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Despite its successes, the U.S. Endangered Species Act (ESA) has proven challenging to implement due to funding limitations, workload backlog, and other problems. As threats to species survival intensify and as more species come under threat, the need for the ESA and similar conservation laws and policies in other countries to function efficiently has grown. Attempts by the U.S. Fish and Wildlife Service (USFWS) to streamline ESA decisions include multispecies recovery plans and habitat conservation plans. We address species status assessment (SSA), a USFWS process to inform ESA decisions from listing to recovery, within the context of multispecies and ecosystem planning. Although existing SSAs have a single-species focus, ecosystem-based research can efficiently inform multiple SSAs within a region and provide a foundation for transition to multispecies SSAs in the future. We considered at-risk grassland species and ecosystems within the southeastern United States, where a disproportionate number of rare and endemic species are associated with grasslands. To initiate our ecosystem-based approach, we used a combined literature-based and structured World Café workshop format to identify science needs for SSAs. Discussions concentrated on 5 categories of threats to grassland species and ecosystems, consistent with recommendations to make shared threats a focus of planning under the ESA: (1) habitat loss, fragmentation, and disruption of functional connectivity; (2) climate change; (3) altered disturbance regimes; (4) invasive species; and (5) localized impacts. For each threat, workshop participants identified science and information needs, including database availability, research priorities, and modeling and mapping needs. Grouping species by habitat and shared threats can make the SSA process and other planning processes for conservation of at-risk species worldwide more efficient and useful. We found a combination of literature review and structured discussion effective for identifying the scientific information and analysis needed to support the development of multiple SSAs. Article impact statement: Species status assessments can be improved by an ecosystem-based approach that groups imperiled species by shared habitats and threats.Mejoramiento de la Evaluación del Estado de una Especie bajo el Acta de Especies en Peligro de los Estados Unidos y Sus Consecuencias para los Retos de la Conservación Multiespecie a Nivel Mundial Resumen A pesar de su éxito, el Acta de Especies en Peligro de los E.U.A. (AEP) ha sido un reto de implementación por las limitaciones en su financiamiento, el retraso en la carga de trabajo y otros problemas. Conforme se intensifican las amenazas a la supervivencia de las especies y más especies resultan amenazadas, aumenta la necesidad de que la AEP y las políticas similares de otros países funcionen efectivamente. Los intentos por parte del Servicio Estadounidense de Pesca y Fauna (SEPF) para optimizar las decisiones de la AEP incluyen planes multiespecie de recuperación y planes de conservación de hábitat (PRH). Abordamos la evaluación del estado de las especies (EEE), un proceso del SEPF para orientar las decisiones del AEP desde el listado hasta la recuperación, dentro del contexto de la planeación multiespecie y de ecosistemas. Aunque las EEE existentes tienen un enfoque sobre una única especie, la investigación basada en el ecosistema puede orientar eficientemente a múltiples EEE dentro de una región y proporcionar una base para la transición a las EEE multiespecie en el futuro. Consideramos a las especies y los ecosistemas en riesgo de los pastizales del sureste de los Estados Unidos, en donde un número desproporcionado de especies raras y endémicas está asociado con los pastizales. Para iniciar nuestra estrategia basada en el ecosistema, usamos un formato de taller de World Café estructurado y basado en la literatura para identificar la necesidad de tener EEE. Las discusiones se centraron en cinco categorías de amenazas para las especies y ecosistemas de los pastizales, consistentes con las recomendaciones para volver a las amenazas compartidas un foco de la planeación bajo la AEP: (1) pérdida del hábitat, fragmentación y disrupción de la conectividad funcional; (2) cambio climático; (3) regímenes alterados de perturbación; (4) especies invasoras; y (5) impactos localizados. Para cada amenaza, los participantes del taller identificaron las necesidades científicas y de información, incluyendo la disponibilidad de bases de datos, prioridades de la investigación y necesidades de modelado y mapeado. La agrupación de las especies por hábitat y amenaza compartida puede hacer más eficientes y útiles el proceso de EEE y otros procesos de planeación de la conservación de especies en riesgo a nivel mundial. Encontramos una combinación de revisiones bibliográficas y discusiones estructuradas para identificar la información y el análisis necesarios para respaldar el desarrollo de múltiples EEE.尽管《美国濒危物种法案》 (U.S. Endangered Species Act, ESA) 已取得一定成功, 但由于资金限制、工作量积压及其它问题, 该法案的实施仍面临挑战。随着威胁的加剧和受到威胁的物种增加, 人们对于 ESA 及其它国家类似的保护法律和政策发挥有效作用的需求也越来越强烈。同时, 美国鱼类及野生动物管理局也在努力简化包括多物种恢复计划和栖息地保护计划在内的ESA决策过程。本研究以多物种和生态系统规划为背景, 进行了物种状态评估, 这是美国鱼类及野生动物管理局为物种从列入名录到恢复的一系列ESA决策提供信息的过程。现有的物种状态评估侧重于单一物种, 而基于生态系统的研究则可以有效地指导一个区域内多个物种状态评估过程, 并为未来向多物种状态评估过渡提供基础。本研究关注美国东南部濒危的草地物种和生态系统, 该地区草地稀有种和特有种的数量不成比例得高。为了实施基于生态系统的方法, 我们将基于文献和结构化世界咖啡馆研讨会的形式相结合, 以确定物种状态估计的科学需求。我们集中讨论了草地物种和生态系统面临的5类威胁, 并建议将共同存在的威胁作为ESA的规划重点, 这些威胁包括 (1) 栖息地丧失、破碎化和功能连接度中断; (2) 气候变化; (3) 干扰情况变化; (4) 入侵物种; (5) 局部地区的影响。研讨会参与者确定了每种威胁的科学需求和信息需求, 包括数据库可用性、优先研究内容以及建模和测绘需求。根据栖息地和共同威胁对物种进行分组, 可以使物种状态评估过程和全球其它濒危物种保护的规划过程更加有用和高效。我们发现, 将文献综述与结构化讨论相结合, 可以有效地确定支持多个物种状态评估发展所需的科学信息和分析。【翻译: 胡怡思; 审校: 聂永刚】.

