Abstract
Tallgrass prairie ecosystems in North America are heavily degraded and require effective restoration strategies if prairie specialist taxa are to be preserved. One common management tool used to restore grassland is the application of a seed-mix of native prairie plant species. While this technique is effective in the short-term, it is critical that species’ resilience to changing climate be evaluated when designing these mixes. By utilizing species distribution models (SDMs), species’ bioclimatic envelopes–and thus the geographic area suitable for them–can be quantified and predicted under various future climate regimes, and current seed-mixes may be modified to include more climate resilient species or exclude more affected species. We evaluated climate response on plant functional groups to examine the generalizability of climate response among species of particular functional groups. We selected fourteen prairie species representing the functional groups of cool-season and warm-season grasses, forbs, and legumes and we modeled their responses under both a moderate and more extreme predicted future. Our functional group ‘composite maps’ show that warm-season grasses, forbs, and legumes responded similarly to other species within their functional group, while cool-season grasses showed less inter-species concordance. The value of functional group as a rough method for evaluating climate-resilience is therefor supported, but candidate cool-season grass species will require more individualized attention. This result suggests that seed-mix designers may be able to use species with more occurrence records to generate functional group-level predictions to assess the climate response of species for which there are prohibitively few occurrence records for modeling.
Highlights
Prairies in the United States are among the most degraded habitats in the world (Larson et al, 2011), and as such, have necessitated active restoration, for the plant communities historically found in these systems (Vogel et al, 2007; Debinski et al, 2011; Pillsbury et al, 2011; Delaney et al, 2015)
Only 14 species were selected for modeling based on sufficient occurrence records. These species represent four functional groups: cool-season (C3) grasses, warm-season (C4) grasses, forbs, and legumes (Table 1). While this functional group approach leaves three of the functional groups presented here with relatively few included species, the limited number of species with enough occurrence records to model is likely to be a constraint encountered by managers using this approach, so modeling proceeded despite the reduced representation in some groups
Occurrence records were thinned in multivariate environmental space to account for potential oversampling of environmental conditions following from geographic sampling bias via principal components analysis (PCA) of the predictor variables associated with each occurrence record
Summary
Prairies in the United States are among the most degraded habitats in the world (Larson et al, 2011), and as such, have necessitated active restoration, for the plant communities historically found in these systems (Vogel et al, 2007; Debinski et al, 2011; Pillsbury et al, 2011; Delaney et al, 2015). The addition of native plant seeds via seed-mixes is one restoration tool used to speed the re-colonization of degraded prairies by native prairie plant species (Dickson and Busby, 2009; Larson et al, 2011). Modeling approaches can serve as a valuable tool in this regard, especially when the input data are collected or publicly available
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