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Geology topics

Tracy R. Holcombe

Publications and source records attributed to Tracy R. Holcombe.

13 recordsLinked to original sources

Forecasting weed distributions using climate data: a GIS early warning tool

The number of invasive exotic plant species establishing in the United States is continuing to rise. When prevention of exotic species from entering into a country fails at the national level and the species establishes, reproduces, spreads, and becomes invasive, the most successful action at a local level is early detection followed eradication. We have developed a simple geographic information system (GIS) analysis for developing watch lists for early detection of invasive exotic plants that relies upon currently available species distribution data coupled with environmental data to aid in describing coarse-scale potential distributions. This GIS analysis tool develops environmental envelopes for species based upon the known distribution of a species thought to be invasive and represents the first approximation of its potential habitat while the necessary data are collected to perform more in­-depth analyses. To validate this method we looked at a time series of species distributions for 66 species in Pacific Northwest, and northern Rocky Mountain counties. The time series analysis presented here did select counties that the invasive exotic weeds invaded in subsequent years, showing that this technique could be useful in developing watch lists for the spread of particular exotic species. We applied this same habitat-matching model based upon bioclimaric envelopes to 100 invasive exotics with various levels of known distributions within continental U.S. counties. For species with climatically limited distributions, county watch lists describe county-specific vulnerability to invasion. Species with matching habitats in a county would be added to that county's list. These watch lists can influence management decisions for early warning, control prioritization, and targeted research to determine specific locations within vulnerable counties. This tool provides useful information for rapid assessment of the potential distribution based upon climate envelopes of current distributions for new invasive exotic species.

Invasive Plant Science and Management

Ecology and space: A case study in mapping harmful invasive species

The establishment and invasion of non-native plant species have the ability to alter the composition of native species and functioning of ecological systems with financial costs resulting from mitigation and loss of ecological services. Spatially documenting invasions has applications for management and theory, but the utility of maps is challenged by availability and uncertainty of data, and the reliability of extrapolating mapped data in time and space. The extent and resolution of projections also impact the ability to inform invasive species science and management. Early invasive species maps were coarse-grained representations that underscored the phenomena, but had limited capacity to direct management aside from development of watch lists for priorities for prevention and containment. Integrating mapped data sets with fine-resolution environmental variables in the context of species-distribution models allows a description of species-environment relationships and an understanding of how, why, and where invasions may occur. As with maps, the extent and resolution of models impact the resulting insight. Models of cheatgrass ( Bromus tectorum ) across a variety of spatial scales and grain result in divergent species-environment relationships. New data can improve models and efficiently direct further inventories. Mapping can target areas of greater model uncertainty or the bounds of modeled distribution to efficiently refine models and maps. This iterative process results in dynamic, living maps capable of describing the ongoing process of species invasions.

Book chapter

Minimizing effects of methodological decisions on interpretation and prediction in species distribution studies: An example with background selection

Evaluating the conditions where a species can persist is an important question in ecology both to understand tolerances of organisms and to predict distributions across landscapes. Presence data combined with background or pseudo-absence locations are commonly used with species distribution modeling to develop these relationships. However, there is not a standard method to generate background or pseudo-absence locations, and method choice affects model outcomes. We evaluated combinations of both model algorithms (simple and complex generalized linear models, multivariate adaptive regression splines, Maxent, boosted regression trees, and random forest) and background methods (random, minimum convex polygon, and continuous and binary kernel density estimator (KDE)) to assess the sensitivity of model outcomes to choices made. We evaluated six questions related to model results, including five beyond the common comparison of model accuracy assessment metrics (biological interpretability of response curves, cross-validation robustness, independent data accuracy and robustness, and prediction consistency). For our case study with cheatgrass in the western US, random forest was least sensitive to background choice and the binary KDE method was least sensitive to model algorithm choice. While this outcome may not hold for other locations or species, the methods we used can be implemented to help determine appropriate methodologies for particular research questions.

