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Alexa McKerrow

Publications and source records attributed to Alexa McKerrow.

31 records · Page 2Linked to original sources

How a national vegetation classification can help ecological research and management

The elegance of classification lies in its ability to compile and systematize various terminological conventions and masses of information that are unattainable during typical research projects. Imagine a discipline without standards for collection, analysis, and interpretation; unfortunately, that describes much of 20th-century vegetation ecology. With differing methods, how do we assess community dynamics over decades, much less centuries? How do we compare plant communities from different areas? The need for a widely applied vegetation classification has long been clear. Now imagine a multi-decade effort to assimilate hundreds of disparate vegetation classifications into one common classification for the US. In this letter, we introduce the US National Vegetation Classification (USNVC; www.usnvc.org) as a powerful tool for research and conservation, analogous to the argument made by Schimel and Chadwick (2013) for soils. The USNVC provides a national framework to classify and describe vegetation; here we describe the USNVC and offer brief examples of its efficacy.

Frontiers in Ecology and the Environment

Linking state-and-transition simulation and timber supply models for forest biomass production scenarios

We linked state-and-transition simulation models (STSMs) with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS) was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.

AIMS Environmental Science

2014-2015 Partnership accomplishments report on joint activities: National Gap Analysis Program and LANDFIRE

The intended target audience for this document initially is management and project technical specialist and scientists involved in the Gap Analysis Program (GAP) and the Landscape Fire and Resource Management Planning Tools - (LANDFIRE) program to help communicate coordination activities to all involved parties. This document is also intended to give background information in other parts of the USGS and beyond, although some details given are relatively oriented to management of the respective programs. Because the Gap Analysis Program (GAP) and the Landscape Fire and Resource Management Planning Tools - LANDFIRE programs both rely on characterizations of land cover using similar scales and resolutions, the programs have been coordinating their work to improve scientific consistency and efficiency of production. Initial discussions and informal sharing of ideas and work began in 2008. Although this collaboration was fruitful, there was no formal process for reporting results, plans, or outstanding issues, nor was there any formally-defined coordinated management team that spanned the two programs. In 2012, leadership from the two programs agreed to strengthen the coordination of their respective work efforts. In 2013 the GAP and LANDFIRE programs developed an umbrella plan of objectives and components related to three mutual focus areas for the GAP and LANDFIRE collaboration for the years 2013 and 2014 (GAP/LANDFIRE 2013). The evolution of this partnership resulted in the drafting of an inter-program Memorandum of Understanding (MOU) in 2014. This MOU identified three coordination topics relevant to the two programs participating at this point in the MOU history: Vegetation mapping Disturbance classes Formal quality assessment

Report

The Multi-Resolution Land Characteristics (MRLC) Consortium: 20 years of development and integration of USA national land cover data

The Multi-Resolution Land Characteristics (MRLC) Consortium demonstrates the national benefits of USA Federal collaboration. Starting in the mid-1990s as a small group with the straightforward goal of compiling a comprehensive national Landsat dataset that could be used to meet agencies’ needs, MRLC has grown into a group of 10 USA Federal Agencies that coordinate the production of five different products, including the National Land Cover Database (NLCD), the Coastal Change Analysis Program (C-CAP), the Cropland Data Layer (CDL), the Gap Analysis Project (GAP), and the Landscape Fire and Resource Management Planning Tools (LANDFIRE). As a set, the products include almost every aspect of land cover from impervious surface to detailed crop and vegetation types to fire fuel classes. Some products can be used for land cover change assessments because they cover multiple time periods. The MRLC Consortium has become a collaborative forum, where members share research, methodological approaches, and data to produce products using established protocols, and we believe it is a model for the production of integrated land cover products at national to continental scales. We provide a brief overview of each of the main products produced by MRLC and examples of how each product has been used. We follow that with a discussion of the impact of the MRLC program and a brief overview of future plans.

Remote Sensing

The southern megalopolis: using the past to predict the future of urban sprawl in the Southeast U.S.

