The influence of geographic variation in vegetation characteristics on habitat use and productivity of an endangered warbler

Long, Ashley M.; Mathewson, Heather A.; Morrison, Michael L.

doi:10.1016/j.foreco.2020.118857

Cited by 2 publications

(2 citation statements)

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“…We conducted our research from March to August of 2013 and 2014 across a broad spatial extent within four Major Land Resource Areas that represented regional vegetation communities and plant responses to disturbance (USDA NRCS 2006) and documented variation in warbler-and vireo-habitat use and demographics (Grzybowski et al 1994, Long et al 2021…”

Section: Study Areasmentioning

confidence: 99%

Demonstration of a multi‐species, multi‐response state‐and‐transition model approach for wildlife management

et al. 2021

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Land management agencies have collaborated to standardize assessments of rangeland health.These assessments incorporate state-and-transition concepts of ecosystem function using ecological site descriptions (ESDs) initially developed to provide information on the soil, topography, climate, and vegetation at areas of interest. Combined, ESDs and state-and-transition models (STMs) describe existing and potential plant community dynamics. Unlike previous methods used to assess rangeland health, STMs take into account that multiple states exist in space and time across sites and that reversible and directional changes in vegetation can occur in response to factors such as fire, erosion, weather, and management activities. Wildlife responses are seldom incorporated into this framework. However, combining STMs, ESDs, and species-specific habitat use and demographic data could provide land managers with tools that classify current ecosystem conditions, predict vegetative change, and inform management for maintaining or improving key habitat features for species of interest. To demonstrate a multi-species, multi-response STM approach for wildlife management, we quantified vegetation structure and composition as a function of time since prescribed burning and wildfire in four geographically distinct study areas. We found no significant differences in the topographic or vegetative characteristics of ecological sites within our study areas. Thus, we visualized habitat use and demographic data for our two avian study species, the golden-cheeked warbler (Setophaga chrysoparia) and the black-capped vireo (Vireo atricapilla), along with plant community transformations, in a single STM per study area. Our research demonstrates how STMs could be operationalized for wildlife management in such a way that accounts for co-occurring species with contrasting habitat requirements. In addition, our approach further illustrates how STMs could provide land managers with guidance to minimize the negative effects or enhance the positive effects of disturbance and management activities on wildlife.

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Section: Study Areasmentioning

confidence: 99%

Demonstration of a multi‐species, multi‐response state‐and‐transition model approach for wildlife management

et al. 2021

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“…Species distribution models or habitat suitability models allow potentially predicting human effects on biodiversity patterns at different spatial scales, the origin more of modeling methods to predict of fauna and flora distribution have in environmental-species relations [11]. Habitat models of habitat-wildlife relationships are used to assess the potential of the area [12] and to create habitat patterns for species that are introduced or present in the area [13,14]. Digital distribution maps of species for basic and applied environmental research [15] based on powerful statistical software and Geographic Information System (GIS) tools, depending on the environmental needs of the species and their geographical distribution, lead to the development of habitat modeling [16].…”

Section: Introductionmentioning

confidence: 99%

Habitat Suitability Modeling for Wildlife Management Objectives by Using Maximum Entropy Method

Naqibzadeh

Sarhangzadeh

Sotoudeh

et al. 2021

J. Hum. Earth Future

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Habitat suitability models are useful tools for a variety of wildlife management objectives. Distributions of wildlife species can be predicted for geographical areas that have not been extensively surveyed. The basis of these models' work is to minimize the relationship between species distribution and biotic and abiotic environments. For some species, there is information about presence and absence that allows the use of a variety of standard statistical methods. However, absence data is not available for most species. Nowadays, the methods that need presence-only data have been expanded. One of these methods is the Maximum Entropy (MaxEnt) model. The purpose of this study is to model the habitat of Urial (Ovis orientalis arkal) in the Samelghan plain in the North East of Iran with the MaxEnt method. This algorithm uses the Jackknife plot and percent contribution values to determine the significance of the variables. The results showed that variables such as southern aspects, Juniperus-Acer, Artemisia-Perennial plants, slope 0-5%, and asphalt road were the most important factors affecting the species’ habitat selection. The area under the curve (AUC) Receiver Operating Characteristic (ROC) showed excellent model performance. Suitable habitat was classified based on the threshold value (0.0513) and the ROC, which, based on the results, 28% of the area was a suitable habitat for Urial. Doi: 10.28991/HEF-2021-02-04-05 Full Text: PDF

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The influence of geographic variation in vegetation characteristics on habitat use and productivity of an endangered warbler

Cited by 2 publications

References 44 publications

Demonstration of a multi‐species, multi‐response state‐and‐transition model approach for wildlife management

Demonstration of a multi‐species, multi‐response state‐and‐transition model approach for wildlife management

Habitat Suitability Modeling for Wildlife Management Objectives by Using Maximum Entropy Method

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