Habitat Suitability Index Models: Muskellunge

USGS Publications Warehouse

Cook, Mark F.; Solomon, R. Charles

1987-01-01

A review and synthesis of existing information were used to develop a Habitat Suitability Index (HSI) model for the muskellunge (Esox masquinongy Mitchell). The model consolidates habitat use information into a framework appropriate for field application, and is scaled to produce an index between 0.0 (unsuitable habitat) to 1.0 (optimum habitat). HSI models are designed to be used with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

Evaluation of a habitat suitability index model

USGS Publications Warehouse

Farmer, A.H.; Cade, B.S.; Stauffer, D.F.

2002-01-01

We assisted with development of a model for maternity habitat of the Indiana bat (Myotis soda/is), for use in conducting assessments of projects potentially impacting this endangered species. We started with an existing model, modified that model in a workshop, and evaluated the revised model, using data previously collected by others. Our analyses showed that higher indices of habitat suitability were associated with sites where Indiana bats were present and, thus, the model may be useful for identifying suitable habitat. Utility of the model, however, was based on a single component-density of suitable roost trees. Percentage of landscape in forest did not allow differentiation between sites occupied and not occupied by Indiana bats. Moreover, in spite of a general opinion by participants in the workshop that bodies of water were highly productive feeding areas and that a diversity of feeding habitats was optimal, we found no evidence to support either hypothesis.

Habitat features and predictive habitat modeling for the Colorado chipmunk in southern New Mexico

USGS Publications Warehouse

Rivieccio, M.; Thompson, B.C.; Gould, W.R.; Boykin, K.G.

2003-01-01

Two subspecies of Colorado chipmunk (state threatened and federal species of concern) occur in southern New Mexico: Tamias quadrivittatus australis in the Organ Mountains and T. q. oscuraensis in the Oscura Mountains. We developed a GIS model of potentially suitable habitat based on vegetation and elevation features, evaluated site classifications of the GIS model, and determined vegetation and terrain features associated with chipmunk occurrence. We compared GIS model classifications with actual vegetation and elevation features measured at 37 sites. At 60 sites we measured 18 habitat variables regarding slope, aspect, tree species, shrub species, and ground cover. We used logistic regression to analyze habitat variables associated with chipmunk presence/absence. All (100%) 37 sample sites (28 predicted suitable, 9 predicted unsuitable) were classified correctly by the GIS model regarding elevation and vegetation. For 28 sites predicted suitable by the GIS model, 18 sites (64%) appeared visually suitable based on habitat variables selected from logistic regression analyses, of which 10 sites (36%) were specifically predicted as suitable habitat via logistic regression. We detected chipmunks at 70% of sites deemed suitable via the logistic regression models. Shrub cover, tree density, plant proximity, presence of logs, and presence of rock outcrop were retained in the logistic model for the Oscura Mountains; litter, shrub cover, and grass cover were retained in the logistic model for the Organ Mountains. Evaluation of predictive models illustrates the need for multi-stage analyses to best judge performance. Microhabitat analyses indicate prospective needs for different management strategies between the subspecies. Sensitivities of each population of the Colorado chipmunk to natural and prescribed fire suggest that partial burnings of areas inhabited by Colorado chipmunks in southern New Mexico may be beneficial. These partial burnings may later help avoid a fire

Habitat Suitability Index Models: Pronghorn

USGS Publications Warehouse

Allen, Arthur W.; Cook, John G.; Armbruster, Michael J.

1984-01-01

This is one of a series of publications that provide information on the habitat requirements of selected fish and wildlife species. Literature describing the relationship between habitat variables related to life requisites and habitat suitability for the pronghorn (Antilocapra americana) are synthesized. These data are subsequently used to develop Habitat Suitability Index (HSI) models. The HSI models are designed to provide information that can be used in impact assessment and habitat management.

Habitat Suitability Index Models: Laughing gull

USGS Publications Warehouse

Zale, Alexander V.; Mulholland, Rosemarie

1985-01-01

A review and synthesis of existing information were used to develop a habitat model for laughing gull (Larus atricilla). The model is scaled to produce an index of habitat suitability between 0 (unsuitable habitat) and 1.0 (optimally suitable habitat) for areas along the Gulf of Mexico coast. Habitat suitability indices are designed for use with the Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service. Guidelines for application of the model and techniques for measuring model variables are described.

GIS-based niche modeling for mapping species' habitats

USGS Publications Warehouse

Rotenberry, J.T.; Preston, K.L.; Knick, S.

2006-01-01

Ecological a??niche modelinga?? using presence-only locality data and large-scale environmental variables provides a powerful tool for identifying and mapping suitable habitat for species over large spatial extents. We describe a niche modeling approach that identifies a minimum (rather than an optimum) set of basic habitat requirements for a species, based on the assumption that constant environmental relationships in a species' distribution (i.e., variables that maintain a consistent value where the species occurs) are most likely to be associated with limiting factors. Environmental variables that take on a wide range of values where a species occurs are less informative because they do not limit a species' distribution, at least over the range of variation sampled. This approach is operationalized by partitioning Mahalanobis D2 (standardized difference between values of a set of environmental variables for any point and mean values for those same variables calculated from all points at which a species was detected) into independent components. The smallest of these components represents the linear combination of variables with minimum variance; increasingly larger components represent larger variances and are increasingly less limiting. We illustrate this approach using the California Gnatcatcher (Polioptila californica Brewster) and provide SAS code to implement it.

Chapter 5. Using Habitat Models for Habitat Mapping and Monitoring

Treesearch

Samuel A. Cushman; Timothy J. Mersmann; Gretchen G. Moisen; Kevin S. McKelvey; Christina D. Vojta

2013-01-01

This chapter provides guidance for applying existing habitat models to map and monitor wildlife habitat. Chapter 2 addresses the use of conceptual models to create a solid foundation for selecting habitat attributes to monitor and to translate these attributes into quantifiable and reportable monitoring measures. Most wildlife species, however, require a complex suite...

Habitat Suitability Index Models: Hairy woodpecker

USGS Publications Warehouse

Sousa, Patrick J.

1987-01-01

A review and synthesis of existing information were used to develop a Habitat Suitability Index (HSI) model for the hairy woodpecker (Picoides villosus). The model consolidates habitat use information into a framework appropriate for field application, and is scaled to produce an index between 0.0 (unsuitable habitat) to 1.0 (optimum habitat). HSI models are designed to be used with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

Habitat Suitability Index Models: Snapping turtle

USGS Publications Warehouse

Graves, Brent M.; Anderson, Stanley H.

1987-01-01

A review and synthesis of existing information were used to develop a Habitat Suitability Index (HSI) model for the snapping turtle (Chelydra serpentina). The model consolidates habitat use information into a framework appropriate for field application, and is scaled to produce an index between 0.0 (unsuitable habitat) and 1.0 (optimum habitat). HSI models are designed to be used with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

Habitat Suitability Index Models: Spotted owl

USGS Publications Warehouse

Laymon, Stephen A.; Salwasser, Hal; Barrett, Reginald H.

1985-01-01

A review and synthesis of existing information were used to develop a Habitat Suitability Index (HSI) model for the spotted owl (Strix occidentalis). The model consolidates habitat use information into a framework appropriate for field application, and is scaled to produce an index between 0.0 (unsuitable habitat) to 1.0 (optimum habitat). HSI models are designed to be used with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

Habitat Suitability Index Models: Eastern meadowlark

USGS Publications Warehouse

Schroeder, Richard L.; Sousa, Patrick J.

1982-01-01

Habitat preferences of the eastern meadowlark (Sturnella magna) are described in this publication, which is one of a series of Habitat Suitability Index (HSI) models. Habitat use information is presented in a synthesis of the literature on the species-habitat requirements of the eastern meadowlark, followed by the development of the HSI model. The model is presented in three formats: graphic, word, and mathematical, and is designed to provide information for use in impact assessment and habitat management activities.

Habitat Suitability Index Models: Pine warbler

USGS Publications Warehouse

Schroeder, Richard L.

1982-01-01

Habitat preferences of the pine warbler (Dendroica pinus) are described in this publication, which is one of a series of Habitat Suitability Index (HSI) models. Habitat use information is presented in a synthesis of the literature on the species-habitat requirements of the pine warbler, followed by the development of the HSI model. The model is presented in three formats: graphic, word, and mathematical, and is designed to provide information for use in impact assessment and habitat management activities.

Dynamic habitat models: using telemetry data to project fisheries bycatch

PubMed Central

Žydelis, Ramūnas; Lewison, Rebecca L.; Shaffer, Scott A.; Moore, Jeffrey E.; Boustany, Andre M.; Roberts, Jason J.; Sims, Michelle; Dunn, Daniel C.; Best, Benjamin D.; Tremblay, Yann; Kappes, Michelle A.; Halpin, Patrick N.; Costa, Daniel P.; Crowder, Larry B.

2011-01-01

Fisheries bycatch is a recognized threat to marine megafauna. Addressing bycatch of pelagic species however is challenging owing to the dynamic nature of marine environments and vagility of these organisms. In order to assess the potential for species to overlap with fisheries, we propose applying dynamic habitat models to determine relative probabilities of species occurrence for specific oceanographic conditions. We demonstrate this approach by modelling habitats for Laysan (Phoebastria immutabilis) and black-footed albatrosses (Phoebastria nigripes) using telemetry data and relating their occurrence probabilities to observations of Hawaii-based longline fisheries in 1997–2000. We found that modelled habitat preference probabilities of black-footed albatrosses were high within some areas of the fishing range of the Hawaiian fleet and such preferences were important in explaining bycatch occurrence. Conversely, modelled habitats of Laysan albatrosses overlapped little with Hawaii-based longline fisheries and did little to explain the bycatch of this species. Estimated patterns of albatross habitat overlap with the Hawaiian fleet corresponded to bycatch observations: black-footed albatrosses were more frequently caught in this fishery despite being 10 times less abundant than Laysan albatrosses. This case study demonstrates that dynamic habitat models based on telemetry data may help to project interactions with pelagic animals relative to environmental features and that such an approach can serve as a tool to guide conservation and management decisions. PMID:21429921

Habitat Suitability Index Models: Yellow perch

USGS Publications Warehouse

Krieger, Douglas A.; Terrell, James W.; Nelson, Patrick C.

1983-01-01

A review and synthesis of existing information were used to develop riverine and lacustrine habitat models for yellow perch (Perca flavescens). The models are scaled to produce an index of habitat suitability between 0 (unsuitable habitat) to 1 (optimally suitable habitat) for riverine, lacustrine, and palustrine habitat in the 48 contiguous United States. Habitat Suitability Indexes (HSI's) are designed for use with the Habitat Evaluation Procedures developed by the U.S. Fish and Wildlife Service. Also included are discussions of Suitability Index (SI) curves as used in the Instream Flow Incremental Methodology (IFIM) and SI curves available for an IFIM analysis of yellow perch habitat.

Habitat Suitability Index Models: Black-shouldered kite

USGS Publications Warehouse

Faanes, Craig A.; Howard, Rebecca J.

1987-01-01

A review and synthesis of existing information were used to develop a model for evaluating black-shouldered kite habitat quality. The model is scaled to produce an index between 0 (unsuitable habitat) to 1.0 (optimal habitat). Habitat suitability index models are designed for use with the Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service. Guidelines for model application are provided.

Lessons learned while integrating habitat, dispersal, disturbance, and life-history traits into species habitat models under climate change

Treesearch

Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Matthew P. Peters

2011-01-01

We present an approach to modeling potential climate-driven changes in habitat for tree and bird species in the eastern United States. First, we took an empirical-statistical modeling approach, using randomForest, with species abundance data from national inventories combined with soil, climate, and landscape variables, to build abundance-based habitat models for 134...

Proceedings of a workshop on fish habitat suitability index models

USGS Publications Warehouse

Terrell, James W.

1984-01-01

One of the habitat-based methodologies for impact assessment currently in use by the U.S. Fish and Wildlife Service is the Habitat Evaluation Procedures (HEP) (U.S. Fish and Wildlife Service 1980). HEP is based on the assumption that the quality of an area as wildlife habitat at a specified target year can be described by a single number, called a Habitat Suitability Index (HSI). An HSI of 1.0 represents optimum habitat: an HSI of 0.0 represents unsuitable habitat. The verbal or mathematical rules by which an HSI is assigned to an area are called an HSI model. A series of Habitat Suitability Index (HSI) models, described by Schamberger et al. (1982), have been published to assist users in applying HEP. HSI model building approaches are described in U.S. Fish and Wildlife Service (1981). One type of HSI model described in detail requires the development of Suitability Index (SI) graphs for habitat variables believed to be important for the growth, survival, standing crop, or other measure of well-being for a species. Suitability indices range from 0 to 1.0, with 1.0 representing optimum conditions for the variable. When HSI models based on suitability indices are used, habitat variable values are measured, or estimated, and converted to SI's through the use of a Suitability Index graph for each variable. Individual SI's are aggregated into an HSI. Standard methods for testing this type of HSI model did not exist at the time the studies reported in this document were performed. A workshop was held in Fort Collins, Colorado, February 14-15, 1983, that brought together biologists experienced in the use, development, and testing of aquatic HSI models, in an effort to address the following objectives: (1) review the needs of HSI model users; (2) discuss and document the results of aquatic HSI model tests; and (3) provide recommendations for the future development, testing, modification, and use of HSI models. Individual presentations, group discussions, and group

Modeling sensitive elasmobranch habitats

NASA Astrophysics Data System (ADS)

Pennino, M. Grazia; Muñoz, Facundo; Conesa, David; López-Quílez, Antonio; Bellido, José Marí; a

2013-10-01

Basic information on the distribution and habitat preferences of ecologically important species is essential for their management and protection. In the Mediterranean Sea there is increasing concern over elasmobranch species because their biological (ecological) characteristics make them highly vulnerable to fishing pressure. Their removal could affect the structure and function of marine ecosystems, inducing changes in trophic interactions at the community level due to the selective elimination of predators or prey species, competitors and species replacement. In this study Bayesian hierarchical spatial models are used to map the sensitive habitats of the three most caught elasmobranch species (Galeus melastomus, Scyliorhinus canicula, Etmopterus spinax) in the western Mediterranean Sea, based on fishery-dependent bottom trawl data. Results show that habitats associated with hard substrata and sandy beds, mainly in deep waters and with a high seabed gradient, have a greater probability registering the presence of the studied species than those associated with muddy shallow waters. Temperature and chlorophyll-α concentration show a negative relationship with S. canicula occurrence. Our results identify some of the sensitive habitats for elasmobranchs in the western Mediterranean Sea (GSA06 South), providing essential and easy-to-use interpretation tools, such as predictive distribution maps, with the final aim of improving management and conservation of these vulnerable species.

Comparing Habitat Suitability and Connectivity Modeling Methods for Conserving Pronghorn Migrations

PubMed Central

Poor, Erin E.; Loucks, Colby; Jakes, Andrew; Urban, Dean L.

2012-01-01

Terrestrial long-distance migrations are declining globally: in North America, nearly 75% have been lost. Yet there has been limited research comparing habitat suitability and connectivity models to identify migration corridors across increasingly fragmented landscapes. Here we use pronghorn (Antilocapra americana) migrations in prairie habitat to compare two types of models that identify habitat suitability: maximum entropy (Maxent) and expert-based (Analytic Hierarchy Process). We used distance to wells, distance to water, NDVI, land cover, distance to roads, terrain shape and fence presence to parameterize the models. We then used the output of these models as cost surfaces to compare two common connectivity models, least-cost modeling (LCM) and circuit theory. Using pronghorn movement data from spring and fall migrations, we identified potential migration corridors by combining each habitat suitability model with each connectivity model. The best performing model combination was Maxent with LCM corridors across both seasons. Maxent out-performed expert-based habitat suitability models for both spring and fall migrations. However, expert-based corridors can perform relatively well and are a cost-effective alternative if species location data are unavailable. Corridors created using LCM out-performed circuit theory, as measured by the number of pronghorn GPS locations present within the corridors. We suggest the use of a tiered approach using different corridor widths for prioritizing conservation and mitigation actions, such as fence removal or conservation easements. PMID:23166656

Comparing habitat suitability and connectivity modeling methods for conserving pronghorn migrations.

PubMed

Poor, Erin E; Loucks, Colby; Jakes, Andrew; Urban, Dean L

2012-01-01

Terrestrial long-distance migrations are declining globally: in North America, nearly 75% have been lost. Yet there has been limited research comparing habitat suitability and connectivity models to identify migration corridors across increasingly fragmented landscapes. Here we use pronghorn (Antilocapra americana) migrations in prairie habitat to compare two types of models that identify habitat suitability: maximum entropy (Maxent) and expert-based (Analytic Hierarchy Process). We used distance to wells, distance to water, NDVI, land cover, distance to roads, terrain shape and fence presence to parameterize the models. We then used the output of these models as cost surfaces to compare two common connectivity models, least-cost modeling (LCM) and circuit theory. Using pronghorn movement data from spring and fall migrations, we identified potential migration corridors by combining each habitat suitability model with each connectivity model. The best performing model combination was Maxent with LCM corridors across both seasons. Maxent out-performed expert-based habitat suitability models for both spring and fall migrations. However, expert-based corridors can perform relatively well and are a cost-effective alternative if species location data are unavailable. Corridors created using LCM out-performed circuit theory, as measured by the number of pronghorn GPS locations present within the corridors. We suggest the use of a tiered approach using different corridor widths for prioritizing conservation and mitigation actions, such as fence removal or conservation easements.

INTERACTIVE HABITAT MODELS FOR MID-ATLANTIC HIGHLAND STREAM FISHES

EPA Science Inventory

In most wadeable streams of the Mid-Atlantic Highland region of the eastern United States, habitat alteration resulting from development in the watershed is the primary stressor for fish. Models that predict the presence of stream fish species based on habitat characteristics ca...

Linking population viability, habitat suitability, and landscape simulation models for conservation planning

Treesearch

Michael A. Larson; Frank R., III Thompson; Joshua J. Millspaugh; William D. Dijak; Stephen R. Shifley

2004-01-01

Methods for habitat modeling based on landscape simulations and population viability modeling based on habitat quality are well developed, but no published study of which we are aware has effectively joined them in a single, comprehensive analysis. We demonstrate the application of a population viability model for ovenbirds (Seiurus aurocapillus)...

Relating FIA data to habitat classifications via tree-based models of canopy cover

Treesearch

Mark D. Nelson; Brian G. Tavernia; Chris Toney; Brian F. Walters

2012-01-01

Wildlife species-habitat matrices are used to relate lists of species with abundance of their habitats. The Forest Inventory and Analysis Program provides data on forest composition and structure, but these attributes may not correspond directly with definitions of wildlife habitats. We used FIA tree data and tree crown diameter models to estimate canopy cover, from...

Habitat Suitability Index Models: Red-winged blackbird

USGS Publications Warehouse

Short, Henry L.

1985-01-01

A review and synthesis of existing information were used to develop a Habitat Suitability Index (HSI) model for the red-winged blackbird (Agelaius phoeniceus L.). The model consolidates habitat use information into a framework appropriate for field application, and is scaled to produce an index between 0.0 (unsuitable habitat) to 1.0 (optimum habitat). HSI models are designed to be used with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

Habitat Suitability Index Models: Red king crab

USGS Publications Warehouse

Jewett, Stephen C.; Onuf, Christopher P.

1988-01-01

A review and synthesis of existing information were used to develop a Habitat Suitability Index (HSI) model for evaluating habitat of different life stages of red king crab (Paralithodes camtschatica). A model consolidates habitat use information into a framework appropriate for field application, and is scaled to produce an index between 0.0 (unsuitable habitat) and 1.0 (optimum habitat) in Alaskan coastal waters, especially in the Gulf of Alaska and the southeastern Bering Sea. HSI models are designed to be used with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

ESTIMATING THE DISTRIBUTION OF HARVESTED ESTUARINE BIVALVES WITH NATURAL-HISTORY-BASED HABITAT SUITABILITY MODELS.

EPA Science Inventory

Habitat suitability models are used to forecast how environmental change may affect the abundance or distribution of species of interest. The development of habitat suitability models may be used to estimate the vulnerability of this valued ecosystem good to natural or anthropog...

Towards a resource-based habitat approach for spatial modelling of vector-borne disease risks.

PubMed

Hartemink, Nienke; Vanwambeke, Sophie O; Purse, Bethan V; Gilbert, Marius; Van Dyck, Hans

2015-11-01

Given the veterinary and public health impact of vector-borne diseases, there is a clear need to assess the suitability of landscapes for the emergence and spread of these diseases. Current approaches for predicting disease risks neglect key features of the landscape as components of the functional habitat of vectors or hosts, and hence of the pathogen. Empirical-statistical methods do not explicitly incorporate biological mechanisms, whereas current mechanistic models are rarely spatially explicit; both methods ignore the way animals use the landscape (i.e. movement ecology). We argue that applying a functional concept for habitat, i.e. the resource-based habitat concept (RBHC), can solve these issues. The RBHC offers a framework to identify systematically the different ecological resources that are necessary for the completion of the transmission cycle and to relate these resources to (combinations of) landscape features and other environmental factors. The potential of the RBHC as a framework for identifying suitable habitats for vector-borne pathogens is explored and illustrated with the case of bluetongue virus, a midge-transmitted virus affecting ruminants. The concept facilitates the study of functional habitats of the interacting species (vectors as well as hosts) and provides new insight into spatial and temporal variation in transmission opportunities and exposure that ultimately determine disease risks. It may help to identify knowledge gaps and control options arising from changes in the spatial configuration of key resources across the landscape. The RBHC framework may act as a bridge between existing mechanistic and statistical modelling approaches. © 2014 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

Habitat Suitability Index Models: Yellow-headed blackbird

USGS Publications Warehouse

Schroeder, Richard L.

1982-01-01

Habitat preferences of the yellow-headed blackbird (Xanthocephalus xanthocephalus) are described in this publication. It is one of a series of Habitat Suitability Index (HSI) models and was developed through an analysis of available infomration on the species-habitat requirements of the species. Habitat use information is presented in a review of the literature, followed by the development of an HSI model, designed for use in impact assessment and habitat management activities.

Physiology-based modelling approaches to characterize fish habitat suitability: Their usefulness and limitations

NASA Astrophysics Data System (ADS)

Teal, Lorna R.; Marras, Stefano; Peck, Myron A.; Domenici, Paolo

2018-02-01

Models are useful tools for predicting the impact of global change on species distribution and abundance. As ectotherms, fish are being challenged to adapt or track changes in their environment, either in time through a phenological shift or in space by a biogeographic shift. Past modelling efforts have largely been based on correlative Species Distribution Models, which use known occurrences of species across landscapes of interest to define sets of conditions under which species are likely to maintain populations. The practical advantages of this correlative approach are its simplicity and the flexibility in terms of data requirements. However, effective conservation management requires models that make projections beyond the range of available data. One way to deal with such an extrapolation is to use a mechanistic approach based on physiological processes underlying climate change effects on organisms. Here we illustrate two approaches for developing physiology-based models to characterize fish habitat suitability. (i) Aerobic Scope Models (ASM) are based on the relationship between environmental factors and aerobic scope (defined as the difference between maximum and standard (basal) metabolism). This approach is based on experimental data collected by using a number of treatments that allow a function to be derived to predict aerobic metabolic scope from the stressor/environmental factor(s). This function is then integrated with environmental (oceanographic) data of current and future scenarios. For any given species, this approach allows habitat suitability maps to be generated at various spatiotemporal scales. The strength of the ASM approach relies on the estimate of relative performance when comparing, for example, different locations or different species. (ii) Dynamic Energy Budget (DEB) models are based on first principles including the idea that metabolism is organised in the same way within all animals. The (standard) DEB model aims to describe

Modeling habitat dynamics accounting for possible misclassification

USGS Publications Warehouse

Veran, Sophie; Kleiner, Kevin J.; Choquet, Remi; Collazo, Jaime; Nichols, James D.

2012-01-01

Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.

Habitat modeling for biodiversity conservation.

Treesearch

Bruce G. Marcot

2006-01-01

Habitat models address only 1 component of biodiversity but can be useful in addressing and managing single or multiple species and ecosystem functions, for projecting disturbance regimes, and in supporting decisions. I review categories and examples of habitat models, their utility for biodiversity conservation, and their roles in making conservation decisions. I...

Modeling Bird Migration in Changing Habitats: Space-based Ornithology using Satellites and GIS

NASA Technical Reports Server (NTRS)

Smith, James A.; Deppe, Jill L.

2008-01-01

Understanding bird migration and avian biodiversity is one of the most compelling and challenging problems of modern biology with major implications for human health and conservation biology. Migration and conservation efforts cross national boundaries and are subject to numerous international agreements and treaties presenting challenges in both geographic space and time. Space based technology, coupled with geographic information systems, yields new opportunities to shed light on the distribution and movement of organisms on the planet and their sensitivity to human disturbances and environmental changes. At NASA, we are creating ecological forecasting tools for science and application users to address the consequences of loss of wetlands, flooding, drought or other natural disasters such as hurricanes on avian biodiversity and bird migration. In our work, we use individual organism biophysical models and drive these models with satellite observations and numerical weather predictions of the spatio-temporal gradients in climate and habitat. Geographic information system technology comprises one component of our overall simulation framework, especially for characterizing the changing habitats and conditions encountered by en-route migratory birds. Simulation provides a tool for studying bird migration across multiple scales and can be linked to mechanistic processes describing the time and energy budget states of migrating birds. Such models yield an understanding of how a migratory flyway and its component habitats function as a whole and link stop-over ecology with biological conservation and management. We present examples of our simulation of shorebirds, principally, pectoral sandpipers, along the central flyways of the United States and Canada from the Gulf of Mexico to Alaska.

Habitat models to assist plant protection efforts in Shenandoah National Park, Virginia, USA

USGS Publications Warehouse

Van Manen, F.T.; Young, J.A.; Thatcher, C.A.; Cass, W.B.; Ulrey, C.

2005-01-01

During 2002, the National Park Service initiated a demonstration project to develop science-based law enforcement strategies for the protection of at-risk natural resources, including American ginseng (Panax quinquefolius L.), bloodroot (Sanguinaria canadensis L.), and black cohosh (Cimicifuga racemosa (L.) Nutt. [syn. Actaea racemosa L.]). Harvest pressure on these species is increasing because of the growing herbal remedy market. We developed habitat models for Shenandoah National Park and the northern portion of the Blue Ridge Parkway to determine the distribution of favorable habitats of these three plant species and to demonstrate the use of that information to support plant protection activities. We compiled locations for the three plant species to delineate favorable habitats with a geographic information system (GIS). We mapped potential habitat quality for each species by calculating a multivariate statistic, Mahalanobis distance, based on GIS layers that characterized the topography, land cover, and geology of the plant locations (10-m resolution). We tested model performance with an independent dataset of plant locations, which indicated a significant relationship between Mahalanobis distance values and species occurrence. We also generated null models by examining the distribution of the Mahalanobis distance values had plants been distributed randomly. For all species, the habitat models performed markedly better than their respective null models. We used our models to direct field searches to the most favorable habitats, resulting in a sizeable number of new plant locations (82 ginseng, 73 bloodroot, and 139 black cohosh locations). The odds of finding new plant locations based on the habitat models were 4.5 (black cohosh) to 12.3 (American ginseng) times greater than random searches; thus, the habitat models can be used to improve the efficiency of plant protection efforts, (e.g., marking of plants, law enforcement activities). The field searches also

Toward Dynamic Ocean Management: Fisheries assessment and climate projections informed by community developed habitat models based on dynamic coastal oceanography

NASA Astrophysics Data System (ADS)

Kohut, J. T.; Manderson, J.; Palamara, L. J.; Saba, V. S.; Saba, G.; Hare, J. A.; Curchitser, E. N.; Moore, P.; Seibel, B.; DiDomenico, G.

2016-12-01

Through a multidisciplinary study group of experts in marine ecology, physical oceanography and stock assessment from the fishing industry, government and academia we developed a method to explicitly account for shifting habitat distributions in fish population assessments. We used data from field surveys throughout the Northwest Atlantic Ocean to develop a parametric thermal niche model for an important short-lived pelagic forage fish, Atlantic Butterfish. This niche model was coupled to a hindcast of daily bottom water temperature derived from a regional numerical ocean model in order to project daily thermal habitat suitability over the last 40 years. This ecological hindcast was used to estimate the proportion of thermal habitat suitability available on the U.S. Northeast Shelf that was sampled on fishery-independent surveys, accounting for the relative motions of thermal habitat and the trajectory of sampling on the survey. The method and habitat based estimates of availability was integrated into the catchability estimate used to scale population size in the butterfish stock assessment model accepted by the reviewers of the 59th NEFSC stock assessment review, as well as the mid-Atlantic Council's Scientific and Statistical Committee. The contribution of the availability estimate (along with an estimate of detectability) allowed for the development of fishery reference points, a change in stock status from unknown to known, and the establishment of a directed fishery with an allocation of 20,000 metric tons of quota. This presentation will describe how a community based workgroup utilized ocean observing technologies combined with ocean models to better understand the physical ocean that structures marine ecosystems. Using these approaches we will discuss opportunities to inform ecological hindcasts and climate projections with mechanistic models that link species-specific physiology to climate-based thermal scenarios.

Toward Dynamic Ocean Management: Fisheries assessment and climate projections informed by community developed habitat models based on dynamic coastal oceanography

NASA Astrophysics Data System (ADS)

Kohut, J. T.; Manderson, J.; Palamara, L. J.; Saba, V. S.; Saba, G.; Hare, J. A.; Curchitser, E. N.; Moore, P.; Seibel, B.; DiDomenico, G.

2016-02-01

Through a multidisciplinary study group of experts in marine ecology, physical oceanography and stock assessment from the fishing industry, government and academia we developed a method to explicitly account for shifting habitat distributions in fish population assessments. We used data from field surveys throughout the Northwest Atlantic Ocean to develop a parametric thermal niche model for an important short-lived pelagic forage fish, Atlantic Butterfish. This niche model was coupled to a hindcast of daily bottom water temperature derived from a regional numerical ocean model in order to project daily thermal habitat suitability over the last 40 years. This ecological hindcast was used to estimate the proportion of thermal habitat suitability available on the U.S. Northeast Shelf that was sampled on fishery-independent surveys, accounting for the relative motions of thermal habitat and the trajectory of sampling on the survey. The method and habitat based estimates of availability was integrated into the catchability estimate used to scale population size in the butterfish stock assessment model accepted by the reviewers of the 59th NEFSC stock assessment review, as well as the mid-Atlantic Council's Scientific and Statistical Committee. The contribution of the availability estimate (along with an estimate of detectability) allowed for the development of fishery reference points, a change in stock status from unknown to known, and the establishment of a directed fishery with an allocation of 20,000 metric tons of quota. This presentation will describe how a community based workgroup utilized ocean observing technologies combined with ocean models to better understand the physical ocean that structures marine ecosystems. Using these approaches we will discuss opportunities to inform ecological hindcasts and climate projections with mechanistic models that link species-specific physiology to climate-based thermal scenarios.

Sex-specific habitat suitability models for Panthera tigris in Chitwan National Park, Nepal

NASA Astrophysics Data System (ADS)

Battle, Curtis Scott

Although research on wildlife species across taxa has shown that males and females differentially select habitat, sex-specific models of habitat suitability for endangered species are uncommon. Here, we developed such models for Bengal Tigers (Panthera tigris) based on camera trap data collected from 20 January to 22 March, 2010, within Chitwan National Park, Nepal, and its buffer zone. We compared these to a sex-indiscriminate habitat suitability model in order to identify information that is lost when occurrence data for both sexes are included in the same model, as well as to assess the benefits of a sex-specific approach to habitat suitability modelling. Our sex-specific models allowed us to produce more informative and detailed habitat suitability maps, highlighting key differences in the distribution of suitable habitats for males and females, preferences in vegetation structure, and habitat use near human settlements. In the context of global tiger conservation, such information is essential to fulfilling established conservation goals and population recovery targets.

Assessing the Wildlife Habitat Value of New England Salt Marshes: I. Model and Application

EPA Science Inventory

We developed an assessment model to quantify the wildlife habitat value of New England salt marshes based on marsh characteristics and the presence of habitat types that influence habitat use by terrestrial wildlife. Applying the model to12 salt marshes located in Narragansett B...

A Bayesian spawning habitat suitability model for American shad in southeastern United States rivers

USGS Publications Warehouse

Hightower, Joseph E.; Harris, Julianne E.; Raabe, Joshua K.; Brownell, Prescott; Drew, C. Ashton

2012-01-01

Habitat suitability index models for American shad Alosa sapidissima were developed by Stier and Crance in 1985. These models, which were based on a combination of published information and expert opinion, are often used to make decisions about hydropower dam operations and fish passage. The purpose of this study was to develop updated habitat suitability index models for spawning American shad in the southeastern United States, building on the many field and laboratory studies completed since 1985. We surveyed biologists who had knowledge about American shad spawning grounds, assembled a panel of experts to discuss important habitat variables, and used raw data from published and unpublished studies to develop new habitat suitability curves. The updated curves are based on resource selection functions, which can model habitat selectivity based on use and availability of particular habitats. Using field data collected in eight rivers from Virginia to Florida (Mattaponi, Pamunkey, Roanoke, Tar, Neuse, Cape Fear, Pee Dee, St. Johns), we obtained new curves for temperature, current velocity, and depth that were generally similar to the original models. Our new suitability function for substrate was also similar to the original pattern, except that sand (optimal in the original model) has a very low estimated suitability. The Bayesian approach that we used to develop habitat suitability curves provides an objective framework for updating the model as new studies are completed and for testing the model's applicability in other parts of the species' range.

Annual variation in habitat-specific recruitment success: Implications from an individual-based model of Lake Michigan alewife (Alosa pseudoharengus)

USGS Publications Warehouse

Hook, T.O.; Rutherford, E.S.; Croley, T.E.; Mason, D.M.; Madenjian, C.P.

2008-01-01

The identification of important spawning and nursery habitats for fish stocks can aid fisheries management, but is complicated by various factors, including annual variation in recruitment success. The alewife (Alosa pseudoharengus) is an ecologically important species in Lake Michigan that utilizes a variety of habitats for spawning and early life growth. While productive, warm tributary mouths (connected to Lake Michigan) may contribute disproportionately more recruits (relative to their habitat volume) to the adult alewife population than cooler, less productive nearshore habitats, the extent of interannual variation in the relative contributions of recruits from these two habitat types remains unknown. We used an individual-based bioenergetics simulation model and input data on daily temperatures to estimate alewife recruitment to the adult population by these different habitat types. Simulations suggest that nearshore lake habitats typically produce the vast majority of young alewife recruits. However, tributary habitats may contribute the majority of alewife recruits during years of low recruitment. We suggest that high interannual variation in the relative importance of habitats for recruitment is a common phenomenon, which should be considered when developing habitat management plans for fish populations. ?? 2008 NRC.

Matrix population models as a tool in development of habitat models

Treesearch

Gregory D. Hayward; David B. McDonald

1997-01-01

Building sophisticated habitat models for conservation of owls must stem from an understanding of the relative quality of habitats at a variety of geographic and temporal scales. Developing these models requires knowing the relationship between habitat conditions and owl performance. What measure should be used to compare the quality of habitats? Matrix population...

NORTHWOODS Wildlife Habitat Data Base

Treesearch

Mark D. Nelson; Janine M. Benyus; Richard R. Buech

1992-01-01

Wildlife habitat data from seven Great Lakes National Forests were combined into a wildlife-habitat matrix named NORTHWOODS. Several electronic file formats of NORTHWOODS data base and documentation are available on floppy disks for microcomputers.

Persistence in a Two-Dimensional Moving-Habitat Model.

PubMed

Phillips, Austin; Kot, Mark

2015-11-01

Environmental changes are forcing many species to track suitable conditions or face extinction. In this study, we use a two-dimensional integrodifference equation to analyze whether a population can track a habitat that is moving due to climate change. We model habitat as a simple rectangle. Our model quickly leads to an eigenvalue problem that determines whether the population persists or declines. After surveying techniques to solve the eigenvalue problem, we highlight three findings that impact conservation efforts such as reserve design and species risk assessment. First, while other models focus on habitat length (parallel to the direction of habitat movement), we show that ignoring habitat width (perpendicular to habitat movement) can lead to overestimates of persistence. Dispersal barriers and hostile landscapes that constrain habitat width greatly decrease the population's ability to track its habitat. Second, for some long-distance dispersal kernels, increasing habitat length improves persistence without limit; for other kernels, increasing length is of limited help and has diminishing returns. Third, it is not always best to orient the long side of the habitat in the direction of climate change. Evidence suggests that the kurtosis of the dispersal kernel determines whether it is best to have a long, wide, or square habitat. In particular, populations with platykurtic dispersal benefit more from a wide habitat, while those with leptokurtic dispersal benefit more from a long habitat. We apply our model to the Rocky Mountain Apollo butterfly (Parnassius smintheus).

Deep Space Habitat Configurations Based On International Space Station Systems

NASA Technical Reports Server (NTRS)

Smitherman, David; Russell, Tiffany; Baysinger, Mike; Capizzo, Pete; Fabisinski, Leo; Griffin, Brand; Hornsby, Linda; Maples,Dauphne; Miernik, Janie

2012-01-01

A Deep Space Habitat (DSH) is the crew habitation module designed for long duration missions. Although humans have lived in space for many years, there has never been a habitat beyond low-Earth-orbit. As part of the Advanced Exploration Systems (AES) Habitation Project, a study was conducted to develop weightless habitat configurations using systems based on International Space Station (ISS) designs. Two mission sizes are described for a 4-crew 60-day mission, and a 4-crew 500-day mission using standard Node, Lab, and Multi-Purpose Logistics Module (MPLM) sized elements, and ISS derived habitation systems. These durations were selected to explore the lower and upper bound for the exploration missions under consideration including a range of excursions within the Earth-Moon vicinity, near earth asteroids, and Mars orbit. Current methods for sizing the mass and volume for habitats are based on mathematical models that assume the construction of a new single volume habitat. In contrast to that approach, this study explored the use of ISS designs based on existing hardware where available and construction of new hardware based on ISS designs where appropriate. Findings included a very robust design that could be reused if the DSH were assembled and based at the ISS and a transportation system were provided for its return after each mission. Mass estimates were found to be higher than mathematical models due primarily to the use of multiple ISS modules instead of one new large module, but the maturity of the designs using flight qualified systems have potential for improved cost, schedule, and risk benefits.

Deep Space Habitat Configurations Based on International Space Station Systems

NASA Technical Reports Server (NTRS)

Smitherman, David; Russell, Tiffany; Baysinger, Mike; Capizzo, Pete; Fabisinski, Leo; Griffin, Brand; Hornsby, Linda; Maples, Dauphne; Miernik, Janie

2012-01-01

A Deep Space Habitat (DSH) is the crew habitation module designed for long duration missions. Although humans have lived in space for many years, there has never been a habitat beyond low-Earth-orbit. As part of the Advanced Exploration Systems (AES) Habitation Project, a study was conducted to develop weightless habitat configurations using systems based on International Space Station (ISS) designs. Two mission sizes are described for a 4-crew 60-day mission, and a 4-crew 500-day mission using standard Node, Lab, and Multi-Purpose Logistics Module (MPLM) sized elements, and ISS derived habitation systems. These durations were selected to explore the lower and upper bound for the exploration missions under consideration including a range of excursions within the Earth-Moon vicinity, near earth asteroids, and Mars orbit. Current methods for sizing the mass and volume for habitats are based on mathematical models that assume the construction of a new single volume habitat. In contrast to that approach, this study explored the use of ISS designs based on existing hardware where available and construction of new hardware based on ISS designs where appropriate. Findings included a very robust design that could be reused if the DSH were assembled and based at the ISS and a transportation system were provided for its return after each mission. Mass estimates were found to be higher than mathematical models due primarily to the use of multiple ISS modules instead of one new large module, but the maturity of the designs using flight qualified systems have potential for improved cost, schedule, and risk benefits.

Multivariate model of female black bear habitat use for a Geographic Information System

USGS Publications Warehouse

Clark, Joseph D.; Dunn, James E.; Smith, Kimberly G.

1993-01-01

Simple univariate statistical techniques may not adequately assess the multidimensional nature of habitats used by wildlife. Thus, we developed a multivariate method to model habitat-use potential using a set of female black bear (Ursus americanus) radio locations and habitat data consisting of forest cover type, elevation, slope, aspect, distance to roads, distance to streams, and forest cover type diversity score in the Ozark Mountains of Arkansas. The model is based on the Mahalanobis distance statistic coupled with Geographic Information System (GIS) technology. That statistic is a measure of dissimilarity and represents a standardized squared distance between a set of sample variates and an ideal based on the mean of variates associated with animal observations. Calculations were made with the GIS to produce a map containing Mahalanobis distance values within each cell on a 60- × 60-m grid. The model identified areas of high habitat use potential that could not otherwise be identified by independent perusal of any single map layer. This technique avoids many pitfalls that commonly affect typical multivariate analyses of habitat use and is a useful tool for habitat manipulation or mitigation to favor terrestrial vertebrates that use habitats on a landscape scale.

HABITAT MODELING APPROACHES FOR RESTORATION SITE SELECTION

EPA Science Inventory

Numerous modeling approaches have been used to develop predictive models of species-environment and species-habitat relationships. These models have been used in conservation biology and habitat or species management, but their application to restoration efforts has been minimal...

A GIS modeling method applied to predicting forest songbird habitat

USGS Publications Warehouse

Dettmers, Randy; Bart, Jonathan

1999-01-01

We have developed an approach for using a??presencea?? data to construct habitat models. Presence data are those that indicate locations where the target organism is observed to occur, but that cannot be used to define locations where the organism does not occur. Surveys of highly mobile vertebrates often yield these kinds of data. Models developed through our approach yield predictions of the amount and the spatial distribution of good-quality habitat for the target species. This approach was developed primarily for use in a GIS context; thus, the models are spatially explicit and have the potential to be applied over large areas. Our method consists of two primary steps. In the first step, we identify an optimal range of values for each habitat variable to be used as a predictor in the model. To find these ranges, we employ the concept of maximizing the difference between cumulative distribution functions of (1) the values of a habitat variable at the observed presence locations of the target organism, and (2) the values of that habitat variable for all locations across a study area. In the second step, multivariate models of good habitat are constructed by combining these ranges of values, using the Boolean operators a??anda?? and a??or.a?? We use an approach similar to forward stepwise regression to select the best overall model. We demonstrate the use of this method by developing species-specific habitat models for nine forest-breeding songbirds (e.g., Cerulean Warbler, Scarlet Tanager, Wood Thrush) studied in southern Ohio. These models are based on speciesa?? microhabitat preferences for moisture and vegetation characteristics that can be predicted primarily through the use of abiotic variables. We use slope, land surface morphology, land surface curvature, water flow accumulation downhill, and an integrated moisture index, in conjunction with a land-cover classification that identifies forest/nonforest, to develop these models. The performance of these

Optimising Habitat-Based Models for Wide-Ranging Marine Predators: Scale Matters

NASA Astrophysics Data System (ADS)

Scales, K. L.; Hazen, E. L.; Jacox, M.; Edwards, C. A.; Bograd, S. J.

2016-12-01

Predicting the responses of marine top predators to dynamic oceanographic conditions requires habitat-based models that sufficiently capture environmental preferences. Spatial resolution and temporal averaging of environmental data layers is a key aspect of model construction. The utility of surfaces contemporaneous to animal movement (e.g. daily, weekly), versus synoptic products (monthly, seasonal, climatological) is currently under debate, as is the optimal spatial resolution for predictive products. Using movement simulations with built-in environmental preferences (correlated random walks, multi-state hidden Markov-type models) together with modeled (Regional Oceanographic Modeling System, ROMS) and remotely-sensed (MODIS-Aqua) datasets, we explored the effects of degrading environmental surfaces (3km - 1 degree, daily - climatological) on model inference. We simulated the movements of a hypothetical wide-ranging marine predator through the California Current system over a three month period (May-June-July), based on metrics derived from previously published blue whale Balaenoptera musculus tracking studies. Results indicate that models using seasonal or climatological data fields can overfit true environmental preferences, in both presence-absence and behaviour-based model formulations. Moreover, the effects of a degradation in spatial resolution are more pronounced when using temporally averaged fields than when using daily, weekly or monthly datasets. In addition, we observed a notable divergence between the `best' models selected using common methods (e.g. AUC, AICc) and those that most accurately reproduced built-in environmental preferences. These findings have important implications for conservation and management of marine mammals, seabirds, sharks, sea turtles and large teleost fish, particularly in implementing dynamic ocean management initiatives and in forecasting responses to future climate-mediated ecosystem change.

