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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., (© 2023 The Authors. Ecological Applications published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

A major goal in ecology is to make generalizable predictions of organism responses to environmental variation based on their traits. However, straightforward relationships between traits and fitness are rare and likely to vary with environmental context. Characterizing how traits mediate demographic responses to the environment may enhance the predictions of organism responses to global change. We synthesized 15 years of demographic data and species-level traits in a shortgrass steppe to determine whether the effects of leaf and root traits on growth and survival depended on seasonal water availability. We predicted that (1) species with drought-tolerant traits, such as lower leaf turgor loss point (TLP) and higher leaf and root dry matter content (LDMC and RDMC), would be more likely to survive and grow in drier years due to higher wilting resistance, (2) these traits would not predict fitness in wetter years, and (3) traits that more directly measure physiological mechanisms of water use such as TLP would best predict demographic responses. We found that graminoids with more negative TLP and higher LDMC and RDMC had higher survival rates in drier years. Forbs demonstrated similar yet more variable responses. Graminoids grew larger in wetter years, regardless of traits. However, in both wet and dry years, graminoids with more negative TLP and higher LDMC and RDMC grew larger than less negative TLP and low LDMC and RDMC species. Traits significantly mediated the impact of drought on survival, but not growth, suggesting that survival could be a stronger driver of species' drought response in this system. TLP predicted survival in drier years, but easier to measure LDMC and RDMC were equal or better predictors. These results advance our understanding of the mechanisms by which drought drives population dynamics, and show that abiotic context determines how traits drive fitness., (© 2022 The Ecological Society of America.)

This data set consists of 101 permanent 1 m × 1 m (1-m 2 ) quadrats located within southwestern ponderosa pine ecosystems near Flagstaff, Arizona, USA. Individual plants in these quadrats were identified and mapped annually for 19 years (2002-2020). The original chart quadrats were established between 1912 and 1927 to determine the effects of domestic livestock grazing on herbaceous plants and pine seedlings. Today these data provide opportunities to examine the effects of climate and land-use change on plant demography, population dynamics, and community processes. We provide the following data and data formats: (1) digitized maps of all plant locations in shapefile and geodatabase format, (2) shapefiles showing annual locations of each individual plant species, (3) annual maps of each quadrat in TIFF and PDF format, (4) annual basal area of each species per quadrat for species mapped as polygons, (5) tabular representation of polygon areas and centroid locations for plant species mapped as polygons, (6) tabular representation of point locations for plant species mapped as points, (7) plot-scale 20 m × 20 m overstory tree canopy cover, tree basal area, parent material, and elevation, (8) quadrat-scale information (e.g., quadrat site and number, coordinates in UTM Zone 12 and latitude/longitude, and descriptive comments for each quadrat), (9) plant species list, (10) summary of plant species observed in each quadrat, (11) summary of quadrats mapped by site and year, and (12) data formatted for use in Integral Projection Models (IPM) and plant population analyses. There are no copyright restrictions; please cite this paper and the associated data set when data are used in publications., (© 2022 The Ecological Society of America.)

The functional trait values that constitute a whole-plant phenotype interact with the environment to determine demographic rates. Current approaches often fail to explicitly consider trait × trait and trait × environment interactions, which may lead to missed information that is valuable for understanding and predicting the drivers of demographic rates and functional diversity. Here, we consider these interactions by modeling growth performance landscapes that span multidimensional trait spaces along environmental gradients. We utilize individual-level leaf, stem, and root trait data combined with growth data from tree seedlings along soil nutrient and light gradients in a hyper-diverse tropical rainforest. We find that multiple trait combinations in phenotypic space (i.e., alternative designs) lead to multiple growth performance peaks that shift along light and soil axes such that no single or set of interacting traits consistently results in peak growth performance. Evidence from these growth performance peaks also generally indicates frequent independence of above- and belowground resource acquisition strategies. These results help explain how functional diversity is maintained in ecological communities and question the practice of utilizing a single trait or environmental variable, in isolation, to predict the growth performance of individual trees., (© 2020 by the Ecological Society of America.)

