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1.
Ecol Evol ; 13(7): e10317, 2023 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-37456080

RESUMEN

Body condition is a frequently used physiological indicator of avian health and can be affected by an array of environmental variables. Although a number of studies have investigated the specific effects of individual weather variables on body condition in birds, few have analyzed the effects of both temperature and precipitation within the context of an extreme weather event such as hurricanes. In this study, we examined the relationship between breeding-season body condition and daily maximum temperature, daily minimum temperature, and monthly total precipitation for three passerine bird species at the Welder Wildlife Refuge near Rockport, Texas. We also evaluated yearly changes in body condition over a 12-year period for northern cardinals (Cardinalis cardinalis), painted buntings (Passerina ciris), and white-eyed vireos (Vireo griseus), focusing on the extreme precipitation event of Hurricane Harvey, which caused heavy localized flooding. We found that body condition declined with average daily minimum and maximum temperatures, while precipitation had varied, species-specific effects in the three species analyzed. Our results also suggest that northern cardinals experienced a notable reduction in average body condition in the 2 years following Hurricane Harvey. Taken together, we conclude that short-term precipitation and temperature drivers can be important correlates of body condition in songbirds and that severe weather events may reduce body condition in some bird species.

2.
J Environ Manage ; 75(4): 379-97, 2005 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-15854730

RESUMEN

In this paper, we describe a model designed to simulate seasonal dynamics of warm and cool season grasses and forbs, as well as the dynamics of woody plant succession through five seral stages, in each of nine different plant communities on the Rob and Bessie Welder Wildlife Refuge. The Welder Wildlife Refuge (WWR) is located in the Gulf Coastal Prairies and Marshes ecoregion of Texas. The model utilizes and integrates data from a wide array of research projects that have occurred in south Texas and WWR. It is designed to investigate the effects of alternative livestock grazing programs and brush control practices, with particular emphasis on prescribed burning, the preferred treatment for brush on the WWR. We evaluated the model by simulating changes in the plant communities under historical (1974-2000) temperature, rainfall, livestock grazing rotation, and brush control regimes, and comparing simulation results to field data on herbaceous biomass and brush canopy cover collected on the WWR over the same period. We then used the model to simulate the effects of 13 alternative management schemes, under each of four weather regimes, over the next 25 years. We found that over the simulation period, years 1974-2000, the model does well in simulating the magnitude and seasonality of herbaceous biomass production and changes in percent brush canopy cover on the WWR. It also does well in simulating the effects of variations in cattle stocking rates, grazing rotation programs, and brush control regimes on plant communities, thus providing insight into the combined effects of temperature, precipitation, cattle stocking rates, grazing rotation programs, and brush control on the overall productivity and state of woody plant succession on the WWR. Simulation of alternative management schemes suggests that brush canopy removal differs little between summer and winter prescribed burn treatments when precipitation remains near the long-term average, but during periods of low precipitation canopy removal is greater under winter prescribed burning. The model provides a useful tool to assist refuge personnel with developing long-term brush management and livestock grazing strategies.


Asunto(s)
Algoritmos , Crianza de Animales Domésticos/métodos , Animales Domésticos/fisiología , Ecosistema , Modelos Teóricos , Fenómenos Fisiológicos de las Plantas , Animales , Simulación por Computador , Incendios , Lluvia , Estaciones del Año , Temperatura , Texas
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