Observed ecological responses to climate change are highly individualistic across species and locations, and understanding the drivers of this variability is essential for management and conservation efforts. While it is clear that differences in exposure, sensitivity, and adaptive capacity all contribute to heterogeneity in climate change vulnerability, predicting these features at macroecological scales remains a critical challenge. We explore multiple drivers of heterogeneous vulnerability across the distributions of 96 vegetation types of the ecologically diverse western US, using data on observed climate trends from 1948 to 2014 to highlight emerging patterns of change. We ask three novel questions about factors potentially shaping vulnerability across the region: (a) How does sensitivity to different climate variables vary geographically and across vegetation classes? (b) How do multivariate climate exposure patterns interact with these sensitivities to shape vulnerability patterns? (c) How different are these vulnerability patterns according to three widely implemented vulnerability paradigms-niche novelty (decline in modeled suitability), temporal novelty (standardized anomaly), and spatial novelty (inbound climate velocity)-each of which uses a distinct frame of reference to quantify climate departure? We propose that considering these three novelty paradigms in combination could help improve our understanding and prediction of heterogeneous climate change responses, and we discuss the distinct climate adaptation strategies connected with different combinations of high and low novelty across the three metrics. Our results reveal a diverse mosaic of climate change vulnerability signatures across the region's plant communities. Each of the above factors contributes strongly to this heterogeneity: climate variable sensitivity exhibits clear patterns across vegetation types, multivariate climate change data reveal highly diverse exposure signatures across locations, and the three novelty paradigms diverge widely in their climate change vulnerability predictions. Together, these results shed light on potential drivers of individualistic climate change responses and may help to inform effective management strategies.

In 2021, the Biden administration signed an executive order to protect 30% of American lands by 2030. Accomplishing this ambitious goal in the U.S. requires understanding the relative contribution of public and private lands toward supporting biodiversity. New approaches are needed because existing approaches focus on quantity of habitat without incorporating quality. To fill this need, we developed a 30 m resolution national habitat condition index (HCI) that integrates quality and quantity measures of habitat. We hypothesized that including an evaluation of the quality of habitat at landscape scales, both in conservation-focused preserves and working lands would provide a better assessment of the value of geographies for conservation. We divided the conterminous U.S. by major land cover type and into natural and cultivated lands and then spatially mapped multiple anthropogenic stressors, proximity to aquatic habitat, and vegetation departure from expected natural disturbance regimes. Each map layer was then scored for site impact and distance decay and combined into a final national index. Field observations providing scored relative ecological conditions were used for HCI calibration and validation at both CONUS and regional scales. Finally, we evaluate lands by management (conservation versus working lands) and ownership (public versus private) testing the value of these lands for conservation. While we found regional differences across CONUS, functional habitat was largely independent of protection status: working lands provide clear habitat and other values. These results are relevant for guiding strategies to achieve the U.S. 30 by 30 goals. Where similar data exist in other countries, analogous modeling could be used to meet their national conservation commitments.

