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Influence of Landscape Composition and Structure on Antler Size of White‐Tailed Deer

Identifieur interne : 000995 ( Main/Merge ); précédent : 000994; suivant : 000996

Influence of Landscape Composition and Structure on Antler Size of White‐Tailed Deer

Auteurs : Bronson K. Strickland [États-Unis] ; Stephen Demarais [États-Unis]

Source :

RBID : ISTEX:052AB2BEF4EF3C3D5D8DB109C22B3F16FAEC60DF

English descriptors

Abstract

Abstract: Cause for spatial variation in phenotypic quality of white‐tailed deer (Odocoileus virginianus) populations is of great interest to wildlife managers. Relating phenotypic variation of populations to large‐scale land‐use patterns may provide insight into why populations exhibit spatial variation and elucidate how management can influence population phenotype. We used an information‐theoretic approach to relate average antler size of 203 deer populations to composition and structure of the habitat occupied by those populations. We used interspersion, edge, and diversity indices to represent habitat structure and percentage of area in vegetation types to represent habitat composition. Landscape composition was a better predictor of deer population antler size than was landscape structure. Percentages of the management unit in agriculture, pasture, and pine forest were variables commonly found in the region‐specific set of best models. Model‐averaged estimates of agriculture and pasture parameters were always positive and estimates of pine forest parameters were always negative, which suggests that land‐use types that promote growth of early successional herbaceous plants will positively influence antler size and, most likely, body growth and reproduction of white‐tailed deer populations. Conversely, our findings suggest landscapes dominated by pine forests did not provide optimal amounts of quality forages for white‐tailed deer. Pine forest effects should be mitigated using a combination of increased harvest to lower deer density and silvicultural practices like thinning, prescribed burning, and selective herbicide applications that stimulate growth of high‐quality forages beneath the forest canopy to improve deer phenotypic quality.

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DOI: 10.2193/2007-381

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ISTEX:052AB2BEF4EF3C3D5D8DB109C22B3F16FAEC60DF

Le document en format XML

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<div type="abstract">Abstract: Cause for spatial variation in phenotypic quality of white‐tailed deer (Odocoileus virginianus) populations is of great interest to wildlife managers. Relating phenotypic variation of populations to large‐scale land‐use patterns may provide insight into why populations exhibit spatial variation and elucidate how management can influence population phenotype. We used an information‐theoretic approach to relate average antler size of 203 deer populations to composition and structure of the habitat occupied by those populations. We used interspersion, edge, and diversity indices to represent habitat structure and percentage of area in vegetation types to represent habitat composition. Landscape composition was a better predictor of deer population antler size than was landscape structure. Percentages of the management unit in agriculture, pasture, and pine forest were variables commonly found in the region‐specific set of best models. Model‐averaged estimates of agriculture and pasture parameters were always positive and estimates of pine forest parameters were always negative, which suggests that land‐use types that promote growth of early successional herbaceous plants will positively influence antler size and, most likely, body growth and reproduction of white‐tailed deer populations. Conversely, our findings suggest landscapes dominated by pine forests did not provide optimal amounts of quality forages for white‐tailed deer. Pine forest effects should be mitigated using a combination of increased harvest to lower deer density and silvicultural practices like thinning, prescribed burning, and selective herbicide applications that stimulate growth of high‐quality forages beneath the forest canopy to improve deer phenotypic quality.</div>
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