Optimising Habitat-Based Models for Wide-Ranging Marine Predators: Scale Matters

NASA Astrophysics Data System (ADS)

Scales, K. L.; Hazen, E. L.; Jacox, M.; Edwards, C. A.; Bograd, S. J.

2016-02-01

Predicting the responses of marine top predators to dynamic oceanographic conditions requires habitat-based models that sufficiently capture environmental preferences. Spatial resolution and temporal averaging of environmental data layers is a key aspect of model construction. The utility of surfaces contemporaneous to animal movement (e.g. daily, weekly), versus synoptic products (monthly, seasonal, climatological) is currently under debate, as is the optimal spatial resolution for predictive products. Using movement simulations with built-in environmental preferences (correlated random walks, multi-state hidden Markov-type models) together with modeled (Regional Oceanographic Modeling System, ROMS) and remotely-sensed (MODIS-Aqua) datasets, we explored the effects of degrading environmental surfaces (3km - 1 degree, daily - climatological) on model inference. We simulated the movements of a hypothetical wide-ranging marine predator through the California Current system over a three month period (May-June-July), based on metrics derived from previously published blue whale Balaenoptera musculus tracking studies. Results indicate that models using seasonal or climatological data fields can overfit true environmental preferences, in both presence-absence and behaviour-based model formulations. Moreover, the effects of a degradation in spatial resolution are more pronounced when using temporally averaged fields than when using daily, weekly or monthly datasets. In addition, we observed a notable divergence between the `best' models selected using common methods (e.g. AUC, AICc) and those that most accurately reproduced built-in environmental preferences. These findings have important implications for conservation and management of marine mammals, seabirds, sharks, sea turtles and large teleost fish, particularly in implementing dynamic ocean management initiatives and in forecasting responses to future climate-mediated ecosystem change.

Habitat Suitability Index Models: Diamondback terrapin (nesting) - Atlantic coast

USGS Publications Warehouse

Palmer, William M.; Cordes, Carroll L.

1988-01-01

A review and synthesis of existing information were used to develop a Habitat Suitability Index (HSI) model for the diamondback terrapin (Malaclemys terrapin). The model consolidates habitat use information into a framework appropriate for field application, and is scaled to produce an index between 0.0 (unsuitable habitat) to 1.0 (optimum habitat). HSI models are designed to be used with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

Evaluating the habitat capability model for Merriam's turkeys

Treesearch

Mark A. Rumble; Stanley H. Anderson

1995-01-01

Habitat capability (HABCAP) models for wildlife assist land managers in predicting the consequences of their management decisions. Models must be tested and refined prior to using them in management planning. We tested the predicted patterns of habitat selection of the R2 HABCAP model using observed patterns of habitats selected by radio-marked Merriam’s turkey (

A habitat suitability model for Chinese sturgeon determined using the generalized additive method

NASA Astrophysics Data System (ADS)

Yi, Yujun; Sun, Jie; Zhang, Shanghong

2016-03-01

The Chinese sturgeon is a type of large anadromous fish that migrates between the ocean and rivers. Because of the construction of dams, this sturgeon's migration path has been cut off, and this species currently is on the verge of extinction. Simulating suitable environmental conditions for spawning followed by repairing or rebuilding its spawning grounds are effective ways to protect this species. Various habitat suitability models based on expert knowledge have been used to evaluate the suitability of spawning habitat. In this study, a two-dimensional hydraulic simulation is used to inform a habitat suitability model based on the generalized additive method (GAM). The GAM is based on real data. The values of water depth and velocity are calculated first via the hydrodynamic model and later applied in the GAM. The final habitat suitability model is validated using the catch per unit effort (CPUEd) data of 1999 and 2003. The model results show that a velocity of 1.06-1.56 m/s and a depth of 13.33-20.33 m are highly suitable ranges for the Chinese sturgeon to spawn. The hydraulic habitat suitability indexes (HHSI) for seven discharges (4000; 9000; 12,000; 16,000; 20,000; 30,000; and 40,000 m3/s) are calculated to evaluate integrated habitat suitability. The results show that the integrated habitat suitability reaches its highest value at a discharge of 16,000 m3/s. This study is the first to apply a GAM to evaluate the suitability of spawning grounds for the Chinese sturgeon. The study provides a reference for the identification of potential spawning grounds in the entire basin.

Habitat-based constraints on food web structure and parasite life cycles.

PubMed

Rossiter, Wayne; Sukhdeo, Michael V K

2014-04-01

Habitat is frequently implicated as a powerful determinant of community structure and species distributions, but few studies explicitly evaluate the relationship between habitat-based patterns of species' distributions and the presence or absence of trophic interactions. The complex (multi-host) life cycles of parasites are directly affected by these factors, but almost no data exist on the role of habitat in constraining parasite-host interactions at the community level. In this study the relationship(s) between species abundances, distributions and trophic interactions (including parasitism) were evaluated in the context of habitat structure (classic geomorphic designations of pools, riffles and runs) in a riverine community (Raritan River, Hunterdon County, NJ, USA). We report 121 taxa collected over a 2-year period, and compare the observed food web patterns to null model expectations. The results show that top predators are constrained to particular habitat types, and that species' distributions are biased towards pool habitats. However, our null model (which incorporates cascade model assumptions) accurately predicts the observed patterns of trophic interactions. Thus, habitat strongly dictates species distributions, and patterns of trophic interactions arise as a consequence of these distributions. Additionally, we find that hosts utilized in parasite life cycles are more overlapping in their distributions, and this pattern is more pronounced among those involved in trophic transmission. We conclude that habitat structure may be a strong predictor of parasite transmission routes, particularly within communities that occupy heterogeneous habitats.

Development and validation of a habitat suitability model for ...

EPA Pesticide Factsheets

We developed a spatially-explicit, flexible 3-parameter habitat suitability model that can be used to identify and predict areas at higher risk for non-native dwarf eelgrass (Zostera japonica) invasion. The model uses simple environmental parameters (depth, nearshore slope, and salinity) to quantitatively describe habitat suitable for Z. japonica invasion based on ecology and physiology from the primary literature. Habitat suitability is defined with values ranging from zero to one, where one denotes areas most conducive to Z. japonica and zero denotes areas not likely to support Z. japonica growth. The model was applied to Yaquina Bay, Oregon, USA, an area that has well documented Z. japonica expansion over the last two decades. The highest suitability values for Z. japonica occurred in the mid to upper portions of the intertidal zone, with larger expanses occurring in the lower estuary. While the upper estuary did contain suitable habitat, most areas were not as large as in the lower estuary, due to inappropriate depth, a steeply sloping intertidal zone, and lower salinity. The lowest suitability values occurred below the lower intertidal zone, within the Yaquina River channel. The model was validated by comparison to a multi-year time series of Z. japonica maps, revealing a strong predictive capacity. Sensitivity analysis performed to evaluate the contribution of each parameter to the model prediction revealed that depth was the most important factor. Sh

Tests of a habitat suitability model for black-capped chickadees

USGS Publications Warehouse

Schroeder, Richard L.

1990-01-01

The black-capped chickadee (Parus atricapillus) Habitat Suitability Index (HSI) model provides a quantitative rating of the capability of a habitat to support breeding, based on measures related to food and nest site availability. The model assumption that tree canopy volume can be predicted from measures of tree height and canopy closure was tested using data from foliage volume studies conducted in the riparian cottonwood habitat along the South Platte River in Colorado. Least absolute deviations (LAD) regression showed that canopy cover and over story tree height yielded volume predictions significantly lower than volume estimated by more direct methods. Revisions to these model relations resulted in improved predictions of foliage volume. The relation between the HSI and estimates of black-capped chickadee population densities was examined using LAD regression for both the original model and the model with the foliage volume revisions. Residuals from these models were compared to residuals from both a zero slope model and an ideal model. The fit model for the original HSI differed significantly from the ideal model, whereas the fit model for the original HSI did not differ significantly from the ideal model. However, both the fit model for the original HSI and the fit model for the revised HSI did not differ significantly from a model with a zero slope. Although further testing of the revised model is needed, its use is recommended for more realistic estimates of tree canopy volume and habitat suitability.

Factors influencing behavior and transferability of habitat models for a benthic stream fish

Treesearch

Kevin N. Leftwich; Paul L. Angermeier; C. Andrew Dolloff

1997-01-01

The authors examined the predictive power and transferability of habitat-based models by comparing associations of tangerine darter Percina aurantiaca and stream habitat at local and regional scales in North Fork Holston River (NFHR) and Little River, VA. The models correctly predicted the presence or absence of tangerine darters in NFHR for 64 percent (local model)...

A multiscaled model of southwestern willow flycatcher breeding habitat

USGS Publications Warehouse

Hatten, J.R.; Paradzick, C.E.

2003-01-01

The southwestern willow flycatcher (SWFL; Empidonax traillii extimus) is an endangered songbird whose habitat has declined dramatically over the last century. Understanding habitat selection patterns and the ability to identify potential breeding areas for the SWFL is crucial to the management and conservation of this species. We developed a multiscaled model of SWTL breeding habitat with a Geographic Information System (GIS), survey data, GIS variables, and multiple logistic regressions. We obtained presence and absence survey data from a riverine ecosystem and a reservoir delta in south-central Arizona, USA, in 1999. We extracted the GIS variables from satellite imagery and digital elevation models to characterize vegetation and floodplain within the project area. We used multiple logistic regressions within a cell-based (30 X 30 m) modeling environment to (1) determine associations between GIS variables and breeding-site occurrence at different spatial scales (0.09-72 ha), and (2) construct a predictive model. Our best model explained 54% of the variability in breeding-site occurrence with the following variables: vegetation density at the site (0.09 ha), proportion of dense vegetation and variability in vegetation density within a 4.5-ha neighborhood, and amount of floodplain or flat terrain within a 41-ha neighborhood. The density of breeding sites was highest in areas that the model predicted to be most suitable within the project area and at an external test site 200 km away. Conservation efforts must focus on protecting not only occupied patches, but also surrounding riparian forests and floodplain to ensure long-term viability of SWTL. We will use the multiscaled model to map SWTL breeding habitat in Arizona, prioritize future survey effort, and examine changes in habitat abundance and quality over time.

Linking occurrence and fitness to persistence: Habitat-based approach for endangered Greater Sage-Grouse

USGS Publications Warehouse

Aldridge, Cameron L.; Boyce, Mark S.

2007-01-01

approach to habitat-based population viability modeling has merit for many species of concern. ?? 2007 by the Ecological Society of America.

Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico

NASA Astrophysics Data System (ADS)

Roberts, Jason J.; Best, Benjamin D.; Mannocci, Laura; Fujioka, Ei; Halpin, Patrick N.; Palka, Debra L.; Garrison, Lance P.; Mullin, Keith D.; Cole, Timothy V. N.; Khan, Christin B.; McLellan, William A.; Pabst, D. Ann; Lockhart, Gwen G.

2016-03-01

Cetaceans are protected worldwide but vulnerable to incidental harm from an expanding array of human activities at sea. Managing potential hazards to these highly-mobile populations increasingly requires a detailed understanding of their seasonal distributions and habitats. Pursuant to the urgent need for this knowledge for the U.S. Atlantic and Gulf of Mexico, we integrated 23 years of aerial and shipboard cetacean surveys, linked them to environmental covariates obtained from remote sensing and ocean models, and built habitat-based density models for 26 species and 3 multi-species guilds using distance sampling methodology. In the Atlantic, for 11 well-known species, model predictions resembled seasonal movement patterns previously suggested in the literature. For these we produced monthly mean density maps. For lesser-known taxa, and in the Gulf of Mexico, where seasonal movements were less well described, we produced year-round mean density maps. The results revealed high regional differences in small delphinoid densities, confirmed the importance of the continental slope to large delphinoids and of canyons and seamounts to beaked and sperm whales, and quantified seasonal shifts in the densities of migratory baleen whales. The density maps, freely available online, are the first for these regions to be published in the peer-reviewed literature.

Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico

PubMed Central

Roberts, Jason J.; Best, Benjamin D.; Mannocci, Laura; Fujioka, Ei; Halpin, Patrick N.; Palka, Debra L.; Garrison, Lance P.; Mullin, Keith D.; Cole, Timothy V. N.; Khan, Christin B.; McLellan, William A.; Pabst, D. Ann; Lockhart, Gwen G.

2016-01-01

Cetaceans are protected worldwide but vulnerable to incidental harm from an expanding array of human activities at sea. Managing potential hazards to these highly-mobile populations increasingly requires a detailed understanding of their seasonal distributions and habitats. Pursuant to the urgent need for this knowledge for the U.S. Atlantic and Gulf of Mexico, we integrated 23 years of aerial and shipboard cetacean surveys, linked them to environmental covariates obtained from remote sensing and ocean models, and built habitat-based density models for 26 species and 3 multi-species guilds using distance sampling methodology. In the Atlantic, for 11 well-known species, model predictions resembled seasonal movement patterns previously suggested in the literature. For these we produced monthly mean density maps. For lesser-known taxa, and in the Gulf of Mexico, where seasonal movements were less well described, we produced year-round mean density maps. The results revealed high regional differences in small delphinoid densities, confirmed the importance of the continental slope to large delphinoids and of canyons and seamounts to beaked and sperm whales, and quantified seasonal shifts in the densities of migratory baleen whales. The density maps, freely available online, are the first for these regions to be published in the peer-reviewed literature. PMID:26936335

Fine-scale habitat modeling of a top marine predator: do prey data improve predictive capacity?

PubMed

Torres, Leigh G; Read, Andrew J; Halpin, Patrick

2008-10-01

Predators and prey assort themselves relative to each other, the availability of resources and refuges, and the temporal and spatial scale of their interaction. Predictive models of predator distributions often rely on these relationships by incorporating data on environmental variability and prey availability to determine predator habitat selection patterns. This approach to predictive modeling holds true in marine systems where observations of predators are logistically difficult, emphasizing the need for accurate models. In this paper, we ask whether including prey distribution data in fine-scale predictive models of bottlenose dolphin (Tursiops truncatus) habitat selection in Florida Bay, Florida, U.S.A., improves predictive capacity. Environmental characteristics are often used as predictor variables in habitat models of top marine predators with the assumption that they act as proxies of prey distribution. We examine the validity of this assumption by comparing the response of dolphin distribution and fish catch rates to the same environmental variables. Next, the predictive capacities of four models, with and without prey distribution data, are tested to determine whether dolphin habitat selection can be predicted without recourse to describing the distribution of their prey. The final analysis determines the accuracy of predictive maps of dolphin distribution produced by modeling areas of high fish catch based on significant environmental characteristics. We use spatial analysis and independent data sets to train and test the models. Our results indicate that, due to high habitat heterogeneity and the spatial variability of prey patches, fine-scale models of dolphin habitat selection in coastal habitats will be more successful if environmental variables are used as predictor variables of predator distributions rather than relying on prey data as explanatory variables. However, predictive modeling of prey distribution as the response variable based on

Modeling the impact of hydromorphological alterations by dams and channelization on fish habitat.

NASA Astrophysics Data System (ADS)

Parasiewicz, Piotr; Suska, Katarzyna

2017-04-01

As a consequence of introduction of Water Framework Directive it has been discovered that hydromorphological pressures are one of the main causes of impact on aquatic fauna. However, the impact may vary depending on river type and fish community. To test this hypothesis, we modelled alterations of fish habitat on 6 river sections across Poland using MesoHABSIM approach. The original models of habitat for Target Fish Community were based on repeated field surveys in reference river sections, classified into four fish-ecological classes. Introducing to the models three hydromorphological modification types (damming, channelization and dredging) changed persistent habitat availability for the fish community. The change was measured with Habitat Stress Days Alteration index. Overall the modifications caused increase of habitat stress days, but impact varied depending on season, hydromorphologic river type and expected fish community.

Mapping Thermal Habitat of Ectotherms Based on Behavioral Thermoregulation in a Controlled Thermal Environment

NASA Astrophysics Data System (ADS)

Fei, T.; Skidmore, A.; Liu, Y.

2012-07-01

Thermal environment is especially important to ectotherm because a lot of physiological functions rely on the body temperature such as thermoregulation. The so-called behavioural thermoregulation function made use of the heterogeneity of the thermal properties within an individual's habitat to sustain the animal's physiological processes. This function links the spatial utilization and distribution of individual ectotherm with the thermal properties of habitat (thermal habitat). In this study we modelled the relationship between the two by a spatial explicit model that simulates the movements of a lizard in a controlled environment. The model incorporates a lizard's transient body temperatures with a cellular automaton algorithm as a way to link the physiology knowledge of the animal with the spatial utilization of its microhabitat. On a larger spatial scale, 'thermal roughness' of the habitat was defined and used to predict the habitat occupancy of the target species. The results showed the habitat occupancy can be modelled by the cellular automaton based algorithm at a smaller scale, and can be modelled by the thermal roughness index at a larger scale.

Habitat associated with Barred Owl (Strix varia) locations in southeastern Manitoba: a review of a habitat model

Treesearch

James R. Duncan; Amy E. Kearns

1997-01-01

A Habitat Suitability Index (HSI) model was developed for the Barred Owl (Strix varia) in southeastern Manitoba. An initial validation of the model was performed within three sizes of circular plots (314, 1,256, and 2,827 ha) centered on 28 Barred Owl locations. The model was able to predict suitable habitat at the 314 ha scale. Forest habitat...

A test of the habitat suitability model for Merriam's wild turkeys

Treesearch

Mark A. Rumble; Stanley H. Anderson

1996-01-01

An important research area regarding the wild turkey (Meleagris gallopavo) is development of sound habitat models. Habitat models provide standardized methods to quantify wild turkey habitat and stimulate new research hypotheses. Habitat suitability index (HSI) models show species-habitat relationships on a scale of O-l, with 1 being optimum. A...

Landscape habitat suitability index software

Treesearch

William D. Dijak; Chadwick D. Rittenhouse; Michael A. Larson; Frank R. III Thompson; Joshua J. Millspaugh

2007-01-01

Habitat suitability index (HSI) models are traditionally used to evaluate habitat quality for wildlife at a local scale. Rarely have such models incorporated spatial relationships of habitat components. We introduce Landscape HSImodels, a new Microsoft Windowst (Microsoft, Redmond, WA)-based program that incorporates local habitat as well as landscape-scale attributes...

Two-dimensional habitat modeling in the Yellowstone/Upper Missouri River system

USGS Publications Warehouse

Waddle, T. J.; Bovee, K.D.; Bowen, Z.H.

1997-01-01

This study is being conducted to provide the aquatic biology component of a decision support system being developed by the U.S. Bureau of Reclamation. In an attempt to capture the habitat needs of Great Plains fish communities we are looking beyond previous habitat modeling methods. Traditional habitat modeling approaches have relied on one-dimensional hydraulic models and lumped compositional habitat metrics to describe aquatic habitat. A broader range of habitat descriptors is available when both composition and configuration of habitats is considered. Habitat metrics that consider both composition and configuration can be adapted from terrestrial biology. These metrics are most conveniently accessed with spatially explicit descriptors of the physical variables driving habitat composition. Two-dimensional hydrodynamic models have advanced to the point that they may provide the spatially explicit description of physical parameters needed to address this problem. This paper reports progress to date on applying two-dimensional hydraulic and habitat models on the Yellowstone and Missouri Rivers and uses examples from the Yellowstone River to illustrate the configurational metrics as a new tool for assessing riverine habitats.

Sensitivity of wildlife habitat models to uncertainties in GIS data

NASA Technical Reports Server (NTRS)

Stoms, David M.; Davis, Frank W.; Cogan, Christopher B.

1992-01-01

Decision makers need to know the reliability of output products from GIS analysis. For many GIS applications, it is not possible to compare these products to an independent measure of 'truth'. Sensitivity analysis offers an alternative means of estimating reliability. In this paper, we present a CIS-based statistical procedure for estimating the sensitivity of wildlife habitat models to uncertainties in input data and model assumptions. The approach is demonstrated in an analysis of habitat associations derived from a GIS database for the endangered California condor. Alternative data sets were generated to compare results over a reasonable range of assumptions about several sources of uncertainty. Sensitivity analysis indicated that condor habitat associations are relatively robust, and the results have increased our confidence in our initial findings. Uncertainties and methods described in the paper have general relevance for many GIS applications.

Anthropogenic habitat disturbance and the dynamics of hantavirus using remote sensing, GIS, and a spatially explicit agent-based model

NASA Astrophysics Data System (ADS)

Cao, Lina

Sin Nombre virus (SNV), a strain of hantavirus, causes hantavirus pulmonary syndrome (HPS) in humans, a deadly disease with high mortality rate (>50%). The primary virus host is deer mice, and greater deer mice abundance has been shown to increase the human risk of HPS. There is a great need in understanding the nature of the virus host, its temporal and spatial dynamics, and its relation to the human population with the purpose of predicting human risk of the disease. This research studies SNV dynamics in deer mice in the Great Basin Desert of central Utah, USA using multiyear field data and integrated geospatial approaches including remote sensing, Geographic Information System (GIS), and a spatially explicit agent-based model. The goal is to advance our understanding of the important ecological and demographic factors that affect the dynamics of deer mouse population and SNV prevalence. The primary research question is how climate, habitat disturbance, and deer mouse demographics affect deer mouse population density, its movement, and SNV prevalence in the sagebrush habitat. The results show that the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) can be good predictors of deer mouse density and the number of infected deer mice with a time lag of 1.0 to 1.3 years. This information can be very useful in predicting mouse abundance and SNV risk. The results also showed that climate, mouse density, sex, mass, and SNV infection had significant effects on deer mouse movement. The effect of habitat disturbance on mouse movement varies according to climate conditions with positive relationship in predrought condition and negative association in postdrought condition. The heavier infected deer mice moved the most. Season and disturbance alone had no significant effects. The spatial agent-based model (SABM) simulation results show that prevalence was negatively related to the disturbance levels and the sensitivity analysis showed that

Effects of spatial extent on modeled relations between habitat and anadromous salmonid spawning success

Treesearch

Steven F. Railsback; Bret C. Harvey; Jason L. White

2015-01-01

We address the question of spatial extent: how model results depend on the amount and type of space represented. For models of how stream habitat affects fish populations, how do the amount and characteristics of habitat represented in the model affect its results and how well do those results represent the whole stream? Our analysis used inSalmo, an individual-based...

Tests of wildlife habitat models to evaluate oak-mast production

USGS Publications Warehouse

Schroeder, R.L.; Vangilder, L.D.

1997-01-01

We measured oak-mast production and forest structure and composition in the Ozark Mountains of Missouri and tested the accuracy of oak-mast prediction variables from 5 Habitat Suitability Index (HSI) species models. Acorn production was positively associated with several measures of abundance and canopy cover of oak trees, and with an index of mast production for all 5 HSI models. We developed 2 modified oak-mast models, based on inputs related to either oak tree density or oak canopy cover and diversity of oak tree species. The revised models accounted for 22-32% of the variance associated with acorn abundance. Future tests of HSI models should consider: (1) the concept of upper limits imposed by habitat and the effects of nonhabitat factors; (2) the benefits of a top-down approach to model development; and (3) testing models across broad geographic regions.

Integrating distributional, spatial prioritization, and individual-based models to evaluate potential critical habitat networks: A case study using the Northern Spotted Owl

EPA Science Inventory

As part of the northern spotted owl recovery planning effort, we evaluated a series of alternative critical habitat scenarios using a species-distribution model (MaxEnt), a conservation-planning model (Zonation), and an individual-based population model (HexSim). With this suite ...

Bridging the gap between habitat-modeling research and bird conservation with dynamic landscape and population models

Treesearch

Frank R., III Thompson

2009-01-01

Habitat models are widely used in bird conservation planning to assess current habitat or populations and to evaluate management alternatives. These models include species-habitat matrix or database models, habitat suitability models, and statistical models that predict abundance. While extremely useful, these approaches have some limitations.

An Ecohydraulic Model to Identify and Monitor Moapa Dace Habitat

PubMed Central

Hatten, James R.; Batt, Thomas R.; Scoppettone, Gary G.; Dixon, Christopher J.

2013-01-01

Moapa dace (Moapa coriacea) is a critically endangered thermophilic minnow native to the Muddy River ecosystem in southeastern Nevada, USA. Restricted to temperatures between 26.0 and 32.0°C, these fish are constrained to the upper two km of the Muddy River and several small tributaries fed by warm springs. Habitat alterations, nonnative species invasion, and water withdrawals during the 20th century resulted in a drastic decline in the dace population and in 1979 the Moapa Valley National Wildlife Refuge (Refuge) was created to protect them. The goal of our study was to determine the potential effects of reduced surface flows that might result from groundwater pumping or water diversions on Moapa dace habitat inside the Refuge. We accomplished our goal in several steps. First, we conducted snorkel surveys to determine the locations of Moapa dace on three warm-spring tributaries of the Muddy River. Second, we conducted hydraulic simulations over a range of flows with a two-dimensional hydrodynamic model. Third, we developed a set of Moapa dace habitat models with logistic regression and a geographic information system. Fourth, we estimated Moapa dace habitat over a range of flows (plus or minus 30% of base flow). Our spatially explicit habitat models achieved classification accuracies between 85% and 91%, depending on the snorkel survey and creek. Water depth was the most significant covariate in our models, followed by substrate, Froude number, velocity, and water temperature. Hydraulic simulations showed 2–11% gains in dace habitat when flows were increased by 30%, and 8–32% losses when flows were reduced by 30%. To ensure the health and survival of Moapa dace and the Muddy River ecosystem, groundwater and surface-water withdrawals and diversions need to be carefully monitored, while fully implementing a proactive conservation strategy. PMID:23408999

An ecohydraulic model to identify and monitor moapa dace habitat

USGS Publications Warehouse

Hatten, James R.; Batt, Thomas R.; Scoppettone, Gayton G.; Dixon, Christopher J.

2013-01-01

Moapa dace (Moapa coriacea) is a critically endangered thermophilic minnow native to the Muddy River ecosystem in southeastern Nevada, USA. Restricted to temperatures between 26.0 and 32.0°C, these fish are constrained to the upper two km of the Muddy River and several small tributaries fed by warm springs. Habitat alterations, nonnative species invasion, and water withdrawals during the 20th century resulted in a drastic decline in the dace population and in 1979 the Moapa Valley National Wildlife Refuge (Refuge) was created to protect them. The goal of our study was to determine the potential effects of reduced surface flows that might result from groundwater pumping or water diversions on Moapa dace habitat inside the Refuge. We accomplished our goal in several steps. First, we conducted snorkel surveys to determine the locations of Moapa dace on three warm-spring tributaries of the Muddy River. Second, we conducted hydraulic simulations over a range of flows with a two-dimensional hydrodynamic model. Third, we developed a set of Moapa dace habitat models with logistic regression and a geographic information system. Fourth, we estimated Moapa dace habitat over a range of flows (plus or minus 30% of base flow). Our spatially explicit habitat models achieved classification accuracies between 85% and 91%, depending on the snorkel survey and creek. Water depth was the most significant covariate in our models, followed by substrate, Froude number, velocity, and water temperature. Hydraulic simulations showed 2-11% gains in dace habitat when flows were increased by 30%, and 8-32% losses when flows were reduced by 30%. To ensure the health and survival of Moapa dace and the Muddy River ecosystem, groundwater and surface-water withdrawals and diversions need to be carefully monitored, while fully implementing a proactive conservation strategy.

Using urban forest assessment tools to model bird habitat potential

USGS Publications Warehouse

Lerman, Susannah B.; Nislow, Keith H.; Nowak, David J.; DeStefano, Stephen; King, David I.; Jones-Farrand, D. Todd

2014-01-01

The alteration of forest cover and the replacement of native vegetation with buildings, roads, exotic vegetation, and other urban features pose one of the greatest threats to global biodiversity. As more land becomes slated for urban development, identifying effective urban forest wildlife management tools becomes paramount to ensure the urban forest provides habitat to sustain bird and other wildlife populations. The primary goal of this study was to integrate wildlife suitability indices to an existing national urban forest assessment tool, i-Tree. We quantified available habitat characteristics of urban forests for ten northeastern U.S. cities, and summarized bird habitat relationships from the literature in terms of variables that were represented in the i-Tree datasets. With these data, we generated habitat suitability equations for nine bird species representing a range of life history traits and conservation status that predicts the habitat suitability based on i-Tree data. We applied these equations to the urban forest datasets to calculate the overall habitat suitability for each city and the habitat suitability for different types of land-use (e.g., residential, commercial, parkland) for each bird species. The proposed habitat models will help guide wildlife managers, urban planners, and landscape designers who require specific information such as desirable habitat conditions within an urban management project to help improve the suitability of urban forests for birds.

Obtaining environmental measures to facilitate vertebrate habitat modeling

USGS Publications Warehouse

Karl, J.W.; Wright, N.M.; Heglund, P.J.; Scott, J.M.

1999-01-01

Published literature generally lacks habitat information needed to adequately model the habitats of most wildlife species at large scales (>1:100,000). We searched in primary and secondary literature for occurrence of several potentially useful habitat measures for 20 species of interest to the Idaho Department of Fish and Game. We found adequate information for modeling only the habitats of certain game species and species of special interest. We suggest that many more researchers could collect simple habitat information regarding vegetation composition and structure, topographic features, soils, temperature, and distance to special landscape features such that current research expenses would not be increased significantly. We recommend that habitat data be consistently reported in peer-reviewed literature or deposited into a central data repository. This will not only help fill the gaps in our current knowledge of wildlife but also place it in a format that is readily accessible by the scientific community.

Individual-Based Spatially-Explicit Model of an Herbivore and Its Resource: The Effect of Habitat Reduction and Fragmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostova, T; Carlsen, T; Kercher, J

2002-06-17

We present an individual-based, spatially-explicit model of the dynamics of a small mammal and its resource. The life histories of each individual animal are modeled separately. The individuals can have the status of residents or wanderers and belong to behaviorally differing groups of juveniles or adults and males or females. Their territory defending and monogamous behavior is taken into consideration. The resource, green vegetation, grows depending on seasonal climatic characteristics and is diminished due to the herbivore's grazing. Other specifics such as a varying personal energetic level due to feeding and starvation of the individuals, mating preferences, avoidance of competitors,more » dispersal of juveniles, as a result of site overgrazing, etc. are included in the model. We determined model parameters from real data for the species Microtus ochrogaster (prairie vole). The simulations are done for a case of an enclosed habitat without predators or other species competitors. The goal of the study is to find the relation between size of habitat and population persistence. The experiments with the model show the populations go extinct due to severe overgrazing, but that the length of population persistence depends on the area of the habitat as well as on the presence of fragmentation. Additionally, the total population size of the vole population obtained during the simulations exhibits yearly fluctuations as well as multi-yearly peaks of fluctuations. This dynamics is similar to the one observed in prairie vole field studies.« less

Using habitat suitability models to target invasive plant species surveys

USGS Publications Warehouse

Crall, Alycia W.; Jarnevich, Catherine S.; Panke, Brendon; Young, Nick; Renz, Mark; Morisette, Jeffrey

2013-01-01

Managers need new tools for detecting the movement and spread of nonnative, invasive species. Habitat suitability models are a popular tool for mapping the potential distribution of current invaders, but the ability of these models to prioritize monitoring efforts has not been tested in the field. We tested the utility of an iterative sampling design (i.e., models based on field observations used to guide subsequent field data collection to improve the model), hypothesizing that model performance would increase when new data were gathered from targeted sampling using criteria based on the initial model results. We also tested the ability of habitat suitability models to predict the spread of invasive species, hypothesizing that models would accurately predict occurrences in the field, and that the use of targeted sampling would detect more species with less sampling effort than a nontargeted approach. We tested these hypotheses on two species at the state scale (Centaurea stoebe and Pastinaca sativa) in Wisconsin (USA), and one genus at the regional scale (Tamarix) in the western United States. These initial data were merged with environmental data at 30-m2 resolution for Wisconsin and 1-km2 resolution for the western United States to produce our first iteration models. We stratified these initial models to target field sampling and compared our models and success at detecting our species of interest to other surveys being conducted during the same field season (i.e., nontargeted sampling). Although more data did not always improve our models based on correct classification rate (CCR), sensitivity, specificity, kappa, or area under the curve (AUC), our models generated from targeted sampling data always performed better than models generated from nontargeted data. For Wisconsin species, the model described actual locations in the field fairly well (kappa = 0.51, 0.19, P 2) = 47.42, P < 0.01). From these findings, we conclude that habitat suitability models can be

Modeling effects of climate change on Yakima River salmonid habitats

USGS Publications Warehouse

Hatten, James R.; Batt, Thomas R.; Connolly, Patrick J.; Maule, Alec G.

2014-01-01

We evaluated the potential effects of two climate change scenarios on salmonid habitats in the Yakima River by linking the outputs from a watershed model, a river operations model, a two-dimensional (2D) hydrodynamic model, and a geographic information system (GIS). The watershed model produced a discharge time series (hydrograph) in two study reaches under three climate scenarios: a baseline (1981–2005), a 1-°C increase in mean air temperature (plus one scenario), and a 2-°C increase (plus two scenario). A river operations model modified the discharge time series with Yakima River operational rules, a 2D model provided spatially explicit depth and velocity grids for two floodplain reaches, while an expert panel provided habitat criteria for four life stages of coho and fall Chinook salmon. We generated discharge-habitat functions for each salmonid life stage (e.g., spawning, rearing) in main stem and side channels, and habitat time series for baseline, plus one (P1) and plus two (P2) scenarios. The spatial and temporal patterns in salmonid habitats differed by reach, life stage, and climate scenario. Seventy-five percent of the 28 discharge-habitat responses exhibited a decrease in habitat quantity, with the P2 scenario producing the largest changes, followed by P1. Fry and spring/summer rearing habitats were the most sensitive to warming and flow modification for both species. Side channels generally produced more habitat than main stem and were more responsive to flow changes, demonstrating the importance of lateral connectivity in the floodplain. A discharge-habitat sensitivity analysis revealed that proactive management of regulated surface waters (i.e., increasing or decreasing flows) might lessen the impacts of climate change on salmonid habitats.

Development and field validation of a regional, management-scale habitat model: A koala Phascolarctos cinereus case study.

PubMed

Law, Bradley; Caccamo, Gabriele; Roe, Paul; Truskinger, Anthony; Brassil, Traecey; Gonsalves, Leroy; McConville, Anna; Stanton, Matthew

2017-09-01

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional-scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using independently-collected field data. We reduced substantial spatial clustering of records in coastal urban areas using a 2-km spatial filter and by modeling separately two subregions separated by the 500-m elevational contour. A bias file was prepared that accounted for variable survey effort. Frequency of wildfire, soil type, floristics and elevation had the highest relative contribution to the model, while a number of other variables made minor contributions. The model was effective in discriminating different habitat suitability classes when compared with koala records not used in modeling. We validated the MaxEnt model at 65 ground-truth sites using independent data on koala occupancy (acoustic sampling) and habitat quality (browse tree availability). Koala bellows ( n  = 276) were analyzed in an occupancy modeling framework, while site habitat quality was indexed based on browse trees. Field validation demonstrated a linear increase in koala occupancy with higher modeled habitat suitability at ground-truth sites. Similarly, a site habitat quality index at ground-truth sites was correlated positively with modeled habitat suitability. The MaxEnt model provided a better fit to estimated koala occupancy than the site-based habitat quality index, probably because many variables were considered simultaneously by the model rather than just browse species. The positive relationship of the model with both site occupancy and habitat quality indicates that the model is fit for application at relevant management scales. Field-validated models of similar resolution would assist in

Fuels planning: science synthesis and integration; environmental consequences fact sheet 15: The Wildlife Habitat Response Model

Treesearch

David Pilliod

2005-01-01

The Wildlife Habitat Response Model (WHRM) is a Web-based computer tool for evaluating the potential effects of fuel-reduction projects on terrestrial wildlife habitats. It uses species-habitat associations in ponderosa pine (Pinus ponderosa), dry-type Douglas-fir (Pseudotsuga menziesii), lodgepole pine (Pinus...

INTERACTIVE HABITAT SUITABILITY MODELS FOR STREAM FISHES IN THE MID-ATLANTIC HIGHLANDS

EPA Science Inventory

Models that predict the presence of stream fish species based on habitat characteristics can be useful in watershed management. We developed such models for each of fourteen Mid-Atlantic Highlands stream fish species/groups.

A test of 3 models of Kirtland's warbler habitat suitability

Treesearch

Mark D. Nelson; Richard R. Buech

1996-01-01

We tested 3 models of Kirtland's warbler (Dendroica kirtlandii) habitat suitability during a period when we believe there was a surplus of good quality breeding habitat. A jack pine canopy-cover model was superior to 2 jack pine stem-density models in predicting Kirtland's warbler habitat use and non-use. Estimated density of birds in high...

A novel approach to assessing environmental disturbance based on habitat selection by zebra fish as a model organism.

PubMed

Araújo, Cristiano V M; Griffith, Daniel M; Vera-Vera, Victoria; Jentzsch, Paul Vargas; Cervera, Laura; Nieto-Ariza, Beatriz; Salvatierra, David; Erazo, Santiago; Jaramillo, Rusbel; Ramos, Luis A; Moreira-Santos, Matilde; Ribeiro, Rui

2018-04-01

Aquatic ecotoxicity assays used to assess ecological risk assume that organisms living in a contaminated habitat are forcedly exposed to the contamination. This assumption neglects the ability of organisms to detect and avoid contamination by moving towards less disturbed habitats, as long as connectivity exists. In fluvial systems, many environmental parameters vary spatially and thus condition organisms' habitat selection. We assessed the preference of zebra fish (Danio rerio) when exposed to water samples from two western Ecuadorian rivers with apparently distinct disturbance levels: Pescadillo River (highly disturbed) and Oro River (moderately disturbed). Using a non-forced exposure system in which water samples from each river were arranged according to their spatial sequence in the field and connected to allow individuals to move freely among samples, we assayed habitat selection by D. rerio to assess environmental disturbance in the two rivers. Fish exposed to Pescadillo River samples preferred downstream samples near the confluence zone with the Oro River. Fish exposed to Oro River samples preferred upstream waters. When exposed to samples from both rivers simultaneously, fish exhibited the same pattern of habitat selection by preferring the Oro River samples. Given that the rivers are connected, preference for the Oro River enabled us to predict a depression in fish populations in the Pescadillo River. Although these findings indicate higher disturbance levels in the Pescadillo River, none of the physical-chemical variables measured was significantly correlated with the preference pattern towards the Oro River. Non-linear spatial patterns of habitat preference suggest that other environmental parameters like urban or agricultural contaminants play an important role in the model organism's habitat selection in these rivers. The non-forced exposure system represents a habitat selection-based approach that can serve as a valuable tool to unravel the factors

A test of an expert-based bird-habitat relationship model in South Carolina

Treesearch

John C. Kilgo; David L. Gartner; Brian R. Chapman; John B. Dunnin; Kathleen E. Franzreb; Sidney A. Gauthreaux; Cathryn H. Greenberg; Douglas J. Levey; Karl V. Miller; Scott F. Pearson

2002-01-01

Wildlife-habitat relationships models are used widely by land managers to provide information on which species are likely to occur in an area of interest and may be impacted by a proposed management activity. Few such models have been tested. We used recent avian census data from the Savannah River Site, South Carolina to validate BIRDHAB, a geographic information...

Modeling effects of conservation grassland losses on amphibian habitat

USGS Publications Warehouse

Mushet, David M.; Neau, Jordan L.; Euliss, Ned H.

2014-01-01

Amphibians provide many ecosystem services valued by society. However, populations have declined globally with most declines linked to habitat change. Wetlands and surrounding terrestrial grasslands form habitat for amphibians in the North American Prairie Pothole Region (PPR). Wetland drainage and grassland conversion have destroyed or degraded much amphibian habitat in the PPR. However, conservation grasslands can provide alternate habitat. In the United States, the Conservation Reserve Program (CRP) is the largest program maintaining grasslands on agricultural lands. We used an ecosystem services model (InVEST) parameterized for the PPR to quantify amphibian habitat over a six-year period (2007–2012). We then quantified changes in availability of amphibian habitat under various land-cover scenarios representing incremental losses (10%, 25%, 50%, 75%, and 100%) of CRP grasslands from 2012 levels. The area of optimal amphibian habitat in the four PPR ecoregions modeled (i.e., Northern Glaciated Plains, Northwestern Glaciated Plains, Lake Agassiz Plain, Des Moines Lobe) declined by approximately 22%, from 3.8 million ha in 2007 to 2.9 million ha in 2012. These losses were driven by the conversion of CRP grasslands to croplands, primarily for corn and soybean production. Our modeling identified an additional 0.8 million ha (26%) of optimal amphibian habitat that would be lost if remaining CRP lands are returned to crop production. An economic climate favoring commodity production over conservation has resulted in substantial losses of amphibian habitat across the PPR that will likely continue into the future. Other regions of the world face similar challenges to maintaining amphibian habitats.

Modeling critical habitat for Flammulated Owls (Otus flammeolus)

Treesearch

David A. Christie; Astrid M. van Woudenberg

1997-01-01

Multiple logistic regression analysis was used to produce a prediction model for Flammulated Owl (Otus flammeolus) breeding habitat within the Kamloops Forest Region in south-central British Columbia. Using the model equation, a pilot habitat prediction map was created within a Geographic Information System (GIS) environment that had a 75.7 percent...

Estimating the distribution of harvested estuarine bivalves with natural-history-based habitat suitability models

EPA Science Inventory

Habitat suitability models are useful to forecast how environmental change may affect the abundance or distribution of species of concern. In the case of harvested bivalves, those models may be used to estimate the vulnerability of this valued ecosystem good to natural or human-...

Evaluation of habitat suitability models for forest passerines using demographic data

Treesearch

Chadwick D. Rittenhouse; Frank R., III Thompson; William D. Dijak; Joshua J. Millspaugh; Richard L. Clawson

2010-01-01

Habitat suitability is often used as a surrogate for demographic responses (i.e., abundance, survival, fecundity, or population viability) in the application of habitat suitability index (HSI) models. Whether habitat suitability actually relates to demographics, however, has rarely been evaluated. We validated HSI models of breeding habitat suitability for wood thrush...

Virtual Construction of Space Habitats: Connecting Building Information Models (BIM) and SysML

NASA Technical Reports Server (NTRS)

Polit-Casillas, Raul; Howe, A. Scott

2013-01-01

Current trends in design, construction and management of complex projects make use of Building Information Models (BIM) connecting different types of data to geometrical models. This information model allow different types of analysis beyond pure graphical representations. Space habitats, regardless their size, are also complex systems that require the synchronization of many types of information and disciplines beyond mass, volume, power or other basic volumetric parameters. For this, the state-of-the-art model based systems engineering languages and processes - for instance SysML - represent a solid way to tackle this problem from a programmatic point of view. Nevertheless integrating this with a powerful geometrical architectural design tool with BIM capabilities could represent a change in the workflow and paradigm of space habitats design applicable to other aerospace complex systems. This paper shows some general findings and overall conclusions based on the ongoing research to create a design protocol and method that practically connects a systems engineering approach with a BIM architectural and engineering design as a complete Model Based Engineering approach. Therefore, one hypothetical example is created and followed during the design process. In order to make it possible this research also tackles the application of IFC categories and parameters in the aerospace field starting with the application upon the space habitats design as way to understand the information flow between disciplines and tools. By building virtual space habitats we can potentially improve in the near future the way more complex designs are developed from very little detail from concept to manufacturing.

Food-web models predict species abundances in response to habitat change.

PubMed

Gotelli, Nicholas J; Ellison, Aaron M

2006-10-01

Plant and animal population sizes inevitably change following habitat loss, but the mechanisms underlying these changes are poorly understood. We experimentally altered habitat volume and eliminated top trophic levels of the food web of invertebrates that inhabit rain-filled leaves of the carnivorous pitcher plant Sarracenia purpurea. Path models that incorporated food-web structure better predicted population sizes of food-web constituents than did simple keystone species models, models that included only autecological responses to habitat volume, or models including both food-web structure and habitat volume. These results provide the first experimental confirmation that trophic structure can determine species abundances in the face of habitat loss.

Food-Web Models Predict Species Abundances in Response to Habitat Change

PubMed Central

Gotelli, Nicholas J; Ellison, Aaron M

2006-01-01

Plant and animal population sizes inevitably change following habitat loss, but the mechanisms underlying these changes are poorly understood. We experimentally altered habitat volume and eliminated top trophic levels of the food web of invertebrates that inhabit rain-filled leaves of the carnivorous pitcher plant Sarracenia purpurea. Path models that incorporated food-web structure better predicted population sizes of food-web constituents than did simple keystone species models, models that included only autecological responses to habitat volume, or models including both food-web structure and habitat volume. These results provide the first experimental confirmation that trophic structure can determine species abundances in the face of habitat loss. PMID:17002518

A Rapid Approach to Modeling Species-Habitat Relationships

NASA Technical Reports Server (NTRS)

Carter, Geoffrey M.; Breinger, David R.; Stolen, Eric D.