The future health of ecosystems is arguably as dependent on urban sprawl as it is on human-caused climatic warming. Urban sprawl strongly impacts the urban ecosystems it creates and the natural and agro-ecosystems that it displaces and fragments. Here, we project urban sprawl changes for the next 50 years for the fast-growing Southeast U.S. Previous studies have focused on modeling population density, but the urban extent is arguably as important as population density per se in terms of its ecological and conservation impacts. We develop simulations using the SLEUTH urban growth model that complement population-driven models but focus on spatial pattern and extent. To better capture the reach of low-density suburban development, we extend the capabilities of SLEUTH by incorporating street-network information. Our simulations point to a future in which the extent of urbanization in the Southeast is projected to increase by 101% to 192%. Our results highlight areas where ecosystem fragmentation is likely, and serve as a benchmark to explore the challenging tradeoffs between ecosystem health, economic growth and cultural desires.

PLoS ONE

Terrestrial ecosystems: national inventory of vegetation and land use

The Gap Analysis Project (GAP)/Landscape Fire and Resource Management Planning Tools (LANDFIRE) National Terrestrial Ecosystems Data represents detailed data on the vegetation and land-use patterns of the United States, including Alaska, Hawaii, and Puerto Rico. This national dataset combines detailed land cover data generated by the GAP with LANDFIRE data (http://www.landfire.gov/). LANDFIRE is an interagency vegetation, fire, and fuel characteristics mapping program sponsored by the U.S. Department of the Interior (DOI) and the U.S. Department of Agriculture Forest Service.

Fact Sheet

PAD-US—National inventory of protected areas

The Gap Analysis Project produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The Protected Areas Database of the United States (PAD-US) is the official inventory of public parks and other protected open space. Consisting of more than 7 billion acres in 436,000 land and marine units, the spatial data in PAD–US include areas managed by greater than 30,000 agencies and nonprofit organizations.

Fact Sheet

Representation of ecological systems within the protected areas network of the continental United States

If conservation of biodiversity is the goal, then the protected areas network of the continental US may be one of our best conservation tools for safeguarding ecological systems (i.e., vegetation communities). We evaluated representation of ecological systems in the current protected areas network and found insufficient representation at three vegetation community levels within lower elevations and moderate to high productivity soils. We used national-level data for ecological systems and a protected areas database to explore alternative ways we might be able to increase representation of ecological systems within the continental US. By following one or more of these alternatives it may be possible to increase the representation of ecological systems in the protected areas network both quantitatively (from 10% up to 39%) and geographically and come closer to meeting the suggested Convention on Biological Diversity target of 17% for terrestrial areas. We used the Landscape Conservation Cooperative framework for regional analysis and found that increased conservation on some private and public lands may be important to the conservation of ecological systems in Western US, while increased public-private partnerships may be important in the conservation of ecological systems in Eastern US. We have not assessed the pros and cons of following the national or regional alternatives, but rather present them as possibilities that may be considered and evaluated as decisions are made to increase the representation of ecological systems in the protected areas network across their range of ecological, geographical, and geophysical occurrence in the continental US into the future.

PLoS ONE

Tools and data for meeting America's conservation challenges

The Gap Analysis Project (GAP) produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The GAP is managed by the U.S. Geological Survey, Department of the Interior. GAP supports a wide range of national, State, and local agencies as well as nongovernmental organizations and businesses with scientific tools and data. GAP uses a collaborative approach to do research, analysis, and data development, resulting in a history of cooperation with more than 500 agencies and organizations nationally.

General Information Product

Species data: National inventory of range maps and distribution models

The Gap Analysis Project (GAP) produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The GAP species data includes vertebrate range maps and distribution models for the continental United States, as well as Alaska, Hawaii, Puerto Rico, and U.S. Virgin Islands. The vertebrate species include amphibians, birds, mammals, and reptiles. Furthermore, data used to create the distribution models (for example, percent canopy cover, elevation, and so forth) also are available.

