Geology topics

Matthew J. Rubino

Publications and source records attributed to Matthew J. Rubino.

7 recordsLinked to original sources

USGS2022

Methods for evaluating Gap Analysis Project habitat distribution maps with species occurrence data

The National Gap Analysis Project created species habitat distribution models for all terrestrial vertebrates in the United States to support conservation assessments and explore patterns of species richness. Those models link species to specific habitats throughout the range of each species. For most vertebrates, there are not enough occurrence data to drive inductive, range-wide species habitat distribution models at high spatial and thematic resolution. However, it is possible to use occurrence data for model evaluation. The combination of citizen science, formal species survey work, and digitized specimen archives are making millions of observations available to the scientific community. Our challenge is to combine the mostly unstructured data into metrics that help us characterize and understand patterns of biodiversity. In this work, we propose two model-evaluation metrics. The first, a buffer proportion assessment, is based on the proportion of habitat in the range relative to the mean proportion of habitat around each of the species’ occurrence records. The second is a measure of the sensitivity (proportion of true presence) to buffer distances around occurrence records. The buffer proportion is a modification of model prevalence versus point prevalence metric, whereby comparison to a null model allows us to determine if the model performs better or worse than random. In this report, we describe the workflow used to compile and filter the species occurrence records from online resources (for example, the Global Biodiversity Information Facility) and show results for a single species, Desmognathus quadramaculatus (black-bellied salamander). For the salamander, 222 occurrence points met our criteria for inclusion in the evaluation. We found the model performed better than random with a buffer proportion index of 1.745, indicating about 5 times as much habitat was found adjacent to known occurrence records than would be expected from randomly located sites throughout the range. Sensitivity increased with larger buffer distances and leveled off to around 0.7 between 1,000- and 2,000-meter buffer distances, indicating the model is likely best suited for scales exceeding 1,000 meters. We plan to report the buffer proportion assessment and sensitivity metrics along with the full species model reports to increase understanding of the model’s performance and to use the metrics to help prioritize revisions to the models.

Alabama, Georgia, North Carolina, Tennessee, Virgi↗

USGS2021

Quantifying the representation of plant communities in the protected areas of the U.S.: An analysis based on the U.S. National Vegetation Classification Groups

Plant communities represent the integration of ecological and biological processes and they serve as an important component for the protection of biological diversity. To measure progress towards protection of ecosystems in the United States for various stated conservation targets we need datasets at the appropriate thematic, spatial, and temporal resolution. The recent release of the LANDFIRE Existing Vegetation Data Products (2016 Remap) with a legend based on U.S. National Vegetation Classification allowed us to assess the conservation status of plant communities of the U.S. The map legend is based on the Group level of the USNVC, which characterizes the regional differences in plant communities based on dominant and diagnostic plant species. By combining the Group level map with the Protected Areas Database of the United States (PAD-US Ver 2.1), we quantified the representation of each Group. If the mapped vegetation is assumed to be 100% accurate, using the Aichi Biodiversity target (17% land in protection by 2020) we found that 159 of the 265 natural Groups have less than 17% in GAP Status 1 & 2 lands and 216 of the 265 Groups fail to meet a 30% representation target. Only four of the twenty ecoregions have >17% of their extent in Status 1 & 2 lands. Sixteen ecoregions are dominated by Groups that are under-represented. Most ecoregions have many hectares of natural or ruderal vegetation that could contribute to future conservation efforts and this analysis helps identify specific targets and opportunities for conservation across the U.S.

Forests↗

USGS2019

Gap Analysis Project (GAP) Terrestrial Vertebrate Species Richness Maps for the Conterminous U.S.

The mission of the Gap Analysis Project (GAP) is to support national and regional assessments of the conservation status of vertebrate species and plant communities. This report explains conterminous United States species richness maps created by the U.S. Geological Survey for four major classes in the phylum Chordata: mammals, birds, reptiles, and amphibians. In this work, we focus on terrestrial vertebrate species and the spatial patterns of richness derived from species’ habitat distribution models. We created species’ habitat distribution models for 1,590 species (282 amphibians, 621 birds, 365 mammals, 322 reptiles) and an additional 129 subspecies (2 amphibians, 28 birds, 94 mammals, 5 reptiles) that occur in the conterminous United States. The 1,590 species level models were spatially combined to create the taxa richness maps at a spatial resolution of 30 meters. Based on those maps we identified the maximum species richness for each of the taxa (43 amphibians, 163 birds, 72 mammals, and 54 reptiles) and show variation in richness across the conterminous United States. Because these habitat models remove unsuitable areas within the range of the species, the patterns of richness presented here are different from the coarse-resolution species’ habitat distribution models commonly presented in the literature. These maps provide a new, more spatially refined richness map. In addition, since these models are logically linked to mapped data layers that constitute habitat suitability, this suite of data can provide an intuitive data system for further exploration of biodiversity and implications for change at ecosystem and landscape scales.

Scientific Investigations Report↗

USGS2018

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

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.