Invasive annual grasses, primarily Bromus tectorum, are a severe risk to native vegetation of the intermountain West. Once established, annual grasses alter natural fire regimes and outcompete natives until, in some places, they become the overwhelming dominant. We developed a regional spatial model encompassing eight ecoregions to indicate the relative abundance of invasive annual grass at five levels of canopy cover. We used field sample data representing invasive annual grass abundance to build and calibrate the model. Explanatory variables, represented as map inputs, included image indices, climate, landform, soil, and human-induced surface disturbance. As a novel modeling approach, we built multiple models based on classes of invasive annual grass cover abundance were developed individually and then combined into a final 90-m pixel resolution model that indicates locations relative to invasive annual grass abundance into classes of 45% cover. Each component model was validated using held-out sample data, and relative accuracy was 86%, 74%, 62%, 62%, and 60%, respectively, with an overall kappa of 0.773. The Columbia Plateau, Northern Basin and Range, and Snake River Plain ecoregions appear to have the greatest overall proportions (48−62%) mapped within at least one of the invasive cover categories. Overlay of the resulting model with major vegetation types indicated > 50 major vegetation types that are affected by current distribution of annual grasses and are at risk of expansion. Among these, Intermountain Basins, Big Sagebrush Steppe, and Columbia Plateau Steppe and Grassland each consistently scored high for invasive risk where they occur. Spatial models of this type should assist with rangeland restoration and for decisions involving placement of infrastructure, vegetation treatments where further surface disturbance could trigger additional cheatgrass expansion. Options exist for extending this model, using climate projections over upcoming decades, to indicate areas of increasing risk for invasion.

In support of natural resource agencies in Canada, the United States, and Mexico, we report on a series of component analyses and an updated Landscape Conservation Design for temperate grassland conservation. We targeted 12 major grassland ecosystem types that occur across the Great Plains and Chihuahuan Desert regions. Component analyses included (1) documenting long-term trends in extent by grassland type, (2) identifying species of concern associated with the major grassland types, (3) documenting current protected areas including each grassland type, (4) assessing landscape intactness and connectivity among grassland areas, and (5) identifying Grassland Potential Conservation Areas (GPCAs) to advance grassland conservation. Most severe declines in grassland extent have occurred in tallgrass prairie types, followed by mixed-grass, shortgrass, and semi-desert grasslands. Similar trends by type were documented for landscape intactness and connectivity. Some 174 species of vertebrates, invertebrates, and plants considered by NatureServe as critically imperiled, imperiled, or vulnerable are strongly associated with these grassland types, and 103 are listed under protective legislation in one or more countries. Just 1.2% of historic extent for all types combined is currently found within designated protected areas. A total of 177 GPCAs were identified to represent grassland type diversity in areas least likely to conflict with other land uses. Within identified GPCAs, type-specific representation varied from a low of just 1% of historic extent for Texas Blackland Tallgrass Prairie to a high of 27% for Western Great Plains Sand Prairie. Combined across all 12 grassland types, 15% of historic extent is represented.

Conservation decisions are well supported by predictive spatial models that indicate the relative ecological condition of a given place. The intent of this 90 m pixel landscape condition model is to use nationally available spatial data from the USA, Mexico, and Canada to express assumptions regarding the relative ecological effects of land uses on terrestrial natural communities and species. This approach emphasizes and updateable and transparent design which takes advantage of empirical biodiversity data from the USA to both calibrate and validate the model. Map layers depicting infrastructure, land use, and modified vegetation were each scored for site impact and distance decay, and then combined into one map surface. Field observations from Natural Heritage Programs, each scored for relative ecological condition (in categories A = excellent to D = poor), were used to calibrate distance decay parameters. Some 90,000 observations for at-risk species, invasive plant species, and natural communities were used for model validation. Statistically significant distinctions in ecological condition among validation samples were predicted by the resultant spatial model. Variation in landscape condition was then summarized by regional U.S. Landscape Conservation Cooperatives (LCCs) in terms of areas approximating A–D condition. Montane and desert LCCs scored on average much higher in area approximating “A” and “B” landscape condition, while LCCs with more substantial agricultural and urban footprints scored overwhelmingly within the “D” range of condition. Similar analyses illustrated range-wide scoring of landscape condition for major vegetation types across temperate North America.