Fact Sheet

Developing an outcome-based biodiversity metric in support of the field to market project: Final report

Our objective was to create a metric that would calculate the relative impact of common commercial agricultural practices on terrestrial vertebrate richness. We sought to define impacts in fields (including field borders) of the southeastern region’s commercial production of corn, wheat, soy, and cotton. The metric is intended to serve as an educational tool, allowing producers to see how operational decisions made at the field level impact overall vertebrate species richness and to explore decision impacts to targeted species groups (e.g. game, pest, or beneficial species). Agricultural landscapes are often mistakenly thought to be unsuitable habitat for most species. However, as demonstrated by results reported here, even large-scale, conventional agricultural producers are potentially important partners in biodiversity conservation. Many vertebrate species do inhabit agricultural landscapes, benefitting from the provision of water, food, or shelter within cultivated fields and their immediate borders (e.g., Holland et al. 2012). In the Southeastern US, of the 613 terrestrial vertebrate species modeled by the Southeast Gap Analysis Program (SEGAP) (http://www.basic.ncsu.edu/segap/index.html), 263 utilize row crop and associated agricultural land cover classes as potential habitat (Box 1). While some species may be sensitive to certain operational practices (e.g., tillage, pest management, or field border management practices), others are generally tolerant, and some may benefit either directly or indirectly. For example, field margins and ditches often serve as semi-natural habitats providing foraging resources and shelter for vertebrates and are shown to positively influence species richness and abundance (Billeter et al. 2007; Herzon & Helenius 2008; Marshall & Moonen 2002; Shore et al. 2005; Weibull et al. 2003; Wuczyńskia et al. 2011). Biodiversity responses are, therefore, complex, as an individual species’ responses to agricultural production practices depends on that animal’s resource specialization, mobility, and life history strategies (Jeanneret et al. 2003a, b; Jennings & Pocock 2009). The knowledge necessary to define the biodiversity contribution of agricultural lands is specialized, dispersed, and nuanced, and thus not readily accessible. Given access to clearly defined biodiversity tradeoffs between alternative agricultural practices, landowners, land managers and farm operators could collectively enhance the conservation and economic value of agricultural landscapes. Therefore, Field to Market: The Keystone Alliance for Sustainable Agriculture and The Nature Conservancy jointly funded a pilot project to develop a biodiversity metric to integrate into Field to Market’s existing sustainability calculator, The Fieldprint Calculator (http://www. fieldtomarket.org/). Field to Market: The Keystone Alliance for Sustainable Agriculture is an alliance among producers, agribusinesses, food companies, and conservation organizations seeking to create sustainable outcomes for agriculture. The Fieldprint Calculator supports the Keystone Alliance’s vision to achieve safe, accessible, and nutritious food, fiber and fuel in thriving ecosystems to meet the needs of 9 billion people in 2050. In support of this same vision, our project provides proof-of-concept for an outcome-based biodiversity metric for Field to Market to quantify biodiversity impacts of commercial row crop production on terrestrial vertebrate richness. Little research exists examining the impacts of alternative commercial agricultural practices on overall terrestrial biodiversity (McLaughlin & Mineau 1995). Instead, most studies compare organic versus conventional practices (e.g. Freemark & Kirk 2001; Wickramasinghe et al. 2004), and most studies focus on flora, avian, or invertebrate communities (Jeanneret et al. 2003a; Maes et al. 2008; Pollard & Relton 1970). Therefore, we used an expert-knowledge-based approach to develop a metric that predicts expected impacts to shelter and forage resources, individual species, and overall biodiversity (species richness). This approach is modeled after an ecosystems services concept (WRI 2005), except that we examine services (i.e., resources) provided to vertebrate wildlife rather than service provided to the human population. SEGAP predicts species that are potentially present in an area given landscape-scale habitat availability, configuration, and context (e.g., patch size, proximity to resources, connectivity, potential for disturbance). Based on the prediction of species that may be potentially present, the impacts of management decisions within fields and around their borders can be analyzed based on the impact of those practices to the availability of species’ resources. The final metric provides an index of a producer’s relative impact, but perhaps even more importantly, the underlying database allows producers to explore details such as which species are most impacted or how alternative decisions would impact their score.

Technical Bulletin

Use of occupancy models to evaluate expert knowledge-based species-habitat relationships

Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee ( Contopus virens ) and Brown-headed Nuthatch ( Sitta pusilla ), occupancy was strongly influenced by vegetation types classified as “optimal habitat” by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker ( Melanerpes erythrocephalus ) models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.

Avian Conservation and Ecology