Ecological Modelling

Benefits and limitations of using decision analytic tools to assess uncertainty and prioritize Landscape Conservation Cooperative information needs

The Landscape Conservation Cooperatives (LCCs) are a network of partnerships throughout North America that are tasked with integrating science and management to support more effective delivery of conservation at a landscape scale. In order to achieve this integration, some LCCs have adopted the approach of providing their partners with better scientific information in an effort to facilitate more effective and coordinated conservation decisions. Taking this approach has led many LCCs to begin funding research to provide the information for improved decision making. To ensure that funding goes to research projects with the highest likelihood of leading to more integrated broad scale conservation, some LCCs have also developed approaches for prioritizing which information needs will be of most benefit to their partnerships. We describe two case studies in which decision analytic tools were used to quantitatively assess the relative importance of information for decisions made by partners in the Plains and Prairie Potholes LCC. The results of the case studies point toward a few valuable lessons in terms of using these tools with LCCs. Decision analytic tools tend to help shift focus away from research oriented discussions and toward discussions about how information is used in making better decisions. However, many technical experts do not have enough knowledge about decision making contexts to fully inform the latter type of discussion. When assessed in the right decision context, however, decision analyses can point out where uncertainties actually affect optimal decisions and where they do not. This helps technical experts understand that not all research is valuable in improving decision making. But perhaps most importantly, our results suggest that decision analytic tools may be more useful for LCCs as way of developing integrated objectives for coordinating partner decisions across the landscape, rather than simply ranking research priorities.

Journal of Fish and Wildlife Management

Assessing range-wide habitat suitability for the Lesser Prairie-Chicken

Population declines of many wildlife species have been linked to habitat loss incurred through land-use change. Incorporation of conservation planning into development planning may mitigate these impacts. The threatened Lesser Prairie-Chicken ( Tympanuchus pallidicinctus ) is experiencing loss of native habitat and high levels of energy development across its multijurisdictional range. Our goal was to explore relationships of the species occurrence with landscape characteristics and anthropogenic effects influencing its distribution through evaluation of habitat suitability associated with one particular habitat usage, lekking. Lekking has been relatively well-surveyed, though not consistently, in all jurisdictions. All five states in which Lesser Prairie-Chickens occur cooperated in development of a Maxent habitat suitability model. We created two models, one with state as a factor and one without state. When state was included it was the most important predictor, followed by percent of land cover consisting of known or suspected used vegetation classes within a 5000 m area around a lek. Without state, land cover was the most important predictor of relative habitat suitability for leks. Among the anthropogenic predictors, landscape condition, a measure of human impact integrated across several factors, was most important, ranking third in importance without state. These results quantify the relative suitability of the landscape within the current occupied range of Lesser Prairie-Chickens. These models, combined with other landscape information, form the basis of a habitat assessment tool that can be used to guide siting of development projects and targeting of areas for conservation.

Colorado, Kansas, New Mexico, Oklahoma, Texas

Caveats for correlative species distribution modeling

Correlative species distribution models are becoming commonplace in the scientific literature and public outreach products, displaying locations, abundance, or suitable environmental conditions for harmful invasive species, threatened and endangered species, or species of special concern. Accurate species distribution models are useful for efficient and adaptive management and conservation, research, and ecological forecasting. Yet, these models are often presented without fully examining or explaining the caveats for their proper use and interpretation and are often implemented without understanding the limitations and assumptions of the model being used. We describe common pitfalls, assumptions, and caveats of correlative species distribution models to help novice users and end users better interpret these models. Four primary caveats corresponding to different phases of the modeling process, each with supporting documentation and examples, include: (1) all sampling data are incomplete and potentially biased; (2) predictor variables must capture distribution constraints; (3) no single model works best for all species, in all areas, at all spatial scales, and over time; and (4) the results of species distribution models should be treated like a hypothesis to be tested and validated with additional sampling and modeling in an iterative process.

Ecological Informatics

Simulating long-term effectiveness and efficiency of management scenarios for an invasive grass

Resource managers are often faced with trade-offs in allocating limited resources to manage plant invasions. These decisions must often be made with uncertainty about the location of infestations, their rate of spread and effectiveness of management actions. Landscape level simulation tools such as state-and-transition simulation models (STSMs) can be used to evaluate the potential long term consequences of alternative management strategies and help identify those strategies that make efficient use of resources. We analyzed alternative management scenarios for African buffelgrass ( Pennisetum ciliare syn. Cenchrus ciliaris ) at Ironwood Forest National Monument, Arizona using a spatially explicit STSM implemented in the Tool for Exploratory Landscape Scenario Analyses (TELSA). Buffelgrass is an invasive grass that is spreading rapidly in the Sonoran Desert, affecting multiple habitats and jurisdictions. This invasion is creating a novel fire risk and transforming natural ecosystems. The model used in this application incorporates buffelgrass dispersal and establishment and management actions and effectiveness including inventory, treatment and post-treatment maintenance. We simulated 11 alternative scenarios developed in consultation with buffelgrass managers and other stakeholders. The scenarios vary according to the total budget allocated for management and the allocation of that budget between different kinds of management actions. Scenario results suggest that to achieve an actual reduction and stabilization of buffelgrass populations, management unconstrained by fiscal restrictions and across all jurisdictions and private lands is required; without broad and aggressive management, buffelgrass populations are expected to increase over time. However, results also suggest that large upfront investments can achieve control results that require relatively minimal spending in the future. Investing the necessary funds upfront to control the invasion results in the most efficient use of resources to achieve lowest invaded acreage in the long-term.

