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ARS Home » Pacific West Area » Burns, Oregon » Range and Meadow Forage Management Research » Research » Publications at this Location » Publication #402211

Research Project: Restoration and Conservation of Great Basin Ecosystems

Location: Range and Meadow Forage Management Research

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

item BERTUOL-GARCIA, DIANA - University Of Victoria
item LADOUCEUR, EMMA - Martin Luther University
item BRUDVIG, LARS - Michigan State University
item LAUGHLIN, DANIEL - University Of Wyoming
item MUNSON, SETH - Us Geological Survey (USGS)
item CURRAN, MICHAEL - Abnova Ecological Solutions
item Davies, Kirk
item Svejcar, Lauren
item SHACKELFORD, NANCY - University Of Victoria

Submitted to: Ecological Applications
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/18/2023
Publication Date: 9/29/2023
Citation: Bertuol-Garcia, D., Ladouceur, E., Brudvig, L.A., Laughlin, D.C., Munson, S.M., Curran, M.F., Davies, K.W., Svejcar, L.N., Shackelford, N. 2023. Testing the hierarchy of predictability in grassland restoration across a gradient of environmental severity. Ecological Applications. 33(8). Article e2922.

Interpretive Summary: Ecological restoration is a critical tool for promoting recovery in degraded ecosystems but is challenged by variable success and lack of predictability. We analysed data from 52 grassland sites to test how predictable grassland seed-based restoration can be. We found that the level of predicatability of restoration efforts highly depended on the metric being measured. Similarly, dominant species had higher levels of predictability than rare species.

Technical Abstract: 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 identities was unpredictable, but another dimension of taxonomic composition indicating whether exotic or native species dominated the community was highly predictable. Taxonomic diversity (i.e., species richness) and functional composition (i.e., mean trait values) were intermittently predictable. Predictability also did not increase consistently with aridity. The dimension of taxonomic composition related to the identity of species in restored communities was more predictable (i.e., smaller residuals) in more arid sites, but functional composition was less predictable (i.e., larger residuals), and other outcomes showed no significant trend. Restoration outcomes were most predictable when they related to variation in dominant species, while those responding to rare species were harder to predict, indicating a potential role of scale in restoration predictability. Overall, our results highlight additional factors that might influence restoration predictability and add support to the importance of continuous monitoring and active management beyond one-time seed addition for successful grassland restoration in the United States.