Nordén Jenni, Harrison Philip J, Mair Louise, Siitonen Juha, Lundström Anders, Kindvall Oskar, Snäll Tord
Norwegian Institute for Nature Research Oslo Norway.
Artdatabanken Swedish University of Agricultural Sciences (SLU) Uppsala Sweden.
Ecol Evol. 2020 Mar 3;10(6):3079-3089. doi: 10.1002/ece3.6124. eCollection 2020 Mar.
Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood-dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large-scale occupancies of species with differing landscape-scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization-extinction models, conducting the modeling at alternative spatial scales and using fine- or coarse-resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization-extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization-extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization-extinction models over occupancy models, modeling the process at the finest resource-unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity.
了解时空种群趋势及其驱动因素是种群生态学的一个关键目标。我们还需要能够预测长期来看，不断变化的景观和气候如何影响种群的动态和规模。然而，未来种群趋势的预测对一系列建模假设很敏感。依赖枯木的真菌是测试不同固着物种预测模型性能的绝佳系统，因为这些物种具有不同的稀有度和空间种群动态，种群在不同空间尺度上结构不同，并且它们利用不同的底物。我们测试了在未来一个世纪，不同建模假设如何影响具有不同景观尺度占有率的物种的预计大规模占有率。我们将基于占有率模型的预测与定殖 - 灭绝模型进行了比较，在不同空间尺度上进行建模，并使用精细或粗分辨率的枯木数据。我们还测试了关键解释变量对物种出现和定殖 - 灭绝动态的影响。所应用的分层贝叶斯模型拟合了对174个斑块的枯木和真菌进行的广泛重复调查。与定殖 - 灭绝模型相比，我们使用占有率模型预测出更高的出现概率和更积极的趋势，对于占有率、定殖率和定殖：灭绝比估计较低的物种，差异比这些统计量估计较高的物种更大。未来占有率增加的幅度强烈依赖于空间建模尺度和资源分辨率。我们鼓励使用定殖 - 灭绝模型而非占有率模型，在物种可利用的最精细资源单位分辨率下对过程进行建模，并在进行模型拟合的相同空间尺度和资源分辨率下进行预测。此外，所应用的模型应包括驱动集合种群动态的关键变量，如合适资源单位的可用性、栖息地质量和空间连通性。
