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Bioregions are important tools for understanding and managing natural resources. Bioregions should describe locations of relatively homogenous assemblages of species occur, enabling managers to better regulate activities that might affect these assemblages. Many existing bioregionalization approaches, which rely on expert-derived, Delphic comparisons or environmental surrogates, do not explicitly include observed biological data in such analyses. We highlight that, for bioregionalizations to be useful and reliable for systems scientists and managers, the bioregionalizations need to be based on biological data; to include an easily understood assessment of uncertainty, preferably in a spatial format matching the bioregions; and to be scientifically transparent and reproducible. Statistical models provide a scientifically robust, transparent, and interpretable approach for ensuring that bioregions are formed on the basis of observed biological and physical data. Using statistically derived bioregions provides a repeatable framework for the spatial representation of biodiversity at multiple spatial scales. This results in better-informed management decisions and biodiversity conservation outcomes.

As the source providing units for several goods and services required for human survival (e.g. food, fuel, fiber, water provision and purification, etc.) ecosystems must be sustainably managed. This will require a globally comprehensive and detailed understanding of the distribution of ecosystems on Earth. While there have been several attempts to partition the planet into large ecologically meaningful areas (ecoregions), a high spatial resolution map of Earth's terrestrial ecosystems at the on-the-ground occurrences (patch) level has heretofore been lacking. A new, high resolution (250 m) map of data-derived World Terrestrial Ecosystems is characterized, and its utility for assessing policy-mandated ecosystem conservation targets is described.

Representation of ecosystems in protected area networks and conservation strategies is a core principle of global conservation priority setting approaches and a commitment in Aichi Target 11 of the Convention on Biological Diversity. The 2030 Sustainable Development Goals (SDGs) explicitly call for the conservation of terrestrial, freshwater, and marine ecosystems. Accurate ecosystem distribution maps are required to assess representation of ecosystems in protected areas, but standardized, high spatial resolution, and globally comprehensive ecosystem maps have heretofore been lacking. While macroscale global ecoregions maps have been used in global conservation priority setting exercises, they do not identify distinct localized ecosystems at the occurrence (patch) level, and instead describe large ecologically meaningful areas within which additional conservation planning and management are necessary. We describe a new set of maps of globally consistent climate regions and ecosystems at a much finer spatial resolution (250 m) than existing ecological regionalizations. We then describe a global gap analysis of the representation of these ecosystems in protected areas. The new map of terrestrial World Ecosystems was derived from the objective development and integration of 1) global temperature domains, 2) global moisture domains, 3) global landforms, and 4) 2015 global vegetation and land use. These new terrestrial World Ecosystems do not include either freshwater or marine ecosystems, but analog products for the freshwater and marine domains are in development. A total of 431 World Ecosystems were identified, and of these a total of 278 units were natural or semi-natural vegetation/environment combinations, including different kinds of forestlands, shrublands, grasslands, bare areas, and ice/snow regions. The remaining classes were different kinds of croplands and settlements. Of the 278 natural and semi-natural classes, 9 were not represented in global protected areas with a strict biodiversity conservation management objective (IUCN management categories I-IV), and an additional 206 were less than 8.5% protected (half way to the 17% Aichi Target 11 goal). Forty four classes were between 8.5% and 17% protected (more than half way towards the Aichi 17% target), and only 19 classes exceeded the 17% Aichi target. However, when all protected areas (IUCN management categories I-VI plus protected areas with no IUCN designation) were included in a separate global gap analysis, representation of ecosystems increases substantially, with a third of the ecosystems exceeding the 17% Aichi target, and another third between 8.5% and 17%. The overall protection (representation) of global ecosystems in protected areas is considerably less when assessed using only strictly conserved protected areas, and more if all protected areas are included in the analysis. Protected area effectiveness should be included in further evaluations of global ecosystem protection. The ecosystems with the highest representation in protected areas were often bare or sparsely vegetated and found in inhospitable environments (e.g. cold mountains, deserts), and the eight most protected ecosystems were all snow and ice ecosystems. In addition to the global gap analysis of World Ecosystems in protected areas, we report on the representation results for the ecosystems in each biogeographic realm (Neotropical, Nearctic, Afrotropical, Palearctic, Indomalayan, Australasian, and Oceania).