Diversity and Distributions↗

USGS2016

Assessing climate-sensitive ecosystems in the southeastern United States

Climate change impacts ecosystems in many ways, from effects on species to phenology to wildfire dynamics. Assessing the potential vulnerability of ecosystems to future changes in climate is an important first step in prioritizing and planning for conservation. Although assessments of climate change vulnerability commonly are done for species, fewer have been done for ecosystems. To aid regional conservation planning efforts, we assessed climate change vulnerability for ecosystems in the Southeastern United States and Caribbean. First, we solicited input from experts to create a list of candidate ecosystems for assessment. From that list, 12 ecosystems were selected for a vulnerability assessment that was based on a synthesis of available geographic information system (GIS) data and literature related to 3 components of vulnerability—sensitivity, exposure, and adaptive capacity. This literature and data synthesis comprised “Phase I” of the assessment. Sensitivity is the degree to which the species or processes in the ecosystem are affected by climate. Exposure is the likely future change in important climate and sea level variables. Adaptive capacity is the degree to which ecosystems can adjust to changing conditions. Where available, GIS data relevant to each of these components were used. For example, we summarized observed and projected climate, protected areas existing in 2011, projected sea-level rise, and projected urbanization across each ecosystem’s distribution. These summaries were supplemented with information in the literature, and a short narrative assessment was compiled for each ecosystem. We also summarized all information into a qualitative vulnerability rating for each ecosystem. Next, for 2 of the 12 ecosystems (East Gulf Coastal Plain Near-Coast Pine Flatwoods and Nashville Basin Limestone Glade and Woodland), the NatureServe Habitat Climate Change Vulnerability Index (HCCVI) framework was used as an alternative approach for assessing vulnerability. Use of the HCCVI approach comprised “Phase II” of the assessment. This approach uses summaries of GIS data and models to develop a series of numeric indices for components of vulnerability. We incorporated many of the data sources used in Phase I, but added the results of several other data sources, including climate envelope modeling and vegetation dynamics modeling. The results of Phase II were high and low numeric vulnerability ratings for mid-century and the end of century for each ecosystem. The high and low ratings represented the potential range of vulnerability scores owing to uncertainties in future climate conditions and ecosystem effects. Of the 12 ecosystems assessed in the first approach, five were rated as having high vulnerability (Caribbean Coastal Mangrove, Caribbean Montane Wet Elfin Forest, East Gulf Coastal Plain Southern Loess Bluff Forest, Edwards Plateau Limestone Shrubland, and Nashville Basin Limestone Glade and Woodland). Six ecosystems had medium vulnerability, and one ecosystem had low vulnerability. For the two ecosystems assessed with both approaches, vulnerability ratings generally agreed. The assessment concluded by comparing the two approaches, identifying critical research needs, and making suggestions for future ecosystem vulnerability assessments in the Southeast and beyond. Research needs include reducing uncertainty in the degree of climate exposure likely in the future, as well as acquiring more information on how climate might affect biotic interactions and hydrologic processes. Ideally, a comprehensive vulnerability assessment would include both the narrative summaries that resulted from the synthesis in Phase I, as well as a numeric index that incorporates uncertainty as in Phase II.

Alabama, Arkansas, Florida, Georgia, Kentucky, Lou↗

USGS2016

Projected gains and losses of wildlife habitat from bioenergy-induced landscape change

Domestic and foreign renewable energy targets and financial incentives have increased demand for woody biomass and bioenergy in the southeastern United States. This demand is expected to be met through purpose-grown agricultural bioenergy crops, short-rotation tree plantations, thinning and harvest of planted and natural forests, and forest harvest residues. With results from a forest economics model, spatially explicit state-and-transition simulation models, and species–habitat models, we projected change in habitat amount for 16 wildlife species caused by meeting a renewable fuel target and expected demand for wood pellets in North Carolina, USA. We projected changes over 40 years under a baseline ‘business-as-usual’ scenario without bioenergy production and five scenarios with unique feedstock portfolios. Bioenergy demand had potential to influence trends in habitat availability for some species in our study area. We found variation in impacts among species, and no scenario was the ‘best’ or ‘worst’ across all species. Our models projected that shrub-associated species would gain habitat under some scenarios because of increases in the amount of regenerating forests on the landscape, while species restricted to mature forests would lose habitat. Some forest species could also lose habitat from the conversion of forests on marginal soils to purpose-grown feedstocks. The conversion of agricultural lands on marginal soils to purpose-grown feedstocks increased habitat losses for one species with strong associations with pasture, which is being lost to urbanization in our study region. Our results indicate that landscape-scale impacts on wildlife habitat will vary among species and depend upon the bioenergy feedstock portfolio. Therefore, decisions about bioenergy and wildlife will likely involve trade-offs among wildlife species, and the choice of focal species is likely to affect the results of landscape-scale assessments. We offer general principals to consider when crafting lists of focal species for bioenergy impact assessments at the landscape scale.

GCB Bioenergy↗

USGS2014

Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach

The presence of endocrine-disrupting compounds (EDCs), particularly estrogenic compounds, in the environment has drawn public attention across the globe, yet a clear understanding of the extent and distribution of estrogenic EDCs in surface waters and their relationship to potential sources is lacking. The objective of the present study was to identify and examine the potential input of estrogenic EDC sources in North Carolina water bodies using a geographic information system (GIS) mapping and analysis approach. Existing data from state and federal agencies were used to create point and nonpoint source maps depicting the cumulative contribution of potential sources of estrogenic EDCs to North Carolina surface waters. Water was collected from 33 sites (12 associated with potential point sources, 12 associated with potential nonpoint sources, and 9 reference), to validate the predictive results of the GIS analysis. Estrogenicity (measured as 17β-estradiol equivalence) ranged from 0.06 ng/L to 56.9 ng/L. However, the majority of sites (88%) had water 17β-estradiol concentrations below 1 ng/L. Sites associated with point and nonpoint sources had significantly higher 17β-estradiol levels than reference sites. The results suggested that water 17β-estradiol was reflective of GIS predictions, confirming the relevance of landscape-level influences on water quality and validating the GIS approach to characterize such relationships.

Environmental Toxicology and Chemistry↗