Comparing Habitat Suitability and Connectivity Modeling Methods for Conserving Pronghorn Migrations

Poor, Erin E.; Jakes, Andrew F.; Urban, Dean L.

doi:10.1371/journal.pone.0049390

Cited by 121 publications

(103 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…MaxEnt was chosen because of its widespread use in modeling movement corridors (Liu, McShea, & Li, 2017; Poor, Loucks, Jakes, & Urban, 2012), because it provides an easy‐to‐use GUI interface, and because it is permanently open‐source through the American Museum of Natural History (Elith et al., 2011; Phillips, Anderson, Dudík, Schapire, & Blair, 2017). This step produced a connectivity surface (Figure 2: O 4a ) for G. fuscipes tsetse flies in northern Uganda that accounts for genetics of the target species in a specific region of interest.…”

Section: Methodsmentioning

confidence: 99%

A spatial genetics approach to inform vector control of tsetse flies (Glossina fuscipes fuscipes) in Northern Uganda

Saarman

Burak

Opiro

et al. 2018

Ecology and Evolution

View full text Add to dashboard Cite

Tsetse flies (genus Glossina) are the only vector for the parasitic trypanosomes responsible for sleeping sickness and nagana across sub‐Saharan Africa. In Uganda, the tsetse fly Glossina fuscipes fuscipes is responsible for transmission of the parasite in 90% of sleeping sickness cases, and co‐occurrence of both forms of human‐infective trypanosomes makes vector control a priority. We use population genetic data from 38 samples from northern Uganda in a novel methodological pipeline that integrates genetic data, remotely sensed environmental data, and hundreds of field‐survey observations. This methodological pipeline identifies isolated habitat by first identifying environmental parameters correlated with genetic differentiation, second, predicting spatial connectivity using field‐survey observations and the most predictive environmental parameter(s), and third, overlaying the connectivity surface onto a habitat suitability map. Results from this pipeline indicated that net photosynthesis was the strongest predictor of genetic differentiation in G. f. fuscipes in northern Uganda. The resulting connectivity surface identified a large area of well‐connected habitat in northwestern Uganda, and twenty‐four isolated patches on the northeastern margin of the G. f. fuscipes distribution. We tested this novel methodological pipeline by completing an ad hoc sample and genetic screen of G. f. fuscipes samples from a model‐predicted isolated patch, and evaluated whether the ad hoc sample was in fact as genetically isolated as predicted. Results indicated that genetic isolation of the ad hoc sample was as genetically isolated as predicted, with differentiation well above estimates made in samples from within well‐connected habitat separated by similar geographic distances. This work has important practical implications for the control of tsetse and other disease vectors, because it provides a way to identify isolated populations where it will be safer and easier to implement vector control and that should be prioritized as study sites during the development and improvement of vector control methods.

show abstract

Section: Methodsmentioning

confidence: 99%

A spatial genetics approach to inform vector control of tsetse flies (Glossina fuscipes fuscipes) in Northern Uganda

Saarman

Burak

Opiro

et al. 2018

Ecology and Evolution

View full text Add to dashboard Cite

show abstract

“…These user defined resistance models have been tested based on limited inference from few radiomarked individuals (Driezen et al 2007). However, examples exist of deriving resistance values from occurrence probability from occupancy models (Walpole et al 2012) or using a variety of different threshold values based on the most traversable habitat from radio-marked individuals (Poor et al 2012). Of importance is that these applications fail to utilize the information from animal movements to directly estimate landscape resistance values.…”

Section: Landscape Management and Corridor Designmentioning

confidence: 99%

Unifying population and landscape ecology with spatial capture–recapture

Royle¹,

Fuller

Sutherland³

2017

Ecography

129

172

View full text Add to dashboard Cite

Spatial heterogeneity in the environment induces variation in population demographic rates and dispersal patterns, which result in spatio-temporal variation in density and gene flow. Unfortunately, applying theory to learn about the role of spatial structure on populations has been hindered by the lack of mechanistic spatial models and inability to make precise observations of population state and structure. Spatial capture-recapture (SCR) represents an individual-based analytic framework for overcoming this fundamental obstacle that has limited the utility of ecological theory. SCR methods make explicit use of spatial encounter information on individuals in order to model density and other spatial aspects of animal population structure, and they have been widely adopted in the last decade. We review the historical context and emerging developments in SCR models that enable the integration of explicit ecological hypotheses about landscape connectivity, movement, resource selection, and spatial variation in density, directly with individual encounter history data obtained by new technologies (e.g. camera trapping, non-invasive DNA sampling). We describe ways in which SCR methods stand to advance the study of animal population ecology.

show abstract

“…Based on the RF model results, we considered the potential habitat areas as the areas over the threshold of the 'receiver operating characteristic' (ROC) curve [16]. Although various researchers insist that SDMs could overestimate the probability presence, SDMs appear to be a superior choice for mapping the distribution of species, as they require less research effort [50].…”

Section: Ratio (%) =mentioning

confidence: 99%

Applying Topographic Classification, Based on the Hydrological Process, to Design Habitat Linkages for Climate Change

Lee

Song

et al. 2017

Forests

View full text Add to dashboard Cite

Abstract:The use of biodiversity surrogates has been discussed in the context of designing habitat linkages to support the migration of species affected by climate change. Topography has been proposed as a useful surrogate in the coarse-filter approach, as the hydrological process caused by topography such as erosion and accumulation is the basis of ecological processes. However, some studies that have designed topographic linkages as habitat linkages, so far have focused much on the shape of the topography (morphometric topographic classification) with little emphasis on the hydrological processes (generic topographic classification) to find such topographic linkages. We aimed to understand whether generic classification was valid for designing these linkages. First, we evaluated whether topographic classification is more appropriate for describing actual (coniferous and deciduous) and potential (mammals and amphibians) habitat distributions. Second, we analyzed the difference in the linkages between the morphometric and generic topographic classifications. The results showed that the generic classification represented the actual distribution of the trees, but neither the morphometric nor the generic classification could represent the potential animal distributions adequately. Our study demonstrated that the topographic classes, according to the generic classification, were arranged successively according to the flow of water, nutrients, and sediment; therefore, it would be advantageous to secure linkages with a width of 1 km or more. In addition, the edge effect would be smaller than with the morphometric classification. Accordingly, we suggest that topographic characteristics, based on the hydrological process, are required to design topographic linkages for climate change.

show abstract

Comparing Habitat Suitability and Connectivity Modeling Methods for Conserving Pronghorn Migrations

Cited by 121 publications

References 63 publications

A spatial genetics approach to inform vector control of tsetse flies (Glossina fuscipes fuscipes) in Northern Uganda

A spatial genetics approach to inform vector control of tsetse flies (Glossina fuscipes fuscipes) in Northern Uganda

Unifying population and landscape ecology with spatial capture–recapture

Applying Topographic Classification, Based on the Hydrological Process, to Design Habitat Linkages for Climate Change

Contact Info

Product

Resources

About