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Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site—its constituency—as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites' environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions "centered" on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These "specialist" sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context. [ABSTRACT FROM AUTHOR]

Theoretical work suggests that species’ ecological niches should remain relatively constant over long-term ecological time periods, but empirical tests are few. We present longitudinal studies of 23 extant mammal species, modelling ecological niches and predicting geographical distributions reciprocally between the Last Glacial Maximum and present to test this evolutionary conservatism. This study covered distributional shifts in mammal species across the lower 48 states of the United States. We used a machine-learning tool for modelling species’ ecological niches, based on known occurrences and electronic maps summarizing ecological dimensions, to assess the ability of ecological niches as modelled in one time period to predict the geographical distribution of the species in another period, and vice versa. High intertemporal predictivity between niche models and species’ occurrences indicate that niche conservatism is widespread among the taxa studied, particularly when statistical power is considered as a reason for failure of reciprocal predictions. Niche projections to the present for 8 mammal taxa that became extinct at the end of the Pleistocene generally increased in area, and thus do not support the hypothesis of niche collapse as a major driving force in their extinction. Ecological niches represent long-term stable constraints on the distributional potential of species; indeed, this study suggests that mammal species have tracked consistent climate profiles throughout the drastic climate change events that marked the end of the Pleistocene glaciations. Many current modelling efforts focusing on anticipating climate change effects on species’ potential geographical distributions will be bolstered by this result — in essence, the first longitudinal demonstration of niche conservatism. [ABSTRACT FROM AUTHOR]

The article offers information on the National Ecological Observatory Network (NEON), a new approach for studying the biosphere. It stated that the ecologist of the U.S. National Science Foundation (NSF) are planning a NEON which the conceptual design of the network rises several general questions on ecosystems and the responses of biochemistry, biodiversity, hydroecology, and bioticstructure. It discusses the potential of NEON in answering the questions by providing data and other facilities supporting the development of ecological forecasting at continental scales. In addition, the NEON information system allows a natural merger between local and regional observations and national-scale satellite observations to link detailed ecological observations with global surveillance.

Habitat valuation methods were implemented to support remedial decisions for aquatic and terrestrial contaminated sites at the East Tennessee Technology Park (ETTP) on the US Department of Energy (DOE) Oak Ridge Reservation in Oak Ridge, TN, USA. The habitat valuation was undertaken for six contaminated sites: Contractor's Spoil Area, K-901-N Disposal Area, K-770 Scrapyard, K-1007-P1 pond, K-901 pond, and the Mitchell Branch stream. Four of these sites are within the industrial use area of ETTP and two are in the Black Oak Ridge Conservation Easement. These sites represent terrestrial and aquatic habitat for vertebrates, terrestrial habitat for plants, and aquatic habitat for benthic invertebrates. Current and potential future, no-action (no remediation) scenarios were evaluated primarily using existing information. Valuation metrics and scoring criteria were developed in a companion paper, this volume. The habitat valuation consists of extensive narratives, as well as scores for aspects of site use value, site rarity, and use value added from spatial context. Metrics for habitat value were expressed with respect to different spatial scales, depending on data availability. There was significant variation in habitat value among the six sites, among measures for different taxa at a single site, between measures of use and rarity at a single site, and among measures for particular taxa at a single site with respect to different spatial scales. Most sites had aspects of low, medium, and high habitat value. Few high scores for current use value were given. These include: wetland plant communities at all aquatic sites, Lepomid sunfish and waterbirds at 1007-P1 pond, and Lepomid sunfish and amphibians at K-901 pond. Aquatic sites create a high-value ecological corridor for waterbirds, and the Contractor's Spoil Area and possibly the K-901-N Disposal Site have areas that are part of a strong terrestrial ecological corridor. The only example of recent observations of rare species at these sites is the gray bat observed at the K-1007-P1 pond. Some aspects of habitat value are expected to improve under no-action scenarios at a few of the sites. Methods are applicable to other contaminated sites where sufficient ecological data are available for the site and region.

Multivariate clustering based on fine spatial resolution maps of elevation, temperature, precipitation, soil characteristics, and solar inputs has been used at several specified levels of division to produce a spectrum of quantitative ecoregion maps for the conterminous United States. The coarse ecoregion divisions accurately capture intuitively-understood regional environmental differences, whereas the finer divisions highlight local condition gradients, ecotones, and clines. Such statistically generated ecoregions can be produced based on user-selected continuous variables, allowing customized regions to be delineated for any specific problem. By creating an objective ecoregion classification, the ecoregion concept is removed from the limitations of human subjectivity, making possible a new array of ecologically useful derivative products. A red-green-blue visualization based on principal components analysis of ecoregion centroids indicates with color the relative combination of environmental conditions found within each ecoregion. Multiple geographic areas can be classified into a single common set of quantitative ecoregions to provide a basis for comparison, or maps of a single area through time can be classified to portray climatic or environmental changes geographically in terms of current conditions. Quantified representativeness can characterize borders between ecoregions as gradual, sharp, or of changing character along their length. Similarity of any ecoregion to all other ecoregions can be quantified and displayed as a "representativeness" map. The representativeness of an existing spatial array of sample locations or study sites can be mapped relative to a set of quantitative ecoregions, suggesting locations for additional samples or sites. In addition, the shape of Hutchinsonian niches in environment space can be defined if a multivariate range map of species occurrence is available.