Arizona

Regional distribution models with lack of proximate predictors: Africanized honeybees expanding north

Species distribution models have often been hampered by poor local species data, reliance on coarse-scale climate predictors and the assumption that species–environment relationships, even with non-proximate predictors, are consistent across geographical space. Yet locally accurate maps of invasive species, such as the Africanized honeybee (AHB) in North America, are needed to support conservation efforts. Current AHB range maps are relatively coarse and are inconsistent with observed data. Our aim was to improve distribution maps using more proximate predictors (phenology) and using regional models rather than one across the entire range of interest to explore potential differences in drivers.

Diversity and Distributions

VisTrails SAHM: visualization and workflow management for species habitat modeling

The Software for Assisted Habitat Modeling (SAHM) has been created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model through the established workflow management and visualization VisTrails software. This paper provides an overview of the VisTrails:SAHM software including a link to the open source code, a table detailing the current SAHM modules, and a simple example modeling an invasive weed species in Rocky Mountain National Park, USA.

Ecography: Pattern and Diversity in Ecology

Impacts of land-use change to ecosystem services

Increasing human populations on the landscape and globe coincide with increasing demands for food, energy, and other natural resources, with generally negative impacts to wildlife habitat, air and water quality, and natural scenery. Here we define and describe the impacts of land-use change on ecosystem services – the services that ecosystems provide humans such as filtering air and water, providing food, resources, recreation, and esthetics. We show how the human footprint is rapidly expanding due to population growth, demand for resources, and globalization. Increased trade and transportation has brought all the continents back together, creating new challenges for conserving native species and ecosystems.

Book chapter

Buffelgrass-Integrated modeling of an invasive plant

Buffelgrass (Pennisetum ciliare) poses a problem in the deserts of the United States, growing in dense stands and introducing a wildfire risk in an ecosystem not adapted to fire. The Invasive Species Science Branch of the Fort Collins Science Center has worked with many partners to develop a decision support model and a data management system to address the problem. The decision support model evaluates potential strategies for resource use and allocation. The data management system is a portal where users can submit, view, and download buffelgrass data. These tools provide a case study showcasing how the FORT is working to address the urgent issue of invasive species in the United States.

Fact Sheet

From points to forecasts: Predicting invasive species habitat suitability in the near term

We used near-term climate scenarios for the continental United States, to model 12 invasive plants species. We created three potential habitat suitability models for each species using maximum entropy modeling: (1) current; (2) 2020; and (3) 2035. Area under the curve values for the models ranged from 0.92 to 0.70, with 10 of the 12 being above 0.83 suggesting strong and predictable species-environment matching. Change in area between the current potential habitat and 2035 ranged from a potential habitat loss of about 217,000 km 2 , to a potential habitat gain of about 133,000 km 2 .

Diversity

Invasive species management and research using GIS

Geographical Information Systems (GIS) are powerful tools in the field of invasive species management. GIS can be used to create potential distribution maps for all manner of taxa, including plants, animals, and diseases. GIS also performs well in the early detection and rapid assessment of invasive species. Here, we used GIS applications to investigate species richness and invasion patterns in fish in the United States (US) at the 6-digit Hydrologic Unit Code (HUC) level. We also created maps of potential spread of the cane toad (Bufo marinus) in the southeastern US at the 8-digit HUC level using regression and environmental envelope techniques. Equipped with this potential map, resource managers can target their field surveys to areas most vulnerable to invasion. Advances in GIS technology, maps, data, and many of these techniques can be found on websites such as the National Institute of Invasive Species Science (www.NIISS.org). Such websites provide a forum for data sharing and analysis that is an invaluable service to the invasive species community.

Conference Paper