Temporal variability and predictability predict alpine plant community composition and distribution patterns

IF 4.4 2区 环境科学与生态学 Q1 ECOLOGY Ecology Pub Date : 2024-10-26 DOI:10.1002/ecy.4450
William J. Reed, Aaron J. Westmoreland, Katharine N. Suding, Daniel F. Doak, William D. Bowman, Nancy C. Emery
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Abstract

One of the most reliable features of natural systems is that they change through time. Theory predicts that temporally fluctuating conditions shape community composition, species distribution patterns, and life history variation, yet features of temporal variability are rarely incorporated into studies of species–environment associations. In this study, we evaluated how two components of temporal environmental variation—variability and predictability—impact plant community composition and species distribution patterns in the alpine tundra of the Southern Rocky Mountains in Colorado (USA). Using the Sensor Network Array at the Niwot Ridge Long-Term Ecological Research site, we used in situ, high-resolution temporal measurements of soil moisture and temperature from 13 locations (“nodes”) distributed throughout an alpine catchment to characterize the annual mean, variability, and predictability in these variables in each of four consecutive years. We combined these data with annual vegetation surveys at each node to evaluate whether variability over short (within-day) and seasonal (2- to 4-month) timescales could predict patterns in plant community composition, species distributions, and species abundances better than models that considered average annual conditions alone. We found that metrics for variability and predictability in soil moisture and soil temperature, at both daily and seasonal timescales, improved our ability to explain spatial variation in alpine plant community composition. Daily variability in soil moisture and temperature, along with seasonal predictability in soil moisture, was particularly important in predicting community composition and species occurrences. These results indicate that the magnitude and patterns of fluctuations in soil moisture and temperature are important predictors of community composition and plant distribution patterns in alpine plant communities. More broadly, these results highlight that components of temporal change provide important niche axes that can partition species with different growth and life history strategies along environmental gradients in heterogeneous landscapes.

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预测高山植物群落组成和分布模式的时变性和可预测性
自然系统最可靠的特征之一是随时间而变化。理论预测,随时间波动的条件会影响群落组成、物种分布模式和生活史变异,然而时间变异的特征很少被纳入物种与环境关联的研究中。在这项研究中,我们评估了时间环境变化的两个组成部分--变异性和可预测性--如何影响美国科罗拉多州南落基山脉高山苔原的植物群落组成和物种分布模式。我们利用尼沃特山脊长期生态研究基地的传感器网络阵列,对分布在高山集水区的 13 个地点("节点")的土壤水分和温度进行了现场高分辨率时间测量,以确定这些变量在连续四年中每年的年均值、变异性和可预测性。我们将这些数据与每个节点的年度植被调查相结合,以评估短期(日内)和季节性(2 至 4 个月)时间尺度上的变异性是否能比仅考虑年平均条件的模型更好地预测植物群落组成、物种分布和物种丰度的模式。我们发现,土壤水分和土壤温度在日和季节时间尺度上的可变性和可预测性指标提高了我们解释高山植物群落组成空间变化的能力。土壤水分和温度的日变异性以及土壤水分的季节可预测性在预测群落组成和物种出现方面尤为重要。这些结果表明,土壤水分和温度波动的幅度和模式是预测高山植物群落组成和植物分布模式的重要因素。更广泛地说,这些结果突出表明,时间变化的成分提供了重要的生态位轴线,可以将具有不同生长和生活史策略的物种沿着异质景观中的环境梯度分隔开来。
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来源期刊
Ecology
Ecology 环境科学-生态学
CiteScore
8.30
自引率
2.10%
发文量
332
审稿时长
3 months
期刊介绍: Ecology publishes articles that report on the basic elements of ecological research. Emphasis is placed on concise, clear articles documenting important ecological phenomena. The journal publishes a broad array of research that includes a rapidly expanding envelope of subject matter, techniques, approaches, and concepts: paleoecology through present-day phenomena; evolutionary, population, physiological, community, and ecosystem ecology, as well as biogeochemistry; inclusive of descriptive, comparative, experimental, mathematical, statistical, and interdisciplinary approaches.
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