Restoring forest structure and composition is an important component of urban land management, but we lack clear understanding of the mechanisms driving restoration success. Here we studied two indicators of restoration success in temperate rainforests: native tree regeneration and epiphyte colonization. We hypothesized that ecosystem properties such as forest canopy openness, abundance of exotic herbaceous weeds, and the microclimate directly affect the density and diversity of native tree seedlings and epiphytes. Relationships between environmental conditions and the plant community were investigated in 27 restored urban forests spanning 3-70 years in age and in unrestored and remnant urban forests. We used structural equation modelling to determine the direct and indirect drivers of native tree regeneration and epiphyte colonization in the restored forests. Compared to remnant forest, unrestored forest had fewer native canopy tree species, significantly more light reaching the forest floor annually, and higher exotic weed cover. Additionally, epiphyte density was lower and native tree regeneration density was marginally lower in the unrestored forests. In restored forests, light availability was reduced to levels found in remnant forests within 20 years of restoration planting, followed shortly thereafter by declines in herbaceous exotic weeds and reduced fluctuation of relative humidity and soil temperatures. Contrary to expectations, canopy openness was only an indirect driver of tree regeneration and epiphyte colonization, but it directly regulated weed cover and microclimatic fluctuations, both of which directly drove the density and richness of regeneration and epiphyte colonization. Epiphyte density and diversity were also positively related to forest basal area, as large trees provide physical habitat for colonization. These results imply that ecosystem properties change predictably after initial restoration plantings, and that reaching critical thresholds in some ecosystem properties makes conditions suitable for the regeneration of late successional species, which is vital for restoration success and long-term ecosystem sustainability. Abiotic and biotic conditions that promote tree regeneration and epiphyte colonization will likely be present in forests with a basal area ≥27 m 2 /ha. We recommend that urban forest restoration plantings be designed to promote rapid canopy closure to reduce light availability, suppress herbaceous weeds, and stabilize the microclimate., (© 2017 by the Ecological Society of America.)

We analyzed one of the longest-term ecological data sets to evaluate how forest overstory structure is related to herbaceous understory plant strategies in a ponderosa pine forest. Eighty-two permanent 1-m2 chart quadrats that were established as early as 1912 were remeasured in 2007. We reconstructed historical forest structure using dendrochronological techniques. Ponderosa pine basal area increased from an average of 4 m2/ha in the early 1900s to 29 m2/ha in 2007. Understory plant foliar cover declined by 21%, species richness declined by two species per square meter, and functional diversity also declined. The relative cover of C4 graminoids decreased by 18% and C3 graminoids increased by 19%. Herbaceous plant species with low leaf and fine root nitrogen concentrations, low specific leaf area, high leaf dry matter content, large seed mass, low specific root length, short maximum height, and early flowering date increased in relative abundance in sites where pine basal area increased the most. Overall, we observed a long-term shift in composition toward more conservative shade- and stress-tolerant herbaceous species. Our analysis of temporal changes in plant strategies provides a general framework for evaluating compositional and functional changes in terrestrial plant communities.

We evaluate the predictive power and generality of Shipley's maximum entropy (maxent) model of community assembly in the context of 96 quadrats over a 120-km2 area having a large (79) species pool and strong gradients. Quadrats were sampled in the herbaceous understory of ponderosa pine forests in the Coconino National Forest, Arizona, U.S.A. The maxent model accurately predicted species relative abundances when observed community-weighted mean trait values were used as model constraints. Although only 53% of the variation in observed relative abundances was associated with a combination of 12 environmental variables, the maxent model based only on the environmental variables provided highly significant predictive ability, accounting for 72% of the variation that was possible given these environmental variables. This predictive ability largely surpassed that of nonmetric multidimensional scaling (NMDS) or detrended correspondence analysis (DCA) ordinations. Using cross-validation with 1000 independent runs, the median correlation between observed and predicted relative abundances was 0.560 (the 2.5% and 97.5% quantiles were 0.045 and 0.825). The qualitative predictions of the model were also noteworthy: dominant species were correctly identified in 53% of the quadrats, 83% of rare species were correctly predicted to have a relative abundance of < 0.05, and the median predicted relative abundance of species actually absent from a quadrat was 5 x 10(-5).