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Disentangling the effects of climate, density dependence, and harvest on an iconic large herbivore's population dynamics

机译:解析气候,密度依赖性和收获对标志性大型草食动物种群动态的影响

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摘要

Understanding the relative effects of climate, harvest, and density dependence on population dynamics is critical for guiding sound population management, especially for ungulates in arid and semiarid environments experiencing climate change. To address these issues for bison in southern Utah, USA, we applied a Bayesian state-space model to a 72-yr time series of abundance counts. While accounting for known harvest (as well as live removal) from the population, we found that the bison population in southern Utah exhibited a strong potential to grow from low density (beta(0) = 0.26; Bayesian credible interval based on 95% of the highest posterior density [BCI] = 0.19-0.33), and weak but statistically significant density dependence (beta(1) = -0.02, BCI = -0.04 to -0.004). Early spring temperatures also had strong positive effects on population growth (beta(fat1) = 0.09, BCI = 0.04-0.14), much more so than precipitation and other temperature-related variables (model weight. three times more than that for other climate variables). Although we hypothesized that harvest is the primary driving force of bison population dynamics in southern Utah, our elasticity analysis indicated that changes in early spring temperature could have a greater relative effect on equilibrium abundance than either harvest or the strength of density dependence. Our findings highlight the utility of incorporating elasticity analyses into state-space population models, and the need to include climatic processes in wildlife management policies and planning.
机译:了解气候,收获和密度对种群动态的相对影响对于指导合理的种群管理至关重要,尤其是对于干旱和半干旱环境中有蹄类动物有气候变化的指导。为了解决美国犹他州南部的野牛的这些问题,我们将贝叶斯状态空间模型应用于72年的丰度计数时间序列。当考虑到已知的种群收获(以及活体搬迁)时,我们发现犹他州南部的野牛种群具有从低密度增长的强大潜力(beta(0)= 0.26;基于95%的贝叶斯可信区间)最高后验密度[BCI] = 0.19-0.33),并且密度依赖性较弱但具有统计学意义(β(1)= -0.02,BCI = -0.04至-0.004)。早春的温度也对人口增长产生了积极的积极影响(β(fat1)= 0.09,BCI = 0.04-0.14),远高于降水量和其他与温度相关的变量(模型权重。比其他气候变量高三倍) )。尽管我们假设收获是犹他州南部野牛种群动态的主要驱动力,但我们的弹性分析表明,早春温度的变化可能比收获或密度依赖强度对平衡丰度的影响更大。我们的发现强调了将弹性分析纳入状态空间人口模型的效用,以及将气候过程纳入野生动植物管理政策和规划的必要性。

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