首页> 外文期刊>Journal of Wildlife Management >Home Range and Resource Selection by GPS-Monitored Adult Golden Eagles in the Columbia Plateau Ecoregion: Implications for Wind Power Development
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Home Range and Resource Selection by GPS-Monitored Adult Golden Eagles in the Columbia Plateau Ecoregion: Implications for Wind Power Development

机译:GPS监测的成年金鹰在哥伦比亚高原生态区的住宅范围和资源选择:对风电开发的影响

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Recent national interest in golden eagle (Aquila chrysaetos) conservation and wind energy development prompted us to investigate golden eagle home range and resource use in the Columbia Plateau Ecoregion (CPE) in Washington and Oregon. From 2004 to 2013, we deployed satellite transmitters on adult eagles (n=17) and monitored their movements for up to 7 years. We used the Brownian bridge movement model (BBMM) to estimate range characteristics from global position system (GPS) fixes and flight paths of 10 eagles, and modeled resource selection probability functions (RSPFs). Multi-year home ranges of resident eagles were large (99% volume contour; (x) over bar = 245.7km(2), SD=370.2km(2)) but were one-third the size ((x) over bar = 82.3km2, SD=94.6km(2)) and contained half as many contours when defined by 95% isopleths. Annual ranges accounted for 66% of multi-year range size. During the breeding season (16 Jan-15 Aug), eagles occupied ranges that were less fragmented, about half as large, and largely contained within ranges they used outside the breeding season ((x) over bar overlap=82.5%, SD=19.0). Eagles selected upper slopes, rugged terrain, and ridge tops that appear to reflect underlying influences of prey, deflective wind currents, and proximity to nests. Fix distribution predicted by our resource selection model and that of 4 eagles monitored independently in the CPE were highly correlated (r(s)=0.992). Our findings suggest conservative landscape management strategies addressing development in lower-elevation montane and shrub-steppe/grassland ecosystems can best define golden eagle ranges using exclusive 12.8-km buffers around nests. Less conservative strategies based on 9.6-km buffers must include identification and management of upper slopes, ridge-tops, and areas of varied terrain defined by predictive models or GPS telemetry. For both strategies, high, year-round intensity of eagle flight and perch use within 50% volume contours (average 3.2km from nests) due to nest centricity may dramatically increase the probability of eagle conflict with wind turbines in core areas as evidenced by eagle turbine strikes that studies have documented within and beyond this zone. (c) 2014 The Wildlife Society.
机译:最近国家对金鹰(Aquila chrysaetos)保护和风能开发的兴趣促使我们研究华盛顿和俄勒冈州哥伦比亚高原生态区(CPE)的金鹰栖息地和资源利用情况。从2004年到2013年,我们在成年雄鹰(n = 17)上部署了卫星发射器,并监测了它们的活动长达7年。我们使用布朗桥移动模型(BBMM)从全球定位系统(GPS)定位和10头鹰的飞行路径估计范围特征,并建模资源选择概率函数(RSPF)。驻地鹰的多年居所范围很大(99%的体积轮廓;(x)超过bar = 245.7km(2),SD = 370.2km(2)),但只有其大小的三分之一(超过(bar)= [x] 82.3km2,SD = 94.6km(2)),并且由95%的等值线定义时包含的轮廓是其一半。年度范围占多年范围大小的66%。在繁殖季节(1月16日至8月15日),老鹰占据的区域零散程度较小,大约一半,并且大部分被包含在繁殖季节以外使用的范围内((x)重叠重叠= 82.5%,SD = 19.0) )。 Eagles选择了上坡,崎terrain的地形和山脊顶部,这些表面似乎反映了猎物,偏流和偏向巢穴的潜在影响。我们的资源选择模型预测的固定分布与CPE中独立监控的4只鹰的分布高度相关(r(s)= 0.992)。我们的发现表明,针对低海拔山区和灌木草原/草原生态系统发展的保守景观管理策略可以最好地利用巢周围的12.8公里缓冲带来确定金鹰范围。基于9.6公里缓冲区的较不保守的策略必须包括识别和管理由预测模型或GPS遥测定义的上坡,山脊顶和变化的地形区域。对于这两种策略,由于巢中心性,鹰的全年飞行强度和栖息地在50%的体积轮廓内(距巢平均3.2公里)的全年高强度可能会大大增加鹰与核心区域中的风力涡轮机发生冲突的可能性。研究已经记录了该区域内外的涡轮机撞击。 (c)2014年野生动物协会。

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