2005-01-01

A growing number of species require conservation or management efforts. Success of these activities requires knowledge of the species' occurrence pattern. Species-habitat models developed from GIS data sources are commonly used to predict species occurrence but commonly used data sources are often developed for purposes other than predicting species occurrence and are of inappropriate scale and the techniques used to extract predictor variables are often time consuming and cannot be repeated easily and thus cannot efficiently reflect changing conditions. We used digital orthophotographs and a grid cell classification scheme to develop an efficient technique to extract predictor variables. We combined our classification scheme with a priori hypothesis development using expert knowledge and a previously published habitat suitability index and used an objective model selection procedure to choose candidate models. We were able to classify a large area (57,000 ha) in a fraction of the time that would be required to map vegetation and were able to test models at varying scales using a windowing process. Interpretation of the selected models confirmed existing knowledge of factors important to Florida scrub-jay habitat occupancy. The potential uses and advantages of using a grid cell classification scheme in conjunction with expert knowledge or an habitat suitability index (HSI) and an objective model selection procedure are discussed.

Seasonal variation in coastal marine habitat use by the European shag: Insights from fine scale habitat selection modeling and diet

NASA Astrophysics Data System (ADS)

Michelot, Candice; Pinaud, David; Fortin, Matthieu; Maes, Philippe; Callard, Benjamin; Leicher, Marine; Barbraud, Christophe

2017-07-01

Studies of habitat selection by higher trophic level species are necessary for using top predator species as indicators of ecosystem functioning. However, contrary to terrestrial ecosystems, few habitat selection studies have been conducted at a fine scale for coastal marine top predator species, and fewer have coupled diet data with habitat selection modeling to highlight a link between prey selection and habitat use. The aim of this study was to characterize spatially and oceanographically, at a fine scale, the habitats used by the European Shag Phalacrocorax aristotelis in the Special Protection Area (SPA) of Houat-Hœdic in the Mor Braz Bay during its foraging activity. Habitat selection models were built using in situ observation data of foraging shags (transect sampling) and spatially explicit environmental data to characterize marine benthic habitats. Observations were first adjusted for detectability biases and shag abundance was subsequently spatialized. The influence of habitat variables on shag abundance was tested using Generalized Linear Models (GLMs). Diet data were finally confronted to habitat selection models. Results showed that European shags breeding in the Mor Braz Bay changed foraging habitats according to the season and to the different environmental and energetic constraints. The proportion of the main preys also varied seasonally. Rocky and coarse sand habitats were clearly preferred compared to fine or muddy sand habitats. Shags appeared to be more selective in their foraging habitats during the breeding period and the rearing of chicks, using essentially rocky areas close to the colony and consuming preferentially fish from the Labridae family and three other fish families in lower proportions. During the post-breeding period shags used a broader range of habitats and mainly consumed Gadidae. Thus, European shags seem to adjust their feeding strategy to minimize energetic costs, to avoid intra-specific competition and to maximize access

Using habitat suitability models to target invasive plant species surveys.

PubMed

Crall, Alycia W; Jarnevich, Catherine S; Panke, Brendon; Young, Nick; Renz, Mark; Morisette, Jeffrey

2013-01-01

Managers need new tools for detecting the movement and spread of nonnative, invasive species. Habitat suitability models are a popular tool for mapping the potential distribution of current invaders, but the ability of these models to prioritize monitoring efforts has not been tested in the field. We tested the utility of an iterative sampling design (i.e., models based on field observations used to guide subsequent field data collection to improve the model), hypothesizing that model performance would increase when new data were gathered from targeted sampling using criteria based on the initial model results. We also tested the ability of habitat suitability models to predict the spread of invasive species, hypothesizing that models would accurately predict occurrences in the field, and that the use of targeted sampling would detect more species with less sampling effort than a nontargeted approach. We tested these hypotheses on two species at the state scale (Centaurea stoebe and Pastinaca sativa) in Wisconsin (USA), and one genus at the regional scale (Tamarix) in the western United States. These initial data were merged with environmental data at 30-m2 resolution for Wisconsin and 1-km2 resolution for the western United States to produce our first iteration models. We stratified these initial models to target field sampling and compared our models and success at detecting our species of interest to other surveys being conducted during the same field season (i.e., nontargeted sampling). Although more data did not always improve our models based on correct classification rate (CCR), sensitivity, specificity, kappa, or area under the curve (AUC), our models generated from targeted sampling data always performed better than models generated from nontargeted data. For Wisconsin species, the model described actual locations in the field fairly well (kappa = 0.51, 0.19, P < 0.01), and targeted sampling did detect more species than nontargeted sampling with less

Assessing ecoregional-scale habitat suitability index models for priority landbirds

Treesearch

John M. Tirpak; D. Todd Jones-Farrand; Frank R. Thompson; Daniel J. Twedt; Charles K. Baxter; Jane A. Fitzgerald; William B. Uihlein

2009-01-01

Emerging methods in habitat and wildlife population modeling promise new horizons in conservation but only if these methods provide robust population-habitat linkages. We used Breeding Bird Survey (BBS) data to verify and validate newly developed habitat suitability index (HSI) models for 40 priority landbird species in the Central Hardwoods and West Gulf Coastal Plain...

Wildlife species richness in shelterbelts: test of a habitat model

USGS Publications Warehouse

Schroeder, Richard L.; Cable, Ted T.; Haire, Sandra L.

1992-01-01

Shelterbelts are human-made habitats consisting of rows of shrubs and trees planted either in fields or on the windward side of farmstead dwellings. Shelterbelts provide wooded habitat for a large variety of birds and other wildlife. A model to predict wildlife species richness in shelterbelts (Schroeder 1986) was published as part of the U.S. Fish and Wildlife Service Habitat Suitability Index (HSI) model series (Schamberger et al. 1982). HSI models have been used extensively by wildlife managers and land use planners to assess habitat quality. Several HSI models have become the focus of a test program that includes analysis of field data for corroboration, refutation, or modification of model hypotheses. Previous tests of HSI models focused either on single species (e.g., Cook and Irwin 1985, Morton et al. 1989, Schroeder 1990) or examined portions of HSI models, such as the relationship between cavity abundance and tree diameter (Allen and Corn 1990). The shelterbelt model, however, assesses habitat value at the community level. The effects of habitat characteristics, area, and perimeter on diversity and abundance of bird and mammal species in shelterbelts were first studied by Yahner (1983a, b). Johnson and Beck (1988) confirmed the importance of shelterbelts to wildlife and identified area, perimeter, and diversity and complexity of vegetation as key measurements of habitat quality. The shelterbelt model incorporates both specific habitat variables and larger scale parameters, such as area and configuration, to predict wildlife species richness. This shift in perspective comes at a time of increasing interest in conservation and planning beyond the species levels (e.g., Graul and Miller 1984, Hutto et al. 1987, Schroeder 1987: 26).We report results of a 3-year study of spatial and vegetative parameters and their relationship to breeding bird species richness (BSR) in 34 Kansas shelterbelts. Our objectives were to test the hypothesis presented in the original

Modeling and simulation of an aquatic habitat for bioregenerative life support research

NASA Astrophysics Data System (ADS)

Drayer, Gregorio E.; Howard, Ayanna M.

2014-01-01

Long duration human spaceflight poses challenges for spacecraft autonomy and the regeneration of life support consumables, such as oxygen and water. Bioregenerative life support systems (BLSS), which make use of biological processes to transform biological byproducts back into consumables, have the ability to recycle organic byproducts and are the preferred option for food production. A limitation in BLSS research is in the non-availability of small-scale experimental capacities that may help to better understand the challenges in system closure, integration, and control. Ground-based aquatic habitats are an option for small-scale research relevant to bioregenerative life support systems (BLSS), given that they can operate as self-contained systems enclosing a habitat composed of various species in a single volume of water. The purpose of this paper is to present the modeling and simulation of a reconfigurable aquatic habitat for experiments in regenerative life support automation; it supports the use of aquatic habitats as a small-scale approach to experiments relevant to larger-scale regenerative life support systems. It presents ground-based aquatic habitats as an option for small-scale BLSS research focusing on the process of respiration, and elaborates on the description of biological processes by introducing models of ecophysiological phenomena for consumers and producers: higher plants of the species Bacopa monnieri produce O2 for snails of the genus Pomacea; the snails consume O2 and generate CO2, which is used by the plants in combination with radiant energy to generate O2 through the process of photosynthesis. Feedback controllers are designed to regulate the concentration of dissolved oxygen in the water. This paper expands the description of biological processes by introducing models of ecophysiological phenomena of the organisms involved. The model of the plants includes a description of the rate of CO2 assimilation as a function of irradiance

Using a rule-based envelope model to predict the expansion of habitat suitability within New Zealand for the tick Haemaphysalis longicornis, with future projections based on two climate change scenarios.

PubMed

Lawrence, K E; Summers, S R; Heath, A C G; McFadden, A M J; Pulford, D J; Tait, A B; Pomroy, W E

2017-08-30

Haemaphysalis longicornis is the only species of tick present in New Zealand which infests livestock and is also the only competent vector for Theileria orientalis. Since 2012, New Zealand has suffered from an epidemic of infectious bovine anaemia associated with T. orientalis, an obligate intracellular protozoan parasite of cattle and buffaloes. The aim of this study was to predict the spatial distribution of habitat suitability of New Zealand for the tick H. longicornis using a simple rule-based climate envelope model, to validate the model against published data and use the validated model to project an expansion in habitat suitability for H. longicornis under two alternative climate change scenarios for the periods 2046-2065 and 2081-2100, relative to the climate of 1981-2010. A rule-based climate envelope model was developed based on the environmental requirements for off-host tick survival. The resulting model was validated against a maximum entropy environmental niche model of environmental suitability for T. orientalis transmission and against a H. longicornis occurrence map. Validation was completed using the I-similarity statistic and by linear regression. The H. longicornis climate envelope model predicted that 75% of cattle farms in the North Island, 3% of cattle farms in the South Island and 54% of cattle farms in New Zealand overall have habitats potentially suitable for the establishment of H. longicornis. The validation methods showed an acceptable level of agreement between the envelope model and published data. Both of the climate change scenarios, for each of the time periods, projected only slight to moderate increases in the average farm habitat suitability scores for all the South Island regions. However, only for the West Coast, Marlborough, Tasman, and Nelson regions did these increases in environmental suitability translate into an increased proportion of cattle farms with low or high H. longicornis habitat suitability. These results will

An empirical assessment and comparison of species-based and habitat-based surrogates: a case study of forest vertebrates and large old trees.

PubMed

Lindenmayer, David B; Barton, Philip S; Lane, Peter W; Westgate, Martin J; McBurney, Lachlan; Blair, David; Gibbons, Philip; Likens, Gene E

2014-01-01

A holy grail of conservation is to find simple but reliable measures of environmental change to guide management. For example, particular species or particular habitat attributes are often used as proxies for the abundance or diversity of a subset of other taxa. However, the efficacy of such kinds of species-based surrogates and habitat-based surrogates is rarely assessed, nor are different kinds of surrogates compared in terms of their relative effectiveness. We use 30-year datasets on arboreal marsupials and vegetation structure to quantify the effectiveness of: (1) the abundance of a particular species of arboreal marsupial as a species-based surrogate for other arboreal marsupial taxa, (2) hollow-bearing tree abundance as a habitat-based surrogate for arboreal marsupial abundance, and (3) a combination of species- and habitat-based surrogates. We also quantify the robustness of species-based and habitat-based surrogates over time. We then use the same approach to model overall species richness of arboreal marsupials. We show that a species-based surrogate can appear to be a valid surrogate until a habitat-based surrogate is co-examined, after which the effectiveness of the former is lost. The addition of a species-based surrogate to a habitat-based surrogate made little difference in explaining arboreal marsupial abundance, but altered the co-occurrence relationship between species. Hence, there was limited value in simultaneously using a combination of kinds of surrogates. The habitat-based surrogate also generally performed significantly better and was easier and less costly to gather than the species-based surrogate. We found that over 30 years of study, the relationships which underpinned the habitat-based surrogate generally remained positive but variable over time. Our work highlights why it is important to compare the effectiveness of different broad classes of surrogates and identify situations when either species- or habitat-based surrogates are likely

Predicting 21st-century polar bear habitat distribution from global climate models

USGS Publications Warehouse

Durner, George M.; Douglas, David C.; Nielson, R.M.; Amstrup, Steven C.; McDonald, T.L.; Stirling, I.; Mauritzen, Mette; Born, E.W.; Wiig, O.; Deweaver, E.; Serreze, Mark C.; Belikov, Stanislav; Holland, M.M.; Maslanik, J.; Aars, Jon; Bailey, D.A.; Derocher, A.E.

2009-01-01

Projections of polar bear (Ursus maritimus) sea ice habitat distribution in the polar basin during the 21st century were developed to understand the consequences of anticipated sea ice reductions on polar bear populations. We used location data from satellitecollared polar bears and environmental data (e.g., bathymetry, distance to coastlines, and sea ice) collected from 1985 to 1995 to build resource selection functions (RSFs). RSFs described habitats that polar bears preferred in summer, autumn, winter, and spring. When applied to independent data from 1996 to 2006, the RSFs consistently identified habitats most frequently used by polar bears. We applied the RSFs to monthly maps of 21st-century sea ice concentration projected by 10 general circulation models (GCMs) used in the Intergovernmental Panel of Climate Change Fourth Assessment Report, under the A1B greenhouse gas forcing scenario. Despite variation in their projections, all GCMs indicated habitat losses in the polar basin during the 21st century. Losses in the highest-valued RSF habitat (optimal habitat) were greatest in the southern seas of the polar basin, especially the Chukchi and Barents seas, and least along the Arctic Ocean shores of Banks Island to northern Greenland. Mean loss of optimal polar bear habitat was greatest during summer; from an observed 1.0 million km2 in 1985-1995 (baseline) to a projected multi-model mean of 0.32 million km2 in 2090-2099 (-68% change). Projected winter losses of polar bear habitat were less: from 1.7 million km2 in 1985-1995 to 1.4 million km2 in 2090-2099 (-17% change). Habitat losses based on GCM multi-model means may be conservative; simulated rates of habitat loss during 1985-2006 from many GCMs were less than the actual observed rates of loss. Although a reduction in the total amount of optimal habitat will likely reduce polar bear populations, exact relationships between habitat losses and population demographics remain unknown. Density and energetic

HABSEED: a Simple Spatially Explicit Meta-Populations Model Using Remote Sensing Derived Habitat Quality Data

NASA Astrophysics Data System (ADS)

Heumann, B. W.; Guichard, F.; Seaquist, J. W.

2005-05-01

The HABSEED model uses remote sensing derived NPP as a surrogate for habitat quality as the driving mechanism for population growth and local seed dispersal. The model has been applied to the Sahel region of Africa. Results show that the functional response of plants to habitat quality alters population distribution. Plants more tolerant of medium quality habitat have greater distributions to the North while plants requiring only the best habitat are limited to the South. For all functional response types, increased seed production results in diminishing returns. Functional response types have been related to life history tradeoffs and r-K strategies based on the results. Results are compared to remote sensing derived vegetation land cover.

A spatial model of white sturgeon rearing habitat in the lower Columbia River, USA

USGS Publications Warehouse

Hatten, J.R.; Parsley, M.J.

2009-01-01

Concerns over the potential effects of in-water placement of dredged materials prompted us to develop a GIS-based model that characterizes in a spatially explicit manner white sturgeon Acipenser transmontanus rearing habitat in the lower Columbia River, USA. The spatial model was developed using water depth, riverbed slope and roughness, fish positions collected in 2002, and Mahalanobis distance (D2). We created a habitat suitability map by identifying a Mahalanobis distance under which >50% of white sturgeon locations occurred in 2002 (i.e., high-probability habitat). White sturgeon preferred relatively moderate to high water depths, and low to moderate riverbed slope and roughness values. The eigenvectors indicated that riverbed slope and roughness were slightly more important than water depth, but all three variables were important. We estimated the impacts that fill might have on sturgeon habitat by simulating the addition of fill to the thalweg, in 3-m increments, and recomputing Mahalanobis distances. Channel filling simulations revealed that up to 9 m of fill would have little impact on high-probability habitat, but 12 and 15 m of fill resulted in habitat declines of ???12% and ???45%, respectively. This is the first spatially explicit predictive model of white sturgeon rearing habitat in the lower Columbia River, and the first to quantitatively predict the impacts of dredging operations on sturgeon habitat. Future research should consider whether water velocity improves the accuracy and specificity of the model, and to assess its applicability to other areas in the Columbia River.

Object-Based Classification as an Alternative Approach to the Traditional Pixel-Based Classification to Identify Potential Habitat of the Grasshopper Sparrow

NASA Astrophysics Data System (ADS)

Jobin, Benoît; Labrecque, Sandra; Grenier, Marcelle; Falardeau, Gilles

2008-01-01

The traditional method of identifying wildlife habitat distribution over large regions consists of pixel-based classification of satellite images into a suite of habitat classes used to select suitable habitat patches. Object-based classification is a new method that can achieve the same objective based on the segmentation of spectral bands of the image creating homogeneous polygons with regard to spatial or spectral characteristics. The segmentation algorithm does not solely rely on the single pixel value, but also on shape, texture, and pixel spatial continuity. The object-based classification is a knowledge base process where an interpretation key is developed using ground control points and objects are assigned to specific classes according to threshold values of determined spectral and/or spatial attributes. We developed a model using the eCognition software to identify suitable habitats for the Grasshopper Sparrow, a rare and declining species found in southwestern Québec. The model was developed in a region with known breeding sites and applied on other images covering adjacent regions where potential breeding habitats may be present. We were successful in locating potential habitats in areas where dairy farming prevailed but failed in an adjacent region covered by a distinct Landsat scene and dominated by annual crops. We discuss the added value of this method, such as the possibility to use the contextual information associated to objects and the ability to eliminate unsuitable areas in the segmentation and land cover classification processes, as well as technical and logistical constraints. A series of recommendations on the use of this method and on conservation issues of Grasshopper Sparrow habitat is also provided.

Interfacing models of wildlife habitat and human development to predict the future distribution of puma habitat

USGS Publications Warehouse

Burdett, Christopher L.; Crooks, Kevin R.; Theobald, David M.; Wilson, Kenneth R.; Boydston, Erin E.; Lyren, Lisa A.; Fisher, Robert N.; Vickers, T. Winston; Morrison, Scott A.; Boyce, Walter M.

2010-01-01

The impact of human land uses on ecological systems typically differ relative to how extensively natural conditions are modified. Exurban development is intermediate-intensity residential development that often occurs in natural landscapes. Most species-habitat models do not evaluate the effects of such intermediate levels of human development and even fewer predict how future development patterns might affect the amount and configuration of habitat. We addressed these deficiencies by interfacing a habitat model with a spatially-explicit housing-density model to study the effect of human land uses on the habitat of pumas (Puma concolor) in southern California. We studied the response of pumas to natural and anthropogenic features within their home ranges and how mortality risk varied across a gradient of human development. We also used our housing-density model to estimate past and future housing densities and model the distribution of puma habitat in 1970, 2000, and 2030. The natural landscape for pumas in our study area consisted of riparian areas, oak woodlands, and open, conifer forests embedded in a chaparral matrix. Pumas rarely incorporated suburban or urban development into their home ranges, which is consistent with the hypothesis that the behavioral decisions of individuals can be collectively manifested as population-limiting factors at broader spatial scales. Pumas incorporated rural and exurban development into their home ranges, apparently perceiving these areas as modified, rather than non-habitat. Overall, pumas used exurban areas less than expected and showed a neutral response to rural areas. However, individual pumas that selected for or showed a neutral response to exurban areas had a higher risk of mortality than pumas that selected against exurban habitat. Exurban areas are likely hotspots for puma-human conflict in southern California. Approximately 10% of our study area will transform from exurban, rural, or undeveloped areas to suburban or

Combining correlative and mechanistic habitat suitability models to improve ecological compensation.

PubMed

Meineri, Eric; Deville, Anne-Sophie; Grémillet, David; Gauthier-Clerc, Michel; Béchet, Arnaud

2015-02-01

Only a few studies have shown positive impacts of ecological compensation on species dynamics affected by human activities. We argue that this is due to inappropriate methods used to forecast required compensation in environmental impact assessments. These assessments are mostly descriptive and only valid at limited spatial and temporal scales. However, habitat suitability models developed to predict the impacts of environmental changes on potential species' distributions should provide rigorous science-based tools for compensation planning. Here we describe the two main classes of predictive models: correlative models and individual-based mechanistic models. We show how these models can be used alone or synoptically to improve compensation planning. While correlative models are easier to implement, they tend to ignore underlying ecological processes and lack accuracy. On the contrary, individual-based mechanistic models can integrate biological interactions, dispersal ability and adaptation. Moreover, among mechanistic models, those considering animal energy balance are particularly efficient at predicting the impact of foraging habitat loss. However, mechanistic models require more field data compared to correlative models. Hence we present two approaches which combine both methods for compensation planning, especially in relation to the spatial scale considered. We show how the availability of biological databases and software enabling fast and accurate population projections could be advantageously used to assess ecological compensation requirement efficiently in environmental impact assessments. © 2014 The Authors. Biological Reviews © 2014 Cambridge Philosophical Society.

Modeling demographic performance of northern spotted owls relative to forest habitat in Oregon

USGS Publications Warehouse

Olson, Gail S.; Glenn, Elizabeth M.; Anthony, Robert G.; Forsman, Eric D.; Reid, Janice A.; Loschl, Peter J.; Ripple, William J.

2004-01-01

Northern spotted owls (Strix occidentalis caurina) are known to be associated with late-successional forests in the Pacific Northwest of the United States, but the effects of habitat on their demographic performance are relatively unknown. We developed statistical models relating owl survival and productivity to forest cover types within the Roseburg Study Area in the Oregon Coast Range of Oregon, USA. We further combined these demographic parameters using a Leslie-type matrix to obtain an estimate of habitat fitness potential for each owl territory (n = 94). We used mark–recapture methods to develop models for survival and linear mixed models for productivity. We measured forest composition and landscape patterns at 3 landscape scales centered on nest and activity sites within owl territories using an aerial photo-based map and a Geographic Information System (GIS). We also considered additional covariates such as age, sex, and presence of barred owls (Strix varia), and seasonal climate variables (temperature and precipitation) in our models. We used Akaike's Information Criterion (AIC) to rank and compare models. Survival had a quadratic relationship with the amount of late- and mid-seral forests within 1,500 m of nesting centers. Survival also was influenced by the amount of precipitation during the nesting season. Only 16% of the variability in survival was accounted for by our best model, but 85% of this was due to the habitat variable. Reproductive rates fluctuated biennially and were positively related to the amount of edge between late- and mid-seral forests and other habitat classes. Reproductive rates also were influenced by parent age, amount of precipitation during nesting season, and presence of barred owls. Our best model accounted for 84% of the variability in productivity, but only 3% of that was due to the habitat variable. Estimates of habitat fitness potential (which may range from 0 to infinity) for the 94 territories ranged from 0.74 to 1

Lidar: shedding new light on habitat characterization and modeling.

Treesearch

Kerri T. Vierling; Lee A. Vierling; William A. Gould; Sebastian Martinuzzi; Rick M. Clawges

2008-01-01

Ecologists need data on animal–habitat associations in terrestrial and aquatic environments to design and implement effective conservation strategies. Habitat characteristics used in models typically incorporate (1) field data of limited spatial extent and/or (2) remote sensing data that do not characterize the vertical habitat structure. Remote sensing tools that...

A Spatially Based Area–Time Inundation Index Model Developed to Assess Habitat Opportunity in Tidal–Fluvial Wetlands and Restoration Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Andre M.; Diefenderfer, Heida L.; Ward, Duane L.

The hydrodynamics of tidal wetland areas in the lower Columbia River floodplain and estuary directly affect habitat opportunity for endangered salmonid fishes. Physical and biological structures and functions in the system are directly affected by inundation patterns influenced by tidal cycles, hydropower operations, river discharge, upriver water withdrawals, climate, and physical barriers such as dikes, culverts, and tide gates. Ongoing ecosystem restoration efforts are intended to increase the opportunity for salmon to access beneficial habitats by hydrologically reconnecting main-stem river channels and diked areas within the historical floodplain. To address the need to evaluate habitat opportunity, a geographic information system-basedmore » Area-Time Inundation Index Model (ATIIM) was developed. The ATIIM integrates in situ or modeled hourly water-surface elevation (WSE) data and advanced terrain processing of high-resolution elevation data. The ATIIM uses a spatially based wetted-area algorithm to determine site average bankfull elevation, two- and three-dimensional inundation extent, and other site metrics. Hydrological process metrics such as inundation frequency, duration, maximum area, and maximum frequency area can inform evaluation of proposed restoration sites; e.g., determine trade-offs between WSE and habitat opportunity, contrast alternative restoration designs, predict impacts of altered flow regimes, and estimate nutrient and biomass fluxes. In an adaptive management framework, this model can be used to provide standardized site comparisons and effectiveness monitoring of changes in the developmental trajectories of restoration sites. Results are presented for 11 wetlands representative of tidal marshes, tidal forested wetlands, and restoration sites.« less

Modifying climate change habitat models using tree species-specific assessments of model uncertainty and life history-factors

Treesearch

Stephen N. Matthews; Louis R. Iverson; Anantha M. Prasad; Matthew P. Peters; Paul G. Rodewald

2011-01-01

Species distribution models (SDMs) to evaluate trees' potential responses to climate change are essential for developing appropriate forest management strategies. However, there is a great need to better understand these models' limitations and evaluate their uncertainties. We have previously developed statistical models of suitable habitat, based on both...

HABITAT DISTRIBUTION MODELS FOR 37 VERTEBRATE SPECIES ADDRESSED BY THE MULTI-SPECIES HABITAT CONSERVATION PLAN OF CLARK COUNTY, NEVADA

EPA Science Inventory

Thirty-seven species identified in the Clark County Multi-Species Habitat Conservation Plan were

previously modeled through the Southwest Regional Gap Analysis Project. Existing SWReGAP habitat

models and modeling databases were used to facilitate the revision of mo...

Multistate modeling of habitat dynamics: Factors affecting Florida scrub transition probabilities

USGS Publications Warehouse

Breininger, D.R.; Nichols, J.D.; Duncan, B.W.; Stolen, Eric D.; Carter, G.M.; Hunt, D.K.; Drese, J.H.

2010-01-01

Many ecosystems are influenced by disturbances that create specific successional states and habitat structures that species need to persist. Estimating transition probabilities between habitat states and modeling the factors that influence such transitions have many applications for investigating and managing disturbance-prone ecosystems. We identify the correspondence between multistate capture-recapture models and Markov models of habitat dynamics. We exploit this correspondence by fitting and comparing competing models of different ecological covariates affecting habitat transition probabilities in Florida scrub and flatwoods, a habitat important to many unique plants and animals. We subdivided a large scrub and flatwoods ecosystem along central Florida's Atlantic coast into 10-ha grid cells, which approximated average territory size of the threatened Florida Scrub-Jay (Aphelocoma coerulescens), a management indicator species. We used 1.0-m resolution aerial imagery for 1994, 1999, and 2004 to classify grid cells into four habitat quality states that were directly related to Florida Scrub-Jay source-sink dynamics and management decision making. Results showed that static site features related to fire propagation (vegetation type, edges) and temporally varying disturbances (fires, mechanical cutting) best explained transition probabilities. Results indicated that much of the scrub and flatwoods ecosystem was resistant to moving from a degraded state to a desired state without mechanical cutting, an expensive restoration tool. We used habitat models parameterized with the estimated transition probabilities to investigate the consequences of alternative management scenarios on future habitat dynamics. We recommend this multistate modeling approach as being broadly applicable for studying ecosystem, land cover, or habitat dynamics. The approach provides maximum-likelihood estimates of transition parameters, including precision measures, and can be used to assess

A Habitat-based Wind-Wildlife Collision Model with Application to the Upper Great Plains Region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forcey, Greg, M.

Most previous studies on collision impacts at wind facilities have taken place at the site-specific level and have only examined small-scale influences on mortality. In this study, we examine landscape-level influences using a hierarchical spatial model combined with existing datasets and life history knowledge for: Horned Lark, Red-eyed Vireo, Mallard, American Avocet, Golden Eagle, Whooping Crane, red bat, silver-haired bat, and hoary bat. These species were modeled in the central United States within Bird Conservation Regions 11, 17, 18, and 19. For the bird species, we modeled bird abundance from existing datasets as a function of habitat variables known tomore » be preferred by each species to develop a relative abundance prediction for each species. For bats, there are no existing abundance datasets so we identified preferred habitat in the landscape for each species and assumed that greater amounts of preferred habitat would equate to greater abundance of bats. The abundance predictions for bird and bats were modeled with additional exposure factors known to influence collisions such as visibility, wind, temperature, precipitation, topography, and behavior to form a final mapped output of predicted collision risk within the study region. We reviewed published mortality studies from wind farms in our study region and collected data on reported mortality of our focal species to compare to our modeled predictions. We performed a sensitivity analysis evaluating model performance of 6 different scenarios where habitat and exposure factors were weighted differently. We compared the model performance in each scenario by evaluating observed data vs. our model predictions using spearmans rank correlations. Horned Lark collision risk was predicted to be highest in the northwestern and west-central portions of the study region with lower risk predicted elsewhere. Red-eyed Vireo collision risk was predicted to be the highest in the eastern portions of the study region

An Empirical Assessment and Comparison of Species-Based and Habitat-Based Surrogates: A Case Study of Forest Vertebrates and Large Old Trees

PubMed Central

Lindenmayer, David B.; Barton, Philip S.; Lane, Peter W.; Westgate, Martin J.; McBurney, Lachlan; Blair, David; Gibbons, Philip; Likens, Gene E.

2014-01-01

A holy grail of conservation is to find simple but reliable measures of environmental change to guide management. For example, particular species or particular habitat attributes are often used as proxies for the abundance or diversity of a subset of other taxa. However, the efficacy of such kinds of species-based surrogates and habitat-based surrogates is rarely assessed, nor are different kinds of surrogates compared in terms of their relative effectiveness. We use 30-year datasets on arboreal marsupials and vegetation structure to quantify the effectiveness of: (1) the abundance of a particular species of arboreal marsupial as a species-based surrogate for other arboreal marsupial taxa, (2) hollow-bearing tree abundance as a habitat-based surrogate for arboreal marsupial abundance, and (3) a combination of species- and habitat-based surrogates. We also quantify the robustness of species-based and habitat-based surrogates over time. We then use the same approach to model overall species richness of arboreal marsupials. We show that a species-based surrogate can appear to be a valid surrogate until a habitat-based surrogate is co-examined, after which the effectiveness of the former is lost. The addition of a species-based surrogate to a habitat-based surrogate made little difference in explaining arboreal marsupial abundance, but altered the co-occurrence relationship between species. Hence, there was limited value in simultaneously using a combination of kinds of surrogates. The habitat-based surrogate also generally performed significantly better and was easier and less costly to gather than the species-based surrogate. We found that over 30 years of study, the relationships which underpinned the habitat-based surrogate generally remained positive but variable over time. Our work highlights why it is important to compare the effectiveness of different broad classes of surrogates and identify situations when either species- or habitat-based surrogates are likely

Habitat classification modelling with incomplete data: Pushing the habitat envelope

Treesearch

Phoebe L. Zarnetske; Thomas C. Edwards; Gretchen G. Moisen

2007-01-01

Habitat classification models (HCMs) are invaluable tools for species conservation, land-use planning, reserve design, and metapopulation assessments, particularly at broad spatial scales. However, species occurrence data are often lacking and typically limited to presence points at broad scales. This lack of absence data precludes the use of many statistical...

Models of Marine Fish Biodiversity: Assessing Predictors from Three Habitat Classification Schemes.

PubMed

Yates, Katherine L; Mellin, Camille; Caley, M Julian; Radford, Ben T; Meeuwig, Jessica J

2016-01-01

Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modelling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modelling metrics of fish biodiversity that are

Models of Marine Fish Biodiversity: Assessing Predictors from Three Habitat Classification Schemes

PubMed Central

Yates, Katherine L.; Mellin, Camille; Caley, M. Julian; Radford, Ben T.; Meeuwig, Jessica J.

2016-01-01

Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modelling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modelling metrics of fish biodiversity that are

Importance of the habitat choice behavior assumed when modeling the effects of food and temperature on fish populations

USGS Publications Warehouse

Wildhaber, Mark L.; Lamberson, Peter J.

2004-01-01

Various mechanisms of habitat choice in fishes based on food and/or temperature have been proposed: optimal foraging for food alone; behavioral thermoregulation for temperature alone; and behavioral energetics and discounted matching for food and temperature combined. Along with development of habitat choice mechanisms, there has been a major push to develop and apply to fish populations individual-based models that incorporate various forms of these mechanisms. However, it is not known how the wide variation in observed and hypothesized mechanisms of fish habitat choice could alter fish population predictions (e.g. growth, size distributions, etc.). We used spatially explicit, individual-based modeling to compare predicted fish populations using different submodels of patch choice behavior under various food and temperature distributions. We compared predicted growth, temperature experience, food consumption, and final spatial distribution using the different models. Our results demonstrated that the habitat choice mechanism assumed in fish population modeling simulations was critical to predictions of fish distribution and growth rates. Hence, resource managers who use modeling results to predict fish population trends should be very aware of and understand the underlying patch choice mechanisms used in their models to assure that those mechanisms correctly represent the fish populations being modeled.

Modeling habitat split: landscape and life history traits determine amphibian extinction thresholds.

PubMed

Fonseca, Carlos Roberto; Coutinho, Renato M; Azevedo, Franciane; Berbert, Juliana M; Corso, Gilberto; Kraenkel, Roberto A

2013-01-01

Habitat split is a major force behind the worldwide decline of amphibian populations, causing community change in richness and species composition. In fragmented landscapes, natural remnants, the terrestrial habitat of the adults, are frequently separated from streams, the aquatic habitat of the larvae. An important question is how this landscape configuration affects population levels and if it can drive species to extinction locally. Here, we put forward the first theoretical model on habitat split which is particularly concerned on how split distance - the distance between the two required habitats - affects population size and persistence in isolated fragments. Our diffusive model shows that habitat split alone is able to generate extinction thresholds. Fragments occurring between the aquatic habitat and a given critical split distance are expected to hold viable populations, while fragments located farther away are expected to be unoccupied. Species with higher reproductive success and higher diffusion rate of post-metamorphic youngs are expected to have farther critical split distances. Furthermore, the model indicates that negative effects of habitat split are poorly compensated by positive effects of fragment size. The habitat split model improves our understanding about spatially structured populations and has relevant implications for landscape design for conservation. It puts on a firm theoretical basis the relation between habitat split and the decline of amphibian populations.

Habitat Suitability Index Models: Northern Gulf of Mexico brown shrimp and white shrimp

USGS Publications Warehouse

Turner, Robert Eugene; Brody, Michael S.

1983-01-01

A review and synthesis of existing information were used to develop estuarine habitat models for brown shrimp (Penaeus aztecus) and white shrimp (Penaeus setiferus). The models are scaled to produce an index of habitat suitability between 0 (unsuitable habitat) to 1 (optimally suitable habitat) for estuarine areas of the northern Gulf of Mexico. Habitat suitability indexes are designed for use with the habitat evaluation procedures developed by the U.S. Fish and Wildlife Service.

Multi-criteria Decision Analysis to Model Ixodes ricinus Habitat Suitability.

PubMed

Rousseau, Raphaël; McGrath, Guy; McMahon, Barry J; Vanwambeke, Sophie O

2017-09-01

Tick-borne diseases present a major threat to both human and livestock health throughout Europe. The risk of infection is directly related to the presence of its vector. Thereby it is important to know their distribution, which is strongly associated with environmental factors: the presence and availability of a suitable habitat, of a suitable climate and of hosts. The present study models the habitat suitability for Ixodes ricinus in Ireland, where data on tick distribution are scarce. Tick habitat suitability was estimated at a coarse scale (10 km) with a multi-criteria decision analysis (MCDA) method according to four different scenarios (depending on the variables used and on the weights granted to each of them). The western part of Ireland and the Wicklow mountains in the East were estimated to be the most suitable areas for I. ricinus in the island. There was a good level of agreement between results from the MCDA and recorded tick presence. The different scenarios did not affect the spatial outputs substantially. The current study suggests that tick habitat suitability can be mapped accurately at a coarse scale in a data-scarce context using knowledge-based methods. It can serve as a guideline for future countrywide sampling that would help to determine local risk of tick presence and refining knowledge on tick habitat suitability in Ireland.

Habitat models to predict wetland bird occupancy influenced by scale, anthropogenic disturbance, and imperfect detection

USGS Publications Warehouse

Glisson, Wesley J.; Conway, Courtney J.; Nadeau, Christopher P.; Borgmann, Kathi L.

2017-01-01

Understanding species–habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway's rail (Rallus obsoletus yumanensis), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species' U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat-based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224-m-scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway's rail occupancy was negatively associated with ephemeral and slow-moving riverine features and high-intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low-intensity development. Our modeling approach accounts for common limitations in modeling species–habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.

Modelling seasonal habitat suitability for wide-ranging species: Invasive wild pigs in northern Australia.

PubMed

Froese, Jens G; Smith, Carl S; Durr, Peter A; McAlpine, Clive A; van Klinken, Rieks D

2017-01-01

Invasive wildlife often causes serious damage to the economy and agriculture as well as environmental, human and animal health. Habitat models can fill knowledge gaps about species distributions and assist planning to mitigate impacts. Yet, model accuracy and utility may be compromised by small study areas and limited integration of species ecology or temporal variability. Here we modelled seasonal habitat suitability for wild pigs, a widespread and harmful invader, in northern Australia. We developed a resource-based, spatially-explicit and regional-scale approach using Bayesian networks and spatial pattern suitability analysis. We integrated important ecological factors such as variability in environmental conditions, breeding requirements and home range movements. The habitat model was parameterized during a structured, iterative expert elicitation process and applied to a wet season and a dry season scenario. Model performance and uncertainty was evaluated against independent distributional data sets. Validation results showed that an expert-averaged model accurately predicted empirical wild pig presences in northern Australia for both seasonal scenarios. Model uncertainty was largely associated with different expert assumptions about wild pigs' resource-seeking home range movements. Habitat suitability varied considerably between seasons, retracting to resource-abundant rainforest, wetland and agricultural refuge areas during the dry season and expanding widely into surrounding grassland floodplains, savanna woodlands and coastal shrubs during the wet season. Overall, our model suggested that suitable wild pig habitat is less widely available in northern Australia than previously thought. Mapped results may be used to quantify impacts, assess risks, justify management investments and target control activities. Our methods are applicable to other wide-ranging species, especially in data-poor situations.

Modelling seasonal habitat suitability for wide-ranging species: Invasive wild pigs in northern Australia

PubMed Central

2017-01-01

Invasive wildlife often causes serious damage to the economy and agriculture as well as environmental, human and animal health. Habitat models can fill knowledge gaps about species distributions and assist planning to mitigate impacts. Yet, model accuracy and utility may be compromised by small study areas and limited integration of species ecology or temporal variability. Here we modelled seasonal habitat suitability for wild pigs, a widespread and harmful invader, in northern Australia. We developed a resource-based, spatially-explicit and regional-scale approach using Bayesian networks and spatial pattern suitability analysis. We integrated important ecological factors such as variability in environmental conditions, breeding requirements and home range movements. The habitat model was parameterized during a structured, iterative expert elicitation process and applied to a wet season and a dry season scenario. Model performance and uncertainty was evaluated against independent distributional data sets. Validation results showed that an expert-averaged model accurately predicted empirical wild pig presences in northern Australia for both seasonal scenarios. Model uncertainty was largely associated with different expert assumptions about wild pigs’ resource-seeking home range movements. Habitat suitability varied considerably between seasons, retracting to resource-abundant rainforest, wetland and agricultural refuge areas during the dry season and expanding widely into surrounding grassland floodplains, savanna woodlands and coastal shrubs during the wet season. Overall, our model suggested that suitable wild pig habitat is less widely available in northern Australia than previously thought. Mapped results may be used to quantify impacts, assess risks, justify management investments and target control activities. Our methods are applicable to other wide-ranging species, especially in data-poor situations. PMID:28472113

Habitat suitability index model of the sea cucumber Apostichopus japonicus (Selenka): A case study of Shandong Peninsula, China.

PubMed

Zhang, Zhipeng; Zhou, Jian; Song, Jingjing; Wang, Qixiang; Liu, Hongjun; Tang, Xuexi

2017-09-15

A habitat suitability index (HSI) model for the sea cucumber Apostichopus japonicus (Selenka) was established in the present study. Based on geographic information systems, the HSI model was used to identify potential sites around the Shandong Peninsula suitable for restoration of immature (<25g) and mature (>25g) A. japonicus. Six habitat factors were used as input variables for the HSI model: sediment classification, water temperature, salinity, water depth, pH and dissolved oxygen. The weighting of each habitat factor was defined through the Delphi method. Sediment classification was the most important condition affecting the HSI of A. japonicus in the different study areas, while water temperature was the most important condition in different seasons. The HSI of Western Laizhou Bay was relatively low, meaning the site was not suitable for aquaculture-based restoration of A. japonicus. In contrast, Xiaoheishan Island, Rongcheng Bay and Qingdao were preferable sites, suitable as habitats for restoration efforts. Copyright © 2017 Elsevier Ltd. All rights reserved.

A trait-based test for habitat filtering: Convex hull volume

USGS Publications Warehouse

Cornwell, W.K.; Schwilk, D.W.; Ackerly, D.D.

2006-01-01

Community assembly theory suggests that two processes affect the distribution of trait values within communities: competition and habitat filtering. Within a local community, competition leads to ecological differentiation of coexisting species, while habitat filtering reduces the spread of trait values, reflecting shared ecological tolerances. Many statistical tests for the effects of competition exist in the literature, but measures of habitat filtering are less well-developed. Here, we present convex hull volume, a construct from computational geometry, which provides an n-dimensional measure of the volume of trait space occupied by species in a community. Combined with ecological null models, this measure offers a useful test for habitat filtering. We use convex hull volume and a null model to analyze California woody-plant trait and community data. Our results show that observed plant communities occupy less trait space than expected from random assembly, a result consistent with habitat filtering. ?? 2006 by the Ecological Society of America.

Simple Process-Based Simulators for Generating Spatial Patterns of Habitat Loss and Fragmentation: A Review and Introduction to the G-RaFFe Model

PubMed Central

Pe'er, Guy; Zurita, Gustavo A.; Schober, Lucia; Bellocq, Maria I.; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model “G-RaFFe” generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non

Simple process-based simulators for generating spatial patterns of habitat loss and fragmentation: a review and introduction to the G-RaFFe model.

PubMed

Pe'er, Guy; Zurita, Gustavo A; Schober, Lucia; Bellocq, Maria I; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model "G-RaFFe" generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non

Lunar and Planetary Bases, Habitats, and Colonies

NASA Technical Reports Server (NTRS)

2004-01-01

This special bibliography includes the design and construction of lunar and Mars bases, habitats, and settlements; construction materials and equipment; life support systems; base operations and logistics; thermal management and power systems; and robotic systems.