Documenting changes in ecosystem extent and protection is essential to understanding status of biodiversity and related ecosystem services and have direct applications to measuring Essential Biodiversity Variables, Targets under the Convention on Biological Diversity (CBD), and IUCN Red List of Ecosystems. We developed both potential and current distribution maps of terrestrial ecosystem types for the temperate and tropical Americas; with "potential" estimating where a type would likely occur today had there not been prior land conversion for modern land uses. We utilized a hierarchical classification to describe and map natural ecosystem types at six levels of thematic detail, with lower thematic levels defining more units each with narrower floristic range than upper levels. Current land use/land cover was derived using available global data on human land use intensity and combined with the potential distribution maps to estimate long-term change in extent for each ecosystem type. We also assessed representation of ecosystem types within protected areas as defined by IUCN I-VI land status categories. Of the 749 ecosystem types assessed, represented at 5th (n = 315) vs. 6th (n = 433) levels of the classification hierarchy, 5 types (1.6%) and 31 types (7.1%), respectively, have lost >90% of their potential extent. Some 66 types (20.9%) and 141 types (32.5%), respectively, have lost >50% of their potential extent; thus, crossing thresholds of Vulnerable status under IUCN Red List criterion A3. For ecosystem type representation within IUCN protected area classes, with reference to potential extent of each type, 111 (45.3%) and 125 (28.8%) of types, respectively, have higher representation (>17%) than CBD 2020 targets. Twelve types (3.8%) and 23 (5.3%) of types, respectively, are represented with

Grasslands dominate the central regional landscape of the North America, extending from the Canadian prairies south across the Chihuahuan Desert. We describe this grassland diversity, discussing common forms of ecological classification, and highlight the International Vegetation Classification. We then report on a series of analyses and a Landscape Conservation Design for temperate grassland conservation. We targeted 12 major grassland ecosystem types that occur across this region. Component analyses included: (a) documenting long-term trends in extent by grassland type, (b) assessing landscape intactness among grassland areas, and (c) identifying Grassland Potential Conservation Areas to advance grassland conservation. Most severe declines in grassland extent have occurred in tallgrass prairie types, followed by mixed-grass, shortgrass, and semi-desert grasslands. Similar trends by type were documented for landscape intactness and connectivity. A total of 177 Grassland Potential Conservation Areas (GPCAs) were identified to represent grassland type diversity in areas least likely to conflict with other land uses. Within identified GPCAs, type-specific representation varied from a low of just 1% of historic extent for Texas Blackland Tallgrass Prairie to a high of 27% for Western Great Plains Sand Prairie. Combined across all 12 grassland types, 15% of historic extent is represented.

We applied a framework to assess climate change vulnerability of 52 major vegetation types in the Western United States to provide a spatially explicit input to adaptive management decisions. The framework addressed climate exposure and ecosystem resilience, the latter derived from analyses of ecosystem sensitivity and adaptive capacity. Measures of climate change exposure used observed climate change (1981&ndash, 2014) and then climate projections for the mid-21st century (2040&ndash, 2069 RCP 4.5). Measures of resilience included (under ecosystem sensitivity) landscape intactness, invasive species, fire regime alteration, and forest insect and disease risk, and (under adaptive capacity), measures for topo-climate variability, diversity within functional species groups, and vulnerability of any keystone species. Outputs are generated per 100 km2 hexagonal area for each type. As of 2014, moderate climate change vulnerability was indicated for &gt, 50% of the area of 50 of 52 types. By the mid-21st century, all but 19 types face high or very high vulnerability with &gt, 50% of the area scoring in these categories. Measures for resilience explain most components of vulnerability as of 2014, with most targeted vegetation scoring low in adaptive capacity measures and variably for specific sensitivity measures. Elevated climate exposure explains increases in vulnerability between the current and mid-century time periods.

