Patterns of species richness hotspots and estimates of their protection are sensitive to spatial resolution

Abstract

Aim Species richness is a measure of biodiversity often used in spatial conservation assessments and mapped by summing species distribution maps. Commission errors inherent those maps influence richness patterns and conservation assessments. We sought to further the understanding of the sensitivity of hotspot delineation methods and conservation assessments to commission errors, and choice of threshold for hotspot delineation. Location United States. Methods We created range maps and 30‐m and 1‐km resolution habitat maps for terrestrial vertebrates in the United States and generated species richness maps with each dataset. With the richness maps and the GAP Protected Areas Dataset, we created species richness hotspot maps and calculated the proportion of hotspots within protected areas; calculating protection under a range of thresholds for defining hotspots. Our method allowed us to identify the influence of commission errors by comparing hotspot maps. Results Commission errors from coarse spatial grain data and lack of porosity in the range data inflated richness estimates and altered their spatial patterns. Coincidence of hotspots from different data types was low. The 30‐m hotspots were spatially dispersed, and some were very long distances from the hotspots mapped with coarser data. Estimates of protection were low for each of the taxa. The relationship between estimates of hotspot protection and threshold choice was nonlinear and inconsistent among data types (habitat and range) and grain size (30‐m and 1‐km). Main conclusions Coarse mapping methods and grain sizes can introduce commission errors into species distribution data that could result in misidentifications of the regions where hotspots occur and affect estimates of hotspot protection. Hotspot conservation assessments are also sensitive to choice of threshold for hotspot delineation. There is value in developing species distribution maps with high resolution and low rates of commission error for conservation assessments.

Protected areas lacking for many common fluvial fishes of the conterminous USA

“…This outcome occurs when strictly protected lands are assessed in both local and network stream catchments, and it occurs for most species when even less restrictive, multiple use protected areas are considered. Previous studies have identified shortcomings of protected areas in the conterminous USA to conserve range-restricted species (Jenkins, Van Houtan, Pimm, & Sexton, 2015) or species richness hotspots (McKerrow et al, 2018) for multiple taxa groups; however, this study is the first to extend this knowledge to common species in fluvial habitats. Such a lack of protection for most species in this study may be insufficient in sustaining their commonness (Gaston & Fuller, 2008), leading to both current and future risks for many species.…”

“…Often, such maps represent the most comprehensive information for certain species or regions of the world (Di Marco, Watson, Possingham, & Venter, 2017). However, use of such maps can result in commission errors in species distribution data (i.e., mapping species presences where they do not actually occur) (McKerrow, Tarr, Rubino, & Williams, 2018) and can overestimate species' protection status (Di Marco et al, 2017). This can lead to the incorrect assumption that species that are actually imperilled are sufficiently protected (Pimm et al, 2014).…”

Impact of increased wood pellet demand on biodiversity in the south‐eastern United States

“…Rectangles symbolize maps, and the stack of rectangles symbolizes individual species habitat maps of 811 species included in the analysis. Arrows symbolize adaptations to the maps; 1) modelling of wood pellet demand scenarios using the economic wood market model SRTS and land‐use change model PLUC to create different land‐use projections up to 2030 (see Duden et al, ), 2) summing of species potential habitat maps taken from US‐GAP (McKerrow et al, ) to create maps of potential species richness and 3) spatial analysis using a moving window approach to create spatially explicit projections of species richness index up to 2030…”

“…Rectangles symbolize maps, and the stack of rectangles symbolizes individual species habitat maps of 811 species included in the analysis. Arrows symbolize adaptations to the maps; 1) modelling of wood pellet demand scenarios using the economic wood market model SRTS and land-use change model PLUC to create different land-use projections up to 2030 (see Duden et al, 2017), 2) summing of species potential habitat maps taken from US-GAP (McKerrow et al, 2018) to create maps of potential species richness and 3) spatial analysis using a moving window approach to create spatially explicit projections of species richness index up to 2030 conservation concern (Boyd et al, 2008). For this study, threatened species were defined as those species listed as 1) "vulnerable," "endangered" or "critically endangered" according to the IUCN Red List (International Union for Conservation of Nature, 2017), and/or 2) listed "threatened" or "endangered" by the Endangered Species Act (Department of the Interior U.S.…”

Demonstrating a conceptual model for multispecies landscape pattern indices in landscape conservation

“…Importantly, the spatial distributions of habitat for different species can be partially, completely, or non-overlapping within the landscapes where they co-occur, so a given species' distribution may not be nested within or complementary to another's. Habitat maps have been created for use in regional and national conservation projects including the USGS Gap Analysis Project (McKerrow et al 2018), and prospects are high for the development of more maps given the recent interest in methods for mapping species' distributions (Araújo et al 2019).…”