Application of GIS to predict malaria hotspots based on Anopheles arabiensis habitat suitability in Southern Africa

NASA Astrophysics Data System (ADS)

Gwitira, Isaiah; Murwira, Amon; Zengeya, Fadzai M.; Shekede, Munyaradzi Davis

2018-02-01

Malaria remains a major public health problem and a principal cause of morbidity and mortality in most developing countries. Although malaria still presents health problems, significant successes have been recorded in reducing deaths resulting from the disease. As malaria transmission continues to decline, control interventions will increasingly depend on the ability to define high-risk areas known as malaria hotspots. Therefore, there is urgent need to use geospatial tools such as geographic information system to detect spatial patterns of malaria and delineate disease hot spots for better planning and management. Thus, accurate mapping and prediction of seasonality of malaria hotspots is an important step towards developing strategies for effective malaria control. In this study, we modelled seasonal malaria hotspots as a function of habitat suitability of Anopheles arabiensis (A. Arabiensis) as a first step towards predicting likely seasonal malaria hotspots that could provide guidance in targeted malaria control. We used Geographical information system (GIS) and spatial statistic methods to identify seasonal hotspots of malaria cases at the country level. In order to achieve this, we first determined the spatial distribution of seasonal malaria hotspots using the Getis Ord Gi* statistic based on confirmed positive malaria cases recorded at health facilities in Zimbabwe over four years (1996-1999). We then used MAXENT technique to model habitat suitability of A. arabiensis from presence data collected from 1990 to 2002 based on bioclimatic variables and altitude. Finally, we used autologistic regression to test the extent to which malaria hotspots can be predicted using A. arabiensis habitat suitability. Our results show that A. arabiensis habitat suitability consistently and significantly (p < 0.05) predicts malaria hotspots from 1996 to 1999. Overall, our results show that malaria hotspots can be predicted using A. arabiensis habitat suitability, suggesting

Refinement of the Arc-Habcap model to predict habitat effectiveness for elk

Treesearch

Lakhdar Benkobi; Mark A. Rumble; Gary C. Brundige; Joshua J. Millspaugh

2004-01-01

Wildlife habitat modeling is increasingly important for managers who need to assess the effects of land management activities. We evaluated the performance of a spatially explicit deterministic habitat model (Arc-Habcap) that predicts habitat effectiveness for elk. We used five years of radio-telemetry locations of elk from Custer State Park (CSP), South Dakota, to...

Test and Modification of a Northern Bobwhite Habitat Suitability Index Model

DTIC Science & Technology

1993-04-01

density. Patton (1984) presented a habitat capability model for the Abert squirrel (Sciurus aberti) that produced scores in 5 quality classes from...34. Wildl. Soc. Bull. 3:171-173. Patton, D. R. 1984. A model to evaluate Abert squirrel habitat in uneven-aged ponderosa pine. Wildl. Soc. Bull. 12:408...poor to optimum. Squirrel densities over 4 years on 9 plots were correlated with subsequently classed habitats (r - 0.96). Soniat and Brody (1988

[Habitat suitability index model and minimum habitat area estimation of young Procypris rabaudi (Tchang): a simulation experiment in laboratory].

PubMed

Feng, Xian-Bin; Zhu, Yong-Jiu; Li, Xi; He, Yong-Feng; Zhao, Jian-Hua; Yang, De-Guo

2013-01-01

Under the conditions of simulated micro-habitat in laboratory, and by using experimental ecological methods, this paper evaluated the suitability index (HSI) of young Procypris rabaudi for habitat factors (substrate, light intensity and water depth). The habitat suitability models of the young P. rabaudi were established, and the minimum habitat area of the young P. rabaudi was estimated. The young P. rabaudi preferred the habitats with the gravel diameter from 10 to 15 cm, light intensity from 0.2 to 1.8 lx, and water depth from 0 to 15 cm (distance from the bottom of the tank). The three suitability index models of the substrate, light intensity and water depth for the young P. rabaudi were SI(s) = 1.7338e(-0.997x)(SI(S) is the suitability index of substrate, and x is the gravel diameter; R2 = 0.89, P < 0.01), SI(L) = 3.0121e(-1.339x)(SI(L) is the suitability index of light intensity, and x is the light intensity; R2 = 0.93, P < 0.01), and SI(W) = 2.4055e(-1.245x)(SI(W) is the suitability index of water depth, and x is the water depth; R2 = 0.97, P < 0.01), respectively. Arithmetic mean model HSI = (SI(S)+SI(L)+SI(W))/3 was most available for the estimation of the habitat suitability of young P. rabaudi. A total of seven groups of young P. rabaudi which established and maintained a relatively stable habitat area range were found. This habitat area ranged from 628 to 2015 cm2, with an average of 1114 cm2.

Analysis of habitat characteristics of small pelagic fish based on generalized additive models in Kepulauan Seribu Waters

NASA Astrophysics Data System (ADS)

Rivai, A. A.; Siregar, V. P.; Agus, S. B.; Yasuma, H.

2018-03-01

One of the required information for sustainable fisheries management is about the habitat characteristics of a fish species. This information can be used to map the distribution of fish and map the potential fishing ground. This study aimed to analyze the habitat characteristics of small pelagic fishes (anchovy, squid, sardine and scads) which were mainly caught by lift net in Kepulauan Seribu waters. Research on habitat characteristics had been widely done, but the use of total suspended solid (TSS) parameters in this analysis is still lacking. TSS parameter which was extracted from Landsat 8 along with five other oceanographic parameters, CPUE data and location of fishing ground data from lift net fisheries in Kepulauan Seribu were included in this analysis. This analysis used Generalized Additive Models (GAMs) to evaluate the relationship between CPUE and oceanographic parameters. The results of the analysis showed that each fish species had different habitat characteristics. TSS and sea surface height had a great influence on the value of CPUE from each species. All the oceanographic parameters affected the CPUE of each species. This study demonstrated the effective use of GAMs to identify the essential habitat of a fish species.

Accuracy of gap analysis habitat models in predicting physical features for wildlife-habitat associations in the southwest U.S.

USGS Publications Warehouse

Boykin, K.G.; Thompson, B.C.; Propeck-Gray, S.

2010-01-01

Despite widespread and long-standing efforts to model wildlife-habitat associations using remotely sensed and other spatially explicit data, there are relatively few evaluations of the performance of variables included in predictive models relative to actual features on the landscape. As part of the National Gap Analysis Program, we specifically examined physical site features at randomly selected sample locations in the Southwestern U.S. to assess degree of concordance with predicted features used in modeling vertebrate habitat distribution. Our analysis considered hypotheses about relative accuracy with respect to 30 vertebrate species selected to represent the spectrum of habitat generalist to specialist and categorization of site by relative degree of conservation emphasis accorded to the site. Overall comparison of 19 variables observed at 382 sample sites indicated ???60% concordance for 12 variables. Directly measured or observed variables (slope, soil composition, rock outcrop) generally displayed high concordance, while variables that required judgments regarding descriptive categories (aspect, ecological system, landform) were less concordant. There were no differences detected in concordance among taxa groups, degree of specialization or generalization of selected taxa, or land conservation categorization of sample sites with respect to all sites. We found no support for the hypothesis that accuracy of habitat models is inversely related to degree of taxa specialization when model features for a habitat specialist could be more difficult to represent spatially. Likewise, we did not find support for the hypothesis that physical features will be predicted with higher accuracy on lands with greater dedication to biodiversity conservation than on other lands because of relative differences regarding available information. Accuracy generally was similar (>60%) to that observed for land cover mapping at the ecological system level. These patterns demonstrate

Predictive modeling of spinner dolphin (Stenella longirostris) resting habitat in the main Hawaiian Islands.

PubMed

Thorne, Lesley H; Johnston, David W; Urban, Dean L; Tyne, Julian; Bejder, Lars; Baird, Robin W; Yin, Suzanne; Rickards, Susan H; Deakos, Mark H; Mobley, Joseph R; Pack, Adam A; Chapla Hill, Marie

2012-01-01

Predictive habitat models can provide critical information that is necessary in many conservation applications. Using Maximum Entropy modeling, we characterized habitat relationships and generated spatial predictions of spinner dolphin (Stenella longirostris) resting habitat in the main Hawaiian Islands. Spinner dolphins in Hawai'i exhibit predictable daily movements, using inshore bays as resting habitat during daylight hours and foraging in offshore waters at night. There are growing concerns regarding the effects of human activities on spinner dolphins resting in coastal areas. However, the environmental factors that define suitable resting habitat remain unclear and must be assessed and quantified in order to properly address interactions between humans and spinner dolphins. We used a series of dolphin sightings from recent surveys in the main Hawaiian Islands and a suite of environmental variables hypothesized as being important to resting habitat to model spinner dolphin resting habitat. The model performed well in predicting resting habitat and indicated that proximity to deep water foraging areas, depth, the proportion of bays with shallow depths, and rugosity were important predictors of spinner dolphin habitat. Predicted locations of suitable spinner dolphin resting habitat provided in this study indicate areas where future survey efforts should be focused and highlight potential areas of conflict with human activities. This study provides an example of a presence-only habitat model used to inform the management of a species for which patterns of habitat availability are poorly understood.

Predictive Modeling of Spinner Dolphin (Stenella longirostris) Resting Habitat in the Main Hawaiian Islands

PubMed Central

Thorne, Lesley H.; Johnston, David W.; Urban, Dean L.; Tyne, Julian; Bejder, Lars; Baird, Robin W.; Yin, Suzanne; Rickards, Susan H.; Deakos, Mark H.; Mobley, Joseph R.; Pack, Adam A.; Chapla Hill, Marie

2012-01-01

Predictive habitat models can provide critical information that is necessary in many conservation applications. Using Maximum Entropy modeling, we characterized habitat relationships and generated spatial predictions of spinner dolphin (Stenella longirostris) resting habitat in the main Hawaiian Islands. Spinner dolphins in Hawai'i exhibit predictable daily movements, using inshore bays as resting habitat during daylight hours and foraging in offshore waters at night. There are growing concerns regarding the effects of human activities on spinner dolphins resting in coastal areas. However, the environmental factors that define suitable resting habitat remain unclear and must be assessed and quantified in order to properly address interactions between humans and spinner dolphins. We used a series of dolphin sightings from recent surveys in the main Hawaiian Islands and a suite of environmental variables hypothesized as being important to resting habitat to model spinner dolphin resting habitat. The model performed well in predicting resting habitat and indicated that proximity to deep water foraging areas, depth, the proportion of bays with shallow depths, and rugosity were important predictors of spinner dolphin habitat. Predicted locations of suitable spinner dolphin resting habitat provided in this study indicate areas where future survey efforts should be focused and highlight potential areas of conflict with human activities. This study provides an example of a presence-only habitat model used to inform the management of a species for which patterns of habitat availability are poorly understood. PMID:22937022

A mathematical model of salmonid spawning habitat

Treesearch

Robert N. Havis; Carlos V. Alonzo; Keith E Woeste; Russell F. Thurow

1993-01-01

A simulation model [Salmonid Spawning Analysis Model (SSAM)I was developed as a management tool to evaluate the relative impacts of stream sediment load and water temperature on salmonid egg survival. The model is usefi.il for estimating acceptable sediment loads to spawning habitat that may result from upland development, such as logging and agriculture. Software in...

Identifying malaria vector breeding habitats with remote sensing data and terrain-based landscape indices in Zambia.

PubMed

Clennon, Julie A; Kamanga, Aniset; Musapa, Mulenga; Shiff, Clive; Glass, Gregory E

2010-11-05

Malaria, caused by the parasite Plasmodium falciparum, is a significant source of morbidity and mortality in southern Zambia. In the Mapanza Chiefdom, where transmission is seasonal, Anopheles arabiensis is the dominant malaria vector. The ability to predict larval habitats can help focus control measures. A survey was conducted in March-April 2007, at the end of the rainy season, to identify and map locations of water pooling and the occurrence anopheline larval habitats; this was repeated in October 2007 at the end of the dry season and in March-April 2008 during the next rainy season. Logistic regression and generalized linear mixed modeling were applied to assess the predictive value of terrain-based landscape indices along with LandSat imagery to identify aquatic habitats and, especially, those with anopheline mosquito larvae. Approximately two hundred aquatic habitat sites were identified with 69 percent positive for anopheline mosquitoes. Nine species of anopheline mosquitoes were identified, of which, 19% were An. arabiensis. Terrain-based landscape indices combined with LandSat predicted sites with water, sites with anopheline mosquitoes and sites specifically with An. arabiensis. These models were especially successful at ruling out potential locations, but had limited ability in predicting which anopheline species inhabited aquatic sites. Terrain indices derived from 90 meter Shuttle Radar Topography Mission (SRTM) digital elevation data (DEM) were better at predicting water drainage patterns and characterizing the landscape than those derived from 30 m Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM. The low number of aquatic habitats available and the ability to locate the limited number of aquatic habitat locations for surveillance, especially those containing anopheline larvae, suggest that larval control maybe a cost-effective control measure in the fight against malaria in Zambia and other regions with seasonal

Habitat connectivity and ecosystem productivity: implications from a simple model.

USGS Publications Warehouse

Cloern, J.E.

2007-01-01

The import of resources (food, nutrients) sustains biological production and food webs in resource-limited habitats. Resource export from donor habitats subsidizes production in recipient habitats, but the ecosystem-scale consequences of resource translocation are generally unknown. Here, I use a nutrient-phytoplankton-zooplankton model to show how dispersive connectivity between a shallow autotrophic habitat and a deep heterotrophic pelagic habitat can amplify overall system production in metazoan food webs. This result derives from the finite capacity of suspension feeders to capture and assimilate food particles: excess primary production in closed autotrophic habitats cannot be assimilated by consumers; however, if excess phytoplankton production is exported to food-limited heterotrophic habitats, it can be assimilated by zooplankton to support additional secondary production. Transport of regenerated nutrients from heterotrophic to autotrophic habitats sustains higher system primary production. These simulation results imply that the ecosystem-scale efficiency of nutrient transformation into metazoan biomass can be constrained by the rate of resource exchange across habitats and that it is optimized when the transport rate matches the growth rate of primary producers. Slower transport (i.e., reduced connectivity) leads to nutrient limitation of primary production in autotrophic habitats and food limitation of secondary production in heterotrophic habitats. Habitat fragmentation can therefore impose energetic constraints on the carrying capacity of aquatic ecosystems. The outcomes of ecosystem restoration through habitat creation will be determined by both functions provided by newly created aquatic habitats and the rates of hydraulic connectivity between them.

MODELING PHYSICAL HABITAT PARAMETERS

EPA Science Inventory

Salmonid populations can be affected by alterations in stream physical habitat. Fish productivity is determined by the stream's physical habitat structure ( channel form, substrate distribution, riparian vegetation), water quality, flow regime and inputs from the watershed (sedim...

Two-dimensional hydrologic modeling to evaluate aquatic habitat conditions

Treesearch

Pamela Edwards; Frederica Wood; Michael Little; Peter Vila; Peter Vila

2006-01-01

We describe the modeling and mapping procedures used to examine aquatic habitat conditions and habitat suitability of a small river in north- central West Virginia where fish survival and reproduction in specific reaches are poor. The study includes: (1) surveying cross sections of streambed reaches and measuring discharges and corresponding water-surface elevations,...

Feeding habitat quality and behavioral trade-offs in chimpanzees: a case for species distribution models.

PubMed

Foerster, Steffen; Zhong, Ying; Pintea, Lilian; Murray, Carson M; Wilson, Michael L; Mjungu, Deus C; Pusey, Anne E

2016-01-01

The distribution and abundance of food resources are among the most important factors that influence animal behavioral strategies. Yet, spatial variation in feeding habitat quality is often difficult to assess with traditional methods that rely on extrapolation from plot survey data or remote sensing. Here, we show that maximum entropy species distribution modeling can be used to successfully predict small-scale variation in the distribution of 24 important plant food species for chimpanzees at Gombe National Park, Tanzania. We combined model predictions with behavioral observations to quantify feeding habitat quality as the cumulative dietary proportion of the species predicted to occur in a given location. This measure exhibited considerable spatial heterogeneity with elevation and latitude, both within and across main habitat types. We used model results to assess individual variation in habitat selection among adult chimpanzees during a 10-year period, testing predictions about trade-offs between foraging and reproductive effort. We found that nonswollen females selected the highest-quality habitats compared with swollen females or males, in line with predictions based on their energetic needs. Swollen females appeared to compromise feeding in favor of mating opportunities, suggesting that females rather than males change their ranging patterns in search of mates. Males generally occupied feeding habitats of lower quality, which may exacerbate energetic challenges of aggression and territory defense. Finally, we documented an increase in feeding habitat quality with community residence time in both sexes during the dry season, suggesting an influence of familiarity on foraging decisions in a highly heterogeneous landscape.

Predictive Seagrass Habitat Model

EPA Science Inventory

Restoration of ecosystem services provided by seagrass habitats in estuaries requires a firm understanding of the modes of action of multiple interacting stressors including nutrients, climate change, coastal land-use change, and habitat modification. We explored the application...

Transferability of habitat suitability models for nesting woodpeckers associated with wildfire

Treesearch

Quresh S. Latif; Vicki Saab; Jeff P. Hollenbeck; Jonathan G. Dudley

2016-01-01

Following wildfire, forest managers are challenged with meeting both socioeconomic demands (e.g., salvage logging) and mandates requiring habitat conservation for disturbance-associated wildlife (e.g., woodpeckers). Habitat suitability models for nesting woodpeckers can be informative, but tests of model transferability are needed to understand how broadly...

Habitat modeling and genetic signatures of postglacial recolonization for tidal estuaries

NASA Astrophysics Data System (ADS)

Dolby, G. A.; Jacobs, D. K.

2014-12-01

Pleistocene glacial cycles are a foremost influence on the genetic diversity and species distribution patterns observed today. Though much work has centered on biotic response to such climatic forcing, little of it has regarded estuarine or other aquatic coastal taxa whose habitat formation is a function of sea level, hydrography, and coastal geomorphology. These physical parameters required for habitat formation suggest that glacial cycles impart a significant effect on such taxa through glacially driven eustatic changes. Additionally, the steepened coastline and rainfall-limited Mediterranean climate suggest limited glacial habitat for estuarine species in southern and Baja California. Here we present GIS modeled habitat for tidal estuaries for three co-distributed estuarine fishes (Gillichthys mirabilis, Quietula y-cauda, Fundulus parvipinnis) since the last glacial maximum. Parameterization of sea level and slope enables biologically relevant temporal resolution of near-millennial scale. At lowstand our approach reveals two refuges along the coast at 1000km distance from each other, with habitat rapidly increasing 15 - 12 ka during meltwater pulse 1A. Habitat area peaked in the early Holocene and began decreasing with the current stillstand roughly 7 ka, probably as a result of coastal maturation towards less tidal systems. To target the postglacial recolonization process we applied discriminant function analysis to highly polymorphic microsatellite data to partition out the alleles associated with refuges identified a priori by habitat modeling. The frequencies of these alleles were calculated for all individuals at intervening populations and regressed against geographic distance. This analysis revealed nonlinear mixing curves, suggesting uneven allelic mixing efficiency along the coastline, perhaps as a result of differential habitat origination times as indicated by the habitat models. These results highlight the dynamism of estuarine habitat in recent

Evaluating habitat for black-footed ferrets: Revision of an existing model

USGS Publications Warehouse

Biggins, Dean E.; Lockhart, J. Michael; Godbey, Jerry L.

2006-01-01

Black-footed ferrets (Mustela nigripes) are highly dependent on prairie dogs (Cynomys spp.) as prey, and prairie dog colonies are the only known habitats that sustain black-footed ferret populations. An existing model used extensively for evaluating black-footed ferret reintroduction habitat defined complexes by interconnecting colonies with 7-km line segments. Although the 7-km complex remains a useful construct, we propose additional, smaller-scale evaluations that consider 1.5-km subcomplexes. The original model estimated the carrying capacity of complexes based on energy requirements of ferrets and density estimates of their prairie dog prey. Recent data have supported earlier contentions of intraspecific competition and intrasexual territorial behavior in ferrets. We suggest a revised model that retains the fixed linear relationship of the existing model when prairie dog densities are <18/ha and uses a curvilinear relationship that reflects increasing effects of ferret territoriality when there are 18–42 prairie dogs per hectare. We discuss possible effects of colony size and shape, interacting with territoriality, as justification for the exclusion of territorial influences if a prairie dog colony supports only a single female ferret. We also present data to support continued use of active prairie dog burrow densities as indices suitable for broad-scale estimates of prairie dog density. Calculation of percent of complexes that are occupied by prairie dog colonies was recommended as part of the original habitat evaluation process. That attribute has been largely ignored, resulting in rating anomalies.

Habitat model for the Florida Scrub Jay on John F. Kennedy Space Center

NASA Technical Reports Server (NTRS)

Breininger, David R.

1992-01-01

The Florida Scrub Jay is endemic to Florida. The John F. Kennedy Space Center (KSC) provides habitat for one of the three largest populations of the Florida Scrub Jay. This threatened bird occupies scrub, slash pine flatwoods, disturbed scrub, and coastal strand on KSC. Densities of Florida Scrub Jays were shown to vary with habitat characteristics but not necessarily with vegetation type. Relationships between Florida Scrub Jay densities and habitat characteristics were used to develop a habitat model to provide a tool to compare alternative sites for new facilities and to quantify environmental impacts. This model is being tested using long term demographic studies of colorbanded Florida Scrub Jays. Optimal habitat predicted by the model has greater than or equal to 50 percent of the shrub canopy comprised of scrub oaks, 20-50 percent open space or scrub oak vegetation within 100 m of a ruderal edge, less than or equal to 15 percent pine canopy cover, a shrub height of 120-170 cm, and is greater than or equal to 100 m from a forest. This document reviews life history, social behavior, food, foraging habitat, cover requirements, characteristics of habitat on KSC, and habitat preferences of the Florida Scrub Jay. Construction of the model and its limitations are discussed.

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type.

PubMed

Marshall, Leon; Carvalheiro, Luísa G; Aguirre-Gutiérrez, Jesús; Bos, Merijn; de Groot, G Arjen; Kleijn, David; Potts, Simon G; Reemer, Menno; Roberts, Stuart; Scheper, Jeroen; Biesmeijer, Jacobus C

2015-10-01

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs' usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and

Using a remote sensing/GIS model to predict southwestern Willow Flycatcher breeding habitat along the Rio Grande, New Mexico

USGS Publications Warehouse

Hatten, James R.; Sogge, Mark K.

2007-01-01

middle Rio Grande). The SWFL Recovery Plan (USFWS 2002) recognizes the importance of developing new approaches to habitat identification, and recommends the development of drainage-scale, quantitative habitat models. In particular, the plan suggests using models based on remote sensing and Geographic Information System (GIS) technology that can capture the relatively dynamic habitat changes that occur in southwestern riparian systems. In 1999, Arizona Game and Fish Department (AGFD) developed a GIS-based model (Hatten and Paradzick 2003) to identify SWFL breeding habitat from Landsat Thematic Mapper imagery and 30-m resolution digital elevation models (DEMs). The model was developed with presence/absence survey data acquired along the San Pedro and Gila rivers, and from the Salt River and Tonto Creek inlets to Roosevelt Lake in southern Arizona (collectively called the project area). The GIS-based model used a logistic regression equation to divide riparian vegetation into 5 probability classes based upon characteristics of riparian vegetation and floodplain size. This model was tested by predicting SWFL breeding habitat at Alamo Lake, Arizona, located 200 km from the project area (Hatten and Paradzick 2003). The GIS-based model performed as expected by identifying riparian areas with the highest SWFL nest densities, located in the higher probability classes. In 2002, AGFD applied the GIS-based model throughout Arizona, for riparian areas below 1,524 m (5,000 ft) elevation and within 1.6 km of perennial or intermittent waters (Dockens et al. 2004). Overall model accuracy (using probability classes 1-5, with class 5 having the greatest probability of nesting activity) for predicting the location of 2001 nest sites was 96.5 percent; accuracy decreased when fewer probability classes were defined as suitable. Map accuracy, determined from errors of commission, increased in higher probability classes in a fashion similar to errors of omission. Map accuracy, li

The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps

Treesearch

Steven H. Ackers; Raymond J. Davis; Keith A. Olsen; Katie M. Dugger

2015-01-01

Wildlife habitat mapping has evolved at a rapid pace over the last fewdecades. Beginning with simple, often subjective, hand-drawn maps, habitat mapping now involves complex species distribution models (SDMs) using mapped predictor variables derived from remotely sensed data. For species that inhabit large geographic areas, remote sensing technology is often...

Structural habitat predicts functional dispersal habitat of a large carnivore: how leopards change spots.

PubMed

Fattebert, Julien; Robinson, Hugh S; Balme, Guy; Slotow, Rob; Hunter, Luke

2015-10-01

Natal dispersal promotes inter-population linkage, and is key to spatial distribution of populations. Degradation of suitable landscape structures beyond the specific threshold of an individual's ability to disperse can therefore lead to disruption of functional landscape connectivity and impact metapopulation function. Because it ignores behavioral responses of individuals, structural connectivity is easier to assess than functional connectivity and is often used as a surrogate for landscape connectivity modeling. However using structural resource selection models as surrogate for modeling functional connectivity through dispersal could be erroneous. We tested how well a second-order resource selection function (RSF) models (structural connectivity), based on GPS telemetry data from resident adult leopard (Panthera pardus L.), could predict subadult habitat use during dispersal (functional connectivity). We created eight non-exclusive subsets of the subadult data based on differing definitions of dispersal to assess the predictive ability of our adult-based RSF model extrapolated over a broader landscape. Dispersing leopards used habitats in accordance with adult selection patterns, regardless of the definition of dispersal considered. We demonstrate that, for a wide-ranging apex carnivore, functional connectivity through natal dispersal corresponds to structural connectivity as modeled by a second-order RSF. Mapping of the adult-based habitat classes provides direct visualization of the potential linkages between populations, without the need to model paths between a priori starting and destination points. The use of such landscape scale RSFs may provide insight into predicting suitable dispersal habitat peninsulas in human-dominated landscapes where mitigation of human-wildlife conflict should be focused. We recommend the use of second-order RSFs for landscape conservation planning and propose a similar approach to the conservation of other wide-ranging large

Multi-scale habitat selection modeling: A review and outlook

Treesearch

Kevin McGarigal; Ho Yi Wan; Kathy A. Zeller; Brad C. Timm; Samuel A. Cushman

2016-01-01

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

Stratification of habitats for identifying habitat selection by Merriam's turkeys

Treesearch

Mark A. Rumble; Stanley H. Anderson

1992-01-01

Habitat selection patterns of Merriam’s Turkeys were compared in hierarchical analyses of three levels of habitat stratification. Habitat descriptions in first-level analyses were based on dominant species of vegetation. Habitat descriptions in second-level analyses were based on dominant species of vegetation and overstory canopy cover. Habitat descriptions in third-...

Development and evaluation of habitat models for herpetofauna and small mammals

Treesearch

William M. Block; Michael L. Morrison; Peter E. Scott

1998-01-01

We evaluated the ability of discriminant analysis (DA), logistic regression (LR), and multiple regression (MR) to describe habitat use by amphibians, reptiles, and small mammals found in California oak woodlands. We also compared models derived from pitfall and live trapping data for several species. Habitat relations modeled by DA and LR produced similar results,...

Models that predict standing crop of stream fish from habitat variables: 1950-85.

Treesearch

K.D. Fausch; C.L. Hawkes; M.G. Parsons

1988-01-01

We reviewed mathematical models that predict standing crop of stream fish (number or biomass per unit area or length of stream) from measurable habitat variables and classified them by the types of independent habitat variables found significant, by mathematical structure, and by model quality. Habitat variables were of three types and were measured on different scales...

Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.

PubMed

Keith, David A; Akçakaya, H Resit; Thuiller, Wilfried; Midgley, Guy F; Pearson, Richard G; Phillips, Steven J; Regan, Helen M; Araújo, Miguel B; Rebelo, Tony G

2008-10-23

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.

Varying congruence among spatial patterns of vascular plants and vertebrates based on habitat groups.

PubMed

Xu, Haigen; Cao, Yun; Cao, Mingchang; Wu, Jun; Wu, Yi; Le, Zhifang; Cui, Peng; Li, Jiaqi; Ma, Fangzhou; Liu, Li; Hu, Feilong; Chen, Mengmeng; Tong, Wenjun

2017-11-01

Proxies are adopted to represent biodiversity patterns due to inadequate information for all taxa. Despite the wide use of proxies, their efficacy remains unclear. Previous analyses focused on overall species richness for fewer groups, affecting the generality and depth of inference. Biological taxa often exhibit very different habitat preferences. Habitat groupings may be an appropriate approach to advancing the study of richness patterns. Diverse geographical patterns of species richness and their potential mechanisms were then examined for habitat groups. We used a database of the spatial distribution of 32,824 species of mammals, birds, reptiles, amphibians and plants from 2,376 counties across China, divided the five taxa into 30 habitat groups, calculated Spearman correlations of species richness among taxa and habitat groups, and tested five hypotheses about richness patterns using multivariate models. We identified one major group [i.e., forest- and shrub-dependent (FS) groups], and some minor groups such as grassland-dependent vertebrates and desert-dependent vertebrates. There were mostly high or moderate correlations among FS groups, but mostly low or moderate correlations among other habitat groups. The prominent variables differed among habitat groups of the same taxon, such as birds and reptiles. The sets of predictors were also different within the same habitat, such as forests, grasslands, and deserts. Average correlations among the same habitat groups of vertebrates and among habitat groups of a single taxon were low or moderate, except correlations among FS groups. The sets of prominent variables of species richness differed strongly among habitat groups, although elevation range was the most important variable for most FS groups. The ecological and evolutionary processes that underpin richness patterns might be disparate among different habitat groups. Appropriate groupings based on habitats could reveal important patterns of richness gradients

MODELING THE DYNAMICS OF WILDLIFE HABITAT AND POPULATIONS AT THE LANDSCAPE SCALE

EPA Science Inventory

A forest dynamics model (FORCLIM) was linked to a spatial wildlife population model (PATCH) to assess the effects of habitat change in a landscape on selected wildlife species. The habitat changes included forest responses to harvesting, development, and climate change on a west...

A spatial model to assess the effects of hydropower operations on Columbia River fall Chinook Salmon spawning habitat

USGS Publications Warehouse

Hatten, James R.; Tiffan, Kenneth F.; Anglin, Donald R.; Haeseker, Steven L.; Skalicky, Joseph J.; Schaller, Howard

2009-01-01

Priest Rapids Dam on the Columbia River produces large daily and hourly streamflow fluctuations throughout the Hanford Reach during the period when fall Chinook salmon Oncorhynchus tshawytscha are selecting spawning habitat, constructing redds, and actively engaged in spawning. Concern over the detrimental effects of these fluctuations prompted us to quantify the effects of variable flows on the amount and persistence of fall Chinook salmon spawning habitat in the Hanford Reach. Specifically, our goal was to develop a management tool capable of quantifying the effects of current and alternative hydrographs on predicted spawning habitat in a spatially explicit manner. Toward this goal, we modeled the water velocities and depths that fall Chinook salmon experienced during the 2004 spawning season, plus what they would probably have experienced under several alternative (i.e., synthetic) hydrographs, using both one- and two-dimensional hydrodynamic models. To estimate spawning habitat under existing or alternative hydrographs, we used cell-based modeling and logistic regression to construct and compare numerous spatial habitat models. We found that fall Chinook salmon were more likely to spawn at locations where velocities were persistently greater than 1 m/s and in areas where fluctuating water velocities were reduced. Simulations of alternative dam operations indicate that the quantity of spawning habitat is expected to increase as streamflow fluctuations are reduced during the spawning season. The spatial habitat models that we developed provide management agencies with a quantitative tool for predicting, in a spatially explicit manner, the effects of different flow regimes on fall Chinook salmon spawning habitat in the Hanford Reach. In addition to characterizing temporally varying habitat conditions, our research describes an analytical approach that could be applied in other highly variable aquatic systems.

Using dynamic Brownian bridge movement modelling to measure temporal patterns of habitat selection.

PubMed

Byrne, Michael E; Clint McCoy, J; Hinton, Joseph W; Chamberlain, Michael J; Collier, Bret A

2014-09-01

Accurately describing animal space use is vital to understanding how wildlife use habitat. Improvements in GPS technology continue to facilitate collection of telemetry data at high spatial and temporal resolutions. Application of the recently introduced dynamic Brownian bridge movement model (dBBMM) to such data is promising as the method explicitly incorporates the behavioural heterogeneity of a movement path into the estimated utilization distribution (UD). Utilization distributions defining space use are normally estimated for time-scales ranging from weeks to months, obscuring much of the fine-scale information available from high-volume GPS data sets. By accounting for movement heterogeneity, the dBBMM provides a rigorous, behaviourally based estimate of space use between each set of relocations. Focusing on UDs generated between individual sets of locations allows us to quantify fine-scale circadian variation in habitat use. We used the dBBMM to estimate UDs bounding individual time steps for three terrestrial species with different life histories to illustrate how the method can be used to identify fine-scale variations in habitat use. We also demonstrate how dBBMMs can be used to characterize circadian patterns of habitat selection and link fine-scale patterns of habitat use to behaviour. We observed circadian patterns of habitat use that varied seasonally for a white-tailed deer (Odocoileus virginianus) and coyote (Canis latrans). We found seasonal patterns in selection by the white-tailed deer and were able to link use of conifer forests and agricultural fields to behavioural state of the coyote. Additionally, we were able to quantify the date in which a Rio Grande wild turkey (Meleagris gallopavo intermedia) initiated laying as well as when during the day, she was most likely to visit the nest site to deposit eggs. The ability to quantify circadian patterns of habitat use may have important implications for research and management of wildlife

Restoring and rehabilitating sagebrush habitats

USGS Publications Warehouse

Pyke, David A.; Knick, S.T.; Connelly, J.W.

2011-01-01

Less than half of the original habitat of the Greater Sage-Grouse (Centrocercus uropha-sianus) currently exists. Some has been perma-nently lost to farms and urban areas, but the remaining varies in condition from high quality to no longer adequate. Restoration of sagebrush (Artemisia spp.) grassland ecosystems may be pos-sible for resilient lands. However, Greater Sage-Grouse require a wide variety of habitats over large areas to complete their life cycle. Effective restoration will require a regional approach for prioritizing and identifying appropriate options across the landscape. A landscape triage method is recommended for prioritizing lands for restora-tion. Spatial models can indicate where to protect and connect intact quality habitat with other simi-lar habitat via restoration. The ecological site con-cept of land classification is recommended for characterizing potential habitat across the region along with their accompanying state and transi-tion models of plant community dynamics. These models assist in identifying if passive, manage-ment-based or active, vegetation manipulation?based restoration might accomplish the goals of improved Greater Sage-Grouse habitat. A series of guidelines help formulate questions that manag-ers might consider when developing restoration plans: (1) site prioritization through a landscape triage; (2) soil verification and the implications of soil features on plant establishment success; (3) a comparison of the existing plant community to the potential for the site using ecological site descriptions; (4) a determination of the current successional status of the site using state and transition models to aid in predicting if passive or active restoration is necessary; and (5) implemen-tation of post-treatment monitoring to evaluate restoration effectiveness and post-treatment man-agement implications to restoration success.

Lunar Contour Crafting: A Novel Technique for ISRU-Based Habitat Development

NASA Technical Reports Server (NTRS)

Khoshnevis, Behrokh; Bodiford, Melanie P.; Burks, Kevin H.; Ethridge, Ed; Tucker, Dennis; Kim, Won; Toutanji, Houssam; Fiske, Michael R.

2005-01-01

1. Habitat Structures at MSFC is one element of the In-Situ Fabrication and Repair (ISFR) Program: ISFR develops technologies for fabrication, repair and recycling of tools, parts, and habitats/structures using in-situ resources. ISRU - based habitat structures are considered Class III. 2. Habitat Structure Purpose: Develop Lunar and/or Martian habitat structures for manned missions that maximize the use of in-situ resources to address the following agency topics: bioastronautics critical path roadmap; strategic technical challenges defined in H&RT formulation plan: margins and redundancy; modularity, robotic network, space resource utilization; autonomy, affordable logistics pre-positioning.

[Influence of road on breeding habitat of Nipponia nippon based on MaxEnt model].

PubMed

Zhang, Hui; Gao, Ji Xi; Ma, Meng Xiao; Shao, Fang Ze; Wang, Qiao; Li, Guang Yu; Qiu, Jie; Zhou, Ke Xin

2017-04-18

Quantitative study on effects of roads on suitable breeding habitats of wildlife is one of topics that need in-depth research in road ecology. Crested ibis (Nipponia nippon), a first class nationally protected bird species, is the species of interest in this research. Using the Maximum Entropy Models (MaxEnt) in the Species Distribution Model (SDM) toolbox of ArcGIS, autocorrelation of environmental variables were analyzed and environmental variables with r>0.8 were removed. Ten environmental variables were chosen as impact factors for the breeding habitat of crested ibis, including mean temperature of coldest quarter, landscape type, normalized difference vegetation index(NDVI), slope, aspect, distance to waters, distance to paddy field, distance to high-grade roads (expressway, national way, provincial way), and distance to low-grade roads (country road). By analyzing the contribution rate of each environmental variable, the results showed that the mean temperature of coldest quarter, landscape type, distance to paddy field, and distance to high-grade roads were the main factors determining breeding habitat of crested ibis. The suitable distribution of crested ibis' nesting area was under the following scenarios: variable road present (scenario1), high-grade road absent (scenario2), and low-grade road absent (scenario 3). The results showed that the presence of roads affected suitable nesting areas of crested ibis with high-grade roads showing a larger influence than low-grade roads. The presence of high-grade roads and low-grade roads decreased the suitable nesting areas of crested ibis by 66.23 and 35.69 km 2 , respectively. The crested ibis preferred to nest in areas distant from high-grade roads, with an average road avoidance distance of 1500 m. This study was of great significance for formulating management measures to protect crested ibis and provide a reference for quantitative assessment on impacts of engineering and construction projects on wildlife.

Biodiversity and Habitat Markets—Policy, Economic, and Ecological implications of Market-Based Conservation

USGS Publications Warehouse

Pindilli, Emily J.; Casey, Frank

2015-10-26

This report is a primer on market-like and market-based mechanisms designed to conserve biodiversity and habitat. The types of markets and market-based approaches that were implemented or are emerging to benefit biodiversity and habitat in the United States are examined. The central approaches considered in this report include payments for ecosystem services, conservation banks, habitat exchanges, and eco-labels. Based on literature reviews and input from experts and practitioners, the report characterizes each market-based approach including policy context and structure; the theoretical basis for applying market-based approaches; the ecological effectiveness of practices and tools for measuring performance; and the future outlook for biodiversity and habitat markets. This report draws from previous research and serves as a summary of pertinent information associated with biodiversity and habitat markets while providing references to materials that go into greater detail on specific topics.

Defining habitat covariates in camera-trap based occupancy studies

PubMed Central

Niedballa, Jürgen; Sollmann, Rahel; Mohamed, Azlan bin; Bender, Johannes; Wilting, Andreas

2015-01-01

In species-habitat association studies, both the type and spatial scale of habitat covariates need to match the ecology of the focal species. We assessed the potential of high-resolution satellite imagery for generating habitat covariates using camera-trapping data from Sabah, Malaysian Borneo, within an occupancy framework. We tested the predictive power of covariates generated from satellite imagery at different resolutions and extents (focal patch sizes, 10–500 m around sample points) on estimates of occupancy patterns of six small to medium sized mammal species/species groups. High-resolution land cover information had considerably more model support for small, patchily distributed habitat features, whereas it had no advantage for large, homogeneous habitat features. A comparison of different focal patch sizes including remote sensing data and an in-situ measure showed that patches with a 50-m radius had most support for the target species. Thus, high-resolution satellite imagery proved to be particularly useful in heterogeneous landscapes, and can be used as a surrogate for certain in-situ measures, reducing field effort in logistically challenging environments. Additionally, remote sensed data provide more flexibility in defining appropriate spatial scales, which we show to impact estimates of wildlife-habitat associations. PMID:26596779

VisTrails SAHM: visualization and workflow management for species habitat modeling

USGS Publications Warehouse

Morisette, Jeffrey T.; Jarnevich, Catherine S.; Holcombe, Tracy R.; Talbert, Colin B.; Ignizio, Drew A.; Talbert, Marian; Silva, Claudio; Koop, David; Swanson, Alan; Young, Nicholas E.

2013-01-01

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.

Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management

USGS Publications Warehouse

Coates, Peter S.; Casazza, Michael L.; Brussee, Brianne E.; Ricca, Mark A.; Gustafson, K. Benjamin; Overton, Cory T.; Sanchez-Chopitea, Erika; Kroger, Travis; Mauch, Kimberly; Niell, Lara; Howe, Kristy; Gardner, Scott; Espinosa, Shawn; Delehanty, David J.

2014-01-01

Greater sage-grouse (Centrocercus urophasianus, hereafter referred to as “sage-grouse”) populations are declining throughout the sagebrush (Artemisia spp.) ecosystem, including millions of acres of potential habitat across the West. Habitat maps derived from empirical data are needed given impending listing decisions that will affect both sage-grouse population dynamics and human land-use restrictions. This report presents the process for developing spatially explicit maps describing relative habitat suitability for sage-grouse in Nevada and northeastern California. Maps depicting habitat suitability indices (HSI) values were generated based on model-averaged resource selection functions informed by more than 31,000 independent telemetry locations from more than 1,500 radio-marked sage-grouse across 12 project areas in Nevada and northeastern California collected during a 15-year period (1998–2013). Modeled habitat covariates included land cover composition, water resources, habitat configuration, elevation, and topography, each at multiple spatial scales that were relevant to empirically observed sage-grouse movement patterns. We then present an example of how the HSI can be delineated into categories. Specifically, we demonstrate that the deviation from the mean can be used to classify habitat suitability into three categories of habitat quality (high, moderate, and low) and one non-habitat category. The classification resulted in an agreement of 93–97 percent for habitat versus non-habitat across a suite of independent validation datasets. Lastly, we provide an example of how space use models can be integrated with habitat models to help inform conservation planning. In this example, we combined probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek (traditional breeding ground) using count data to calculate a composite space use index (SUI). The SUI was then classified into two categories of use

Evaluating Habitat Suitability for the Establishment of Monochamus spp. through Climate-Based Niche Modeling

PubMed Central

Estay, Sergio A.; Labra, Fabio A.; Sepulveda, Roger D.; Bacigalupe, Leonardo D.

2014-01-01

Pine sawyer beetle species of the genus Monochamus are vectors of the nematode pest Bursaphelenchus xylophilus. The introduction of these species into new habitats is a constant threat for those regions where the forestry industry depends on conifers, and especially on species of Pinus. To obtain information about the potential risk of establishment of these insects in Chile, we performed climate-based niche modeling using data for five North American and four Eurasian Monochamus species using a Maxent approach. The most important variables that account for current distribution of these species are total annual precipitation and annual and seasonal average temperatures, with some differences between North American and Eurasian species. Projections of potential geographic distribution in Chile show that all species could occupy at least 37% of the area between 30° and 53°S, where industrial plantations of P. radiata are concentrated. Our results indicated that Chile seems more suitable for Eurasian than for North American species. PMID:25019408

Modelling riverine habitat for robust redhorse: assessment for reintroduction of an imperilled species

USGS Publications Warehouse

Fisk, J. M.; Kwak, Thomas J.; Heise, R. J.

2014-01-01

A critical component of a species reintroduction is assessment of contemporary habitat suitability. The robust redhorse, Moxostoma robustum (Cope), is an imperilled catostomid that occupies a restricted range in the south-eastern USA. A remnant population persists downstream of Blewett Falls Dam, the terminal dam in the Pee Dee River, North Carolina. Reintroduction upstream of Blewett Falls Dam may promote long-term survival of this population. Tillery Dam is the next hydroelectric facility upstream, which includes a 30 rkm lotic reach. Habitat suitability indices developed in the Pee Dee River were applied to model suitable habitat for proposed minimum flows downstream of Tillery Dam. Modelling results indicate that the Tillery reach provides suitable robust redhorse habitat, with spawning habitat more abundant than non-spawning habitat. Sensitivity analyses suggested that suitable water depth and substrate were limiting physical habitat variables. These results can inform decisions on flow regulation and guide planning for reintroduction of the robust redhorse and other species.

Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

PubMed

Gogol-Prokurat, Melanie

2011-01-01

If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables

Evaluating habitat suitability models for nesting white-headed woodpeckers in unburned forest

Treesearch

Quresh S. Latif; Victoria A. Saab; Kim Mellen-Mclean; Jonathan G. Dudley

2015-01-01

Habitat suitability models can provide guidelines for species conservation by predicting where species of interest are likely to occur. Presence-only models are widely used but typically provide only relative indices of habitat suitability (HSIs), necessitating rigorous evaluation often using independently collected presence-absence data. We refined and evaluated...

Model development for the assessment of terrestrial and aquatic habitat quality in conservation planning.

PubMed

Terrado, Marta; Sabater, Sergi; Chaplin-Kramer, Becky; Mandle, Lisa; Ziv, Guy; Acuña, Vicenç

2016-01-01

There is a growing pressure of human activities on natural habitats, which leads to biodiversity losses. To mitigate the impact of human activities, environmental policies are developed and implemented, but their effects are commonly not well understood because of the lack of tools to predict the effects of conservation policies on habitat quality and/or diversity. We present a straightforward model for the simultaneous assessment of terrestrial and aquatic habitat quality in river basins as a function of land use and anthropogenic threats to habitat that could be applied under different management scenarios to help understand the trade-offs of conservation actions. We modify the InVEST model for the assessment of terrestrial habitat quality and extend it to freshwater habitats. We assess the reliability of the model in a severely impaired basin by comparing modeled results to observed terrestrial and aquatic biodiversity data. Estimated habitat quality is significantly correlated with observed terrestrial vascular plant richness (R(2)=0.76) and diversity of aquatic macroinvertebrates (R(2)=0.34), as well as with ecosystem functions such as in-stream phosphorus retention (R(2)=0.45). After that, we analyze different scenarios to assess the suitability of the model to inform changes in habitat quality under different conservation strategies. We believe that the developed model can be useful to assess potential levels of biodiversity, and to support conservation planning given its capacity to forecast the effects of management actions in river basins. Copyright © 2015 Elsevier B.V. All rights reserved.

