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首页> 外文期刊>Global ecology and biogeography >Carrying capacity for species richness as a context for conservation: a case study of North American breeding birds.
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Carrying capacity for species richness as a context for conservation: a case study of North American breeding birds.

机译:物种丰富性的保护能力作为保护的前提:以北美种鸟为例。

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Aim: To demonstrate that the concept of carrying capacity for species richness (SK) is highly relevant to the conservation of biodiversity, and to estimate the spatial pattern of SK for native landbirds as a basis for conservation planning. Location: North America. Methods: We evaluated the leading hypotheses on biophysical factors affecting species richness for Breeding Bird Survey routes from areas with little influence of human activities. We then derived a best model based on information theory, and used this model to extrapolate SK across North America based on the biophysical predictor variables. The predictor variables included the latest and probably most accurate satellite and simulation-model derived products. Results: The best model of SK included mean annual and inter-annual variation in gross primary productivity and potential evapotranspiration. This model explained 70% of the variation in landbird species richness. Geographically, predicted SK was lowest at higher latitudes and in the arid west, intermediate in the Rocky Mountains and highest in the eastern USA and the Great Lakes region of the USA and Canada. Main conclusions: Areas that are high in SK but low in human density are high priorities for protection, and areas high in SK and high in human density are high priorities for restoration. Human density was positively related to SK, indicating that humans select environments similar to those with high bird species richness. Federal lands were disproportionately located in areas of low predicted SK.Digital Object Identifier http://dx.doi.org/10.1111/j.1466-8238.2011.00670.x
机译:目的:证明物种丰富度的承载能力( S K )与生物多样性的保护高度相关,并估算的空间格局S K 用于本地陆鸟,作为保护规划的基础。地点:北美。方法:我们在影响人类活动影响较小的地区,评估了影响鸟类繁殖路线物种丰富度的生物物理因素的主要假设。然后,我们基于信息理论导出了一个最佳模型,并使用该模型根据生物物理预测变量对整个北美的 S K 进行了推断。预测变量包括最新的,可能是最准确的卫星和仿真模型衍生产品。结果: S K 的最佳模型包括总初级生产力和潜在蒸散量的年均和年际变化。该模型解释了陆鸟物种丰富度变化的70%。在地理上,预测的 S K 在较高的纬度和干旱的西部最低,在落基山脉中级,在美国东部和西部最高。美国和加拿大的大湖地区。主要结论: S K 较高但人口密度较低的地区是需要优先保护的地区, S较高的地区 K 且人文密度高是恢复工作的重中之重。人的密度与 S K 呈正相关,表明人类选择的环境与鸟类物种丰富的环境相似。联邦土地不成比例地位于预测的 S K 较低的区域。数字对象标识符http://dx.doi.org/10.1111/j .1466-8238.2011.00670.x

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