A vegetation classification approach is needed that can describe the diversity of terrestrial ecosystems and their transformations over large time frames, span the full range of spatial and geographic scales across the globe, and provide knowledge of reference conditions and current states of ecosystems required to make decisions about conservation and resource management. We summarize the scientific basis for EcoVeg, a physiognomic-floristic-ecological classification approach that applies to existing vegetation, both cultural (planted and dominated by human processes) and natural (spontaneously formed and dominated by nonhuman ecological processes). The classification is based on a set of vegetation criteria, including physiognomy (growth forms, structure) and floristics (compositional similarity and characteristic species combinations), in conjunction with ecological characteristics, including site factors, disturbance, bioclimate, and biogeography. For natural vegetation, the rationale for the upper levels (formation types) is based on the relation between global-scale vegetation patterns and macroclimate, hydrology, and substrate. The rationale for the middle levels is based on scaling from regional formations (divisions) to regional floristic-physiognomic types (macrogroup and group) that respond to meso-scale biogeographic, climatic, disturbance, and site factors. Finally, the lower levels (alliance and association) are defined by detailed floristic composition that responds to local to regional topo-edaphic and disturbance gradients. For cultural vegetation, the rationale is similar, but types are based on distinctive vegetation physiognomy and floristics that reflect human activities. The hierarchy provides a structure that organizes regional/continental vegetation patterns in the context of global patterns. A formal nomenclature is provided, along with a descriptive template that provides the differentiating criteria for each type at all levels of the hierarchy. Formation types have been described for the globe; divisions and macrogroups for North America, Latin America and Africa; groups, alliances and associations for the United States, parts of Canada, Latin America and, in partnership with other classifications that share these levels, many other parts of the globe.

Standardized ecological classification units form the foundation for effective data collection, assessment, and reporting on ecosystems. Attempts at regional land cover mapping often falter on this point or struggle along inefficiently. Over the past decade, NatureServe has worked with the Gap Analysis Program and others to map existing vegetation using the US National Vegetation Classification (US-NVC). US-NVC is a system of hierarchical structure and rules that are designed to provide a national classification of existing vegetation. Experience has demonstrated the need to develop map units at conceptual scales intermediate between the narrowly specific alliance (floristic) and the broadly generalized formation (physiognomic) levels of the US-NVC. NatureServe defined over 630 “mesoscale” vegetation-based units that are described across the lower 48 United States. These mesoscale classification units, which we term “terrestrial ecological systems,” are described using multiple plant communities that tend to co-occur based on recurrent similarities in environmental setting and ecological dynamics. By integrating environmental setting and ecological processes with vegetation into the concept of each unit, this classification system lends itself to biophysical modeling and robust characterization of wildlife habitat. These units apply well to land cover mapping and may be augmented with modifiers for specific variants in composition and structure resulting in robust, standardized maps. Regional-scale mapping of “near-natural” land cover was completed by the Southwest Regional Gap Analysis Project using 109 ecological system units, currently the most detailed regional land cover map of its kind. Terrestrial ecological system units provide a direct, systematic link to the US National Vegetation Classification and may also provide a useful framework for integration with ecological site concepts and descriptions.

Land-cover mapping efforts within the USGS Gap Analysis Program have traditionally been state-centered; each state having the responsibility of implementing a project design for the geographic area within their state boundaries. The Southwest Regional Gap Analysis Project (SWReGAP) was the first formal GAP project designed at a regional, multi-state scale. The project area comprises the southwestern states of Arizona, Colorado, Nevada, New Mexico, and Utah. The land-cover map/dataset was generated using regionally consistent geospatial data (Landsat ETM+ imagery (1999–2001) and DEM derivatives), similar field data collection protocols, a standardized land-cover legend, and a common modeling approach (decision tree classifier). Partitioning of mapping responsibilities amongst the five collaborating states was organized around ecoregion-based “mapping zones”. Over the course of 2 1 /2 field seasons approximately 93,000 reference samples were collected directly, or obtained from other contemporary projects, for the land-cover modeling effort. The final map was made public in 2004 and contains 125 landcover classes. An internal validation of 85 of the classes, representing 91% of the land area was performed. Agreement between withheld samples and the validated dataset was 61% (KHAT=.60, n=17,030). This paper presents an overview of the methodologies used to create the regional land-cover dataset and highlights issues associated with large-area mapping within a coordinated, multi-institutional management framework.

