Logistic-growth models measuring density feedback are sensitive to population declines, but not fluctuating carrying capacity.
Logistic-growth models measuring density feedback are sensitive to population declines, but not fluctuating carrying capacity.
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DOI：
10.1002/ece3.10010
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发表时间：
2023-04
影响因子：
2.6
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中科院分区：
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对动物种群丰度的长期趋势的分析提供了对种群动态的见解。人口增长率是生育率、生存率和扩散率等因素的相互作用。然而，在一些生命率（“组件反馈”）上操作的密度反馈可以从使用丰度时间序列估计的种群增长率（“集合反馈”）的密度反馈中解耦。许多负责这种脱钩的机制知之甚少，从而质疑使用逻辑增长模型与生命率来推断长期人口趋势的有效性。为了研究哪些条件会导致解耦，我们模拟了长寿脊椎动物的年龄结构种群，它们经历了组分密度对生存的反馈。然后，我们量化了生存率、密度无关死亡率（灾难、收获样个体移除）和承载能力变化的随机性如何修改了从年龄结构种群模拟的丰度时间序列中的总体反馈。来自普查数据的集合密度反馈的统计检测在很大程度上不受密度独立过程的影响。由密度无关死亡率引起的长期种群下降是使组分与总体密度反馈强度解耦的主要机制。我们的研究支持使用简单的逻辑增长模型来捕捉长期的人口趋势，由人口丰度的变化介导，当生存率是随机的，承载能力波动，人口经历适度的灾难性死亡率随着时间的推移。我们模拟了长寿脊椎动物年龄结构种群中生存的组分密度反馈，并量化了强加的密度无关死亡率和承载能力的变化如何修改从Logistic增长模型估计的总体密度反馈强度，以模拟丰度时间序列。灾难性的和成比例的死亡率侵蚀密度依赖生存对集合反馈强度的影响比承载能力的变化更强烈。因此，现象学模型提供了一个强大的方法来捕捉密度反馈的强度，从非平稳的人口普查数据时，密度无关的死亡率低。
Analysis of long‐term trends in abundance of animal populations provides insights into population dynamics. Population growth rates are the emergent interplay of inter alia fertility, survival, and dispersal. However, the density feedbacks operating on some vital rates (“component feedback”) can be decoupled from density feedbacks on population growth rates estimated using abundance time series (“ensemble feedback”). Many of the mechanisms responsible for this decoupling are poorly understood, thereby questioning the validity of using logistic‐growth models versus vital rates to infer long‐term population trends. To examine which conditions lead to decoupling, we simulated age‐structured populations of long‐lived vertebrates experiencing component density feedbacks on survival. We then quantified how imposed stochasticity in survival rates, density‐independent mortality (catastrophes, harvest‐like removal of individuals) and variation in carrying capacity modified the ensemble feedback in abundance time series simulated from age‐structured populations. The statistical detection of ensemble density feedback from census data was largely unaffected by density‐independent processes. Long‐term population decline caused from density‐independent mortality was the main mechanism decoupling the strength of component versus ensemble density feedbacks. Our study supports the use of simple logistic‐growth models to capture long‐term population trends, mediated by changes in population abundance, when survival rates are stochastic, carrying capacity fluctuates, and populations experience moderate catastrophic mortality over time. We simulated component density feedbacks on survival in age‐structured populations of long‐lived vertebrates and quantified how imposed density‐independent mortality and variation in carryingcapacity modified the ensemble density feedback strength estimated from logistic‐growth models to the simulated abundance time series. Catastrophic and proportional mortality eroded the effect of density‐dependent survival on ensemble‐feedback strength more strongly than variation in carrying capacity. Thus, phenomenological models offer a robust approach to capture the strength of density feedbacks from nonstationary census data when density‐independent mortality is low.
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