cited: Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103. Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38. U.S. Environmental Protection Agency. 2011. Level III and IV ecoregions of the continental United States. U.S. EPA, National Health and Environmental Effects Research Laboratory, Corvallis, Oregon, Map scale 1:3,000,000. Available online at: https://www.epa.gov/eco-research/level-iii-and-iv-ecoregions-continental-united-states. Comments and questions regarding Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.gov

Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). Literature cited: Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103. Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38. U.S. Environmental Protection Agency. 2011. Level III and IV ecoregions of the continental United States. U.S. EPA, National Health and Environmental Effects Research Laboratory, Corvallis, Oregon, Map scale 1:3,000,000. Available online at: https://www.epa.gov/eco-research/level-iii-and-iv-ecoregions-continental-united-states. Comments and questions regarding Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.gov

Landscape ecology is an important subtopic of ecology. As a field, it is inherently interdisciplinary and provides opportunities to teach not only content, but transferable ecological and geographical skills. Given the broad spectrum of topics in general ecology courses, landscape ecology is often relegated to a single lecture or not covered at all, meaning that there is a need for concise, effective lesson content for teachers. Here, we present an adaptable, active lesson on landscape ecology that can be implemented to help address this gap and support student engagement and the application of content knowledge to local systems. Students are presented with an active lecture that introduces key concepts of landscape ecology, then presented with opportunities to apply and reinforce these concepts. First, students work in groups to solve applied challenges about a real environment. These group challenges support greater understanding, content retention, and engage students in collaborative creative problem-solving with their classmates. Second, students apply the concepts of the lesson to a natural space that they are familiar with to increase personal connections to the content and again reinforce the topics. This lesson has been implemented a total of three times in two courses across two universities with distinct student populations. Student feedback has been largely favorable, with students reporting increased understanding of the subject and enjoyment of the lesson, especially the group problem-solving challenges. We provide avenues for instructors to localize the content to help students connect to the topics using examples with which they are familiar.

Primary Image: Group Problem-Solving in Practice: Resources (a map of potential purchase parcels, and a table with the price and a description of each of those parcels) given to students in a group problem-solving challenge that asks students to prioritize funds and maximize the positive impacts on the landscape by purchasing land for a nature preserve.

Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (1995, 2004), Omernik and others (2000), and Gallant and others (1989). Literature cited: Commission for Environmental Cooperation Working Group, 1997, Ecological regions of North America- toward a common perspective: Montreal, Commission for Environmental Cooperation, 71 p. Gallant, A. L., Whittier, T.R., Larsen, D.P., Omernik, J.M., and Hughes, R.M., 1989, Regionalization as a tool for managing environmental resources: Corvallis, Oregon, U.S. Environmental Protection Agency, EPA/600/3-89/060, 152p. Omernik, J.M., 1995, Ecoregions - a framework for environmental management, in Davis, W.S. and Simon, T.P., eds., Biological assessment and criteria-tools for water resource planning and decision making: Boca Raton, Florida, Lewis Publishers, p.49-62. Omernik, J.M., Chapman, S.S., Lillie, R.A., and Dumke, R.T., 2000, Ecoregions of Wisconsin: Transactions of the Wisconsin Academy of Science, Arts, and Letters, v. 88, p. 77-103. Omernik, J.M., 2004, Perspectives on the nature and definitions of ecological regions: Environmental Management, v. 34, Supplement 1, p. s27-s38. Comments and questions regarding Ecoregions should be addressed to Glenn Griffith, USGS, c/o US EPA., 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4465, email:griffith.glenn@epa.gov Alternate: James Omernik, USGS, c/o US EPA, 200 SW 35th Street, Corvallis, OR 97333, (541)-754-4458, email:omernik.james@epa.gov