Hydrologic and water-quality rehabilitation of environments for suitable fish habitat

NASA Astrophysics Data System (ADS)

Zhao, C. S.; Yang, S. T.; Xiang, H.; Liu, C. M.; Zhang, H. T.; Yang, Z. L.; Zhang, Y.; Sun, Y.; Mitrovic, S. M.; Yu, Q.; Lim, R. P.

2015-11-01

Aquatic ecological rehabilitation is attracting increasing public and research attention, but without knowledge of the responses of aquatic species to their habitats the success of habitat restoration is uncertain. Thus efficient study of species response to habitat, through which to prioritize the habitat factors influencing aquatic ecosystems, is highly important. However many current models have too high requirement for assemblage information and have great bias in results due to consideration of only the species' attribute of presence/absence, abundance or biomass, thus hindering the wider utility of these models. This paper, using fish as a case, presents a framework for identification of high-priority habitat factors based on the responses of aquatic species to their habitats, using presence/absence, abundance and biomass data. This framework consists of four newly developed sub-models aiming to determine weightings for the evaluation of species' contributions to their communities, to quantitatively calculate an integrated habitat suitability index for multi-species based on habitat factors, to assess the suitable probability of habitat factors and to assess the rehabilitation priority of habitat factors. The framework closely links hydrologic, physical and chemical habitat factors to fish assemblage attributes drawn from monitoring datasets on hydrology, water quality and fish assemblages at a total of 144 sites, where 5084 fish were sampled and tested. Breakpoint identification techniques based on curvature in cumulated dominance along with a newly developed weighting calculation model based on theory of mass systems were used to help identify the dominant fish, based on which the presence and abundance of multiple fish were normalized to estimate the integrated habitat suitability index along gradients of various factors, based on their variation with principal habitat factors. Then, the appropriate probability of every principal habitat factor was

Assessing habitat connectivity for ground-dwelling animals in an urban environment.

PubMed

Braaker, S; Moretti, M; Boesch, R; Ghazoul, J; Obrist, M K; Bontadina, F

To ensure viable species populations in fragmented landscapes, individuals must be able to move between suitable habitat patches. Despite the increased interest in biodiversity assessment in urban environments, the ecological relevance of habitat connectivity in highly fragmented landscapes remains largely unknown. The first step to understanding the role of habitat connectivity in urban ecology is the challenging task of assessing connectivity in the complex patchwork of contrasting habitats that is found in cities. We developed a data-based framework, minimizing the use of subjective assumptions, to assess habitat connectivity that consists of the following sequential steps: (1) identification of habitat preference based on empirical habitat-use data; (2) derivation of habitat resistance surfaces evaluating various transformation functions; (3) modeling of different connectivity maps with electrical circuit theory (Circuitscape), a method considering all possible pathways across the landscape simultaneously; and (4) identification of the best connectivity map with information-theoretic model selection. We applied this analytical framework to assess habitat connectivity for the European hedgehog Erinaceus europaeus, a model species for ground-dwelling animals, in the city of Zurich, Switzerland, using GPS track points from 40 individuals. The best model revealed spatially explicit connectivity “pinch points,” as well as multiple habitat connections. Cross-validation indicated the general validity of the selected connectivity model. The results show that both habitat connectivity and habitat quality affect the movement of urban hedgehogs (relative importance of the two variables was 19.2% and 80.8%, respectively), and are thus both relevant for predicting urban animal movements. Our study demonstrates that even in the complex habitat patchwork of cities, habitat connectivity plays a major role for ground-dwelling animal movement. Data-based habitat connectivity

Translating statistical species-habitat models to interactive decision support tools

USGS Publications Warehouse

Wszola, Lyndsie S.; Simonsen, Victoria L.; Stuber, Erica F.; Gillespie, Caitlyn R.; Messinger, Lindsey N.; Decker, Karie L.; Lusk, Jeffrey J.; Jorgensen, Christopher F.; Bishop, Andrew A.; Fontaine, Joseph J.

2017-01-01

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.

Translating statistical species-habitat models to interactive decision support tools.

PubMed

Wszola, Lyndsie S; Simonsen, Victoria L; Stuber, Erica F; Gillespie, Caitlyn R; Messinger, Lindsey N; Decker, Karie L; Lusk, Jeffrey J; Jorgensen, Christopher F; Bishop, Andrew A; Fontaine, Joseph J

2017-01-01

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.

Translating statistical species-habitat models to interactive decision support tools

PubMed Central

Simonsen, Victoria L.; Stuber, Erica F.; Gillespie, Caitlyn R.; Messinger, Lindsey N.; Decker, Karie L.; Lusk, Jeffrey J.; Jorgensen, Christopher F.; Bishop, Andrew A.; Fontaine, Joseph J.

2017-01-01

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences. PMID:29236707

Transferability of species distribution models: a functional habitat approach for two regionally threatened butterflies.

PubMed

Vanreusel, Wouter; Maes, Dirk; Van Dyck, Hans

2007-02-01

Numerous models for predicting species distribution have been developed for conservation purposes. Most of them make use of environmental data (e.g., climate, topography, land use) at a coarse grid resolution (often kilometres). Such approaches are useful for conservation policy issues including reserve-network selection. The efficiency of predictive models for species distribution is usually tested on the area for which they were developed. Although highly interesting from the point of view of conservation efficiency, transferability of such models to independent areas is still under debate. We tested the transferability of habitat-based predictive distribution models for two regionally threatened butterflies, the green hairstreak (Callophrys rubi) and the grayling (Hipparchia semele), within and among three nature reserves in northeastern Belgium. We built predictive models based on spatially detailed maps of area-wide distribution and density of ecological resources. We used resources directly related to ecological functions (host plants, nectar sources, shelter, microclimate) rather than environmental surrogate variables. We obtained models that performed well with few resource variables. All models were transferable--although to different degrees--among the independent areas within the same broad geographical region. We argue that habitat models based on essential functional resources could transfer better in space than models that use indirect environmental variables. Because functional variables can easily be interpreted and even be directly affected by terrain managers, these models can be useful tools to guide species-adapted reserve management.

Modeling mountain pine beetle habitat suitability within Sequoia National Park

NASA Astrophysics Data System (ADS)

Nguyen, Andrew

Understanding significant changes in climate and their effects on timber resources can help forest managers make better decisions regarding the preservation of natural resources and land management. These changes may to alter natural ecosystems dependent on historical and current climate conditions. Increasing mountain pine beetle (MBP) outbreaks within the southern Sierra Nevada are the result of these alterations. This study better understands MPB behavior within Sequoia National Park (SNP) and model its current and future habitat distribution. Variables contributing to MPB spread are vegetation stress, soil moisture, temperature, precipitation, disturbance, and presence of Ponderosa (Pinus ponderosa) and Lodgepole (Pinus contorta) pine trees. These variables were obtained using various modeled, insitu, and remotely sensed sources. The generalized additive model (GAM) was used to calculate the statistical significance of each variable contributing to MPB spread and also created maps identifying habitat suitability. Results indicate vegetation stress and forest disturbance to be variables most indicative of MPB spread. Additionally, the model was able to detect habitat suitability of MPB with a 45% accuracy concluding that a geospatial driven modeling approach can be used to delineate potential MPB spread within SNP.

A Modelling Framework to Assess the Effect of Pressures on River Abiotic Habitat Conditions and Biota

PubMed Central

Kail, Jochem; Guse, Björn; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Kleinhans, Maarten; Schuurman, Filip; Fohrer, Nicola; Hering, Daniel; Wolter, Christian

2015-01-01

River biota are affected by global reach-scale pressures, but most approaches for predicting biota of rivers focus on river reach or segment scale processes and habitats. Moreover, these approaches do not consider long-term morphological changes that affect habitat conditions. In this study, a modelling framework was further developed and tested to assess the effect of pressures at different spatial scales on reach-scale habitat conditions and biota. Ecohydrological and 1D hydrodynamic models were used to predict discharge and water quality at the catchment scale and the resulting water level at the downstream end of a study reach. Long-term reach morphology was modelled using empirical regime equations, meander migration and 2D morphodynamic models. The respective flow and substrate conditions in the study reach were predicted using a 2D hydrodynamic model, and the suitability of these habitats was assessed with novel habitat models. In addition, dispersal models for fish and macroinvertebrates were developed to assess the re-colonization potential and to finally compare habitat suitability and the availability / ability of species to colonize these habitats. Applicability was tested and model performance was assessed by comparing observed and predicted conditions in the lowland Treene River in northern Germany. Technically, it was possible to link the different models, but future applications would benefit from the development of open source software for all modelling steps to enable fully automated model runs. Future research needs concern the physical modelling of long-term morphodynamics, feedback of biota (e.g., macrophytes) on abiotic habitat conditions, species interactions, and empirical data on the hydraulic habitat suitability and dispersal abilities of macroinvertebrates. The modelling framework is flexible and allows for including additional models and investigating different research and management questions, e.g., in climate impact research as well

Combining a dispersal model with network theory to assess habitat connectivity.

PubMed

Lookingbill, Todd R; Gardner, Robert H; Ferrari, Joseph R; Keller, Cherry E

2010-03-01

Assessing the potential for threatened species to persist and spread within fragmented landscapes requires the identification of core areas that can sustain resident populations and dispersal corridors that can link these core areas with isolated patches of remnant habitat. We developed a set of GIS tools, simulation methods, and network analysis procedures to assess potential landscape connectivity for the Delmarva fox squirrel (DFS; Sciurus niger cinereus), an endangered species inhabiting forested areas on the Delmarva Peninsula, USA. Information on the DFS's life history and dispersal characteristics, together with data on the composition and configuration of land cover on the peninsula, were used as input data for an individual-based model to simulate dispersal patterns of millions of squirrels. Simulation results were then assessed using methods from graph theory, which quantifies habitat attributes associated with local and global connectivity. Several bottlenecks to dispersal were identified that were not apparent from simple distance-based metrics, highlighting specific locations for landscape conservation, restoration, and/or squirrel translocations. Our approach links simulation models, network analysis, and available field data in an efficient and general manner, making these methods useful and appropriate for assessing the movement dynamics of threatened species within landscapes being altered by human and natural disturbances.

Chapter 5: Application of state-and-transition models to evaluate wildlife habitat

Treesearch

Anita T. Morzillo; Pamela Comeleo; Blair Csuti; Stephanie Lee

2014-01-01

Wildlife habitat analysis often is a central focus of natural resources management and policy. State-and-transition models (STMs) allow for simulation of landscape level ecological processes, and for managers to test “what if” scenarios of how those processes may affect wildlife habitat. This chapter describes the methods used to link STM output to wildlife habitat to...

Estimating habitat volume of living resources using three-dimensional circulation and biogeochemical models

NASA Astrophysics Data System (ADS)

Smith, Katharine A.; Schlag, Zachary; North, Elizabeth W.

2018-07-01

Coupled three-dimensional circulation and biogeochemical models predict changes in water properties that can be used to define fish habitat, including physiologically important parameters such as temperature, salinity, and dissolved oxygen. However, methods for calculating the volume of habitat defined by the intersection of multiple water properties are not well established for coupled three-dimensional models. The objectives of this research were to examine multiple methods for calculating habitat volume from three-dimensional model predictions, select the most robust approach, and provide an example application of the technique. Three methods were assessed: the "Step," "Ruled Surface", and "Pentahedron" methods, the latter of which was developed as part of this research. Results indicate that the analytical Pentahedron method is exact, computationally efficient, and preserves continuity in water properties between adjacent grid cells. As an example application, the Pentahedron method was implemented within the Habitat Volume Model (HabVol) using output from a circulation model with an Arakawa C-grid and physiological tolerances of juvenile striped bass (Morone saxatilis). This application demonstrates that the analytical Pentahedron method can be successfully applied to calculate habitat volume using output from coupled three-dimensional circulation and biogeochemical models, and it indicates that the Pentahedron method has wide application to aquatic and marine systems for which these models exist and physiological tolerances of organisms are known.

Habitat destruction and the extinction debt revisited

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loehle, C.

1996-02-01

A very important analysis of the problem of habitat destruction concluded that such destruction may lead to an extinction debt, which is the irreversible loss of species following a prolonged transient or delay. An error in interpretation of this model led the authors to apply the results to all types of habitat destruction, but in fact the model applies only to an across-the-board decrease in fecundity, not to disturbances. For repeated, spatially random disturbance, a different model applies. For habitat destruction on regional scales (reduction in ecosystem area without disturbance in remnant areas), one must, in contrast, apply species-area relationsmore » based on the distribution of different habitat types (e.g., elevational and rainfall gradients, physiographic and edaphic variability). The error in interpretation of the basic model is presented, followed by clarification of model usage and development of a new model that applies to disturbance events.« less

Bridging gaps: On the performance of airborne LiDAR to model wood mouse-habitat structure relationships in pine forests.

PubMed

Jaime-González, Carlos; Acebes, Pablo; Mateos, Ana; Mezquida, Eduardo T

2017-01-01

LiDAR technology has firmly contributed to strengthen the knowledge of habitat structure-wildlife relationships, though there is an evident bias towards flying vertebrates. To bridge this gap, we investigated and compared the performance of LiDAR and field data to model habitat preferences of wood mouse (Apodemus sylvaticus) in a Mediterranean high mountain pine forest (Pinus sylvestris). We recorded nine field and 13 LiDAR variables that were summarized by means of Principal Component Analyses (PCA). We then analyzed wood mouse's habitat preferences using three different models based on: (i) field PCs predictors, (ii) LiDAR PCs predictors; and (iii) both set of predictors in a combined model, including a variance partitioning analysis. Elevation was also included as a predictor in the three models. Our results indicate that LiDAR derived variables were better predictors than field-based variables. The model combining both data sets slightly improved the predictive power of the model. Field derived variables indicated that wood mouse was positively influenced by the gradient of increasing shrub cover and negatively affected by elevation. Regarding LiDAR data, two LiDAR PCs, i.e. gradients in canopy openness and complexity in forest vertical structure positively influenced wood mouse, although elevation interacted negatively with the complexity in vertical structure, indicating wood mouse's preferences for plots with lower elevations but with complex forest vertical structure. The combined model was similar to the LiDAR-based model and included the gradient of shrub cover measured in the field. Variance partitioning showed that LiDAR-based variables, together with elevation, were the most important predictors and that part of the variation explained by shrub cover was shared. LiDAR derived variables were good surrogates of environmental characteristics explaining habitat preferences by the wood mouse. Our LiDAR metrics represented structural features of the forest

Modelling invasion for a habitat generalist and a specialist plant species

USGS Publications Warehouse

Evangelista, P.H.; Kumar, S.; Stohlgren, T.J.; Jarnevich, C.S.; Crall, A.W.; Norman, J. B.; Barnett, D.T.

2008-01-01

Predicting suitable habitat and the potential distribution of invasive species is a high priority for resource managers and systems ecologists. Most models are designed to identify habitat characteristics that define the ecological niche of a species with little consideration to individual species' traits. We tested five commonly used modelling methods on two invasive plant species, the habitat generalist Bromus tectorum and habitat specialist Tamarix chinensis, to compare model performances, evaluate predictability, and relate results to distribution traits associated with each species. Most of the tested models performed similarly for each species; however, the generalist species proved to be more difficult to predict than the specialist species. The highest area under the receiver-operating characteristic curve values with independent validation data sets of B. tectorum and T. chinensis was 0.503 and 0.885, respectively. Similarly, a confusion matrix for B. tectorum had the highest overall accuracy of 55%, while the overall accuracy for T. chinensis was 85%. Models for the generalist species had varying performances, poor evaluations, and inconsistent results. This may be a result of a generalist's capability to persist in a wide range of environmental conditions that are not easily defined by the data, independent variables or model design. Models for the specialist species had consistently strong performances, high evaluations, and similar results among different model applications. This is likely a consequence of the specialist's requirement for explicit environmental resources and ecological barriers that are easily defined by predictive models. Although defining new invaders as generalist or specialist species can be challenging, model performances and evaluations may provide valuable information on a species' potential invasiveness.

Remote-sensing based approach to forecast habitat quality under climate change scenarios.

PubMed

Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological

Remote-sensing based approach to forecast habitat quality under climate change scenarios

PubMed Central

Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological

Storied experiences of school-based habitat restoration

NASA Astrophysics Data System (ADS)

Bell, Anne C.

The purpose of this study has been to consider the eco-pedagogical promise of school-based habitat restoration. How does the practice of restoration foster a lived sense of being in a more-than-human world1 while inviting alternative approaches to teaching and learning? What opportunities does it offer to resist the societal forces and patterns, reinforced through the school system, which are eroding and effacing human relationships with other life? A literature review sets the broader context for an in-depth exploration of the experiences and understandings of participants (students, teachers, parents) involved in a case study. I proceeded with my research on the assumption that both the discursive and non-discursive dimensions of habitat restoration were key to appreciating its eco-pedagogical potential. Through participant observation over a ten month period, interviewing and a survey, I listened to some of the ways that habitat restoration challenged the typically disembodied, decontextualized organization of schooling by privileging hands-on involvement and encouraging attentive, caring relationships within the human and natural communities of which students were a part. I investigated particular storylines and metaphors which encoded and supported participants' endeavours, especially with regard to their potential to disrupt human-centered values and beliefs. This study suggests that the promise of habitat restoration lies in the openings created to attune to and interact with human and nonhuman others in fully embodied, locally situated and personally meaningful ways. Participants overwhelmingly attested to the importance of the experience of restoration which many deemed to be memorable and motivating and to provide fertile ground for future engagements in/for nature and society. As participants attended to the nuances and complexities of their interactions with a specific place and its inhabitants, their intimate involvement added a depth of feeling and

A female black bear denning habitat model using a geographic information system

USGS Publications Warehouse

Clark, J.D.; Hayes, S.G.; Pledger, J.M.

1998-01-01

We used the Mahalanobis distance statistic and a raster geographic information system (GIS) to model potential black bear (Ursus americanus) denning habitat in the Ouachita Mountains of Arkansas. The Mahalanobis distance statistic was used to represent the standard squared distance between sample variates in the GIS database (forest cover type, elevation, slope, aspect, distance to streams, distance to roads, and forest cover richness) and variates at known bear dens. Two models were developed: a generalized model for all den locations and another specific to dens in rock cavities. Differences between habitat at den sites and habitat across the study area were represented in 2 new GIS themes as Mahalanobis distance values. Cells similar to the mean vector derived from the known dens had low Mahalanobis distance values, and dissimilar cells had high values. The reliability of the predictive model was tested by overlaying den locations collected subsequent to original model development on the resultant den habitat themes. Although the generalized model demonstrated poor reliability, the model specific to rock dens had good reliability. Bears were more likely to choose rock den locations with low Mahalanobis distance values and less likely to choose those with high values. The model can be used to plan the timing and extent of management actions (e.g., road building, prescribed fire, timber harvest) most appropriate for those sites with high or low denning potential. 

Quantile regression models of animal habitat relationships

USGS Publications Warehouse

Cade, Brian S.

2003-01-01

Typically, all factors that limit an organism are not measured and included in statistical models used to investigate relationships with their environment. If important unmeasured variables interact multiplicatively with the measured variables, the statistical models often will have heterogeneous response distributions with unequal variances. Quantile regression is an approach for estimating the conditional quantiles of a response variable distribution in the linear model, providing a more complete view of possible causal relationships between variables in ecological processes. Chapter 1 introduces quantile regression and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of estimates for homogeneous and heterogeneous regression models. Chapter 2 evaluates performance of quantile rankscore tests used for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). A permutation F test maintained better Type I errors than the Chi-square T test for models with smaller n, greater number of parameters p, and more extreme quantiles τ. Both versions of the test required weighting to maintain correct Type I errors when there was heterogeneity under the alternative model. An example application related trout densities to stream channel width:depth. Chapter 3 evaluates a drop in dispersion, F-ratio like permutation test for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). Chapter 4 simulates from a large (N = 10,000) finite population representing grid areas on a landscape to demonstrate various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable (spatially and not spatially structured). Depending on whether interactions of the measured habitat and unmeasured variable were negative

Relevance of multiple spatial scales in habitat models: A case study with amphibians and grasshoppers

NASA Astrophysics Data System (ADS)

Altmoos, Michael; Henle, Klaus

2010-11-01

Habitat models for animal species are important tools in conservation planning. We assessed the need to consider several scales in a case study for three amphibian and two grasshopper species in the post-mining landscapes near Leipzig (Germany). The two species groups were selected because habitat analyses for grasshoppers are usually conducted on one scale only whereas amphibians are thought to depend on more than one spatial scale. First, we analysed how the preference to single habitat variables changed across nested scales. Most environmental variables were only significant for a habitat model on one or two scales, with the smallest scale being particularly important. On larger scales, other variables became significant, which cannot be recognized on lower scales. Similar preferences across scales occurred in only 13 out of 79 cases and in 3 out of 79 cases the preference and avoidance for the same variable were even reversed among scales. Second, we developed habitat models by using a logistic regression on every scale and for all combinations of scales and analysed how the quality of habitat models changed with the scales considered. To achieve a sufficient accuracy of the habitat models with a minimum number of variables, at least two scales were required for all species except for Bufo viridis, for which a single scale, the microscale, was sufficient. Only for the European tree frog ( Hyla arborea), at least three scales were required. The results indicate that the quality of habitat models increases with the number of surveyed variables and with the number of scales, but costs increase too. Searching for simplifications in multi-scaled habitat models, we suggest that 2 or 3 scales should be a suitable trade-off, when attempting to define a suitable microscale.

Forage resource evaluation system for habitat—deer: an interactive deer habitat model

Treesearch

Thomas A. Hanley; Donald E. Spalinger; Kenrick J. Mock; Oran L. Weaver; Grant M. Harris

2012-01-01

We describe a food-based system for quantitatively evaluating habitat quality for deer called the Forage Resource Evaluation System for Habitat and provide its rationale and suggestions for use. The system was developed as a tool for wildlife biologists and other natural resource managers and planners interested in evaluating habitat quality and, especially, comparing...

A comparative framework to infer landscape effects on population genetic structure: Are habitat suitability models effective in explaining gene flow?

Treesearch

Maria C. Mateo-Sanchez; Niko Balkenhol; Samuel Cushman; Trinidad Perez; Ana Dominguez; Santiago Saura

2015-01-01

Most current methods to assess connectivity begin with landscape resistance maps. The prevailing resistance models are commonly based on expert opinion and, more recently, on a direct transformation of habitat suitability. However, habitat associations are not necessarily accurate indicators of dispersal, and thus may fail as a surrogate of resistance to...

Predictive models attribute effects on fish assemblages to toxicity and habitat alteration.

PubMed

de Zwart, Dick; Dyer, Scott D; Posthuma, Leo; Hawkins, Charles P

2006-08-01

Biological assessments should both estimate the condition of a biological resource (magnitude of alteration) and provide environmental managers with a diagnosis of the potential causes of impairment. Although methods of quantifying condition are well developed, identifying and proportionately attributing impairment to probable causes remain problematic. Furthermore, analyses of both condition and cause have often been difficult to communicate. We developed an approach that (1) links fish, habitat, and chemistry data collected from hundreds of sites in Ohio (USA) streams, (2) assesses the biological condition at each site, (3) attributes impairment to multiple probable causes, and (4) provides the results of the analyses in simple-to-interpret pie charts. The data set was managed using a geographic information system. Biological condition was assessed using a RIVPACS (river invertebrate prediction and classification system)-like predictive model. The model provided probabilities of capture for 117 fish species based on the geographic location of sites and local habitat descriptors. Impaired biological condition was defined as the proportion of those native species predicted to occur at a site that were observed. The potential toxic effects of exposure to mixtures of contaminants were estimated using species sensitivity distributions and mixture toxicity principles. Generalized linear regression models described species abundance as a function of habitat characteristics. Statistically linking biological condition, habitat characteristics including mixture risks, and species abundance allowed us to evaluate the losses of species with environmental conditions. Results were mapped as simple effect and probable-cause pie charts (EPC pie diagrams), with pie sizes corresponding to magnitude of local impairment, and slice sizes to the relative probable contributions of different stressors. The types of models we used have been successfully applied in ecology and

Modelling the habitat suitability of cetaceans: Example of the sperm whale in the northwestern Mediterranean Sea

NASA Astrophysics Data System (ADS)

Praca, Emilie; Gannier, Alexandre; Das, Krishna; Laran, Sophie

2009-04-01

Cetaceans are mobile and spend long periods underwater. Because of this, modelling their habitat could be subject to a serious problem of false absence. Furthermore, extensive surveys at sea are time and money consuming, and presence-absence data are difficult to apply. This study compares the ability of two presence-absence and two presence-only habitat modelling methods and uses the example of the sperm whale ( Physeter macrocephalus) in the northwestern Mediterranean Sea. The data consist of summer visual and acoustical detections of sperm whales, compiled between 1998 and 2005. Habitat maps were computed using topographical and hydrological eco-geographical variables. Four methods were compared: principal component analysis (PCA), ecological niche factor analysis (ENFA), generalized linear model (GLM) and multivariate adaptive regression splines (MARS). The evaluation of the models was achieved by calculating the receiver operating characteristic (ROC) of the models and their respective area under the curve (AUC). Presence-absence methods (GLM, AUC=0.70, and MARS, AUC=0.79) presented better AUC than presence-only methods (PCA, AUC=0.58, and ENFA, AUC=0.66), but this difference was not statistically significant, except between the MARS and the PCA models. The four models showed an influence of both topographical and hydrological factors, but the resulting habitat suitability maps differed. The core habitat on the continental slope was well highlighted by the four models, while GLM and MARS maps also showed a suitable habitat in the offshore waters. Presence-absence methods are therefore recommended for modelling the habitat suitability of cetaceans, as they seem more accurate to highlight complex habitat. However, the use of presence-only techniques, in particular ENFA, could be very useful for a first model of the habitat range or when important surveys at sea are not possible.

Are Regional Habitat Models Useful at a Local-Scale? A Case Study of Threatened and Common Insectivorous Bats in South-Eastern Australia

PubMed Central

McConville, Anna; Law, Bradley S.; Mahony, Michael J.

2013-01-01

Habitat modelling and predictive mapping are important tools for conservation planning, particularly for lesser known species such as many insectivorous bats. However, the scale at which modelling is undertaken can affect the predictive accuracy and restrict the use of the model at different scales. We assessed the validity of existing regional-scale habitat models at a local-scale and contrasted the habitat use of two morphologically similar species with differing conservation status (Mormopterus norfolkensis and Mormopterus species 2). We used negative binomial generalised linear models created from indices of activity and environmental variables collected from systematic acoustic surveys. We found that habitat type (based on vegetation community) best explained activity of both species, which were more active in floodplain areas, with most foraging activity recorded in the freshwater wetland habitat type. The threatened M. norfolkensis avoided urban areas, which contrasts with M. species 2 which occurred frequently in urban bushland. We found that the broad habitat types predicted from local-scale models were generally consistent with those from regional-scale models. However, threshold-dependent accuracy measures indicated a poor fit and we advise caution be applied when using the regional models at a fine scale, particularly when the consequences of false negatives or positives are severe. Additionally, our study illustrates that habitat type classifications can be important predictors and we suggest they are more practical for conservation than complex combinations of raw variables, as they are easily communicated to land managers. PMID:23977296

Using dynamic population simulations to extend resource selection analyses and prioritize habitats for conservation

USGS Publications Warehouse

Heinrichs, Julie; Aldridge, Cameron L.; O'Donnell, Michael; Schumaker, Nathan

2017-01-01

Prioritizing habitats for conservation is a challenging task, particularly for species with fluctuating populations and seasonally dynamic habitat needs. Although the use of resource selection models to identify and prioritize habitat for conservation is increasingly common, their ability to characterize important long-term habitats for dynamic populations are variable. To examine how habitats might be prioritized differently if resource selection was directly and dynamically linked with population fluctuations and movement limitations among seasonal habitats, we constructed a spatially explicit individual-based model for a dramatically fluctuating population requiring temporally varying resources. Using greater sage-grouse (Centrocercus urophasianus) in Wyoming as a case study, we used resource selection function maps to guide seasonal movement and habitat selection, but emergent population dynamics and simulated movement limitations modified long-term habitat occupancy. We compared priority habitats in RSF maps to long-term simulated habitat use. We examined the circumstances under which the explicit consideration of movement limitations, in combination with population fluctuations and trends, are likely to alter predictions of important habitats. In doing so, we assessed the future occupancy of protected areas under alternative population and habitat conditions. Habitat prioritizations based on resource selection models alone predicted high use in isolated parcels of habitat and in areas with low connectivity among seasonal habitats. In contrast, results based on more biologically-informed simulations emphasized central and connected areas near high-density populations, sometimes predicted to be low selection value. Dynamic models of habitat use can provide additional biological realism that can extend, and in some cases, contradict habitat use predictions generated from short-term or static resource selection analyses. The explicit inclusion of population

Ensemble modeling to predict habitat suitability for a large-scale disturbance specialist

PubMed Central

Latif, Quresh S; Saab, Victoria A; Dudley, Jonathan G; Hollenbeck, Jeff P

2013-01-01

To conserve habitat for disturbance specialist species, ecologists must identify where individuals will likely settle in newly disturbed areas. Habitat suitability models can predict which sites at new disturbances will most likely attract specialists. Without validation data from newly disturbed areas, however, the best approach for maximizing predictive accuracy can be unclear (Northwestern U.S.A.). We predicted habitat suitability for nesting Black-backed Woodpeckers (Picoides arcticus; a burned-forest specialist) at 20 recently (≤6 years postwildfire) burned locations in Montana using models calibrated with data from three locations in Washington, Oregon, and Idaho. We developed 8 models using three techniques (weighted logistic regression, Maxent, and Mahalanobis D2 models) and various combinations of four environmental variables describing burn severity, the north–south orientation of topographic slope, and prefire canopy cover. After translating model predictions into binary classifications (0 = low suitability to unsuitable, 1 = high to moderate suitability), we compiled “ensemble predictions,” consisting of the number of models (0–8) predicting any given site as highly suitable. The suitability status for 40% of the area burned by eastside Montana wildfires was consistent across models and therefore robust to uncertainty in the relative accuracy of particular models and in alternative ecological hypotheses they described. Ensemble predictions exhibited two desirable properties: (1) a positive relationship with apparent rates of nest occurrence at calibration locations and (2) declining model agreement outside surveyed environments consistent with our reduced confidence in novel (i.e., “no-analogue”) environments. Areas of disagreement among models suggested where future surveys could help validate and refine models for an improved understanding of Black-backed Woodpecker nesting habitat relationships. Ensemble predictions presented here can

Comparing the performance of flat and hierarchical Habitat/Land-Cover classification models in a NATURA 2000 site

NASA Astrophysics Data System (ADS)

Gavish, Yoni; O'Connell, Jerome; Marsh, Charles J.; Tarantino, Cristina; Blonda, Palma; Tomaselli, Valeria; Kunin, William E.

2018-02-01

The increasing need for high quality Habitat/Land-Cover (H/LC) maps has triggered considerable research into novel machine-learning based classification models. In many cases, H/LC classes follow pre-defined hierarchical classification schemes (e.g., CORINE), in which fine H/LC categories are thematically nested within more general categories. However, none of the existing machine-learning algorithms account for this pre-defined hierarchical structure. Here we introduce a novel Random Forest (RF) based application of hierarchical classification, which fits a separate local classification model in every branching point of the thematic tree, and then integrates all the different local models to a single global prediction. We applied the hierarchal RF approach in a NATURA 2000 site in Italy, using two land-cover (CORINE, FAO-LCCS) and one habitat classification scheme (EUNIS) that differ from one another in the shape of the class hierarchy. For all 3 classification schemes, both the hierarchical model and a flat model alternative provided accurate predictions, with kappa values mostly above 0.9 (despite using only 2.2-3.2% of the study area as training cells). The flat approach slightly outperformed the hierarchical models when the hierarchy was relatively simple, while the hierarchical model worked better under more complex thematic hierarchies. Most misclassifications came from habitat pairs that are thematically distant yet spectrally similar. In 2 out of 3 classification schemes, the additional constraints of the hierarchical model resulted with fewer such serious misclassifications relative to the flat model. The hierarchical model also provided valuable information on variable importance which can shed light into "black-box" based machine learning algorithms like RF. We suggest various ways by which hierarchical classification models can increase the accuracy and interpretability of H/LC classification maps.

A remote-sensing, GIS-based approach to identify, characterize, and model spawning habitat for fall-run chum salmon in a sub-arctic, glacially fed river

USGS Publications Warehouse

Wirth, Lisa; Rosenberger, Amanda; Prakash, Anupma; Gens, Rudiger; Margraf, F. Joseph; Hamazaki, Toshihide

2012-01-01

At northern limits of a species’ distribution, fish habitat requirements are often linked to thermal preferences, and the presence of overwintering habitat. However, logistical challenges and hydrologic processes typical of glacial systems could compromize the identification of these habitats, particularly in large river environments. Our goal was to identify and characterize spawning habitat for fall-run chum salmon Oncorhynchus keta and model habitat selection from spatial distributions of tagged individuals in the Tanana River, Alaska using an approach that combined ground surveys with remote sensing. Models included braiding, sinuosity, ice-free water surface area (indicating groundwater influence), and persistent ice-free water (i.e., consistent presence of ice-free water for a 12-year period according to satellite imagery). Candidate models containing persistent ice-free water were selected as most likely, highlighting the utility of remote sensing for monitoring and identifying salmon habitat in remote areas. A combination of ground and remote surveys revealed spatial and temporal thermal characteristics of these habitats that could have strong biological implications. Persistent ice-free sites identified using synthetic aperture radar appear to serve as core areas for spawning fall chum salmon, and the importance of stability through time suggests a legacy of successful reproductive effort for this homing species. These features would not be captured with a one-visit traditional survey but rather required remote-sensing monitoring of the sites through time.

Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA

USGS Publications Warehouse

Villarreal, Miguel L.; van Riper, Charles; Petrakis, Roy E.

2013-01-01

Riparian vegetation provides important wildlife habitat in the Southwestern United States, but limited distributions and spatial complexity often leads to inaccurate representation in maps used to guide conservation. We test the use of data conflation and aggregation on multiple vegetation/land-cover maps to improve the accuracy of habitat models for the threatened western yellow-billed cuckoo (Coccyzus americanus occidentalis). We used species observations (n = 479) from a state-wide survey to develop habitat models from 1) three vegetation/land-cover maps produced at different geographic scales ranging from state to national, and 2) new aggregate maps defined by the spatial agreement of cover types, which were defined as high (agreement = all data sets), moderate (agreement ≥ 2), and low (no agreement required). Model accuracies, predicted habitat locations, and total area of predicted habitat varied considerably, illustrating the effects of input data quality on habitat predictions and resulting potential impacts on conservation planning. Habitat models based on aggregated and conflated data were more accurate and had higher model sensitivity than original vegetation/land-cover, but this accuracy came at the cost of reduced geographic extent of predicted habitat. Using the highest performing models, we assessed cuckoo habitat preference and distribution in Arizona and found that major watersheds containing high-probably habitat are fragmented by a wide swath of low-probability habitat. Focus on riparian restoration in these areas could provide more breeding habitat for the threatened cuckoo, offset potential future habitat losses in adjacent watershed, and increase regional connectivity for other threatened vertebrates that also use riparian corridors.

Hydrologic characteristics of freshwater mussel habitat: novel insights from modeled flows

USGS Publications Warehouse

Drew, C. Ashton; Eddy, Michele; Kwak, Thomas J.; Cope, W. Gregory; Augspurger, Tom

2018-01-01

The ability to model freshwater stream habitat and species distributions is limited by the spatially sparse flow data available from long-term gauging stations. Flow data beyond the immediate vicinity of gauging stations would enhance our ability to explore and characterize hydrologic habitat suitability. The southeastern USA supports high aquatic biodiversity, but threats, such as landuse alteration, climate change, conflicting water-resource demands, and pollution, have led to the imperilment and legal protection of many species. The ability to distinguish suitable from unsuitable habitat conditions, including hydrologic suitability, is a key criterion for successful conservation and restoration of aquatic species. We used the example of the critically endangered Tar River Spinymussel (Parvaspina steinstansana) and associated species to demonstrate the value of modeled flow data (WaterFALL™) to generate novel insights into population structure and testable hypotheses regarding hydrologic suitability. With ordination models, we: 1) identified all catchments with potentially suitable hydrology, 2) identified 2 distinct hydrologic environments occupied by the Tar River Spinymussel, and 3) estimated greater hydrological habitat niche breadth of assumed surrogate species associates at the catchment scale. Our findings provide the first demonstrated application of complete, continuous, regional modeled hydrologic data to freshwater mussel distribution and management. This research highlights the utility of modeling and data-mining methods to facilitate further exploration and application of such modeled environmental conditions to inform aquatic species management. We conclude that such an approach can support landscape-scale management decisions that require spatial information at fine resolution (e.g., enhanced National Hydrology Dataset catchments) and broad extent (e.g., multiple river basins).

Lunar base habitat designs: Characterizing the environment, and selecting habitat designs for future trade-offs

NASA Technical Reports Server (NTRS)

Ganapathi, Gani B.; Ferrall, Joseph; Seshan, P. K.

1993-01-01

A survey of distinct conceptual lunar habitat designs covering the pre- and post-Apollo era is presented. The impact of the significant lunar environmental challenges such as temperature, atmosphere, radiation, soil properties, meteorites, and seismic activity on the habitat design parameters are outlined. Over twenty habitat designs were identified and classified according to mission type, crew size; total duration of stay, modularity, environmental protection measures, and emplacement. Simple selection criteria of (1) post-Apollo design, (2) uniqueness of the habitat design, (3) level of thoroughness in design layout, (4) habitat dimensions are provided, and (5) materials of construction for the habitat shell are specified, are used to select five habitats for future trade studies. Habitat emplacement scenarios are created to examine the possible impact of emplacement of the habitat in different locations, such as lunar poles vs. equatorial, above ground vs. below ground, etc.

Discrete choice modeling of shovelnose sturgeon habitat selection in the Lower Missouri River

USGS Publications Warehouse

Bonnot, T.W.; Wildhaber, M.L.; Millspaugh, J.J.; DeLonay, A.J.; Jacobson, R.B.; Bryan, J.L.

2011-01-01

Substantive changes to physical habitat in the Lower Missouri River, resulting from intensive management, have been implicated in the decline of pallid (Scaphirhynchus albus) and shovelnose (S. platorynchus) sturgeon. To aid in habitat rehabilitation efforts, we evaluated habitat selection of gravid, female shovelnose sturgeon during the spawning season in two sections (lower and upper) of the Lower Missouri River in 2005 and in the upper section in 2007. We fit discrete choice models within an information theoretic framework to identify selection of means and variability in three components of physical habitat. Characterizing habitat within divisions around fish better explained selection than habitat values at the fish locations. In general, female shovelnose sturgeon were negatively associated with mean velocity between them and the bank and positively associated with variability in surrounding depths. For example, in the upper section in 2005, a 0.5 m s-1 decrease in velocity within 10 m in the bank direction increased the relative probability of selection 70%. In the upper section fish also selected sites with surrounding structure in depth (e.g., change in relief). Differences in models between sections and years, which are reinforced by validation rates, suggest that changes in habitat due to geomorphology, hydrology, and their interactions over time need to be addressed when evaluating habitat selection. Because of the importance of variability in surrounding depths, these results support an emphasis on restoring channel complexity as an objective of habitat restoration for shovelnose sturgeon in the Lower Missouri River.

Numerically exploring habitat fragmentation effects on populations using cell-based coupled map lattices

Treesearch

Michael Bevers; Curtis H. Flather

1999-01-01

We examine habitat size, shape, and arrangement effects on populations using a discrete reaction-diffusion model. Diffusion is modeled passively and applied to a cellular grid of territories forming a coupled map lattice. Dispersal mortality is proportional to the amount of nonhabitat and fully occupied habitat surrounding a given cell, with distance decay. After...

A Contemporary Analysis of the O'Neill-Glaser Model for Space-Based Solar Power and Habitat Construction

NASA Technical Reports Server (NTRS)

Curreri, Peter A.; Detweiler, Michael K.

2011-01-01

In 1975 Gerard O Neill published in the journal Science a model for the construction of solar power satellites. He found that the solar power satellites suggested by Peter Glaser would be too massive to launch economically from Earth, but could be financially viable if the workforce was permanently located in free space habitats and if lunar and asteroid materials were used for construction. All new worldwide electrical generating capacity could be then achieved by solar power satellites. The project would financially break even in about 20 years after which it would generate substantial income selling power below fossil fuel prices. Two NASA / Stanford University led studies at Ames Research center during the summers of 1974 and 1976 found the concept technically sound and developed a detailed financial parametric model. Although the project was not undertaken when suggested in the 1970s, several contemporary issues make pursuing the O Neill -- Glaser concept more compelling today. First, our analysis suggests that if in the first ten years of construction that small habitats (compared to the large vista habitats envisioned by O Neill) supporting approximately 300 people were utilized, development costs of the program and the time for financial break even could be substantially improved. Second, the contemporary consensus is developing that carbon free energy is required to mitigate global climate change. It is estimated that 300 GW of new carbon free energy would be necessary per year to stabilize global atmospheric carbon. This is about 4 times greater energy demand than was considered by the O Neill Glaser model. Our analysis suggests that after the initial investments in lunar mining and space manufacturing and transportation, that the profit margin for producing space solar power is very high (even when selling power below fossil fuel prices). We have investigated the financial scaling of ground launched versus space derived space solar power satellites. We

Habitat Use and Selection by Giant Pandas.

PubMed

Hull, Vanessa; Zhang, Jindong; Huang, Jinyan; Zhou, Shiqiang; Viña, Andrés; Shortridge, Ashton; Li, Rengui; Liu, Dian; Xu, Weihua; Ouyang, Zhiyun; Zhang, Hemin; Liu, Jianguo

2016-01-01

Animals make choices about where to spend their time in complex and dynamic landscapes, choices that reveal information about their biology that in turn can be used to guide their conservation. Using GPS collars, we conducted a novel individual-based analysis of habitat use and selection by the elusive and endangered giant pandas (Ailuropoda melanoleuca). We constructed spatial autoregressive resource utilization functions (RUF) to model the relationship between the pandas' utilization distributions and various habitat characteristics over a continuous space across seasons. Results reveal several new insights, including use of a broader range of habitat characteristics than previously understood for the species, particularly steep slopes and non-forest areas. We also used compositional analysis to analyze habitat selection (use with respect to availability of habitat types) at two selection levels. Pandas selected against low terrain position and against the highest clumped forest at the at-home range level, but no significant factors were identified at the within-home range level. Our results have implications for modeling and managing the habitat of this endangered species by illustrating how individual pandas relate to habitat and make choices that differ from assumptions made in broad scale models. Our study also highlights the value of using a spatial autoregressive RUF approach on animal species for which a complete picture of individual-level habitat use and selection across space is otherwise lacking.

Habitat Use and Selection by Giant Pandas

PubMed Central

Hull, Vanessa; Zhang, Jindong; Huang, Jinyan; Zhou, Shiqiang; Viña, Andrés; Shortridge, Ashton; Li, Rengui; Liu, Dian; Xu, Weihua; Ouyang, Zhiyun; Zhang, Hemin; Liu, Jianguo

2016-01-01

Animals make choices about where to spend their time in complex and dynamic landscapes, choices that reveal information about their biology that in turn can be used to guide their conservation. Using GPS collars, we conducted a novel individual-based analysis of habitat use and selection by the elusive and endangered giant pandas (Ailuropoda melanoleuca). We constructed spatial autoregressive resource utilization functions (RUF) to model the relationship between the pandas' utilization distributions and various habitat characteristics over a continuous space across seasons. Results reveal several new insights, including use of a broader range of habitat characteristics than previously understood for the species, particularly steep slopes and non-forest areas. We also used compositional analysis to analyze habitat selection (use with respect to availability of habitat types) at two selection levels. Pandas selected against low terrain position and against the highest clumped forest at the at-home range level, but no significant factors were identified at the within-home range level. Our results have implications for modeling and managing the habitat of this endangered species by illustrating how individual pandas relate to habitat and make choices that differ from assumptions made in broad scale models. Our study also highlights the value of using a spatial autoregressive RUF approach on animal species for which a complete picture of individual-level habitat use and selection across space is otherwise lacking. PMID:27627805

Systems Modeling to Improve River, Riparian, and Wetland Habitat Quality and Area

NASA Astrophysics Data System (ADS)

Alafifi, A.

