Testing the hierarchy of predictability in grassland restoration across a gradient of environmental severity

作者：Diana Bertuol‐Garcia, Emma Ladouceur, Lars A. Brudvig, Daniel C. Laughlin, Seth M. Munson, Michael F. Curran, Kirk W. Davies, Lauren N. Svejcar, Nancy Shackelford · 发表于：Ecological Applications · 年份：2023 · DOI：10.1002/eap.2922 · 被引用次数：7 · 研究领域：Ecology and Vegetation Dynamics Studies、Rangeland and Wildlife Management、Species Distribution and Climate Change

Ecological restoration is critical for recovering degraded ecosystems but is challenged by variable success and low predictability. Understanding which outcomes are more predictable and less variable following restoration can improve restoration effectiveness. Recent theory asserts that the predictability of outcomes would follow an order from most to least predictable from coarse to fine community properties (physical structure > taxonomic diversity > functional composition > taxonomic composition) and that predictability would increase with more severe environmental conditions constraining species establishment. We tested this "hierarchy of predictability" hypothesis by synthesizing outcomes along an aridity gradient with 11 grassland restoration projects across the United States. We used 1829 vegetation monitoring plots from 227 restoration treatments, spread across 52 sites. We fit generalized linear mixed-effects models to predict six indicators of restoration outcomes as a function of restoration characteristics (i.e., seed mixes, disturbance, management actions, time since restoration) and used variance explained by models and model residuals as proxies for restoration predictability. We did not find consistent support for our hypotheses. Physical structure was among the most predictable outcomes when the response variable was relative abundance of grasses, but unpredictable for total canopy cover. Similarly, one dimension of taxonomic composition related to species id...