Ten Caten Cleber, Dallas Tad
Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA.
Proc Biol Sci. 2025 Jan;292(2039):20241644. doi: 10.1098/rspb.2024.1644. Epub 2025 Jan 29.
Populations fluctuate over time and across geographical space, and understanding how different factors contribute to population variability is a central goal in population ecology. There is a particular interest in identifying trends of population variability within geographical ranges as population densities of species can fluctuate substantially across geographical space. A common assumption is that populations vary more near species geographical range edges because of unsuitable environments and higher vulnerability to environmental variability in these areas. However, empirical data rarely support this expectation, suggesting that population variability is not related to its position within species geographical ranges. We propose that performance curves, which describe the relationship between population growth rates and environmental conditions, can be used to disentangle geographical patterns of population variability. Performance curves are important for understanding population variability because populations fluctuate more in locations where they have lower growth rates owing to unsuitable environmental conditions. This is important for the assessment of these geographical patterns in population variability because geographical edges often do not reflect environmental edges. Considering species performance curves when evaluating geographical patterns of population variability would also allow researchers to detect populations that are more susceptible to future changes in environmental conditions.
种群数量会随时间和地理空间而波动,理解不同因素如何导致种群变异性是种群生态学的核心目标。人们尤其关注确定地理范围内种群变异性的趋势,因为物种的种群密度在地理空间中可能会大幅波动。一个常见的假设是,由于环境不适宜以及这些地区对环境变化的更高脆弱性,种群在物种地理范围边缘附近的变化更大。然而,实证数据很少支持这一预期,这表明种群变异性与其在物种地理范围内的位置无关。我们提出,描述种群增长率与环境条件之间关系的性能曲线,可用于理清种群变异性的地理模式。性能曲线对于理解种群变异性很重要,因为由于环境条件不适宜,种群在增长率较低的地方波动更大。这对于评估种群变异性的这些地理模式很重要,因为地理边缘往往并不反映环境边缘。在评估种群变异性的地理模式时考虑物种性能曲线,也将使研究人员能够检测出更容易受到未来环境条件变化影响的种群。