2016-12-01

The suitability of watershed habitat to support the livelihood of its biota primarily depends on managing flow. Ecological restoration requires finding opportunities to reallocate available water in a watershed to increase ecological benefits and maintain other beneficial uses. We present the Watershed Area of Suitable Habitat (WASH) systems model that recommends reservoir releases, streamflows, and water allocations throughout a watershed to maximize the ecosystem habitat quality. WASH embeds and aggregates area-weighted metrics for aquatic, floodplain, and wetland habitat components as an ecosystem objective to maximize, while maintaining water deliveries for domestic and agricultural uses, mass balance, and available budget for restoration actions. The metrics add spatial and temporal functionality and area coverage to traditional habitat quality indexes and can accommodate multiple species of concern. We apply the WASH model to the Utah portion of the Bear River watershed which includes 8 demand sites, 5 reservoirs and 37 nodes between the Utah-Idaho state line and the Great Salt Lake. We recommend water allocations to improve current conservation efforts and show tradeoffs between human and ecosystem uses of water. WASH results are displayed on an open-source web mapping application that allows stakeholders to access, visualize, and interact with the model data and results and compare current and model-recommended operations. Results show that the Bear River is largely developed and appropriated for human water uses. However, increasing reservoirs winter and early spring releases and minimizing late spring spill volumes can significantly improve habitat quality without harming agricultural or urban water users. The spatial and temporal reallocation of spring spills to environmental uses creates additional 70 thousand acres of suitable habitat in the watershed without harming human users. WASH also quantifies the potential environmental gains and losses from

Virtual Habitat -a dynamic simulation of closed life support systems -human model status

NASA Astrophysics Data System (ADS)

Markus Czupalla, M. Sc.; Zhukov, Anton; Hwang, Su-Au; Schnaitmann, Jonas

In order to optimize Life Support Systems on a system level, stability questions must be in-vestigated. To do so the exploration group of the Technical University of Munich (TUM) is developing the "Virtual Habitat" (V-HAB) dynamic LSS simulation software. V-HAB shall provide the possibility to conduct dynamic simulations of entire mission scenarios for any given LSS configuration. The Virtual Habitat simulation tool consists of four main modules: • Closed Environment Module (CEM) -monitoring of compounds in a closed environment • Crew Module (CM) -dynamic human simulation • P/C Systems Module (PCSM) -dynamic P/C subsystems • Plant Module (PM) -dynamic plant simulation The core module of the simulation is the dynamic and environment sensitive human module. Introduced in its basic version in 2008, the human module has been significantly updated since, increasing its capabilities and maturity significantly. In this paper three newly added human model subsystems (thermal regulation, digestion and schedule controller) are introduced touching also on the human stress subsystem which is cur-rently under development. Upon the introduction of these new subsystems, the integration of these into the overall V-HAB human model is discussed, highlighting the impact on the most important I/F. The overall human model capabilities shall further be summarized and presented based on meaningful test cases. In addition to the presentation of the results, the correlation strategy for the Virtual Habitat human model shall be introduced assessing the models current confidence level and giving an outlook on the future correlation strategy. Last but not least, the remaining V-HAB mod-ules shall be introduced shortly showing how the human model is integrated into the overall simulation.

A habitat assessment for Florida panther population expansion into central Florida

USGS Publications Warehouse

Thatcher, C.A.; Van Manen, F.T.; Clark, J.D.

2009-01-01

One of the goals of the Florida panther (Puma concolor coryi) recovery plan is to expand panther range north of the Caloosahatchee River in central Florida. Our objective was to evaluate the potential of that region to support panthers. We used a geographic information system and the Mahalanobis distance statistic to develop a habitat model based on landscape characteristics associated with panther home ranges. We used cross-validation and an independent telemetry data set to test the habitat model. We also conducted a least-cost path analysis to identify potential habitat linkages and to provide a relative measure of connectivity among habitat patches. Variables in our model were paved road density, major highways, human population density, percentage of the area permanently or semipermanently flooded, and percentage of the area in natural land cover. Our model clearly identified habitat typical of that found within panther home ranges based on model testing with recent telemetry data. We identified 4 potential translocation sites that may support a total of approximately 36 panthers. Although we identified potential habitat linkages, our least-cost path analyses highlighted the extreme isolation of panther habitat in portions of the study area. Human intervention will likely be required if the goal is to establish female panthers north of the Caloosahatchee in the near term.

Using small unmanned aerial vehicle for instream habitat evaluation and modelling

NASA Astrophysics Data System (ADS)

Astegiano, Luca; Vezza, Paolo; Comoglio, Claudio; Lingua, Andrea; Spairani, Michele

2015-04-01

Recent advances in digital image collection and processing have led to the increased use of unmanned aerial vehicles (UAV) for river research and management. In this paper, we assess the capabilities of a small UAV to characterize physical habitat for fish in three river stretches of North-Western Italy. The main aim of the study was identifying the advantages and challenges of this technology for environmental river management, in the context of the increasing river exploitation for hydropower production. The UAV used to acquire overlapping images was a small quadcopter with a two different high-resolution (non-metric) cameras (Nikon J1™ and Go-Pro Hero 3 Black Edition™). The quadcopter was preprogrammed to fly set waypoints using a small tablet PC. With the acquired imagery, we constructed a 5-cm resolution orthomosaic image and a digital surface model (DSM). The two products were used to map the distribution of aquatic and riparian habitat features, i.e., wetted area, morphological unit distributions, bathymetry, water surface gradient, substrates and grain sizes, shelters and cover for fish. The study assessed the quality of collected data and used such information to identify key reach-scale metrics and important aspects of fluvial morphology and aquatic habitat. The potential and limitations of using UAV for physical habitat survey were evaluated and the collected data were used to initialize and run common habitat simulation tools (MesoHABSIM). Several advantages of using UAV-based imagery were found, including low cost procedures, high resolution and efficiency in data collection. However, some challenges were identified for bathymetry extraction (vegetation obstructions, white waters, turbidity) and grain size assessment (preprocessing of data and automatic object detection). The application domain and possible limitation for instream habitat mapping were defined and will be used as a reference for future studies. Ongoing activities include the

Modeling marbled murrelet (Brachyramphus marmoratus) habitat using LiDAR-derived canopy data

USGS Publications Warehouse

Hagar, Joan C.; Eskelson, Bianca N.I.; Haggerty, Patricia K.; Nelson, S. Kim; Vesely, David G.

2014-01-01

LiDAR (Light Detection And Ranging) is an emerging remote-sensing tool that can provide fine-scale data describing vertical complexity of vegetation relevant to species that are responsive to forest structure. We used LiDAR data to estimate occupancy probability for the federally threatened marbled murrelet (Brachyramphus marmoratus) in the Oregon Coast Range of the United States. Our goal was to address the need identified in the Recovery Plan for a more accurate estimate of the availability of nesting habitat by developing occupancy maps based on refined measures of nest-strand structure. We used murrelet occupancy data collected by the Bureau of Land Management Coos Bay District, and canopy metrics calculated from discrete return airborne LiDAR data, to fit a logistic regression model predicting the probability of occupancy. Our final model for stand-level occupancy included distance to coast, and 5 LiDAR-derived variables describing canopy structure. With an area under the curve value (AUC) of 0.74, this model had acceptable discrimination and fair agreement (Cohen's κ = 0.24), especially considering that all sites in our sample were regarded by managers as potential habitat. The LiDAR model provided better discrimination between occupied and unoccupied sites than did a model using variables derived from Gradient Nearest Neighbor maps that were previously reported as important predictors of murrelet occupancy (AUC = 0.64, κ = 0.12). We also evaluated LiDAR metrics at 11 known murrelet nest sites. Two LiDAR-derived variables accurately discriminated nest sites from random sites (average AUC = 0.91). LiDAR provided a means of quantifying 3-dimensional canopy structure with variables that are ecologically relevant to murrelet nesting habitat, and have not been as accurately quantified by other mensuration methods.

The Importance of Distance to Resources in the Spatial Modelling of Bat Foraging Habitat

PubMed Central

Rainho, Ana; Palmeirim, Jorge M.

2011-01-01

Many bats are threatened by habitat loss, but opportunities to manage their habitats are now increasing. Success of management depends greatly on the capacity to determine where and how interventions should take place, so models predicting how animals use landscapes are important to plan them. Bats are quite distinctive in the way they use space for foraging because (i) most are colonial central-place foragers and (ii) exploit scattered and distant resources, although this increases flying costs. To evaluate how important distances to resources are in modelling foraging bat habitat suitability, we radio-tracked two cave-dwelling species of conservation concern (Rhinolophus mehelyi and Miniopterus schreibersii) in a Mediterranean landscape. Habitat and distance variables were evaluated using logistic regression modelling. Distance variables greatly increased the performance of models, and distance to roost and to drinking water could alone explain 86 and 73% of the use of space by M. schreibersii and R. mehelyi, respectively. Land-cover and soil productivity also provided a significant contribution to the final models. Habitat suitability maps generated by models with and without distance variables differed substantially, confirming the shortcomings of maps generated without distance variables. Indeed, areas shown as highly suitable in maps generated without distance variables proved poorly suitable when distance variables were also considered. We concluded that distances to resources are determinant in the way bats forage across the landscape, and that using distance variables substantially improves the accuracy of suitability maps generated with spatially explicit models. Consequently, modelling with these variables is important to guide habitat management in bats and similarly mobile animals, particularly if they are central-place foragers or depend on spatially scarce resources. PMID:21547076

Optimal flow for brown trout: Habitat - prey optimization.

PubMed

Fornaroli, Riccardo; Cabrini, Riccardo; Sartori, Laura; Marazzi, Francesca; Canobbio, Sergio; Mezzanotte, Valeria

2016-10-01

The correct definition of ecosystem needs is essential in order to guide policy and management strategies to optimize the increasing use of freshwater by human activities. Commonly, the assessment of the optimal or minimum flow rates needed to preserve ecosystem functionality has been done by habitat-based models that define a relationship between in-stream flow and habitat availability for various species of fish. We propose a new approach for the identification of optimal flows using the limiting factor approach and the evaluation of basic ecological relationships, considering the appropriate spatial scale for different organisms. We developed density-environment relationships for three different life stages of brown trout that show the limiting effects of hydromorphological variables at habitat scale. In our analyses, we found that the factors limiting the densities of trout were water velocity, substrate characteristics and refugia availability. For all the life stages, the selected models considered simultaneously two variables and implied that higher velocities provided a less suitable habitat, regardless of other physical characteristics and with different patterns. We used these relationships within habitat based models in order to select a range of flows that preserve most of the physical habitat for all the life stages. We also estimated the effect of varying discharge flows on macroinvertebrate biomass and used the obtained results to identify an optimal flow maximizing habitat and prey availability. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling habitat and environmental factors affecting mosquito abundance in Chesapeake, Virginia

NASA Astrophysics Data System (ADS)

Bellows, Alan Scott

The models I present in this dissertation were designed to enable mosquito control agencies in the mid-Atlantic region that oversee large jurisdictions to rapidly track the spatial and temporal distributions of mosquito species, especially those species known to be vectors of eastern equine encephalitis and West Nile virus. I was able to keep these models streamlined, user-friendly, and not cost-prohibitive using empirically based digital data to analyze mosquito-abundance patterns in real landscapes. This research is presented in three major chapters: (II) a series of semi-static habitat suitability indices (HSI) grounded on well-documented associations between mosquito abundance and environmental variables, (III) a dynamic model for predicting both spatial and temporal mosquito abundance based on a topographic soil moisture index and recent weather patterns, and (IV) a set of protocols laid out to aid mosquito control agencies for the use of these models. The HSIs (Chapter II) were based on relationships of mosquitoes to digital surrogates of soil moisture and vegetation characteristics. These models grouped mosquitoes species derived from similarities in habitat requirements, life-cycle type, and vector competence. Quantification of relationships was determined using multiple linear regression models. As in Chapter II, relationships between mosquito abundance and environmental factors in Chapter III were quantified using regression models. However, because this model was, in part, a function of changes in weather patterns, it enables the prediction of both 'where' and 'when' mosquito outbreaks are likely to occur. This model is distinctive among similar studies in the literature because of my use of NOAA's NEXRAD Doppler radar (3-hr precipitation accumulation data) to quantify the spatial and temporal distributions in precipitation accumulation. \\ Chapter IV is unique among the chapters in this dissertation because in lieu of presenting new research, it

Modeling spring habitat requirements of the endangered brown eared pheasant Crossoptilon mantchuricum in the Huanglong Mountains, Shaanxi Province, China.

PubMed

Li, Hongqun; Yue, Bisong; Lian, Zhenmin; Zhao, Hongfeng; Zhao, Delong; Xiao, Xiangming

2012-09-01

A detailed understanding of the habitat needs of brown eared pheasants (Crossoptilon mantchuricum) is essential for conserving the species. We carried out field surveys in the Huanglong Mountains of Shaanxi Province, China, from March to June in 2007 and 2008. We arrayed a total of 206 grid plots (200 × 200 m) along transects in 2007 and 2008 and quantified a suite of environmental variables for each one. In the optimal logistic regression model, the most important variables for brown eared pheasants were slope degree, tree cover, distance to nearest water, cover and depth of fallen leaves. Hosmer and Leweshow goodness-of-fit tests explained that logistic models for the species were good fits. The model suggested that spring habitat selection of the brown eared pheasant was negatively related to distance to nearest water and slope degree, and positively to cover of trees and cover and depth of fallen leaves. In addition, the observed detected and undetected grids in 2007 did not show significant differences with predictions based on the model. These results showed that the model could well predict the habitat selection of brown eared pheasants. Based on these predictive models, we suggest that habitat management plans incorporating this new information can now focus more effectively on restrictions on the number of tourists entering the nature reserve, prohibition of firewood collection, livestock grazing, and medicinal plant harvesting by local residents in the core areas, protection of mixed forest and sources of the permanent water in the reserve, and use of alternatives to firewood.

External Device to Incrementally Skid the Habitat (E-DISH)

NASA Technical Reports Server (NTRS)

Brazell, J. W.; Introne, Steve; Bedell, Lisa; Credle, Ben; Holp, Graham; Ly, Siao; Tait, Terry

1994-01-01

A Mars habitat transport system was designed as part of the NASA Mars exploration program. The transport system, the External Device to Incrementally Skid the Habitat (E - DISH), will be used to transport Mars habitats from their landing sites to the colony base and will be detached after unloading. The system requirements for Mars were calculated and scaled for model purposes. Specific model materials are commonly found and recommendations for materials for the Mars design are included.

Predicting cerulean warbler habitat use in the Cumberland Mountains of Tennessee

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buehler, D.A.; Welton, M.J.; Beachy, T.A.

2006-12-15

We developed a habitat model to predict cerulean warbler (Dendroica cerulea) habitat availability in the Cumberland Mountains of eastern Tennessee. We used 7 remotely sensed vegetation and topographic landform explanatory variables and known locations of territorial male cerulean warblers mapped in 2003 as the response variable to develop a Mahalanobis distance statistic model of potential habitat. We evaluated the accuracy of the model based on field surveys for ceruleans during the 2004 breeding season. The model performed well with an 80% correct classification of cerulean presence based on the validation data, although prediction of absence was only 54% correct. Wemore » extrapolated from potential habitat to cerulean abundance based on density estimates from territory mapping on 8 20-ha plots in 2005. Over the 200,000-ha study area, we estimated there were 80,584 ha of potential habitat, capable of supporting about 36,500 breeding pairs. We applied the model to the 21,609-ha state-owned Royal Blue Wildlife Management Area to evaluate the potential effects of coal surface mining as one example of a potential conflict between land use and cerulean warbler conservation. Our models suggest coal surface mining could remove 2,954 ha of cerulean habitat on Royal Blue Wildlife Management Area and could displace 2,540 breeding pairs (23% of the Royal Blue population). A comprehensive conservation strategy is needed to address potential and realized habitat loss and degradation on the breeding grounds, during migration, and on the wintering grounds.« less

Using hierarchical Bayesian multi-species mixture models to estimate tandem hoop-net based habitat associations and detection probabilities of fishes in reservoirs

USGS Publications Warehouse

Stewart, David R.; Long, James M.

2015-01-01

Species distribution models are useful tools to evaluate habitat relationships of fishes. We used hierarchical Bayesian multispecies mixture models to evaluate the relationships of both detection and abundance with habitat of reservoir fishes caught using tandem hoop nets. A total of 7,212 fish from 12 species were captured, and the majority of the catch was composed of Channel Catfish Ictalurus punctatus (46%), Bluegill Lepomis macrochirus(25%), and White Crappie Pomoxis annularis (14%). Detection estimates ranged from 8% to 69%, and modeling results suggested that fishes were primarily influenced by reservoir size and context, water clarity and temperature, and land-use types. Species were differentially abundant within and among habitat types, and some fishes were found to be more abundant in turbid, less impacted (e.g., by urbanization and agriculture) reservoirs with longer shoreline lengths; whereas, other species were found more often in clear, nutrient-rich impoundments that had generally shorter shoreline length and were surrounded by a higher percentage of agricultural land. Our results demonstrated that habitat and reservoir characteristics may differentially benefit species and assemblage structure. This study provides a useful framework for evaluating capture efficiency for not only hoop nets but other gear types used to sample fishes in reservoirs.

SMALL MAMMALS: CONSEQUENCES OF STOCHASTIC DATA VARIATION FOR MODELING INDICATORS OF HABITAT SUITABILITY FOR A WELL-STUDIED RESOURCE

EPA Science Inventory

Increasingly, models of physical habitat variables (i.e. vegetation, soil) are utilized as indicators of small mammal habitat suitability or quality. Presumably, use of physical habitat models indicating habitat suitability or quality would be improved and enhanced by the extens...

Enhancements of the "eHabitat

NASA Astrophysics Data System (ADS)

Santoro, M.; Dubois, G.; Schulz, M.; Skøien, J. O.; Nativi, S.; Peedell, S.; Boldrini, E.

2012-04-01

The number of interoperable research infrastructures has increased significantly with the growing awareness of the efforts made by the Global Earth Observation System of Systems (GEOSS). One of the Social Benefit Areas (SBA) that is benefiting most from GEOSS is biodiversity, given the costs of monitoring the environment and managing complex information, from space observations to species records including their genetic characteristics. But GEOSS goes beyond the simple sharing of the data as it encourages the connectivity of models (the GEOSS Model Web), an approach easing the handling of often complex multi-disciplinary questions such as understanding the impact of environmental and climatological factors on ecosystems and habitats. In the context of GEOSS Architecture Implementation Pilot - Phase 3 (AIP-3), the EC-funded EuroGEOSS and GENESIS projects have developed and successfully demonstrated the "eHabitat" use scenario dealing with Climate Change and Biodiversity domains. Based on the EuroGEOSS multidisciplinary brokering infrastructure and on the DOPA (Digital Observatory for Protected Areas, see http://dopa.jrc.ec.europa.eu/), this scenario demonstrated how a GEOSS-based interoperability infrastructure can aid decision makers to assess and possibly forecast the irreplaceability of a given protected area, an essential indicator for assessing the criticality of threats this protected area is exposed to. The "eHabitat" use scenario was advanced in the GEOSS Sprint to Plenary activity; the advanced scenario will include the "EuroGEOSS Data Access Broker" and a new version of the eHabitat model in order to support the use of uncertain data. The multidisciplinary interoperability infrastructure which is used to demonstrate the "eHabitat" use scenario is composed of the following main components: a) A Discovery Broker: this component is able to discover resources from a plethora of different and heterogeneous geospatial services, presenting them on a single and

Assessing Wildlife Habitat Value of New England Salt Marshes: II. Model Testing and Validation

EPA Science Inventory

We test a previously described model to assess the wildlife habitat value of New England salt marshes by comparing modeled habitat values and scores with bird abundance and species richness at sixteen salt marshes in Narragansett Bay, Rhode Island USA. Assessment scores ranged f...

Alligator, Alligator mississippiensis, habitat suitability index model

USGS Publications Warehouse

Waddle, J. Hardin

2017-01-01

The 2012 Coastal Master Plan utilized Habitat Suitability Indices (HSIs) to evaluate potential project effects on wildlife species. Even though HSIs quantify habitat condition, which may not directly correlate to species abundance, they remain a practical and tractable way to assess changes in habitat quality from various restoration actions. As part of the legislatively mandated five year update to the 2012 plan, the wildlife habitat suitability indices were updated and revised using literature and existing field data where available. The outcome of these efforts resulted in improved, or in some cases entirely new suitability indices. This report describes the development of the habitat suitability indices for the American alligator, Alligator mississippiensis.

Environmental variables and definitive host distribution: a habitat suitability modelling for endohelminth parasites in the marine realm

PubMed Central

Kuhn, Thomas; Cunze, Sarah; Kochmann, Judith; Klimpel, Sven

2016-01-01

Marine nematodes of the genus Anisakis are common parasites of a wide range of aquatic organisms. Public interest is primarily based on their importance as zoonotic agents of the human Anisakiasis, a severe infection of the gastro-intestinal tract as result of consuming live larvae in insufficiently cooked fish dishes. The diverse nature of external impacts unequally influencing larval and adult stages of marine endohelminth parasites requires the consideration of both abiotic and biotic factors. Whereas abiotic factors are generally more relevant for early life stages and might also be linked to intermediate hosts, definitive hosts are indispensable for a parasite’s reproduction. In order to better understand the uneven occurrence of parasites in fish species, we here use the maximum entropy approach (Maxent) to model the habitat suitability for nine Anisakis species accounting for abiotic parameters as well as biotic data (definitive hosts). The modelled habitat suitability reflects the observed distribution quite well for all Anisakis species, however, in some cases, habitat suitability exceeded the known geographical distribution, suggesting a wider distribution than presently recorded. We suggest that integrative modelling combining abiotic and biotic parameters is a valid approach for habitat suitability assessments of Anisakis, and potentially other marine parasite species. PMID:27507328

Environmental variables and definitive host distribution: a habitat suitability modelling for endohelminth parasites in the marine realm

NASA Astrophysics Data System (ADS)

Kuhn, Thomas; Cunze, Sarah; Kochmann, Judith; Klimpel, Sven

2016-08-01

Marine nematodes of the genus Anisakis are common parasites of a wide range of aquatic organisms. Public interest is primarily based on their importance as zoonotic agents of the human Anisakiasis, a severe infection of the gastro-intestinal tract as result of consuming live larvae in insufficiently cooked fish dishes. The diverse nature of external impacts unequally influencing larval and adult stages of marine endohelminth parasites requires the consideration of both abiotic and biotic factors. Whereas abiotic factors are generally more relevant for early life stages and might also be linked to intermediate hosts, definitive hosts are indispensable for a parasite’s reproduction. In order to better understand the uneven occurrence of parasites in fish species, we here use the maximum entropy approach (Maxent) to model the habitat suitability for nine Anisakis species accounting for abiotic parameters as well as biotic data (definitive hosts). The modelled habitat suitability reflects the observed distribution quite well for all Anisakis species, however, in some cases, habitat suitability exceeded the known geographical distribution, suggesting a wider distribution than presently recorded. We suggest that integrative modelling combining abiotic and biotic parameters is a valid approach for habitat suitability assessments of Anisakis, and potentially other marine parasite species.

Physical habitat classification and instream flow modeling to determine habitat availability during low-flow periods, North Fork Shenandoah River, Virginia

USGS Publications Warehouse

Krstolic, Jennifer L.; Hayes, Donald C.; Ruhl, Peter M.

2006-01-01

Increasing development and increasing water withdrawals for public, industrial, and agricultural water supply threaten to reduce streamflows in the Shenandoah River basin in Virginia. Water managers need more information to balance human water-supply needs with the daily streamflows necessary for maintaining the aquatic ecosystems. To meet the need for comprehensive information on hydrology, water supply, and instream-flow requirements of the Shenandoah River basin, the U.S. Geological Survey and the Northern Shenandoah Valley Regional Commission conducted a cooperative investigation of habitat availability during low-flow periods on the North Fork Shenandoah River. Historic streamflow data and empirical data on physical habitat, river hydraulics, fish community structure, and recreation were used to develop a physical habitat simulation model. Hydraulic measurements were made during low, medium, and high flows in six reaches at a total of 36 transects that included riffles, runs, and pools, and that had a variety of substrates and cover types. Habitat suitability criteria for fish were developed from detailed fish-community sampling and microhabitat observations. Fish were grouped into four guilds of species and life stages with similar habitat requirements. Simulated habitat was considered in the context of seasonal flow regimes to show the availability of flows that sustain suitable habitat during months when precipitation and streamflow are scarce. The North Fork Shenandoah River basin was divided into three management sections for analysis purposes: the upper section, middle section, and lower section. The months of July, August, and September were chosen to represent a low-flow period in the basin with low mean monthly flows, low precipitation, high temperatures, and high water withdrawals. Exceedance flows calculated from the combined data from these three months describe low-flow periods on the North Fork Shenandoah River. Long-term records from three

Modeled Tradeoffs between Developed Land Protection and Tidal Habitat Maintenance during Rising Sea Levels

PubMed Central

Cadol, Daniel; Elmore, Andrew J.; Guinn, Steven M.; Engelhardt, Katharina A. M.; Sanders, Geoffrey

2016-01-01

Tidal habitats host a diversity of species and provide hydrological services such as shoreline protection and nutrient attenuation. Accretion of sediment and biomass enables tidal marshes and swamps to grow vertically, providing a degree of resilience to rising sea levels. Even if accelerating sea level rise overcomes this vertical resilience, tidal habitats have the potential to migrate inland as they continue to occupy land that falls within the new tide range elevations. The existence of developed land inland of tidal habitats, however, may prevent this migration as efforts are often made to dyke and protect developments. To test the importance of inland migration to maintaining tidal habitat abundance under a range of potential rates of sea level rise, we developed a spatially explicit elevation tracking and habitat switching model, dubbed the Marsh Accretion and Inundation Model (MAIM), which incorporates elevation-dependent net land surface elevation gain functions. We applied the model to the metropolitan Washington, DC region, finding that the abundance of small National Park Service units and other public open space along the tidal Potomac River system provides a refuge to which tidal habitats may retreat to maintain total habitat area even under moderate sea level rise scenarios (0.7 m and 1.1 m rise by 2100). Under a severe sea level rise scenario associated with ice sheet collapse (1.7 m by 2100) habitat area is maintained only if no development is protected from rising water. If all existing development is protected, then 5%, 10%, and 40% of the total tidal habitat area is lost by 2100 for the three sea level rise scenarios tested. PMID:27788209

Modeled Tradeoffs between Developed Land Protection and Tidal Habitat Maintenance during Rising Sea Levels.

PubMed

Cadol, Daniel; Elmore, Andrew J; Guinn, Steven M; Engelhardt, Katharina A M; Sanders, Geoffrey

2016-01-01

Tidal habitats host a diversity of species and provide hydrological services such as shoreline protection and nutrient attenuation. Accretion of sediment and biomass enables tidal marshes and swamps to grow vertically, providing a degree of resilience to rising sea levels. Even if accelerating sea level rise overcomes this vertical resilience, tidal habitats have the potential to migrate inland as they continue to occupy land that falls within the new tide range elevations. The existence of developed land inland of tidal habitats, however, may prevent this migration as efforts are often made to dyke and protect developments. To test the importance of inland migration to maintaining tidal habitat abundance under a range of potential rates of sea level rise, we developed a spatially explicit elevation tracking and habitat switching model, dubbed the Marsh Accretion and Inundation Model (MAIM), which incorporates elevation-dependent net land surface elevation gain functions. We applied the model to the metropolitan Washington, DC region, finding that the abundance of small National Park Service units and other public open space along the tidal Potomac River system provides a refuge to which tidal habitats may retreat to maintain total habitat area even under moderate sea level rise scenarios (0.7 m and 1.1 m rise by 2100). Under a severe sea level rise scenario associated with ice sheet collapse (1.7 m by 2100) habitat area is maintained only if no development is protected from rising water. If all existing development is protected, then 5%, 10%, and 40% of the total tidal habitat area is lost by 2100 for the three sea level rise scenarios tested.

High Resolution Habitat Suitability Modelling For Restricted-Range Hawaiian Alpine Arthropod Species

NASA Astrophysics Data System (ADS)

Stephenson, N. M.

2016-12-01

Mapping potentially suitable habitat is critical for effective species conservation and management but can be challenging in areas exhibiting complex heterogeneity. An approach that combines non-intrusive spatial data collection techniques and field data can lead to a better understanding of landscapes and species distributions. Nysius wekiuicola, commonly known as the wēkiu bug, is the most studied arthropod species endemic to the Maunakea summit in Hawai`i, yet details about its geographic distribution and habitat use remain poorly understood. To predict the geographic distribution of N. wekiuicola, MaxEnt habitat suitability models were generated from a diverse set of input variables, including fifteen years of species occurrence data, high resolution digital elevation models, surface mineralogy maps derived from hyperspectral remote sensing, and climate data. Model results indicate that elevation (78.2 percent), and the presence of nanocrystalline hematite surface minerals (13.7 percent) had the highest influence, with lesser contributions from aspect, slope, and other surface mineral classes. Climatic variables were not included in the final analysis due to auto-correlation and coarse spatial resolution. Biotic factors relating to predation and competition also likely dictate wēkiu bug capture patterns and influence our results. The wēkiu bug range and habitat suitability models generated as a result of this study will be directly incorporated into management and restoration goals for the summit region and can also be adapted for other arthropod species present, leading to a more holistic understanding of metacommunity dynamics. Key words: Microhabitat, Structure from Motion, Lidar, MaxEnt, Habitat Suitability

Habitat Suitability Index Models: Mink

USGS Publications Warehouse

Allen, Arthur W.

1983-01-01

The mink (Mustela vison) is a predatory, semiaquatic mammal that is generally associated with stream and river banks, lake shores, fresh and saltwater marshes, and marine shore habitats (Gerell 1970).  Mink are chiefly nocturnal and remain active throughout the year (Marshall 1936); Gerell 1969; Burgess 1978).  The species is adaptable in its use of habitat, modifying daily habits according to environmental conditions, particularly prey availability (Wise et al. 1981; Linn and Birds 1981; Birks and Linn 1982).  The species is tolerant of human activity and will inhabit suboptimum habitats as long as an adequate food source is available; however, mink will be more mobile and change home ranges more frequently under such conditions (Linn pers. comm.).

Habitat use affects morphological diversification in dragon lizards

PubMed Central

COLLAR, D C; SCHULTE, J A; O’MEARA, B C; LOSOS, J B

2010-01-01

Habitat use may lead to variation in diversity among evolutionary lineages because habitats differ in the variety of ways they allow for species to make a living. Here, we show that structural habitats contribute to differential diversification of limb and body form in dragon lizards (Agamidae). Based on phylogenetic analysis and ancestral state reconstructions for 90 species, we find that multiple lineages have independently adopted each of four habitat use types: rock-dwelling, terrestriality, semi-arboreality and arboreality. Given these reconstructions, we fit models of evolution to species’ morphological trait values and find that rock-dwelling and arboreality limit diversification relative to terrestriality and semi-arboreality. Models preferred by Akaike information criterion infer slower rates of size and shape evolution in lineages inferred to occupy rocks and trees, and model-averaged rate estimates are slowest for these habitat types. These results suggest that ground-dwelling facilitates ecomorphological differentiation and that use of trees or rocks impedes diversification. PMID:20345808

Summer and winter habitat suitability of Marco Polo argali in southeastern Tajikistan: A modeling approach.

PubMed

Salas, Eric Ariel L; Valdez, Raul; Michel, Stefan

2017-11-01

We modeled summer and winter habitat suitability of Marco Polo argali in the Pamir Mountains in southeastern Tajikistan using these statistical algorithms: Generalized Linear Model, Random Forest, Boosted Regression Tree, Maxent, and Multivariate Adaptive Regression Splines. Using sheep occurrence data collected from 2009 to 2015 and a set of selected habitat predictors, we produced summer and winter habitat suitability maps and determined the important habitat suitability predictors for both seasons. Our results demonstrated that argali selected proximity to riparian areas and greenness as the two most relevant variables for summer, and the degree of slope (gentler slopes between 0° to 20°) and Landsat temperature band for winter. The terrain roughness was also among the most important variables in summer and winter models. Aspect was only significant for winter habitat, with argali preferring south-facing mountain slopes. We evaluated various measures of model performance such as the Area Under the Curve (AUC) and the True Skill Statistic (TSS). Comparing the five algorithms, the AUC scored highest for Boosted Regression Tree in summer (AUC = 0.94) and winter model runs (AUC = 0.94). In contrast, Random Forest underperformed in both model runs.

The Invasive Species Forecasting System (ISFS): An iRODS-Based, Cloud-Enabled Decision Support System for Invasive Species Habitat Suitability Modeling

NASA Technical Reports Server (NTRS)

Gill, Roger; Schnase, John L.

2012-01-01

The Invasive Species Forecasting System (ISFS) is an online decision support system that allows users to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of interest, such as a national park, monument, forest, or refuge. Target customers for ISFS are natural resource managers and decision makers who have a need for scientifically valid, model- based predictions of the habitat suitability of plant species of management concern. In a joint project involving NASA and the Maryland Department of Natural Resources, ISFS has been used to model the potential distribution of Wavyleaf Basketgrass in Maryland's Chesapeake Bay Watershed. Maximum entropy techniques are used to generate predictive maps using predictor datasets derived from remotely sensed data and climate simulation outputs. The workflow to run a model is implemented in an iRODS microservice using a custom ISFS file driver that clips and re-projects data to geographic regions of interest, then shells out to perform MaxEnt processing on the input data. When the model completes, all output files and maps from the model run are registered in iRODS and made accessible to the user. The ISFS user interface is a web browser that uses the iRODS PHP client to interact with the ISFS/iRODS- server. ISFS is designed to reside in a VMware virtual machine running SLES 11 and iRODS 3.0. The ISFS virtual machine is hosted in a VMware vSphere private cloud infrastructure to deliver the online service.

Landscape-based population viability models demonstrate importance of strategic conservation planning for birds

Treesearch

Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh; D. Todd Jones-Farland

2013-01-01

Efforts to conserve regional biodiversity in the face of global climate change, habitat loss and fragmentation will depend on approaches that consider population processes at multiple scales. By combining habitat and demographic modeling, landscape-based population viability models effectively relate small-scale habitat and landscape patterns to regional population...

A modeling framework for integrated harvest and habitat management of North American waterfowl: Case-study of northern pintail metapopulation dynamics

USGS Publications Warehouse

Mattsson, Brady J.; Runge, M.C.; Devries, J.H.; Boomer, G.S.; Eadie, J.M.; Haukos, D.A.; Fleskes, J.P.; Koons, D.N.; Thogmartin, W.E.; Clark, R.G.

2012-01-01

We developed and evaluated the performance of a metapopulation model enabling managers to examine, for the first time, the consequences of alternative management strategies involving habitat conditions and hunting on both harvest opportunity and carrying capacity (i.e., equilibrium population size in the absence of harvest) for migratory waterfowl at a continental scale. Our focus is on the northern pintail (Anas acuta; hereafter, pintail), which serves as a useful model species to examine the potential for integrating waterfowl harvest and habitat management in North America. We developed submodel structure capturing important processes for pintail populations during breeding, fall migration, winter, and spring migration while encompassing spatial structure representing three core breeding areas and two core nonbreeding areas. A number of continental-scale predictions from our baseline parameterization (e.g., carrying capacity of 5.5 million, equilibrium population size of 2.9 million and harvest rate of 12% at maximum sustained yield [MSY]) were within 10% of those from the pintail harvest strategy under current use by the U.S. Fish and Wildlife Service. To begin investigating the interaction of harvest and habitat management, we examined equilibrium population conditions for pintail at the continental scale across a range of harvest rates while perturbing model parameters to represent: (1) a 10% increase in breeding habitat quality in the Prairie Pothole population (PR); and (2) a 10% increase in nonbreeding habitat quantity along in the Gulf Coast (GC). Based on our model and analysis, a greater increase in carrying capacity and sustainable harvest was seen when increasing a proxy for habitat quality in the Prairie Pothole population. This finding and underlying assumptions must be critically evaluated, however, before specific management recommendations can be made. To make such recommendations, we require (1) extended, refined submodels with additional

Spatial Scaling of Environmental Variables Improves Species-Habitat Models of Fishes in a Small, Sand-Bed Lowland River

PubMed Central

Radinger, Johannes; Wolter, Christian; Kail, Jochem

2015-01-01

Habitat suitability and the distinct mobility of species depict fundamental keys for explaining and understanding the distribution of river fishes. In recent years, comprehensive data on river hydromorphology has been mapped at spatial scales down to 100 m, potentially serving high resolution species-habitat models, e.g., for fish. However, the relative importance of specific hydromorphological and in-stream habitat variables and their spatial scales of influence is poorly understood. Applying boosted regression trees, we developed species-habitat models for 13 fish species in a sand-bed lowland river based on river morphological and in-stream habitat data. First, we calculated mean values for the predictor variables in five distance classes (from the sampling site up to 4000 m up- and downstream) to identify the spatial scale that best predicts the presence of fish species. Second, we compared the suitability of measured variables and assessment scores related to natural reference conditions. Third, we identified variables which best explained the presence of fish species. The mean model quality (AUC = 0.78, area under the receiver operating characteristic curve) significantly increased when information on the habitat conditions up- and downstream of a sampling site (maximum AUC at 2500 m distance class, +0.049) and topological variables (e.g., stream order) were included (AUC = +0.014). Both measured and assessed variables were similarly well suited to predict species’ presence. Stream order variables and measured cross section features (e.g., width, depth, velocity) were best-suited predictors. In addition, measured channel-bed characteristics (e.g., substrate types) and assessed longitudinal channel features (e.g., naturalness of river planform) were also good predictors. These findings demonstrate (i) the applicability of high resolution river morphological and instream-habitat data (measured and assessed variables) to predict fish presence, (ii) the

Hydraulic modeling of mussel habitat at a bridge-replacement site, Allegheny River, Pennsylvania, USA

USGS Publications Warehouse

Fulton, John W.; Wagner, Chad R.; Rogers, Megan E.; Zimmerman, Gregory F.

2010-01-01

Based on the statistical targets established, the hydraulic model results suggest that an additional 2428 m2 or a 30-percent increase in suitable mussel habitat could be generated at the replacement-bridge site when compared to the baseline condition associated with the existing bridge at that same location. The study did not address the influences of substrate, acid mine drainage, sediment loads from tributaries, and surface-water/ground-water exchange on mussel habitat. Future studies could include methods for quantifying (1) channel–substrate composition and distribution using tools such as hydroacoustic echosounders specifically designed and calibrated to identify bed composition and mussel populations, (2) surface-water and ground-water interactions, and (3) a high-streamflow event.

GIS-based approach for quantifying landscape connectivity of Javan Hawk-Eagle habitat

NASA Astrophysics Data System (ADS)

Nurfatimah, C.; Syartinilia; Mulyani, Y. A.

2018-05-01

Javan Hawk-Eagle (Nisaetus bartelsi; JHE) is a law-protected endemic raptor which currently faced the decreased in number and size of habitat patches that will lead to patch isolation and species extinction. This study assessed the degree of connectivity between remnant habitat patches in central part of Java by utilizing Conefor Sensinode software as an additional tool for ArcGIS. The connectivity index was determined by three fractions which are infra, flux and connector. Using connectivity indices successfully identified 4 patches as core habitat, 9 patches as stepping-stone habitat and 6 patches as isolated habitat were derived from those connectivity indices. Those patches then being validated with land cover map derived from Landsat 8 of August 2014. 36% of core habitat covered by natural forest, meanwhile stepping stone habitat has 55% natural forest and isolated habitat covered by 59% natural forest. Isolated patches were caused by zero connectivity (PCcon = 0) and the patch size which too small to support viable JHE population. Yet, the condition of natural forest and the surrounding matrix landscape in isolated patches actually support the habitat need. Thus, it is very important to conduct the right conservation management system based on the condition of each patches.

Modeling waterfowl habitat selection in the Central Valley of California to better understand the spatial relationship between commercial poultry and waterfowl

USGS Publications Warehouse

Matchett, Elliott L.; Casazza, Michael L.; Fleskes, Joseph; Kelman, T.; Cadena, M.; Pitesky, M.

2017-01-01

Wildlife researchers frequently study resource and habitat selection of wildlife to understand their potential habitat requirements and to conserve their populations. Understanding wildlife spatial-temporal distributions related to habitat have other applications such as to model interfaces between wildlife and domestic food animals in order to mitigate disease transmission to food animals. The highly pathogenic avian influenza (HPAI) virus represents a significant risk to the poultry industry. The Central Valley of California offers a unique geographical confluence of commercial poultry and wild waterfowl, which are thought to be a key reservoir of avian influenza (AI). Therefore, understanding spatio-temporal distributions of waterfowl could improve our understanding of potential risk of HPAI exposure from a commercial poultry perspective. Using existing radio-telemetry data on waterfowl (U.S. Geological Survey) in combination with habitat and vegetation data based on Geographic Information Systems (GIS), we are developing GIS-based statistical models that predict the probability of waterfowl presence (Habitat Suitability Mapping). Near-real-time application can be developed using recent habitat data derived from Landsat imagery (acquired by satellites and publically available through the U.S. Geological Survey) to predict temporally- and spatially-varying distributions of waterfowl in the Central Valley. These results could be used to provide decision support for the poultry industry in addressing potential risk of HPAI exposure related to waterfowl proximity.

A geospatial modelling approach to predict seagrass habitat recovery under multiple stressor regimes

EPA Science Inventory

Restoration of estuarine seagrass habitats requires a clear understanding of the modes of action of multiple interacting stressors including nutrients, climate change, coastal land-use change, and habitat modification. We have developed and demonstrated a geospatial modeling a...

Ensemble modeling to predict habitat suitability for a large-scale disturbance specialist

Treesearch

Quresh S. Latif; Victoria A. Saab; Jonathan G. Dudley; Jeff P. Hollenbeck

2013-01-01

To conserve habitat for disturbance specialist species, ecologists must identify where individuals will likely settle in newly disturbed areas. Habitat suitability models can predict which sites at new disturbances will most likely attract specialists. Without validation data from newly disturbed areas, however, the best approach for maximizing predictive accuracy can...

Scenario-Led Habitat Modelling of Land Use Change Impacts on Key Species

PubMed Central

Geary, Matthew; Fielding, Alan H.; McGowan, Philip J. K.; Marsden, Stuart J.

2015-01-01

Accurate predictions of the impacts of future land use change on species of conservation concern can help to inform policy-makers and improve conservation measures. If predictions are spatially explicit, predicted consequences of likely land use changes could be accessible to land managers at a scale relevant to their working landscape. We introduce a method, based on open source software, which integrates habitat suitability modelling with scenario-building, and illustrate its use by investigating the effects of alternative land use change scenarios on landscape suitability for black grouse Tetrao tetrix. Expert opinion was used to construct five near-future (twenty years) scenarios for the 800 km2 study site in upland Scotland. For each scenario, the cover of different land use types was altered by 5–30% from 20 random starting locations and changes in habitat suitability assessed by projecting a MaxEnt suitability model onto each simulated landscape. A scenario converting grazed land to moorland and open forestry was the most beneficial for black grouse, and ‘increased grazing’ (the opposite conversion) the most detrimental. Positioning of new landscape blocks was shown to be important in some situations. Increasing the area of open-canopy forestry caused a proportional decrease in suitability, but suitability gains for the ‘reduced grazing’ scenario were nonlinear. ‘Scenario-led’ landscape simulation models can be applied in assessments of the impacts of land use change both on individual species and also on diversity and community measures, or ecosystem services. A next step would be to include landscape configuration more explicitly in the simulation models, both to make them more realistic, and to examine the effects of habitat placement more thoroughly. In this example, the recommended policy would be incentives on grazing reduction to benefit black grouse. PMID:26569604

Hope for the Forests? Habitat Resiliency Illustrated in the Face of Climate Change Using Fine-Scale Modeling

NASA Astrophysics Data System (ADS)

Flint, L. E.; Flint, A. L.; Weiss, S. B.; Micheli, E. R.