Methods for selecting places at regional scales to conserve biodiversity have advanced in recent decades. However, with a rapidly changing climate, new methods will be required to adapt as ecosystems change. Ecoregional planning steps are reviewed, and potential alternatives are identified for adapting to climate change. Common planning steps include defining the planning region, selecting focal targets, mapping target distributions, assessing current conditions, establishing representation objectives, designing regional scenarios, identifying conservation strategies, and measuring success of regional plans. Since decisions that are implemented today will be revisited into the future, an iterative approach of increasing frequency is required.

A new map of standardized, mesoscale (tens to thousands of hectares) terrestrial ecosystems for the conterminous United States was developed by using a biophysical stratification approach. The ecosystems delineated in this top-down, deductive modeling effort are described in NatureServe's classification of terrestrial ecological systems of the United States. The ecosystems were mapped as physically distinct areas and were associated with known distributions of vegetation assemblages by using a standardized methodology first developed for South America. This approach follows the geoecosystems concept of R.J. Huggett and the ecosystem geography approach ofR.G. Bailey. Unique physical environments were delineated through a geospatial combination of national data layers for biogeography, bioclimate, surficial materials lithology, land surface forms, and topographic moisture potential. Combining these layers resulted in a comprehensive biophysical stratification of the conterminous United States, which produced 13,482 unique biophysical areas. These were considered as fundamental units of ecosystem structure and were aggregated into 419 potential terrestrial ecosystems. The ecosystems classification effort preceded the mapping effort and involved the independent development of diagnostic criteria, descriptions, and nomenclature for describing expert-derived ecological systems. The aggregation and labeling of the mapped ecosystem structure units into the ecological systems classification was accomplished in an iterative, expert-knowledge-based process using automated rulesets for identifying ecosystems on the basis of their biophysical and biogeographic attributes. The mapped ecosystems, at a 30-meter base resolution, represent an improvement in spatial and thematic (class) resolution over existing ecoregionalizations and are useful for a variety of applications, including ecosystem services assessments, climate change impact studies, biodiversity conservation, and resource management.

Background The Andes-Amazon basin of Peru and Bolivia is one of the most data-poor, biologically rich, and rapidly changing areas of the world. Conservation scientists agree that this area hosts extremely high endemism, perhaps the highest in the world, yet we know little about the geographic distributions of these species and ecosystems within country boundaries. To address this need, we have developed conservation data on endemic biodiversity (~800 species of birds, mammals, amphibians, and plants) and terrestrial ecological systems (~90; groups of vegetation communities resulting from the action of ecological processes, substrates, and/or environmental gradients) with which we conduct a fine scale conservation prioritization across the Amazon watershed of Peru and Bolivia. We modelled the geographic distributions of 435 endemic plants and all 347 endemic vertebrate species, from existing museum and herbaria specimens at a regional conservation practitioner's scale (1:250,000-1:1,000,000), based on the best available tools and geographic data. We mapped ecological systems, endemic species concentrations, and irreplaceable areas with respect to national level protected areas. Results We found that sizes of endemic species distributions ranged widely (< 20 km2 to > 200,000 km2) across the study area. Bird and mammal endemic species richness was greatest within a narrow 2500-3000 m elevation band along the length of the Andes Mountains. Endemic amphibian richness was highest at 1000-1500 m elevation and concentrated in the southern half of the study area. Geographical distribution of plant endemism was highly taxon-dependent. Irreplaceable areas, defined as locations with the highest number of species with narrow ranges, overlapped slightly with areas of high endemism, yet generally exhibited unique patterns across the study area by species group. We found that many endemic species and ecological systems are lacking national-level protection; a third of endemic species have distributions completely outside of national protected areas. Protected areas cover only 20% of areas of high endemism and 20% of irreplaceable areas. Almost 40% of the 91 ecological systems are in serious need of protection (= < 2% of their ranges protected). Conclusions We identify for the first time, areas of high endemic species concentrations and high irreplaceability that have only been roughly indicated in the past at the continental scale. We conclude that new complementary protected areas are needed to safeguard these endemics and ecosystems. An expansion in protected areas will be challenged by geographically isolated micro-endemics, varied endemic patterns among taxa, increasing deforestation, resource extraction, and changes in climate. Relying on pre-existing collections, publically accessible datasets and tools, this working framework is exportable to other regions plagued by incomplete conservation data.