Applying trait-based models to achieve functional targets for theory-driven ecological restoration

Manipulating community assemblages to achieve functional targets is a key component of restoring degraded ecosystems. The response-and-effect trait framework provides a conceptual foundation for translating restoration goals into functional trait targets, but a quantitative framework has been lacking for translating trait targets into assemblages of species that practitioners can actually manipulate. This study describes new trait-based models that can be used to generate ranges of species abundances to test theories about which traits, which trait values and which species assemblages are most effective for achieving functional outcomes. These models are generalisable, flexible tools that can be widely applied across many terrestrial ecosystems. Examples illustrate how the framework generates assemblages of indigenous species to (1) achieve desired community responses by applying the theories of environmental filtering, limiting similarity and competitive hierarchies, or (2) achieve desired effects on ecosystem functions by applying the theories of mass ratios and niche complementarity. Experimental applications of this framework will advance our understanding of how to set functional trait targets to achieve the desired restoration goals. A trait-based framework provides restoration ecology with a robust scaffold on which to apply fundamental ecological theory to maintain resilient and functioning ecosystems in a rapidly changing world

Seeing the forest for the genes: using metagenomics to infer the aggregated traits of microbial communities

Most environments harbor large numbers of microbial taxa with ecologies that remain poorly described and characterizing the functional capabilities of whole communities remains a key challenge in microbial ecology. Shotgun metagenomic analyses are increasingly recognized as a powerful tool to understand community-level attributes. However, much of this data is under-utilized due, in part, to a lack of conceptual strategies for linking the metagenomic data to the most relevant community-level characteristics. Microbial ecologists could benefit by borrowing the concept of community-aggregated traits (CATs) from plant ecologists to glean more insight from the ever-increasing amount of metagenomic data being generated. CATs can be used to quantify the mean and variance of functional traits found in a given community. A CAT-based strategy will often yield far more useful information for predicting the functional attributes of diverse microbial communities and changes in those attributes than the more commonly used analytical strategies. A more careful consideration of what CATs to measure and how they can be quantified from metagenomic data, will help build a more integrated understanding of complex microbial communities

Inferential tests and modelling of functional trait convergence along environmental gradients

The motivation for this paper comes from a recent study which indicated that the influence of environmental filtering should increase with decreasing soil fertility, based on the premise that individuals will employ a resource-retentive strategy in a less productive ecosystem. Mean annual temperature (MAT) is one indicator of the productivity of the ecosystem. We aim to build a more accurate model of environmental filter and want to statistically test whether the environmental filter is stronger when the MAT is lower compared to when it is higher. Our findings throw an interesting insight into how the trait variability changes as a function of MAT and how it could be better modelled

Theoretical consequences of trait-based environmental filtering for the breadth and shape of the niche: New testable hypotheses generated by the Traitspace model

Every species on Earth fills a unique environmental niche that is driven, in part, by the process of environmental filtering, where the adaptive value of the functional traits of individuals determine their fitness within the given environmental conditions. Despite its long-standing importance in ecology, theoretical investigations of environmental filtering have lagged behind studies of species interactions and neutral dynamics. A new statistical model of trait-based environmental filtering can be a useful tool for exploring the logical consequences of this process while holding all other processes constant. The model uses the logic of objective Bayesian inference to compute the probabilities of species within different environments using two sources of information: the location and dispersion of species within functional trait space, and the statistical relationship between traits and environmental gradients. By varying key parameters in the model, we highlight several testable hypotheses for trait-based ecology. First, niche breadth decreases as intraspecific trait variation decreases, as the strength of the environmental filter increases, and if the trait values do not enhance fitness in any environmental condition in the landscape. Second, niche shape is determined by the form of the trait-environment relationships, where species with extreme trait values are predicted to dominate at the environmental extremes when traits are linearly related to the environment, species with intermediate trait values generally have a selective advantage across a broader environmental range, and bimodal species response curves can occur independently from negative species interactions. The generality of these modelling results can be tested using empirical data from any ecosystem

Meeting forest ecosystem objectives with wildland fire use

Three 2003 Grand Canyon National Park fires burned 83 plots across the park’s North Rim old-growth forests that range from open ponderosa pine groves to dense spruce–fir–aspen stands at 7,300 to 8,800 feet (2,225 to 2,682 m) elevation. Ignited by lightning, these fires were managed by the U.S. Department of the Interior (USDI) National Park Service as wildland fire use (WFU) to meet resource objectives. As outlined below, they provided an excellent opportunity to evaluate low to mixed-severity fire effects

The hill plots: a rare long-term vegetation study

One legacy of the Fort Valley Experimental Forest is the number and quality of long-term studies associated with it. One such study is the “Hill plots,” which began in 1912 and is still being actively studied. Livestock exclosures were built at five sites to examine vegetation recovery when protected from livestock grazing. Sites span a range of soil types and elevations. Materials associated with the Hill plots include historical data, plant specimens, and photographs. In this paper, we summarize the research that has occurred on the Hill plots, historical personnel who worked on them, threats they have experienced, ecological insights they have provided, and current research directions

A century of increasing pine density and associated shifts in understory plant strategies

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

Species richness and soil properties in Pinus ponderosa forests: A structural equation modeling analysis

Question: How are the effects of mineral soil properties on understory plant species richness propagated through a network of processes involving the forest overstory, soil organic matter, soil nitrogen, and understory plant abundance? Location: North-central Arizona, USA. Methods: We sampled 75 0.05-ha plots across a broad soil gradient in a Pinus ponderosa (ponderosa pine) forest ecosystem. We evaluated multivariate models of plant species richness using structural equation modeling. Results: Richness was highest at intermediate levels of understory plant cover, suggesting that both colonization success and competitive exclusion can limit richness in this system. We did not detect a reciprocal positive effect of richness on plant cover. Richness was strongly related to soil nitrogen in the model, with evidence for both a direct negative effect and an indirect non-linear relationship mediated through understory plant cover. Soil organic matter appeared to have a positive influence on understory richness that was independent of soil nitrogen. Richness was lowest where the forest overstory was densest, which can be explained through indirect effects on soil organic matter, soil nitrogen and understory cover. Finally, model results suggest a variety of direct and indirect processes whereby mineral soil properties can influence richness. Conclusions: Understory plant species richness and plant cover in P. ponderosa forests appear to be significantly influenced by soil organic matter and nitrogen, which are, in turn, related to overstory density and composition and mineral soil properties. Thus, soil properties can impose direct and indirect constraints on local species diversity in ponderosa pine forests

Isolation of Mycoplasma from the Genital Tracts of Elephants

The authors report finding arthritogenic agents, mycoplasmas, for the first time in a large group of captive elephants that are frequently crippled with rheumatism

Survival Rates Indicate that Correlations Between Community-Weighted Mean Traits and Environments can be Unreliable Estimates of the Adaptive Value of Traits

Correlations between community-weighted mean (CWM) traits and environmental gradients are often assumed to quantify the adaptive value of traits. We tested this assumption by comparing these correlations with models of survival probability using 46 perennial species from long-term permanent plots in pine forests of Arizona. Survival was modeled as a function of trait-by-environment interactions, plant size, climatic variation, and neighborhood competition. The effect of traits on survival depended on the environmental conditions, but the two statistical approaches were inconsistent. For example, CWM specific leaf area (SLA) and soil fertility were uncorrelated. However, survival was highest for species with low SLA in infertile soil, a result which agreed with expectations derived from the physiological tradeoff underpinning leaf economic theory. CWM trait-environment relationships were unreliable estimates of how traits affected survival, and should only be used in predictive models when there is empirical support for an evolutionary tradeoff that affects vital rates