2010-12-01

In the face of rapid climate change, fine-scale predictions of landscape change are of extreme interest to land managers that endeavor to develop long term adaptive strategies for maintaining biodiversity and ecosystem services. Global climate model (GCM) outputs, which generally focus on estimated increases in air temperature, are increasingly applied to species habitat distribution models. For sensitive species subject to climate change, habitat models predict significant migration (either northward or towards higher elevations), or complete extinction. Current studies typically rely on large spatial scale GCM projections (> 10 km) of changes in precipitation and air temperature: at this scale, these models necessarily neglect subtleties of topographic shading, geomorphic expression of the landscape, and fine-scale differences in soil properties - data that is readily available at meaningful local scales. Recent advances in modeling take advantage of available soils, geology, and topographic data to construct watershed-scale scenarios using GCM inputs and result in improved correlations of vegetation distribution with temperature. For this study, future climate projections were downscaled to 270-m and applied to a physically-based hydrologic model to calculate future changes in recharge, runoff, and climatic water deficit (CWD) for basins draining into the northern San Francisco Bay. CWD was analyzed for mapped vegetation types to evaluate the range of CWD for historic time periods in comparison to future time periods. For several forest communities (including blue oak woodlands, montane hardwoods, douglas-fir, and coast redwood) existing landscape area exhibiting suitable CWD diminishes by up 80 percent in the next century, with a trend towards increased CWD throughout the region. However, no forest community loses all suitable habitat, with islands of potential habitat primarily remaining on north facing slopes and deeper soils. Creation of new suitable habitat

Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble prediction

USGS Publications Warehouse

Jones-Farrand, D. Todd; Fearer, Todd M.; Thogmartin, Wayne E.; Thompson, Frank R.; Nelson, Mark D.; Tirpak, John M.

2011-01-01

Selection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and regression tree (CRT), habitat suitability index (HSI), forest structure database (FS), and habitat association database (HA). We focused our comparison on models for five priority forest-breeding species in the Central Hardwoods Bird Conservation Region: Acadian Flycatcher, Cerulean Warbler, Prairie Warbler, Red-headed Woodpecker, and Worm-eating Warbler. Lacking complete knowledge on the distribution and abundance of each species with which we could illuminate differences between approaches and provide strong grounds for recommending one approach over another, we used two approaches to compare models: rank correlations among model outputs and comparison of spatial correspondence. In general, rank correlations were significantly positive among models for each species, indicating general agreement among the models. Worm-eating Warblers had the highest pairwise correlations, all of which were significant (P , 0.05). Red-headed Woodpeckers had the lowest agreement among models, suggesting greater uncertainty in the relative conservation value of areas within the region. We assessed model uncertainty by mapping the spatial congruence in priorities (i.e., top ranks) resulting from each model for each species and calculating the coefficient of variation across model ranks for each location. This allowed identification of areas more likely to be good targets of conservation effort for a species, those areas that were least likely, and those in between where uncertainty is higher and thus conservation action incorporates more risk. Based on our results, models developed independently for the same purpose

Development of a 1 D hydrodynamic habitat model for the Hippopotamus amphibious as basis for sustainable exploitation of hydroelectric power

NASA Astrophysics Data System (ADS)

Manful, D. Y.; Kaule, G.; Wieprecht, S.; Rees, J.; Hu, W.

2009-12-01

Hydroelectric Power (HEP) is proving to be a good alternative to carbon based energy. In the past hydropower especially large scale hydro attracted significant criticism as a result of its impact on the environment. A new breed of hydroelectric dam is in the offing. The aim is to have as little a footprint as possible on the environment in both pre and post construction phases and thus minimize impact on biodiversity whilst producing clean renewable energy. The Bui dam is 400 MW scheme currently under development on the Black Volta River in the Bui national park in Ghana. The reservoir created by the Bui barrage is expected to impact (through inundation) the habitat of two species of hippos know to exist in the park, the Hippopotamus amphibius and the Choeropsis liberiensis. Computer-based models present a unique opportunity to assess quantitatively the impact of the new reservoir on the habitat of the target species in this case the H. amphibious. Until this undertaking, there were very few studies documenting the habitat of the H. amphibious let alone model it. The work and subsequent presentation will show the development of a habitat model for the Hippopotamus amphibius. The Habitat Information retrieval Program based on Streamflow Analysis, in short HIPStrA, is a one dimensional (1D) in-stream, spatially explicit hybrid construct that combines physico-chemical evidence and expert knowledge to forecast river habitat suitability (Hs) for the Hippopotamus amphibius. The version of the model presented is specifically developed to assess the impact of a reservoir created by a hydroelectric dam on potential dwelling areas in the Bui gorge for hippos. Accordingly, this version of HIPStrA simulates a special reservoir suitability index (Rsi), a metric that captures the”hippo friendliness” of any lake or reservoir. The impact of measured and simulated flood events as well as low flows, representing extreme events is also assessed. Recommendations are made for the

A habitat-based point-count protocol for terrestrial birds, emphasizing Washington and Oregon.

Treesearch

Mark H. Huff; Kelly A. Bettinger; Howard L. Ferguson; Martin J. Brown; Bob. Altman

2000-01-01

We describe a protocol and provide a summary for point-count monitoring of landbirds that is designed for habitat-based objectives. Presentation is in four steps: preparation and planning, selecting monitoring sites, establishing monitoring stations, and conducting point counts. We describe the basis for doing habitat-based point counts, how they are organized, and how...

Climate change impacts on leatherback turtle pelagic habitat in the Southeast Pacific

NASA Astrophysics Data System (ADS)

Willis-Norton, Ellen; Hazen, Elliott L.; Fossette, Sabrina; Shillinger, George; Rykaczewski, Ryan R.; Foley, David G.; Dunne, John P.; Bograd, Steven J.

2015-03-01

Eastern Pacific populations of the leatherback turtle (Dermochelys coriacea) have declined by over 90% during the past three decades. The decline is primarily attributed to human pressures, including unsustainable egg harvest, development on nesting beaches, and by-catch mortality. In particular, the effects of climate change may impose additional stresses upon already threatened leatherback populations. This study analyzes how the pelagic habitat of Eastern Pacific leatherbacks may be affected by climate change over the next century. This population adheres to a persistent migration pattern; following nesting at Playa Grande, Costa Rica, individuals move rapidly through equatorial currents and into foraging habitat within the oligotrophic South Pacific Gyre. Forty-six nesting females were fitted with satellite tags. Based on the turtle positions, ten environmental variables were sampled along the tracks. Presence/absence habitat models were created to determine the oceanographic characteristics of the preferred turtle habitat. Core pelagic habitat was characterized by relatively low sea surface temperatures and chlorophyll-a. Based on these habitat models, we predicted habitat change using output from the Geophysical Fluid Dynamics Laboratory prototype Earth System Model under the Special Report on Emissions Scenario A2 (business-as-usual). Although the model predicted both habitat losses and gains throughout the region, we estimated that overall the core pelagic habitat of the Eastern Pacific leatherback population will decline by approximately 15% within the next century. This habitat modification might increase pressure on a critically endangered population, possibly forcing distributional shifts, behavioral changes, or even extinction.

A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning

USGS Publications Warehouse

Matchett, Elliott L.; Fleskes, Joseph P.; Young, Charles A.; Purkey, David R.

2015-01-01

The amount and quality of natural resources available for terrestrial and aquatic wildlife habitats are expected to decrease throughout the world in areas that are intensively managed for urban and agricultural uses. Changes in climate and management of increasingly limited water supplies may further impact water resources essential for sustaining habitats. In this report, we document adapting a Water Evaluation and Planning (WEAP) system model for the Central Valley of California. We demonstrate using this adapted model (WEAP-CVwh) to evaluate impacts produced from plausible future scenarios on agricultural and wetland habitats used by waterbirds and other wildlife. Processed output from WEAP-CVwh indicated varying levels of impact caused by projected climate, urbanization, and water supply management in scenarios used to exemplify this approach. Among scenarios, the NCAR-CCSM3 A2 climate projection had a greater impact than the CNRM-CM3 B1 climate projection, whereas expansive urbanization had a greater impact than strategic urbanization, on annual availability of waterbird habitat. Scenarios including extensive rice-idling or substantial instream flow requirements on important water supply sources produced large impacts on annual availability of waterbird habitat. In the year corresponding with the greatest habitat reduction for each scenario, the scenario including instream flow requirements resulted in the greatest decrease in habitats throughout all months of the wintering period relative to other scenarios. This approach provides a new and useful tool for habitat conservation planning in the Central Valley and a model to guide similar research investigations aiming to inform conservation, management, and restoration of important wildlife habitats.

Modeling the Habitat Retreat of the Rediscovered Endemic Hawaiian Moth Omiodes continuatalis Wallengren (Lepidoptera: Crambidae)

PubMed Central

Vorsino, Adam E.; King, Cynthia B.; Haines, William P.; Rubinoff, Daniel

2013-01-01

Survey data over the last 100 years indicate that populations of the endemic Hawaiian leafroller moth, Omiodes continuatalis (Wallengren) (Lepidoptera: Crambidae), have declined, and the species is extirpated from large portions of its original range. Declines have been attributed largely to the invasion of non-native parasitoid species into Hawaiian ecosystems. To quantify changes in O. continuatalis distribution, we applied the maximum entropy modeling approach using Maxent. The model referenced historical (1892–1967) and current (2004–2008) survey data, to create predictive habitat suitability maps which illustrate the probability of occurrence of O. continuatalis based on historical data as contrasted with recent survey results. Probability of occurrence is predicted based on the association of biotic (vegetation) and abiotic (proxy of precipitation, proxy of temperature, elevation) environmental factors with 141 recent and historic survey locations, 38 of which O. continuatalis were collected from. Models built from the historical and recent surveys suggest habitat suitable for O. continuatalis has changed significantly over time, decreasing both in quantity and quality. We reference these data to examine the potential effects of non-native parasitoids as a factor in changing habitat suitability and range contraction for O. continuatalis. Synthesis and applications: Our results suggest that the range of O. continuatalis, an endemic Hawaiian species of conservation concern, has shrunk as its environment has degraded. Although few range shifts have been previously demonstrated in insects, such contractions caused by pressure from introduced species may be important factors in insect extinctions. PMID:23300954

A GIS-BASED MULTI-SCALE APPROACH TO HABITAT MODEL FOR THE COMMON LOON, GAVIA IMMER, IN NEW HAMPSHIRE, USA.

EPA Science Inventory

The U.S. EPA National Health and Environmental Effects Research Laboratory's (NHEERL) Wildlife Research Strategy was developed to provide methods, models and data to address concerns related to toxic chemicals and habitat alteration in the context of wildlife risk assessment and ...

The influence of landscape's dynamics on the Oriental Migratory Locust habitat change based on the time-series satellite data.

PubMed

Shi, Yue; Huang, Wenjiang; Dong, Yingying; Peng, Dailiang; Zheng, Qiong; Yang, Puyun

2018-07-15

Landscape structure and vegetation coverage are important habitat conditions for Oriental Migratory Locust infestation in East Asia. Characterizing the landscape's dynamics of locust habitat is meaningful for reducing the occupation of locusts and limiting potential risks. To better understand causes and consequences of landscape pattern and locust habitat, it is not enough to simply detect locust habitat of each year. Rather, landcover transitions causing the change of locust habitat area must also be explored. This paper proposes an integrated implement to quantify the influence of landscape's dynamics on locust habitat changes based on three tenets: 1) temporal context can provide insight into the land cover transitions, 2) the detection of locust habitat area is operated on patches rather than pixels with full consideration of landscape's ecology, 3) the modeling must be flexible and unsupervised. These ideas have not been previously explored in demonstrating the possible role of changes in landscape characteristics to drive locust habitat transitions. The case study focuses on the Dagang district, a hot spot of locust infestation of China, from 2000 to 2015. Firstly, the seasonal characteristics of typical landcovers in NDVI, TVI, and LST were extracted from fused Landsat-MODIS surface reflectance imagery. Subsequently, a landscape membership-based random forest (LMRF) algorithm was proposed to quantify the landscape structure and hydrological regimen of locust habitat at the patch level. Finally, we investigated the correlations between the specific landcover transitions and habitat changes. Within the 16 years observations, our findings suggest that the sparse reeds and weeds in the vicinity of beach land, riverbanks, and wetlands are the dominant landscape structure associated with locust habitat change (R 2  > 0.68), and the fluctuation in the water level is a key ecological factor to facilitate the locust habitat change (R 2  > 0.61). These

Grizzly bear habitat research in Glacier National Park, Montana

USGS Publications Warehouse

Martinka, C.J.; Kendall, K.C.

1986-01-01

Grizzly bear habitat research began in 1967 and is continuing in Glacier National Park, MT. Direct observations and fecal analysis revealed a relatively definable pattern of habitat use by the bears. Habitat data were subsequently used to develop management models and explore the relationships between grizzlies and park visitors. Current research strategy is based on the concept that humans are an integral components of grizzly bear habitat. A geographic information system is being developed to assist in the application of habitat data. In addition, the behavioral response of grizzlies to annual changes in food production is being studied. Management that addresses bears, humans, and their habitat as a system is proposed.

Constructing Ecological Networks Based on Habitat Quality Assessment: A Case Study of Changzhou, China

NASA Astrophysics Data System (ADS)

Gao, Yu; Ma, Lei; Liu, Jiaxun; Zhuang, Zhuzhou; Huang, Qiuhao; Li, Manchun

2017-04-01

Fragmentation and reduced continuity of habitat patches threaten the environment and biodiversity. Recently, ecological networks are increasingly attracting the attention of researchers as they provide fundamental frameworks for environmental protection. This study suggests a set of procedures to construct an ecological network. First, we proposed a method to construct a landscape resistance surface based on the assessment of habitat quality. Second, to analyze the effect of the resistance surface on corridor simulations, we used three methods to construct resistance surfaces: (1) the method proposed in this paper, (2) the entropy coefficient method, and (3) the expert scoring method. Then, we integrated habitat patches and resistance surfaces to identify potential corridors using graph theory. These procedures were tested in Changzhou, China. Comparing the outputs of using different resistance surfaces demonstrated that: (1) different landscape resistance surfaces contribute to how corridors are identified, but only slightly affect the assessment of the importance of habitat patches and potential corridors; (2) the resistance surface, which is constructed based on habitat quality, is more applicable to corridor simulations; and (3) the assessment of the importance of habitat patches is fundamental for ecological network optimization in the conservation of critical habitat patches and corridors.

Eco-hydrologic model cascades: Simulating land use and climate change impacts on hydrology, hydraulics and habitats for fish and macroinvertebrates.

PubMed

Guse, Björn; Kail, Jochem; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Hering, Daniel; Wolter, Christian; Fohrer, Nicola

2015-11-15

Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on

Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale

Treesearch

Lee A. Vierling; Kerri T. Vierling; Patrick Adam; Andrew T. Hudak

2013-01-01

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR...

Evaluation of habitat suitability index models for assessing biotic resources

Treesearch

John C. Rennie; Joseph D. Clark; James M. Sweeney

2000-01-01

Existing habitat suitability index (HSI) models are evaluated for assessing the biotic resources on Champion International Corporation (CIC) lands with data from a standard and an expanded timber inventory. Forty HSI models for 34 species that occur in the Southern Appalachians have been identified from the literature. All of the variables for 14 models are provided (...

Development of a spatially distributed model of fish population density for habitat assessment of rivers

NASA Astrophysics Data System (ADS)

Sui, Pengzhe; Iwasaki, Akito; Ryo, Masahiro; Saavedra, Oliver; Yoshimura, Chihiro

2013-04-01

Flow conditions play an important role in sustaining biodiversity of river ecosystem. However, their relations to freshwater fishes, especially to fish population density, have not been clearly described. This study, therefore, aimed to propose a new methodology to quantitatively link habitat conditions, including flow conditions and other physical conditions, to population density of fish species. We developed a basin-scale fish distribution model by integrating the concept of habitat suitability assessment with a distributed hydrological model (DHM) in order to estimate fish population density with particular attention to flow conditions. Generalized linear model (GLM) was employed to evaluate the relationship between population density of fish species and major environmental factors. The target basin was Sagami River in central Japan, where the river reach was divided into 10 sections by estuary, confluences of tributaries, and river-crossing structures (dams, weirs). The DHM was employed to simulate river discharge from 1998 to 2005, which was used to calculate 10 flow indices including mean discharge, 25th and 75th percentile discharge, duration of low and high flows, number of floods. In addition, 5 water quality parameters and 13 other physical conditions (such as basin area, river width, mean diameter of riverbed material, and number of river-crossing structures upstream and downstream) of each river section were considered as environmental variables. In case of Sagami River, 10 habitat variables among them were then selected based on their correlations to avoid multicollinearity. Finally, the best GLM was developed for each species based on Akaike's information criterion. As results, population densities of 16 fish species in Sagami River were modelled, and correlation coefficients between observed and calculated population densities for 10 species were more than 0.70. The key habitat factors for population density varied among fish species. Minimum

Modeling potential habitats for alien species Dreissena polymorpha in continental USA

USGS Publications Warehouse

Mingyang, Li; Yunwei, Ju; Kumar, Sunil; Stohlgren, Thomas J.

2008-01-01

The effective measure to minimize the damage of invasive species is to block the potential invasive species to enter into suitable areas. 1864 occurrence points with GPS coordinates and 34 environmental variables from Daymet datasets were gathered, and 4 modeling methods, i.e., Logistic Regression (LR), Classification and Regression Trees (CART), Genetic Algorithm for Rule-Set Prediction (GARP), and maximum entropy method (Maxent), were introduced to generate potential geographic distributions for invasive species Dreissena polymorpha in Continental USA. Then 3 statistical criteria of the area under the Receiver Operating Characteristic curve (AUC), Pearson correlation (COR) and Kappa value were calculated to evaluate the performance of the models, followed by analyses on major contribution variables. Results showed that in terms of the 3 statistical criteria, the prediction results of the 4 ecological niche models were either excellent or outstanding, in which Maxent outperformed the others in 3 aspects of predicting current distribution habitats, selecting major contribution factors, and quantifying the influence of environmental variables on habitats. Distance to water, elevation, frequency of precipitation and solar radiation were 4 environmental forcing factors. The method suggested in the paper can have some reference meaning for modeling habitats of alien species in China and provide a direction to prevent Mytilopsis sallei on the Chinese coast line.

Evaluation of models and data for assessing whooping crane habitat in the central Platte River, Nebraska

USGS Publications Warehouse

Farmer, Adrian H.; Cade, Brian S.; Terrell, James W.; Henriksen, Jim H.; Runge, Jeffery T.

2005-01-01

The primary objectives of this evaluation were to improve the performance of the Whooping Crane Habitat Suitability model (C4R) used by the U.S. Fish and Wildlife Service (Service) for defining the relationship between river discharge and habitat availability, and to assist the Service in implementing improved model(s) with existing hydraulic files. The C4R habitat model is applied at the scale of individual river cross-sections, but the model outputs are scaledup to larger reaches of the river using a decision support “model” comprised of other data and procedures. Hence, the validity of the habitat model depends at least partially on how its outputs are incorporated into this larger context. For that reason, we also evaluated other procedures including the PHABSIM data files, the FORTRAN computer programs used to implement the model, and other parameters used to simulate the relationship between river flows and the availability of Whooping Crane roosting habitat along more than 100 miles of heterogeneous river channels. An equally important objective of this report was to fully document these related procedures as well as the model and evaluation results so that interested parties could readily understand the technical basis for the Service’s recommendations.

Identifying western yellow-billed cuckoo breeding habitat with a dual modelling approach

USGS Publications Warehouse

Johnson, Matthew J.; Hatten, James R.; Holmes, Jennifer A.; Shafroth, Patrick B.

2017-01-01

The western population of the yellow-billed cuckoo (Coccyzus americanus) was recently listed as threatened under the federal Endangered Species Act. Yellow-billed cuckoo conservation efforts require the identification of features and area requirements associated with high quality, riparian forest habitat at spatial scales that range from nest microhabitat to landscape, as well as lower-suitability areas that can be enhanced or restored. Spatially explicit models inform conservation efforts by increasing ecological understanding of a target species, especially at landscape scales. Previous yellow-billed cuckoo modelling efforts derived plant-community maps from aerial photography, an expensive and oftentimes inconsistent approach. Satellite models can remotely map vegetation features (e.g., vegetation density, heterogeneity in vegetation density or structure) across large areas with near perfect repeatability, but they usually cannot identify plant communities. We used aerial photos and satellite imagery, and a hierarchical spatial scale approach, to identify yellow-billed cuckoo breeding habitat along the Lower Colorado River and its tributaries. Aerial-photo and satellite models identified several key features associated with yellow-billed cuckoo breeding locations: (1) a 4.5 ha core area of dense cottonwood-willow vegetation, (2) a large native, heterogeneously dense forest (72 ha) around the core area, and (3) moderately rough topography. The odds of yellow-billed cuckoo occurrence decreased rapidly as the amount of tamarisk cover increased or when cottonwood-willow vegetation was limited. We achieved model accuracies of 75–80% in the project area the following year after updating the imagery and location data. The two model types had very similar probability maps, largely predicting the same areas as high quality habitat. While each model provided unique information, a dual-modelling approach provided a more complete picture of yellow-billed cuckoo habitat

Growth potential and habitat requirements of endangered age-0 pallid sturgeon (Scaphirhynchus albus) in the Missouri River, USA, determined using a individual-based model framework

USGS Publications Warehouse

Deslauriers, David; Heironimus, Laura B.; Rapp, Tobias; Graeb, Brian D. S.; Klumb, Robert A.; Chipps, Steven R.

2018-01-01

An individual-based model framework was used to evaluate growth potential of the federally endangered pallid sturgeon (Scaphirhynchus albus) in the Missouri River. The model, developed for age-0 sturgeon, combines information on functional feeding response, bioenergetics and swimming ability to regulate consumption and growth within a virtual foraging arena. Empirical data on water temperature, water velocity and prey density were obtained from three sites in the Missouri River and used as inputs in the model to evaluate hypotheses concerning factors affecting pallid sturgeon growth. The model was also used to evaluate the impacts of environmental heterogeneity and water velocity on individual growth variability, foraging success and dispersal ability. Growth was simulated for a period of 100 days using 100 individuals (first feeding; 19 mm and 0.035 g) per scenario. Higher growth was shown to occur at sites where high densities of Ephemeroptera and Chironomidae larvae occurred throughout the growing season. Highly heterogeneous habitats (i.e., wide range of environmental conditions) and moderate water velocities (0.3 m/s) were also found to positively affect growth rates. The model developed here provides an important management and conservation tool for evaluating growth hypotheses and(or) identifying habitats in the Missouri River that are favourable to age-0 pallid sturgeon growth.

Differences in aquatic habitat quality as an impact of one- and two-dimensional hydrodynamic model simulated flow variables

NASA Astrophysics Data System (ADS)

Benjankar, R. M.; Sohrabi, M.; Tonina, D.; McKean, J. A.

2013-12-01

Aquatic habitat models utilize flow variables which may be predicted with one-dimensional (1D) or two-dimensional (2D) hydrodynamic models to simulate aquatic habitat quality. Studies focusing on the effects of hydrodynamic model dimensionality on predicted aquatic habitat quality are limited. Here we present the analysis of the impact of flow variables predicted with 1D and 2D hydrodynamic models on simulated spatial distribution of habitat quality and Weighted Usable Area (WUA) for fall-spawning Chinook salmon. Our study focuses on three river systems located in central Idaho (USA), which are a straight and pool-riffle reach (South Fork Boise River), small pool-riffle sinuous streams in a large meadow (Bear Valley Creek) and a steep-confined plane-bed stream with occasional deep forced pools (Deadwood River). We consider low and high flows in simple and complex morphologic reaches. Results show that 1D and 2D modeling approaches have effects on both the spatial distribution of the habitat and WUA for both discharge scenarios, but we did not find noticeable differences between complex and simple reaches. In general, the differences in WUA were small, but depended on stream type. Nevertheless, spatially distributed habitat quality difference is considerable in all streams. The steep-confined plane bed stream had larger differences between aquatic habitat quality defined with 1D and 2D flow models compared to results for streams with well defined macro-topographies, such as pool-riffle bed forms. KEY WORDS: one- and two-dimensional hydrodynamic models, habitat modeling, weighted usable area (WUA), hydraulic habitat suitability, high and low discharges, simple and complex reaches

Evaluation of a habitat capability model for nongame birds in the Black Hills, South Dakota

Treesearch

Todd R. Mills; Mark A. Rumble; Lester D. Flake

1996-01-01

Habitat models, used to predict consequences of land management decisions on wildlife, can have considerable economic effect on management decisions. The Black Hills National Forest uses such a habitat capability model (HABCAP), but its accuracy is largely unknown. We tested this model’s predictive accuracy for nongame birds in 13 vegetative structural stages of...

Grizzly bear habitat selection is scale dependent.

PubMed

Ciarniello, Lana M; Boyce, Mark S; Seip, Dale R; Heard, Douglas C

2007-07-01

The purpose of our study is to show how ecologists' interpretation of habitat selection by grizzly bears (Ursus arctos) is altered by the scale of observation and also how management questions would be best addressed using predetermined scales of analysis. Using resource selection functions (RSF) we examined how variation in the spatial extent of availability affected our interpretation of habitat selection by grizzly bears inhabiting mountain and plateau landscapes. We estimated separate models for females and males using three spatial extents: within the study area, within the home range, and within predetermined movement buffers. We employed two methods for evaluating the effects of scale on our RSF designs. First, we chose a priori six candidate models, estimated at each scale, and ranked them using Akaike Information Criteria. Using this method, results changed among scales for males but not for females. For female bears, models that included the full suite of covariates predicted habitat use best at each scale. For male bears that resided in the mountains, models based on forest successional stages ranked highest at the study-wide and home range extents, whereas models containing covariates based on terrain features ranked highest at the buffer extent. For male bears on the plateau, each scale estimated a different highest-ranked model. Second, we examined differences among model coefficients across the three scales for one candidate model. We found that both the magnitude and direction of coefficients were dependent upon the scale examined; results varied between landscapes, scales, and sexes. Greenness, reflecting lush green vegetation, was a strong predictor of the presence of female bears in both landscapes and males that resided in the mountains. Male bears on the plateau were the only animals to select areas that exposed them to a high risk of mortality by humans. Our results show that grizzly bear habitat selection is scale dependent. Further, the

Modeling habitat for Marbled Murrelets on the Siuslaw National Forest, Oregon, using lidar data

USGS Publications Warehouse

Hagar, Joan C.; Aragon, Ramiro; Haggerty, Patricia; Hollenbeck, Jeff P.

2018-03-28

Habitat models using lidar-derived variables that quantify fine-scale variation in vegetation structure can improve the accuracy of occupancy estimates for canopy-dwelling species over models that use variables derived from other remote sensing techniques. However, the ability of models developed at such a fine spatial scale to maintain accuracy at regional or larger spatial scales has not been tested. We tested the transferability of a lidar-based habitat model for the threatened Marbled Murrelet (Brachyramphus marmoratus) between two management districts within a larger regional conservation zone in coastal western Oregon. We compared the performance of the transferred model against models developed with data from the application location. The transferred model had good discrimination (AUC = 0.73) at the application location, and model performance was further improved by fitting the original model with coefficients from the application location dataset (AUC = 0.79). However, the model selection procedure indicated that neither of these transferred models were considered competitive with a model trained on local data. The new model trained on data from the application location resulted in the selection of a slightly different set of lidar metrics from the original model, but both transferred and locally trained models consistently indicated positive relationships between the probability of occupancy and lidar measures of canopy structural complexity. We conclude that while the locally trained model had superior performance for local application, the transferred model could reasonably be applied to the entire conservation zone.

Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands.

PubMed

Mushinzimana, Emmanuel; Munga, Stephen; Minakawa, Noboru; Li, Li; Feng, Chen-Chieng; Bian, Ling; Kitron, Uriel; Schmidt, Cindy; Beck, Louisa; Zhou, Guofa; Githeko, Andrew K; Yan, Guiyun

2006-02-16

In the past two decades the east African highlands have experienced several major malaria epidemics. Currently there is a renewed interest in exploring the possibility of anopheline larval control through environmental management or larvicide as an additional means of reducing malaria transmission in Africa. This study examined the landscape determinants of anopheline mosquito larval habitats and usefulness of remote sensing in identifying these habitats in western Kenya highlands. Panchromatic aerial photos, Ikonos and Landsat Thematic Mapper 7 satellite images were acquired for a study area in Kakamega, western Kenya. Supervised classification of land-use and land-cover and visual identification of aquatic habitats were conducted. Ground survey of all aquatic habitats was conducted in the dry and rainy seasons in 2003. All habitats positive for anopheline larvae were identified. The retrieved data from the remote sensors were compared to the ground results on aquatic habitats and land-use. The probability of finding aquatic habitats and habitats with Anopheles larvae were modelled based on the digital elevation model and land-use types. The misclassification rate of land-cover types was 10.8% based on Ikonos imagery, 22.6% for panchromatic aerial photos and 39.2% for Landsat TM 7 imagery. The Ikonos image identified 40.6% of aquatic habitats, aerial photos identified 10.6%, and Landsate TM 7 image identified 0%. Computer models based on topographic features and land-cover information obtained from the Ikonos image yielded a misclassification rate of 20.3-22.7% for aquatic habitats, and 18.1-25.1% for anopheline-positive larval habitats. One-metre spatial resolution Ikonos images combined with computer modelling based on topographic land-cover features are useful tools for identification of anopheline larval habitats, and they can be used to assist to malaria vector control in western Kenya highlands.

Wetland Accretion Rate Model of Ecosystem Resilience (WARMER) and its application to habitat sustainability for endangered species in the San Francisco Estuary

USGS Publications Warehouse

Swanson, Kathleen M.; Drexler, Judith Z.; Schoellhamer, David H.; Thorne, Karen M.; Casazza, Michael L.; Overton, Cory T.; Callaway, John C.; Takekawa, John Y.

2014-01-01

Salt marsh faunas are constrained by specific habitat requirements for marsh elevation relative to sea level and tidal range. As sea level rises, changes in relative elevation of the marsh plain will have differing impacts on the availability of habitat for marsh obligate species. The Wetland Accretion Rate Model for Ecosystem Resilience (WARMER) is a 1-D model of elevation that incorporates both biological and physical processes of vertical marsh accretion. Here, we use WARMER to evaluate changes in marsh surface elevation and the impact of these elevation changes on marsh habitat for specific species of concern. Model results were compared to elevation-based habitat criteria developed for marsh vegetation, the endangered California clapper rail (Rallus longirostris obsoletus), and the endangered salt marsh harvest mouse (Reithrodontomys raviventris) to determine the response of marsh habitat for each species to predicted >1-m sea-level rise by 2100. Feedback between vertical accretion mechanisms and elevation reduced the effect of initial elevation in the modeled scenarios. Elevation decreased nonlinearly with larger changes in elevation during the latter half of the century when the rate of sea-level rise increased. Model scenarios indicated that changes in elevation will degrade habitat quality within salt marshes in the San Francisco Estuary, and degradation will accelerate in the latter half of the century as the rate of sea-level rise accelerates. A sensitivity analysis of the model results showed that inorganic sediment accumulation and the rate of sea-level rise had the greatest influence over salt marsh sustainability.

Habitat selection by postbreeding female diving ducks: Influence of habitat attributes and conspecifics

USGS Publications Warehouse

Austin, Jane E.; O'Neil, Shawn T.; Warren, Jeffrey M.

2017-01-01

Habitat selection studies of postbreeding waterfowl have rarely focused on within-wetland attributes such as water depth, escape cover, and food availability. Flightless waterfowl must balance habitat selection between avoiding predation risks and feeding. Reproductively successful female ducks face the greatest challenges because they begin the definitive prebasic molt at or near the end of brood rearing, when their body condition is at a low point. We assessed the relative importance of habitat attributes and group effects in habitat selection by postbreeding female lesser scaup Aythya affinis on a 2332-ha montane wetland complex during the peak flightless period (August) over seven years. Hypothesis-based habitat attributes included percent open water, open water:emergent edge density, water depth, percent flooded bare substrate, fetch (distance wind can travel unobstructed), group size, and several interactions representing functional responses to interannual variation in water levels. Surveys of uniquely marked females were conducted within randomly ordered survey blocks. We fitted two-part generalized linear mixed-effects models to counts of marked females within survey blocks, which allowed us to relate habitat attributes to relative probability of occurrence and, given the presence of a marked female, abundance of marked individuals. Postbreeding female scaup selected areas with water depths > 40 cm, large open areas, and intermediate edge densities but showed no relation to flooded bare substrate, suggesting their habitat preferences were more influenced by avoiding predation risks and disturbances than in meeting foraging needs. Grouping behavior by postbreeding scaup suggests habitat selection is influenced in part by behavioral components and/or social information, conferring energetic and survival benefits (predation and disturbance risks) but potentially also contributing to competition for food resources. This study demonstrates the importance of

Multiscale sagebrush rangeland habitat modeling in southwest Wyoming

USGS Publications Warehouse

Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Coan, Michael J.; Bowen, Zachary H.

2009-01-01

Sagebrush-steppe ecosystems in North America have experienced dramatic elimination and degradation since European settlement. As a result, sagebrush-steppe dependent species have experienced drastic range contractions and population declines. Coordinated ecosystem-wide research, integrated with monitoring and management activities, would improve the ability to maintain existing sagebrush habitats. However, current data only identify resource availability locally, with rigorous spatial tools and models that accurately model and map sagebrush habitats over large areas still unavailable. Here we report on an effort to produce a rigorous large-area sagebrush-habitat classification and inventory with statistically validated products and estimates of precision in the State of Wyoming. This research employs a combination of significant new tools, including (1) modeling sagebrush rangeland as a series of independent continuous field components that can be combined and customized by any user at multiple spatial scales; (2) collecting ground-measured plot data on 2.4-meter imagery in the same season the satellite imagery is acquired; (3) effective modeling of ground-measured data on 2.4-meter imagery to maximize subsequent extrapolation; (4) acquiring multiple seasons (spring, summer, and fall) of an additional two spatial scales of imagery (30 meter and 56 meter) for optimal large-area modeling; (5) using regression tree classification technology that optimizes data mining of multiple image dates, ratios, and bands with ancillary data to extrapolate ground training data to coarser resolution sensors; and (6) employing rigorous accuracy assessment of model predictions to enable users to understand the inherent uncertainties. First-phase results modeled eight rangeland components (four primary targets and four secondary targets) as continuous field predictions. The primary targets included percent bare ground, percent herbaceousness, percent shrub, and percent litter. The

Constructing Ecological Networks Based on Habitat Quality Assessment: A Case Study of Changzhou, China

PubMed Central

Gao, Yu; Ma, Lei; Liu, Jiaxun; Zhuang, Zhuzhou; Huang, Qiuhao; Li, Manchun

2017-01-01

Fragmentation and reduced continuity of habitat patches threaten the environment and biodiversity. Recently, ecological networks are increasingly attracting the attention of researchers as they provide fundamental frameworks for environmental protection. This study suggests a set of procedures to construct an ecological network. First, we proposed a method to construct a landscape resistance surface based on the assessment of habitat quality. Second, to analyze the effect of the resistance surface on corridor simulations, we used three methods to construct resistance surfaces: (1) the method proposed in this paper, (2) the entropy coefficient method, and (3) the expert scoring method. Then, we integrated habitat patches and resistance surfaces to identify potential corridors using graph theory. These procedures were tested in Changzhou, China. Comparing the outputs of using different resistance surfaces demonstrated that: (1) different landscape resistance surfaces contribute to how corridors are identified, but only slightly affect the assessment of the importance of habitat patches and potential corridors; (2) the resistance surface, which is constructed based on habitat quality, is more applicable to corridor simulations; and (3) the assessment of the importance of habitat patches is fundamental for ecological network optimization in the conservation of critical habitat patches and corridors. PMID:28393879

An iterative and targeted sampling design informed by habitat suitability models for detecting focal plant species over extensive areas.

PubMed

Wang, Ophelia; Zachmann, Luke J; Sesnie, Steven E; Olsson, Aaryn D; Dickson, Brett G

2014-01-01

Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods

An Iterative and Targeted Sampling Design Informed by Habitat Suitability Models for Detecting Focal Plant Species over Extensive Areas

PubMed Central

Wang, Ophelia; Zachmann, Luke J.; Sesnie, Steven E.; Olsson, Aaryn D.; Dickson, Brett G.

2014-01-01

Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods

Defining landscape resistance values in least-cost connectivity models for the invasive grey squirrel: a comparison of approaches using expert-opinion and habitat suitability modelling.

PubMed

Stevenson-Holt, Claire D; Watts, Kevin; Bellamy, Chloe C; Nevin, Owen T; Ramsey, Andrew D

2014-01-01

Least-cost models are widely used to study the functional connectivity of habitat within a varied landscape matrix. A critical step in the process is identifying resistance values for each land cover based upon the facilitating or impeding impact on species movement. Ideally resistance values would be parameterised with empirical data, but due to a shortage of such information, expert-opinion is often used. However, the use of expert-opinion is seen as subjective, human-centric and unreliable. This study derived resistance values from grey squirrel habitat suitability models (HSM) in order to compare the utility and validity of this approach with more traditional, expert-led methods. Models were built and tested with MaxEnt, using squirrel presence records and a categorical land cover map for Cumbria, UK. Predictions on the likelihood of squirrel occurrence within each land cover type were inverted, providing resistance values which were used to parameterise a least-cost model. The resulting habitat networks were measured and compared to those derived from a least-cost model built with previously collated information from experts. The expert-derived and HSM-inferred least-cost networks differ in precision. The HSM-informed networks were smaller and more fragmented because of the higher resistance values attributed to most habitats. These results are discussed in relation to the applicability of both approaches for conservation and management objectives, providing guidance to researchers and practitioners attempting to apply and interpret a least-cost approach to mapping ecological networks.

Serengeti real estate: density vs. fitness-based indicators of lion habitat quality.

PubMed

Mosser, Anna; Fryxell, John M; Eberly, Lynn; Packer, Craig

2009-10-01

Habitat quality is typically inferred by assuming a direct relationship between consumer density and resource abundance, although it has been suggested that consumer fitness may be a more accurate measure of habitat quality. We examined density vs. fitness-based measures of habitat quality for lions in the Serengeti National Park, Tanzania. A 40-year average of female reproductive success (yearling cubs per female) was best explained by proximity to river confluences, whereas patterns of productivity (yearling cubs per km(2)) and adult female density (individuals per km(2)) were associated with more general measures of habitat quality and areas of shelter in poor habitat. This suggests that density may not accurately distinguish between high-quality 'source' areas and low-quality sites that merely provide refuges for effectively non-reproductive individuals. Our results indicate that density may be a misleading indicator of real estate value, particularly for populations that do not conform to an ideal free distribution.

Integrating species distributional, conservation planning, and individual based population models: A case study in critical habitat evaluation for the Northern Spotted Owl

EPA Science Inventory

Background / Question / Methods As part of the ongoing northern spotted owl recovery planning effort, we evaluated a series of alternative potential critical habitat scenarios using a species-distribution model (MaxEnt), a conservation-planning model (Zonation), and an individua...

Effects of agri-environmental schemes on farmland birds: do food availability measurements improve patterns obtained from simple habitat models?

PubMed Central

Ponce, Carlos; Bravo, Carolina; Alonso, Juan Carlos

2014-01-01

Studies evaluating agri-environmental schemes (AES) usually focus on responses of single species or functional groups. Analyses are generally based on simple habitat measurements but ignore food availability and other important factors. This can limit our understanding of the ultimate causes determining the reactions of birds to AES. We investigated these issues in detail and throughout the main seasons of a bird's annual cycle (mating, postfledging and wintering) in a dry cereal farmland in a Special Protection Area for farmland birds in central Spain. First, we modeled four bird response parameters (abundance, species richness, diversity and “Species of European Conservation Concern” [SPEC]-score), using detailed food availability and vegetation structure measurements (food models). Second, we fitted new models, built using only substrate composition variables (habitat models). Whereas habitat models revealed that both, fields included and not included in the AES benefited birds, food models went a step further and included seed and arthropod biomass as important predictors, respectively, in winter and during the postfledging season. The validation process showed that food models were on average 13% better (up to 20% in some variables) in predicting bird responses. However, the cost of obtaining data for food models was five times higher than for habitat models. This novel approach highlighted the importance of food availability-related causal processes involved in bird responses to AES, which remained undetected when using conventional substrate composition assessment models. Despite their higher costs, measurements of food availability add important details to interpret the reactions of the bird community to AES interventions and thus facilitate evaluating the real efficiency of AES programs. PMID:25165523

Testing a bioenergetics-based habitat choice model: bluegill (Lepomis macrochirus) responses to food availability and temperature

USGS Publications Warehouse

2011-01-01

Using an automated shuttlebox system, we conducted patch choice experiments with 32, 8–12 g bluegill sunfish (Lepomis macrochirus) to test a behavioral energetics hypothesis of habitat choice. When patch temperature and food levels were held constant within patches but different between patches, we expected bluegill to choose patches that maximized growth based on the bioenergetic integration of food and temperature as predicted by a bioenergetics model. Alternative hypotheses were that bluegill may choose patches based only on food (optimal foraging) or temperature (behavioral thermoregulation). The behavioral energetics hypothesis was not a good predictor of short-term (from minutes to weeks) patch choice by bluegill; the behavioral thermoregulation hypothesis was the best predictor. In the short-term, food and temperature appeared to affect patch choice hierarchically; temperature was more important, although food can alter temperature preference during feeding periods. Over a 19-d experiment, mean temperatures occupied by fish offered low rations did decline as predicted by the behavioral energetics hypothesis, but the decline was less than 1.0 °C as opposed to a possible 5 °C decline. A short-term, bioenergetic response to food and temperature may be precluded by physiological costs of acclimation not considered explicitly in the behavioral energetics hypothesis.

Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

USGS Publications Warehouse

Zajac, Zuzanna; Stith, Bradley M.; Bowling, Andrea C.; Langtimm, Catherine A.; Swain, Eric D.

2015-01-01

Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust

Modeling habitat distribution from organism occurrences and environmental data: Case study using anemonefishes and their sea anemone hosts

USGS Publications Warehouse

Guinotte, J.M.; Bartley, J.D.; Iqbal, A.; Fautin, D.G.; Buddemeier, R.W.

2006-01-01

We demonstrate the KGSMapper (Kansas Geological Survey Mapper), a straightforward, web-based biogeographic tool that uses environmental conditions of places where members of a taxon are known to occur to find other places containing suitable habitat for them. Using occurrence data for anemonefishes or their host sea anemones, and data for environmental parameters, we generated maps of suitable habitat for the organisms. The fact that the fishes are obligate symbionts of the anemones allowed us to validate the KGSMapper output: we were able to compare the inferred occurrence of the organism to that of the actual occurrence of its symbiont. Characterizing suitable habitat for these organisms in the Indo-West Pacific, the region where they naturally occur, can be used to guide conservation efforts, field work, etc.; defining suitable habitat for them in the Atlantic and eastern Pacific is relevant to identifying areas vulnerable to biological invasions. We advocate distinguishing between these 2 sorts of model output, terming the former maps of realized habitat and the latter maps of potential habitat. Creation of a niche model requires adding biotic data to the environmental data used for habitat maps: we included data on fish occurrences to infer anemone distribution and vice versa. Altering the selection of environmental variables allowed us to investigate which variables may exert the most influence on organism distribution. Adding variables does not necessarily improve precision of the model output. KGSMapper output distinguishes areas that fall within 1 standard deviation (SD) of the mean environmental variable values for places where members of the taxon occur, within 2 SD, and within the entire range of values; eliminating outliers or data known to be imprecise or inaccurate improved output precision mainly in the 2 SD range and beyond. Thus, KGSMapper is robust in the face of questionable data, offering the user a way to recognize and clean such data. It also

Satellite-based remote sensing of running water habitats at large riverscape scales: Tools to analyze habitat heterogeneity for river ecosystem management

NASA Astrophysics Data System (ADS)

Hugue, F.; Lapointe, M.; Eaton, B. C.; Lepoutre, A.

