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1.
Conserv Biol ; 29(1): 99-109, 2015 Feb.
Article in English | MEDLINE | ID: mdl-25158993

ABSTRACT

In much of the world, the persistence of long-distance migrations by mammals is threatened by development. Even where human population density is relatively low, there are roads, fencing, and energy development that present barriers to animal movement. If we are to conserve species that rely on long-distance migration, then it is critical that we identify existing migration impediments. To delineate stopover sites associated with anthropogenic development, we applied Brownian bridge movement models to high-frequency locations of pronghorn (Antilocapra americana) in the Greater Yellowstone Ecosystem. We then used resource utilization functions to assess the threats to long-distance migration of pronghorn that were due to fences and highways. Migrating pronghorn avoided dense developments of natural gas fields. Highways with relatively high volumes of traffic and woven-wire sheep fence acted as complete barriers. At crossings with known migration bottlenecks, use of high-quality forage and shrub habitat by pronghorn as they approached the highway was lower than expected based on availability of those resources. In contrast, pronghorn consistently utilized high-quality forage close to the highway at crossings with no known migration bottlenecks. Our findings demonstrate the importance of minimizing development in migration corridors in the future and of mitigating existing pressure on migratory animals by removing barriers, reducing the development footprint, or installing crossing structures.


Subject(s)
Animal Migration , Antelopes/physiology , Conservation of Natural Resources , Animals , Ecosystem , Geographic Information Systems , Models, Biological , Wyoming
2.
Curr Biol ; 30(17): 3444-3449.e4, 2020 09 07.
Article in English | MEDLINE | ID: mdl-32619482

ABSTRACT

Animals exhibit a diversity of movement tactics [1]. Tracking resources that change across space and time is predicted to be a fundamental driver of animal movement [2]. For example, some migratory ungulates (i.e., hooved mammals) closely track the progression of highly nutritious plant green-up, a phenomenon called "green-wave surfing" [3-5]. Yet general principles describing how the dynamic nature of resources determine movement tactics are lacking [6]. We tested an emerging theory that predicts surfing and the existence of migratory behavior will be favored in environments where green-up is fleeting and moves sequentially across large landscapes (i.e., wave-like green-up) [7]. Landscapes exhibiting wave-like patterns of green-up facilitated surfing and explained the existence of migratory behavior across 61 populations of four ungulate species on two continents (n = 1,696 individuals). At the species level, foraging benefits were equivalent between tactics, suggesting that each movement tactic is fine-tuned to local patterns of plant phenology. For decades, ecologists have sought to understand how animals move to select habitat, commonly defining habitat as a set of static patches [8, 9]. Our findings indicate that animal movement tactics emerge as a function of the flux of resources across space and time, underscoring the need to redefine habitat to include its dynamic attributes. As global habitats continue to be modified by anthropogenic disturbance and climate change [10], our synthesis provides a generalizable framework to understand how animal movement will be influenced by altered patterns of resource phenology.


Subject(s)
Animal Migration/physiology , Climate Change , Deer/physiology , Ecosystem , Plant Development , Plant Physiological Phenomena , Plants/metabolism , Animals , Geographic Information Systems , Herbivory
3.
Conserv Biol ; 22(4): 1006-15, 2008 Aug.
Article in English | MEDLINE | ID: mdl-18544091

ABSTRACT

Researchers predict that new infrastructure development will sharply increase the rate and extent of deforestation in the Brazilian Amazon. There are no predictions, however, of which species it will affect. We used a spatially explicit model that predicts the location of deforestation in the Brazilian Amazon by 2020 on the basis of historical patterns of deforestation following infrastructure development. We overlaid the predicted deforested areas onto maps of bird ranges to estimate the amount of habitat loss within species ranges. We also estimated the amount of habitat loss within modified ecoregions, which were used as surrogates for areas of bird endemism. We then used the extent of occurrence criterion of the World Conservation Union to predict the future conservation status of birds in the Brazilian Amazon. At current rates of development, our results show that at least 16 species will qualify as threatened or will lose more than half of their forested habitat. We also identified several subspecies and isolated populations that would also qualify as threatened. Most of the taxa we identified are not currently listed as threatened, and the majority are associated with riverine habitats, which have been largely ignored in bird conservation in Amazonia. These habitats and the species they hold will be increasingly relevant to conservation as river courses are altered and hydroelectric dams are constructed in the Brazilian Amazon.


Subject(s)
Birds/physiology , Conservation of Natural Resources , Ecosystem , Animals , Human Activities , Models, Biological , Population Dynamics , Power Plants , Rivers , Trees
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