Mountain Research and Development, 38 (3), ISSN:0276-4741, ISSN:1994-7151

Humans are dependent upon ecosystems for the production of goods and services necessary for their well-being (Daily, 1997). As the service provider units (SPUs) for these benefits of nature (Anderson et al., 2015), ecosystems need to be managed in a way that maximizes their persistence on the planet. Part of that management effort includes knowing a) what the ecosystem types are, b) where they are located on the landscape and in the seascape, and c) what condition they are in. Mapping of ecosystem occurrences as the SPUs for ecosystems goods and services is therefore an important element of ecosystem accounting, an inherently spatial activity. Maps are also needed of the ecosystem accounting areas within which the accounting is conducted. Standardized maps of ecosystem accounting areas and terrestrial ecosystem SPUs have not previously been available for many islands of the Oceania region. We describe the availability of new island shorelines and ecosystems data for Oceania herein, and encourage consideration and evaluation of the data for ecosystem accounting and other applications.

Projected climate and environmental change are expected to increase the pressure on global freshwater resources. To prepare for and cope with the related risks, stakeholders need to devise plans for sustainable management of river systems, which in turn requires the identification of management-appropriate operational units, such as groups of rivers that share similar environmental and biological characteristics. Ideally, these units are of a manageable size, and are biotically or abiotically distinguishable across a variety of river types. Here, we aim to address this need by presenting a new global river classification framework (GloRiC) to establish a common vocabulary and standardized approach to the development of globally comprehensive and integrated river classifications that can be tailored to different goals and requirements. We define the GloRiC conceptual framework based on five categories of variables: (1) hydrology; (2) physiography and climate; (3) fluvial geomorphology; (4) water chemistry; and (5) aquatic biology. We then apply the framework using hydro-environmental attributes provided by a seamless high-resolution river reach database to create initial instances of three sub-classifications (hydrologic, physio-climatic, and geomorphic) which we ultimately combine into 127 river reach types at the global scale. These supervised classifications utilize a mix of statistical analyses and expert interpretation to identify the classifier variables, the number of classes, and their thresholds. In addition, we also present an unsupervised, multivariable k-means statistical clustering of all river reaches into 30 groups. These first-of-their-kind global river reach classifications at high spatial resolution provide baseline information for a total of 35.9 million kilometers of rivers that have been assessed in this study, and are expected to be particularly useful in remote or data-poor river basins. The GloRiC framework and associated data are primarily designed for broad and rapid applicability in assessments that require stratified analyses of river ecosystem conditions at global and regional scales; smaller-scale applications could follow the same conceptual framework yet use more detailed data sources.

The U.S. Fish and Wildlife Service, along with the global conservation community, has recognized that the conservation challenges of the 21st century far exceed the responsibilities and footprint of any individual agency or program. The ecological effects of climate change and other anthropogenic stressors do not recognize geopolitical boundaries and, as such, demand a national geographic framework to provide structure for cross-jurisdictional and landscape-scale conservation strategies. In 2009, a new map of ecologically based conservation regions in which to organize capacity and implement strategic habitat conservation was developed using rapid prototyping and expert elicitation by an interagency team of U.S. Fish and Wildlife Service and U.S. Geological Survey scientists and conservation professionals. Incorporating Bird Conservation Regions, Freshwater Ecoregions, and U.S. Geological Survey hydrologic unit codes, the new geographic framework provides a spatial template for building conservat...

Reducing the rate of biodiversity loss and averting dangerous biodiversity change are international goals, reasserted by the Aichi Targets for 2020 by Parties to the United Nations (UN) Convention on Biological Diversity (CBD) after failure to meet the 2010 target (1, 2). However, there is no global, harmonized observation system for delivering regular, timely data on biodiversity change (3). With the first plenary meeting of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) soon under way, partners from the Group on Earth Observations Biodiversity Observation Network (GEO BON) (4) are developing—and seeking consensus around—Essential Biodiversity Variables (EBVs) that could form the basis of monitoring programs worldwide.

The U.S. Geological Survey (USGS) proposes six strategic directions for managing ecosystems along with modernization of observation networks of land, water, and biological resources.

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.