2016-01-01

We illustrate an approach to quantify patterns in hydraulic habitat composition and local heterogeneity applicable at low cost over very large river extents, with selectable reach window scales. Ongoing developments in remote sensing and geographical information science massively improve efficiencies in analyzing earth surface features. With the development of new satellite sensors and drone platforms and with the lowered cost of high resolution multispectral imagery, fluvial geomorphology is experiencing a revolution in mapping streams at high resolution. Exploiting the power of aerial or satellite imagery is particularly useful in a riverscape research framework (Fausch et al., 2002), where high resolution sampling of fluvial features and very large coverage extents are needed. This study presents a satellite remote sensing method that requires very limited field calibration data to estimate over various scales ranging from 1 m to many tens or river kilometers (i) spatial composition metrics for key hydraulic mesohabitat types and (ii) reach-scale wetted habitat heterogeneity indices such as the hydromorphological index of diversity (HMID). When the purpose is hydraulic habitat characterization applied over long river networks, the proposed method (although less accurate) is much less computationally expensive and less data demanding than two dimensional computational fluid dynamics (CFD). Here, we illustrate the tools based on a Worldview 2 satellite image of the Kiamika River, near Mont Laurier, Quebec, Canada, specifically over a 17-km river reach below the Kiamika dam. In the first step, a high resolution water depth (D) map is produced from a spectral band ratio (calculated from the multispectral image), calibrated with limited field measurements. Next, based only on known river discharge and estimated cross section depths at time of image capture, empirical-based pseudo-2D hydraulic rules are used to rapidly generate a two-dimensional map of flow velocity

Accounting for microbial habitats in modeling soil organic matter dynamics

NASA Astrophysics Data System (ADS)

Chenu, Claire; Garnier, Patricia; Nunan, Naoise; Pot, Valérie; Raynaud, Xavier; Vieublé, Laure; Otten, Wilfred; Falconer, Ruth; Monga, Olivier

2017-04-01

The extreme heterogeneity of soils constituents, architecture and inhabitants at the microscopic scale is increasingly recognized. Microbial communities exist and are active in a complex 3-D physical framework of mineral and organic particles defining pores of various sizes, more or less inter-connected. This results in a frequent spatial disconnection between soil carbon, energy sources and the decomposer organisms and a variety of microhabitats that are more or less suitable for microbial growth and activity. However, current biogeochemical models account for C dynamics at the macroscale (cm, m) and consider time- and spatially averaged relationships between microbial activity and soil characteristics. Different modelling approaches have intended to account for this microscale heterogeneity, based either on considering aggregates as surrogates for microbial habitats, or pores. Innovative modelling approaches are based on an explicit representation of soil structure at the fine scale, i.e. at µm to mm scales: pore architecture and their saturation with water, localization of organic resources and of microorganisms. Three recent models are presented here, that describe the heterotrophic activity of either bacteria or fungi and are based upon different strategies to represent the complex soil pore system (Mosaic, LBios and µFun). These models allow to hierarchize factors of microbial activity in soil's heterogeneous architecture. Present limits of these approaches and challenges are presented, regarding the extensive information required on soils at the microscale and to up-scale microbial functioning from the pore to the core scale.

N-mix for fish: estimating riverine salmonid habitat selection via N-mixture models

USGS Publications Warehouse

Som, Nicholas A.; Perry, Russell W.; Jones, Edward C.; De Juilio, Kyle; Petros, Paul; Pinnix, William D.; Rupert, Derek L.

2018-01-01

Models that formulate mathematical linkages between fish use and habitat characteristics are applied for many purposes. For riverine fish, these linkages are often cast as resource selection functions with variables including depth and velocity of water and distance to nearest cover. Ecologists are now recognizing the role that detection plays in observing organisms, and failure to account for imperfect detection can lead to spurious inference. Herein, we present a flexible N-mixture model to associate habitat characteristics with the abundance of riverine salmonids that simultaneously estimates detection probability. Our formulation has the added benefits of accounting for demographics variation and can generate probabilistic statements regarding intensity of habitat use. In addition to the conceptual benefits, model application to data from the Trinity River, California, yields interesting results. Detection was estimated to vary among surveyors, but there was little spatial or temporal variation. Additionally, a weaker effect of water depth on resource selection is estimated than that reported by previous studies not accounting for detection probability. N-mixture models show great promise for applications to riverine resource selection.

Predicting suitable habitat of the Chinese monal (Lophophorus lhuysii) using ecological niche modeling in the Qionglai Mountains, China.

PubMed

Wang, Bin; Xu, Yu; Ran, Jianghong

2017-01-01

Understanding the distribution and the extent of suitable habitats is crucial for wildlife conservation and management. Knowledge is limited regarding the natural habitats of the Chinese monal ( Lophophorus lhuysii ), which is a vulnerable Galliform species endemic to the high-montane areas of southwest China and a good candidate for being an umbrella species in the Qionglai Mountains. Using ecological niche modeling, we predicted current potential suitable habitats for the Chinese monal in the Qionglai Mountains with 64 presence points collected between 2005 and 2015. Suitable habitats of the Chinese monal were associated with about 31 mm precipitation of the driest quarter, about 15 °C of maximum temperature of the warmest month, and far from the nearest human residential locations (>5,000 m). The predicted suitable habitats of the Chinese monal covered an area of 2,490 km 2 , approximately 9.48% of the Qionglai Mountains, and was highly fragmented. 54.78% of the suitable habitats were under the protection of existing nature reserves and two conservation gaps were found. Based on these results, we provide four suggestions for the conservation management of the Chinese monal: (1) ad hoc surveys targeting potential suitable habitats to determine species occurrence, (2) more ecological studies regarding its dispersal capacity, (3) establishment of more corridors and green bridges across roads for facilitating species movement or dispersal, and (4) minimization of local disturbances.

Landsat-based Earth Observations and Crowd-sourced Data Provide Near Real-time Monitoring of Chimpanzee Habitat

NASA Astrophysics Data System (ADS)

Nackoney, J.; Pintea, L.; Jantz, S.; Hansen, M.

2015-12-01

The endangered chimpanzee (Pan troglodytes) is threatened by habitat loss from resource extraction and land conversion, as well as hunting, disease and the illegal pet trade. It has been estimated that more than 70% of chimpanzee's tropical forest habitats in Africa are now threatened by land use change. Recent developments in remote sensing and cloud computing enable the use of satellite observations to provide a synoptic view of chimpanzee habitats at finer spatial and temporal resolutions that are locally relevant and consistent across the entire species' range. We present a practical Decision Support System to be used by the Jane Goodall Institute and partners to annually monitor and forecast chimpanzee habitat health in Africa. The system integrates Earth observations from 30-meter resolution Landsat data with a species-specific habitat model and a model forecasting future land use change, enhanced by crowd-sourced field data collected by local communities and rangers using the Open Data Kit app and Android mobile smartphones and tablets. While coarser-scale and static chimpanzee habitat models have been previously developed, this project is the first to develop a dynamic monitoring system updated annually via Earth observations data that will systematically monitor threats and changes in habitat over time. Since the chimpanzee is an important keystone, flagship and umbrella species, an annual chimpanzee habitat health index would support conservation goals of other species within its large 2.5 million sq. km range and could be an important indicator of overall ecosystem health of tropical forests in Africa.

Using expert opinion to evaluate a habitat effectiveness model for elk in western Oregon and Washington.

Treesearch

Richard S. Holthausen; Michael J. Wisdom; John Pierce; Daniel K. Edwards; Mary M. Rowland

1994-01-01

We used expert opinion to evaluate the predictive reliability of a habitat effectiveness model for elk in western Oregon and Washington. Twenty-five experts in elk ecology were asked to rate habitat quality for 16 example landscapes. Rankings and ratings of 21 experts were significantly correlated with model output. Expert opinion and model predictions differed for 4...

Classification of upper Mississippi River pools based on contiguous aquatic/geomorphic habitats

USGS Publications Warehouse

Koel, Todd M.

2001-01-01

Navigation pools of the upper Mississippi River (UMR) vary greatly in terms of available contiguous aquatic/geomorphic habitats. These habitats are critical for the biotic diversity and overall productivity of the floodplain corridor of each pool. In this study, similarities among pools 4-26 and an open river reach (river kilometer 47-129) of the UMR were determined from multivariate analysis of eleven habitat types that were hydrologically-contiguous (non-leveed). Isolated floodplain habitats were not included in final analyses because this isolation limits their contribution to overall riverine productivity, in part due to a lack of hydrological connectivity to the main channel during the flood pulse. Cluster analysis based on simple Euclidean distance was used to produce two major pool groups and five pool subgroups. Important habitat variables in defining pool groups, as interpreted from principal components analysis (PCA) axis 1, were contiguous floodplain shallow aquatic area and contiguous impounded area. The habitat variable most important in defining pool subgroups, as interpreted from PCA axis 2, was tertiary channel. Most notably, pool 6 was more similar to pools 14-24 than other upper pools, and pools 19 and 25 were more similar to pools 4-13 than other lower pools. These results were quite different from those of two previous investigators, primarily because only areas of non-isolated aquatic habitat were considered.

Corridor Use Predicted from Behaviors at Habitat Boundaries.

PubMed

Haddad, Nick M

1999-02-01

Through empirical studies and simulation, I demonstrate how simple behaviors can be used in lieu of detailed dispersal studies to predict the effects of corridors on interpatch movements. Movement paths of three butterfly species were measured in large (1.64 ha) experimental patches of open habitat, some of which were connected by corridors. Butterflies that "reflected" off boundaries between open patches and the surrounding forest also emigrated from patches through corridors at rates higher than expected from random movement. This was observed for two open-habitat species, Eurema nicippe and Phoebis sennae; however, edges and corridors had no effect on a habitat generalist, Papilio troilus. Behaviorally based simulation models, which departed from correlated random walks only at habitat boundaries, predicted that corridors increase interpatch movement rates of both open-habitat species. Models also predicted that corridors have proportionately greater effects as corridor width increases, that movement rates increase before leveling off as corridor width increases, and that corridor effects decrease as patch size increases. This study suggests that corridors direct movements of habitat-restricted species and that local behaviors may be used to predict the conservation potential of corridors in fragmented landscapes.

Using Risk Assessment and Habitat Suitability Models to Prioritise Invasive Species for Management in a Changing Climate.

PubMed

Chai, Shauna-Lee; Zhang, Jian; Nixon, Amy; Nielsen, Scott

2016-01-01

Accounting for climate change in invasive species risk assessments improves our understanding of potential future impacts and enhances our preparedness for the arrival of new non-native species. We combined traditional risk assessment for invasive species with habitat suitability modeling to assess risk to biodiversity based on climate change. We demonstrate our method by assessing the risk for 15 potentially new invasive plant species to Alberta, Canada, an area where climate change is expected to facilitate the poleward expansion of invasive species ranges. Of the 15 species assessed, the three terrestrial invasive plant species that could pose the greatest threat to Alberta's biodiversity are giant knotweed (Fallopia sachalinensis), tamarisk (Tamarix chinensis), and alkali swainsonpea (Sphaerophysa salsula). We characterise giant knotweed as 'extremely invasive', with 21 times the suitable habitat between baseline and future projected climate. Tamarisk is 'extremely invasive' with a 64% increase in suitable habitat, and alkali swainsonpea is 'highly invasive' with a 21% increase in suitable habitat. Our methodology can be used to predict and prioritise potentially new invasive species for their impact on biodiversity in the context of climate change.

Simultaneous modeling of habitat suitability, occupancy, and relative abundance: African elephants in Zimbabwe

USGS Publications Warehouse

Martin, Julien; Chamaille-Jammes, Simon; Nichols, James D.; Fritz, Herve; Hines, James E.; Fonnesbeck, Christopher J.; MacKenzie, Darryl I.; Bailey, Larissa L.

2010-01-01

The recent development of statistical models such as dynamic site occupancy models provides the opportunity to address fairly complex management and conservation problems with relatively simple models. However, surprisingly few empirical studies have simultaneously modeled habitat suitability and occupancy status of organisms over large landscapes for management purposes. Joint modeling of these components is particularly important in the context of management of wild populations, as it provides a more coherent framework to investigate the population dynamics of organisms in space and time for the application of management decision tools. We applied such an approach to the study of water hole use by African elephants in Hwange National Park, Zimbabwe. Here we show how such methodology may be implemented and derive estimates of annual transition probabilities among three dry-season states for water holes: (1) unsuitable state (dry water holes with no elephants); (2) suitable state (water hole with water) with low abundance of elephants; and (3) suitable state with high abundance of elephants. We found that annual rainfall and the number of neighboring water holes influenced the transition probabilities among these three states. Because of an increase in elephant densities in the park during the study period, we also found that transition probabilities from low abundance to high abundance states increased over time. The application of the joint habitat–occupancy models provides a coherent framework to examine how habitat suitability and factors that affect habitat suitability influence the distribution and abundance of organisms. We discuss how these simple models can further be used to apply structured decision-making tools in order to derive decisions that are optimal relative to specified management objectives. The modeling framework presented in this paper should be applicable to a wide range of existing data sets and should help to address important ecological

Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

PubMed Central

Vierling, Lee A.; Vierling, Kerri T.; Adam, Patrick; Hudak, Andrew T.

2013-01-01

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2

Mass Spectrometry-Based Visualization of Molecules Associated with Human Habitats.

PubMed

Petras, Daniel; Nothias, Louis-Félix; Quinn, Robert A; Alexandrov, Theodore; Bandeira, Nuno; Bouslimani, Amina; Castro-Falcón, Gabriel; Chen, Liangyu; Dang, Tam; Floros, Dimitrios J; Hook, Vivian; Garg, Neha; Hoffner, Nicole; Jiang, Yike; Kapono, Clifford A; Koester, Irina; Knight, Rob; Leber, Christopher A; Ling, Tie-Jun; Luzzatto-Knaan, Tal; McCall, Laura-Isobel; McGrath, Aaron P; Meehan, Michael J; Merritt, Jonathan K; Mills, Robert H; Morton, Jamie; Podvin, Sonia; Protsyuk, Ivan; Purdy, Trevor; Satterfield, Kendall; Searles, Stephen; Shah, Sahil; Shires, Sarah; Steffen, Dana; White, Margot; Todoric, Jelena; Tuttle, Robert; Wojnicz, Aneta; Sapp, Valerie; Vargas, Fernando; Yang, Jin; Zhang, Chao; Dorrestein, Pieter C

2016-11-15

The cars we drive, the homes we live in, the restaurants we visit, and the laboratories and offices we work in are all a part of the modern human habitat. Remarkably, little is known about the diversity of chemicals present in these environments and to what degree molecules from our bodies influence the built environment that surrounds us and vice versa. We therefore set out to visualize the chemical diversity of five built human habitats together with their occupants, to provide a snapshot of the various molecules to which humans are exposed on a daily basis. The molecular inventory was obtained through untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of samples from each human habitat and from the people that occupy those habitats. Mapping MS-derived data onto 3D models of the environments showed that frequently touched surfaces, such as handles (e.g., door, bicycle), resemble the molecular fingerprint of the human skin more closely than other surfaces that are less frequently in direct contact with humans (e.g., wall, bicycle frame). Approximately 50% of the MS/MS spectra detected were shared between people and the environment. Personal care products, plasticizers, cleaning supplies, food, food additives, and even medications that were found to be a part of the human habitat. The annotations indicate that significant transfer of chemicals takes place between us and our built environment. The workflows applied here will lay the foundation for future studies of molecular distributions in medical, forensic, architectural, space exploration, and environmental applications.

From pest data to abundance-based risk maps combining eco-physiological knowledge, weather, and habitat variability.

PubMed

Lacasella, Federica; Marta, Silvio; Singh, Aditya; Stack Whitney, Kaitlin; Hamilton, Krista; Townsend, Phil; Kucharik, Christopher J; Meehan, Timothy D; Gratton, Claudio

2017-03-01

Noxious species, i.e., crop pest or invasive alien species, are major threats to both natural and managed ecosystems. Invasive pests are of special importance, and knowledge about their distribution and abundance is fundamental to minimize economic losses and prioritize management activities. Occurrence models are a common tool used to identify suitable zones and map priority areas (i.e., risk maps) for noxious species management, although they provide a simplified description of species dynamics (i.e., no indication on species density). An alternative is to use abundance models, but translating abundance data into risk maps is often challenging. Here, we describe a general framework for generating abundance-based risk maps using multi-year pest data. We used an extensive data set of 3968 records collected between 2003 and 2013 in Wisconsin during annual surveys of soybean aphid (SBA), an exotic invasive pest in this region. By using an integrative approach, we modelled SBA responses to weather, seasonal, and habitat variability using generalized additive models (GAMs). Our models showed good to excellent performance in predicting SBA occurrence and abundance (TSS = 0.70, AUC = 0.92; R 2  = 0.63). We found that temperature, precipitation, and growing degree days were the main drivers of SBA trends. In addition, a significant positive relationship between SBA abundance and the availability of overwintering habitats was observed. Our models showed aphid populations were also sensitive to thresholds associated with high and low temperatures, likely related to physiological tolerances of the insects. Finally, the resulting aphid predictions were integrated using a spatial prioritization algorithm ("Zonation") to produce an abundance-based risk map for the state of Wisconsin that emphasized the spatiotemporal consistency and magnitude of past infestation patterns. This abundance-based risk map can provide information on potential foci of pest outbreaks where

Modeling to Support the Development of Habitat Targets for Piping Plovers on the Missouri River

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buenau, Kate E.

2015-05-05

Report on modeling and analyses done in support of developing quantative sandbar habitat targets for piping plovers, including assessment of reference, historical, dams present but not operated, and habitat construction calibrated to meet population viability targets.

A Model of Loggerhead Sea Turtle (Caretta caretta) Habitat and Movement in the Oceanic North Pacific

PubMed Central

Abecassis, Melanie; Senina, Inna; Lehodey, Patrick; Gaspar, Philippe; Parker, Denise; Balazs, George; Polovina, Jeffrey

2013-01-01

Habitat preferences for juvenile loggerhead turtles in the North Pacific were investigated with data from two several-year long tagging programs, using 224 satellite transmitters deployed on wild and captive-reared turtles. Animals ranged between 23 and 81 cm in straight carapace length. Tracks were used to investigate changes in temperature preferences and speed of the animals with size. Average sea surface temperatures along the tracks ranged from 18 to 23 °C. Bigger turtles generally experienced larger temperature ranges and were encountered in warmer surface waters. Seasonal differences between small and big turtles suggest that the larger ones dive deeper than the mixed layer and subsequently target warmer surface waters to rewarm. Average swimming speeds were under 1 km/h and increased with size for turtles bigger than 30 cm. However, when expressed in body lengths per second (bl s−1), smaller turtles showed much higher swimming speeds (>1 bl s −1) than bigger ones (0.5 bl s−1). Temperature and speed values at size estimated from the tracks were used to parameterize a habitat-based Eulerian model to predict areas of highest probability of presence in the North Pacific. The model-generated habitat index generally matched the tracks closely, capturing the north-south movements of tracked animals, but the model failed to replicate observed east-west movements, suggesting temperature and foraging preferences are not the only factors driving large-scale loggerhead movements. Model outputs could inform potential bycatch reduction strategies. PMID:24039901

Defining environmental flows requirements at regional scale by using meso-scale habitat models and catchments classification

NASA Astrophysics Data System (ADS)

Vezza, Paolo; Comoglio, Claudio; Rosso, Maurizio

2010-05-01

The alterations of the natural flow regime and in-stream channel modification due to abstraction from watercourses act on biota through an hydraulic template, which is mediated by channel morphology. Modeling channel hydro-morphology is needed in order to evaluate how much habitat is available for selected fauna under specific environmental conditions, and consequently to assist decision makers in planning options for regulated river management. Meso-scale habitat modeling methods (e.g., MesoHABSIM) offer advantages over the traditional physical habitat evaluation, involving a larger range of habitat variables, allowing longer length of surveyed rivers and enabling understanding of fish behavior at larger spatial scale. In this study we defined a bottom-up method for the ecological discharge evaluation at regional scale, focusing on catchments smaller than 50 km2, most of them located within mountainous areas of Apennines and Alps mountain range in Piedmont (NW Italy). Within the regional study domain we identified 30 representative catchments not affected by water abstractions in order to build up the habitat-flow relationship, to be used as reference when evaluating regulated watercourses or new projects. For each stream we chose a representative reach and obtained fish data by sampling every single functional habitat (i.e. meso-habitat) within the site, keeping separated each area by using nets. The target species were brown trout (Salmo trutta), marble trout (Salmo trutta marmoratus), bullhead (Cottus gobius), chub (Leuciscus cephalus), barbel (Barbus barbus), vairone (Leuciscus souffia) and other rheophilic Cyprinids. The fish habitat suitability criteria was obtained from the observation of habitat use by a selected organism described with a multivariate relationship between habitat characteristics and fish presence. Habitat type, mean slope, cover, biotic choriotop and substrate, stream depth and velocity, water pH, temperature and percentage of dissolved

Intertidal habitat utilization patterns of birds in a Northeast Pacific estuary

EPA Science Inventory

A habitat-based framework is a practical method for developing models (or, ecological production functions, EPFs) to describe the spatial distribution of ecosystem services. To generate EPFs for Yaquina estuary, Oregon, USA, we compared bird use patterns among intertidal habitats...

Seral stage classification and monitoring model for big sagebrush/western wheatgrass/blue grama habitat

Treesearch

Lakhdar Benkobi; Daniel W. Uresk

1996-01-01

An ecological classification model for seral stages was developed for big sagebrush (Artemisia tridentata) shrub steppe habitat in Thunder Basin National Grassland, Wyoming. Four seral stages (early to late succession) were defined in this habitat type. Ecological seral stages were quantitatively identified with an estimated 92% level of accuracy...

Selecting compact habitat reserves for species with differential habitat size needs

Treesearch

Vladimir Marianov; Charles ReVelle; Stephanie Snyder

2008-01-01

We propose a model for the design of protected habitat reserves, which maximizes the number of species represented at least once in a limited set of reserved sites or parcels. Most models for reserve design do not differentiate eligible habitat sites by their size. Also, they assume that protection is guaranteed through the selection of one site for any species, not...

South Fork Shenandoah River habitat-flow modeling to determine ecological and recreational characteristics during low-flow periods

USGS Publications Warehouse

Krstolic, Jennifer L.; Ramey, R. Clay

2012-01-01

The ecological habitat requirements of aquatic organisms and recreational streamflow requirements of the South Fork Shenandoah River were investigated by the U.S. Geological Survey in cooperation with the Central Shenandoah Valley Planning District Commission, the Northern Shenandoah Valley Regional Commission, and Virginia Commonwealth University. Physical habitat simulation modeling was conducted to examine flow as a major determinant of physical habitat availability and recreation suitability using field-collected hydraulic habitat variables such as water depth, water velocity, and substrate characteristics. Fish habitat-suitability criteria specific to the South Fork Shenandoah River were developed for sub-adult and adult smallmouth bass (Micropterus dolomieu), juvenile and sub-adult redbreast sunfish (Lepomis auritus), spotfin or satinfin shiner (Cyprinella spp), margined madtom (Noturus insignis),and river chub (Nocomis micropogon). Historic streamflow statistics for the summer low-flow period during July, August, and September were used as benchmark low-flow conditions and compared to habitat simulation results and water-withdrawal scenarios based on 2005 withdrawal data. To examine habitat and recreation characteristics during droughts, daily fish habitat or recreation suitability values were simulated for 2002 and other selected drought years. Recreation suitability during droughts was extremely low, because the modeling demonstrated that suitable conditions occur when the streamflows are greater than the 50th percentile flow for July, August, and September. Habitat availability for fish is generally at a maximum when streamflows are between the 75th and 25th percentile flows for July, August, and September. Time-series results for drought years, such as 2002, showed that extreme low-flow conditions less than the 5th percentile of flow for July, August, and September corresponded to below-normal habitat availability for both game and nongame fish in the

Modeling suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in North and South America’s coastal waters

USGS Publications Warehouse

Evangelista, Paul H.; Young, Nicholas E.; Schofield, Pamela J.; Jarnevich, Catherine S.

2016-01-01

We used two common correlative species-distribution models to predict suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in the western Atlantic and eastern Pacific Oceans. The Generalized Linear Model (GLM) and the Maximum Entropy (Maxent) model were applied using the Software for Assisted Habitat Modeling. We compared models developed using native occurrences, using non-native occurrences, and using both native and non-native occurrences. Models were trained using occurrence data collected before 2010 and evaluated with occurrence data collected from the invaded range during or after 2010. We considered a total of 22 marine environmental variables. Models built with non-native only or both native and non-native occurrence data outperformed those that used only native occurrences. Evaluation metrics based on the independent test data were highest for models that used both native and non-native occurrences. Bathymetry was the strongest environmental predictor for all models and showed increasing suitability as ocean floor depth decreased, with salinity ranking the second strongest predictor for models that used native and both native and non-native occurrences, indicating low habitat suitability for salinities <30. Our model results also suggest that red lionfish could continue to invade southern latitudes in the western Atlantic Ocean and may establish localized populations in the eastern Pacific Ocean. We reiterate the importance in the choice of the training data source (native, non-native, or native/non-native) used to develop correlative species distribution models for invasive species.

Application and partial validation of a habitat model for moose in the Lake Superior region

USGS Publications Warehouse

Allen, A.W.; Terrell, J.W.; Mangus, W.L.; Lindquist, E.L.

1991-01-01

A modified version of the dormant-season portion of a Habitat Suitability Index (HSI) model developed for assessing moose (Alces alces) habitat in the Lake Superior Region was incorporated in a Geographic Information System (GIS) for 490 km2 of Minnesota's Superior National Forest. Moose locations (n=235) were plotted during aerial surveys conducted in December 1988 and January 1990-1991. Dormant-season forage and cover quality for 1,000-m, 500-m, and 200-m radii plots around random points and moose locations were compared using U.S. Forest Service stand examination data. Cover quality indices were lower than forage quality indices within all plots. The median value for the average cover quality index was greater (P=0.003) within 200-m plots around cow moose locations than for plots around random points for the most severe winter of the study. The proportion of highest-quality winter cover, such as mixed stands dominated by mid-age class white spruce (Picea glauca) and balsam fir (Abies balsanea), was greater within 500-m and 200-m plots around cow moose than within similar plots around random points during the two most severe winters. These results indicate that suboptimum ratings of winter habitat quality used in the GIS for dormant-season forage >100 m from cover, as suggested in the original HSI model, are reasonable. Integrating the habitat model with forest stand data using a GIS permitted analysis of moose habitat within a relatively large geographic area. Simulation of habitat quality indicated a potential shortage of late-winter cover in the study area. The effects of forest management actions on moose habitat quality can be simulated without collecting additional data.

The addition of hydrodynamic variables to predictive cold water coral habitat modeling: The Bari Canyon case-study, southwestern Adriatic Sea

NASA Astrophysics Data System (ADS)

Foglini, Federica; Bargain, Annaëlle; Angeletti, Lorenzo; Bonaldo, Davide; Carniel, Sandro; Taviani, Marco

2017-04-01

Predictive habitat modeling is gaining momentum because of its usefulness to recognize potential distributional patterns of ecosystems thus facilitating their proper governance when required, as it is for instance the case of the Marine Strategy Framework Directive (MSFD). This holds particularly true for the deep-sea in front of its overwhelming areal extent on a global scale and intrinsic technological difficulties (with related costs) for its direct exploration. Cold Water Corals (CWC) is one emblematic, virtually cosmopolitan, ecosystem in the deep, that is under international attention because of its multifaceted ecological importance. CWC is currently represented in the Mediterranean basin by habitats engineered by the arborescent scleractinians Madrepora oculata and Lophelia pertusa associated with a number of other benthic invertebrates. One major CWC hotspot located on the southwestern Adriatic margin, the Bari Canyon cold water coral province, has been targeted for producing habitat suitability maps. Initially the evaluation of the theoretical distribution of CWC in this area has been based upon visual observations, mainly extracted from geo-referenced underwater ROV imagery, coupled with the eco-geographic information derived from bathymetry. This approach relies upon the compilation and comparison of presence-only models (MaxEnt and ENFA), but also presence-absence model (GLMs). However, the pivotal role played by oceanographic factors has been soon added in order to achieve more robust predictive models. In fact, the Bari Canyon CWC province is situated on the main path of the North Adriatic Dense Water cascading, and hypothesized to be sensitive to hydrological factors. Accordingly, the statistical models to assess potential habitat extent have been implemented using hydrodynamic fields provided by ROMS for ocean currents, coupled with SWAN within the COAWST modelling system to account for wave-current interactions. The integration of results is

Pelagic habitat visualization: the need for a third (and fourth) dimension: HabitatSpace

USGS Publications Warehouse

Beegle-Krause, C; Vance, Tiffany; Reusser, Debbie; Stuebe, David; Howlett, Eoin

2009-01-01

Habitat in open water is not simply a 2-D to 2.5-D surface such as the ocean bottom or the air-water interface. Rather, pelagic habitat is a 3-D volume of water that can change over time, leading us to the term habitat space. Visualization and analysis in 2-D is well supported with GIS tools, but a new tool was needed for visualization and analysis in four dimensions. Observational data (cruise profiles (x_o, y_o, z, t_o)), numerical circulation model fields (x,y,z,t), and trajectories (larval fish, 4-D line) need to be merged together in a meaningful way for visualization and analysis. As a first step toward this new framework, UNIDATA’s Integrated Data Viewer (IDV) has been used to create a set of tools for habitat analysis in 4-D. IDV was designed for 3-D+time geospatial data in the meteorological community. NetCDF Java^TM libraries allow the tool to read many file formats including remotely located data (e.g. data available via OPeNDAP ). With this project, IDV has been adapted for use in delineating habitat space for multiple fish species in the ocean. The ability to define and visualize boundaries of a water mass, which meets specific biologically relevant criteria (e.g., volume, connectedness, and inter-annual variability) based on model results and observational data, will allow managers to investigate the survival of individual year classes of commercially important fisheries. Better understanding of the survival of these year classes will lead to improved forecasting of fisheries recruitment.

Evaluating Great Lakes bald eagle nesting habitat with Bayesian inference

Treesearch

Teryl G. Grubb; William W. Bowerman; Allen J. Bath; John P. Giesy; D. V. Chip Weseloh

2003-01-01

Bayesian inference facilitated structured interpretation of a nonreplicated, experience-based survey of potential nesting habitat for bald eagles (Haliaeetus leucocephalus) along the five Great Lakes shorelines. We developed a pattern recognition (PATREC) model of our aerial search image with six habitat attributes: (a) tree cover, (b) proximity and...

Partial gravity habitat study: With application to lunar base design

NASA Technical Reports Server (NTRS)

Capps, Stephen; Lorandos, Jason; Akhidime, Eval; Bunch, Michael; Lund, Denise; Moore, Nathan; Murakawa, Kio; Bell, Larry; Trotti, Guillermo; Neubek, Deb

1989-01-01

Comprehensive design requirements associated with designing habitats for humans in a partial gravity environment were investigated and then applied to a lunar base design. Other potential sites for application include planetary surfaces such as Mars, variable gravity research facilities, or a rotating spacecraft. Design requirements for partial gravity environments include: (1) locomotion changes in less than normal Earth gravity; (2) facility design issues, such as interior configuration, module diameter and geometry; and (3) volumetric requirements based on the previous as well as psychological issues involved in prolonged isolation. For application to a Lunar Base, it was necessary to study the exterior architecture and configuration to insure optimum circulation patterns while providing dual egress. Radiation protection issues were addressed to provide a safe and healthy environment for the crew, and finally, the overall site was studied to locate all associated facilities in context with the habitat. Mission planning was not the purpose of this study; therefore, a Lockheed scenario was used as an outline for the Lunar Base application, which was then modified to meet the project needs.

Pelagic Habitat Analysis Module (PHAM) for GIS Based Fisheries Decision Support

NASA Technical Reports Server (NTRS)

Kiefer, D. A.; Armstrong, Edward M.; Harrison, D. P.; Hinton, M. G.; Kohin, S.; Snyder, S.; O'Brien, F. J.

2011-01-01

We have assembled a system that integrates satellite and model output with fisheries data We have developed tools that allow analysis of the interaction between species and key environmental variables Demonstrated the capacity to accurately map habitat of Thresher Sharks Alopias vulpinus & pelagicus. Their seasonal migration along the California Current is at least partly driven by the seasonal migration of sardine, key prey of the sharks.We have assembled a system that integrates satellite and model output with fisheries data We have developed tools that allow analysis of the interaction between species and key environmental variables Demonstrated the capacity to accurately map habitat of Thresher Sharks Alopias vulpinus nd pelagicus. Their seasonal migration along the California Current is at least partly driven by the seasonal migration of sardine, key prey of the sharks.

Mapping and monitoring Mt. Graham Red Squirrel habitat with GIS and thematic mapper imagery

USGS Publications Warehouse

Hatten, James R.; Koprowski, John L.; Sanderson, H. Reed; Koprowski, John L.

2009-01-01

To estimate the Mt. Graham red squirrel (MGRS) population, personnel visit a proportion of middens each year to determine their occupancy (Snow in this vol.). The method results in very tight confidence intervals (high precision), but the accuracy of the population estimate is dependent upon knowing where all the middens are located. I hypothesized that there might be areas outside the survey boundary that contained Mt. Graham red squirrel middens, but the ruggedness of the Pinaleno Mountains made mountain-wide surveys difficult. Therefore, I started exploring development of a spatially explicit (geographic information system [GIS]-based) habitat model in 1998 that could identify MGRS habitat remotely with satellite imagery and a GIS. A GIS-based model would also allow us to assess changes in MGRS habitat between two time periods because Landsat passes over the same location every 16 days, imaging the earth in 185 km swaths (Aronoff 1989). Specifically, the objectives of this analysis were to (1) develop a pattern recognition model for MGRS habitat, (2) map potential (predicted/modeled) MGRS habitat, (3) identify changes in potential MGRS habitat between 1993 and 2003, and (4) evaluate the current location of the MGRS survey boundary.

Landscape models of brook trout abundance and distribution in lotic habitat with field validation

USGS Publications Warehouse

McKenna, James E.; Johnson, James H.

2011-01-01

Brook trout Salvelinus fontinalis are native fish in decline owing to environmental changes. Predictions of their potential distribution and a better understanding of their relationship to habitat conditions would enhance the management and conservation of this valuable species. We used over 7,800 brook trout observations throughout New York State and georeferenced, multiscale landscape condition data to develop four regionally specific artificial neural network models to predict brook trout abundance in rivers and streams. Land cover data provided a general signature of human activity, but other habitat variables were resistant to anthropogenic changes (i.e., changing on a geological time scale). The resulting models predict the potential for any stream to support brook trout. The models were validated by holding 20% of the data out as a test set and by comparison with additional field collections from a variety of habitat types. The models performed well, explaining more than 90% of data variability. Errors were often associated with small spatial displacements of predicted values. When compared with the additional field collections (39 sites), 92% of the predictions were off by only a single class from the field-observed abundances. Among “least-disturbed” field collection sites, all predictions were correct or off by a single abundance class, except for one where brown trout Salmo trutta were present. Other degrading factors were evident at most sites where brook trout were absent or less abundant than predicted. The most important habitat variables included landscape slope, stream and drainage network sizes, water temperature, and extent of forest cover. Predicted brook trout abundances were applied to all New York streams, providing a synoptic map of the distribution of brook trout habitat potential. These fish models set benchmarks of best potential for streams to support brook trout under broad-scale human influences and can assist with planning and

Blue and Fin Whale Habitat Modeling from Long-Term Year-Round Passive Acoustic Data from the Southern California Bight

DTIC Science & Technology

2014-09-30

be used for habitat modeling include sea surface temperature (SST), sea surface height (SSH), chlorophyll a concentration, and primary production...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Blue and Fin Whale Habitat Modeling from Long-Term Year...predictive, year-round habitat models of the presence of calling blue and fin whales in the Southern California Bight, to facilitate Navy’s operational

Freshwater ecosystems and resilience of Pacific salmon: Habitat Management based on natural variability

USGS Publications Warehouse

Bisson, P.A.; Dunham, J.B.; Reeves, G.H.

2009-01-01

In spite of numerous habitat restoration programs in fresh waters with an aggregate annual funding of millions of dollars, many populations of Pacific salmon remain significantly imperiled. Habitat restoration strategies that address limited environmental attributes and partial salmon life-history requirements or approaches that attempt to force aquatic habitat to conform to idealized but ecologically unsustainable conditions may partly explain this lack of response. Natural watershed processes generate highly variable environmental conditions and population responses, i.e., multiple life histories, that are often not considered in restoration. Examples from several locations underscore the importance of natural variability to the resilience of Pacific salmon. The implication is that habitat restoration efforts will be more likely to foster salmon resilience if they consider processes that generate and maintain natural variability in fresh water. We identify three specific criteria for management based on natural variability: the capacity of aquatic habitat to recover from disturbance, a range of habitats distributed across stream networks through time sufficient to fulfill the requirements of diverse salmon life histories, and ecological connectivity. In light of these considerations, we discuss current threats to habitat resilience and describe how regulatory and restoration approaches can be modified to better incorporate natural variability. ?? 2009 by the author(s).

The Hyper-Envelope Modeling Interface (HEMI): A Novel Approach Illustrated Through Predicting Tamarisk (Tamarix spp.) Habitat in the Western USA

USGS Publications Warehouse

Graham, Jim; Young, Nick; Jarnevich, Catherine S.; Newman, Greg; Evangelista, Paul; Stohlgren, Thomas J.

2013-01-01

Habitat suitability maps are commonly created by modeling a species’ environmental niche from occurrences and environmental characteristics. Here, we introduce the hyper-envelope modeling interface (HEMI), providing a new method for creating habitat suitability models using Bezier surfaces to model a species niche in environmental space. HEMI allows modeled surfaces to be visualized and edited in environmental space based on expert knowledge and does not require absence points for model development. The modeled surfaces require relatively few parameters compared to similar modeling approaches and may produce models that better match ecological niche theory. As a case study, we modeled the invasive species tamarisk (Tamarix spp.) in the western USA. We compare results from HEMI with those from existing similar modeling approaches (including BioClim, BioMapper, and Maxent). We used synthetic surfaces to create visualizations of the various models in environmental space and used modified area under the curve (AUC) statistic and akaike information criterion (AIC) as measures of model performance. We show that HEMI produced slightly better AUC values, except for Maxent and better AIC values overall. HEMI created a model with only ten parameters while Maxent produced a model with over 100 and BioClim used only eight. Additionally, HEMI allowed visualization and editing of the model in environmental space to develop alternative potential habitat scenarios. The use of Bezier surfaces can provide simple models that match our expectations of biological niche models and, at least in some cases, out-perform more complex approaches.

Modeling the Effect of Geomorphic Change Triggered by Large Wood Addition on Salmon Habitat in a Forested Coastal Watershed

NASA Astrophysics Data System (ADS)

Bair, R.; Segura, C.; Lorion, C.

2015-12-01

Large wood (LW) additions are often part of fish habitat restorations in the PNW where historic forest clear-cutting limited natural wood recruitment. These efforts' relative successes are rarely reported in terms of ecological significance to different life stages of fish. Understanding the effectiveness of LW additions will contribute to successfully managing forest land. In this study we quantify the geomorphic change of a restoration project involving LW additions to three alluvial reaches in Mill Creek, OR. The reaches are 110-130m in plane-bed morphology and drain 2-16km2. We quantify the change in available habitat to different life stages of coho salmon in terms of velocity (v), shear stress (t), flow depth, and grain size distributions (GSD) considering existing thresholds in the literature for acceptable habitat. Flow conditions before and after LW additions are assessed using a 2D hydrodynamic model (FaSTMECH). Model inputs include detailed channel topography, discharge, and surface GSD. The spatial-temporal variability of sediment transport was also quantified based the modeled t distributions and the GSD to document changes in the overall geomorphic regime. Initial modeling results for pre wood conditions show mean t and v values ranging between 0 and 26N/m2 and between 0 and 2.4m/s, respectively for up to bankfull flow (Qbf). The distributions of both t and v become progressively wider and peak at higher values as flow increases with the notable exception at Qbf for which the area of low velocity increases noticeably. The spatial distributions of velocity results indicates that the extent of suitable habitat for adult coho decreased by 18% between flows 30 and 55% of BF. However the area of suitable habitat increased by 15% between 0.55Qbf and Qbf as the flow spreads from the channel into the floodplain. We expect the LW will enhance floodplain connectivity and thus available habitat by creating additional areas of low v during winter flows.

76 FR 9590 - Fisheries and Habitat Conservation and Migratory Birds Programs; Draft Land-Based Wind Energy...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-18

..., wildlife and their habitats resulting from construction, operation and maintenance of land-based, wind... these draft Guidelines for all wind turbines, including community scale operations. All comments we...] RIN 1018-AX45 Fisheries and Habitat Conservation and Migratory Birds Programs; Draft Land-Based Wind...

Combining pixel and object based image analysis of ultra-high resolution multibeam bathymetry and backscatter for habitat mapping in shallow marine waters

NASA Astrophysics Data System (ADS)

Ierodiaconou, Daniel; Schimel, Alexandre C. G.; Kennedy, David; Monk, Jacquomo; Gaylard, Grace; Young, Mary; Diesing, Markus; Rattray, Alex

2018-06-01

Habitat mapping data are increasingly being recognised for their importance in underpinning marine spatial planning. The ability to collect ultra-high resolution (cm) multibeam echosounder (MBES) data in shallow waters has facilitated understanding of the fine-scale distribution of benthic habitats in these areas that are often prone to human disturbance. Developing quantitative and objective approaches to integrate MBES data with ground observations for predictive modelling is essential for ensuring repeatability and providing confidence measures for habitat mapping products. Whilst supervised classification approaches are becoming more common, users are often faced with a decision whether to implement a pixel based (PB) or an object based (OB) image analysis approach, with often limited understanding of the potential influence of that decision on final map products and relative importance of data inputs to patterns observed. In this study, we apply an ensemble learning approach capable of integrating PB and OB Image Analysis from ultra-high resolution MBES bathymetry and backscatter data for mapping benthic habitats in Refuge Cove, a temperate coastal embayment in south-east Australia. We demonstrate the relative importance of PB and OB seafloor derivatives for the five broad benthic habitats that dominate the site. We found that OB and PB approaches performed well with differences in classification accuracy but not discernible statistically. However, a model incorporating elements of both approaches proved to be significantly more accurate than OB or PB methods alone and demonstrate the benefits of using MBES bathymetry and backscatter combined for class discrimination.

Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling

USGS Publications Warehouse

Bernal, Nicholas A.; DeAngelis, Donald L.; Schofield, Pamela J.; Sullivan Sealey, Kathleen

2014-01-01

Invasive species may exhibit higher levels of growth and reproduction when environmental conditions are most suitable, and thus their effects on native fauna may be intensified. Understanding potential impacts of these species, especially in the nascent stages of a biological invasion, requires critical information concerning spatial and temporal distributions of habitat suitability. Using empirically supported environmental variables (e.g., temperature, salinity, dissolved oxygen, rugosity, and benthic substrate), our models predicted habitat suitability for the invasive lionfish (Pterois volitans) in Biscayne Bay, Florida. The use of Geographic Information Systems (GIS) as a platform for the modeling process allowed us to quantify correlations between temporal (seasonal) fluctuations in the above variables and the spatial distribution of five discrete habitat quality classes, whose ranges are supported by statistical deviations from the apparent best conditions described in prior studies. Analysis of the resulting models revealed little fluctuation in spatial extent of the five habitat classes on a monthly basis. Class 5, which represented the area with environmental variables closest to the best conditions for lionfish, occupied approximately one-third of Biscayne Bay, with subsequent habitats declining in area. A key finding from this study was that habitat suitability increased eastward from the coastline, where higher quality habitats were adjacent to the Atlantic Ocean and displayed marine levels of ambient water quality. Corroboration of the models with sightings from the USGS-NAS database appeared to support our findings by nesting 79 % of values within habitat class 5; however, field testing (i.e., lionfish surveys) is necessary to confirm the relationship between habitat classes and lionfish distribution.

Using a coupled eco-hydrodynamic model to predict habitat for target species following dam removal

USGS Publications Warehouse

Tomsic, C.A.; Granata, T.C.; Murphy, R.P.; Livchak, C.J.

2007-01-01

A habitat suitability index (HSI) model was developed for a water quality sensitive fish (Greater Redhorse) and macroinvertebrate (Plecoptera) species to determine the restoration success of the St. John Dam removal for the Sandusky River (Ohio). An ArcGIS?? model was created for pre- and post-dam removal scenarios. Inputs to the HSI model consist of substrate distributions from river surveys, and water level and velocity time series, outputs from a hydrodynamic model. The ArcGIS?? model predicted habitat suitability indices at 45 river cross-sections in the hydrodynamic model. The model was programmed to produce polygon layers, using graphical user interfaces that were displayed in the ArcGIS?? environment. The results of the model clearly show an increase of habitat suitability from pre- to post-dam removal periods and in the former reservoir. The change in suitability of the model is attributed mostly to the change in depth in the river following the dam removal for both the fish and invertebrate species. The results of the invertebrate model followed the same positive trend as species enumerations from the river basin. ?? 2007 Elsevier B.V. All rights reserved.