Moving from ecological impacts to social vulnerability in data-scarce places.

Managers need to trace social impacts and vulnerability caused by environmental change all the way to its driving forces to target key system components for intervention. However, most available scientific evidence deals with either the ecological impacts of direct drivers or the value of ecosystem benefits to people. Our matrix-based tool combines these types of evidence to make environmental management problems traceable through a structured yet flexible procedure. The tool consists of a series of matrices that sequentially link direct drivers of environmental change, landscapes, ecological conditions, benefits to people, and stakeholder types. Qualitative matrices result from the integration and synthesis of available evidence from literature reviews, and where data is scarce, these are used to elicit quantitative scores from expert opinion. Expert scoring of links and multiplication of matrices allow for estimating the impacts of each driver of environmental change on each stakeholder type and using this information as input to assess stakeholders' vulnerability through impact-influence diagrams. Applying the tool to the Argentine Gran Chaco, a globally threatened ecoregion, yielded a transparent and reliable picture of this data-scarce place, with important management implications. Tracing stakeholder impacts back to direct drivers confirmed that further encroachment of cleared areas around indigenous lands will increase the vulnerability of this social group. Also, assessing confidence levels for every social-ecological link suggested that incentivizing peasant farmers to restore natural forage supply represents a management opportunity to reverse degradation. Our tool makes interdisciplinary frameworks of linked ecological and social systems operational so managers can use the best available knowledge of a place and account for uncertainty to make environmental management decisions.

Consistent predictors of microbial community composition across spatial scales in grasslands reveal low context-dependency.

Environmental circumstances shaping soil microbial communities have been studied extensively. However, due to disparate study designs, it has been difficult to resolve whether a globally consistent set of predictors exists, or context-dependency prevails. Here, we used a network of 18 grassland sites (11 of those containing regional plant productivity gradients) to examine (i) if similar abiotic or biotic factors predict both large-scale (across sites) and regional-scale (within sites) patterns in bacterial and fungal community composition, and (ii) if microbial community composition differs consistently at two levels of regional plant productivity (low vs. high). Our results revealed that bacteria were associated with particular soil properties (such as base saturation) and both bacteria and fungi were associated with plant community composition across sites and within the majority of sites. Moreover, a discernible microbial community signal emerged, clearly distinguishing high and low-productivity soils across different grasslands independent of their location in the world. Hence, regional productivity differences may be typified by characteristic soil microbial communities across the grassland biome. These results could encourage future research aiming to predict the general effects of global changes on soil microbial community composition in grasslands and to discriminate fertile from infertile systems using generally applicable microbial indicators.

Response to Comment on "Worldwide evidence of a unimodal relationship between productivity and plant species richness".

Tredennick et al. criticize one of our statistical analyses and emphasize the low explanatory power of models relating productivity to diversity. These criticisms do not detract from our key findings, including evidence consistent with the unimodal constraint relationship predicted by the humped-back model and evidence of scale sensitivities in the form and strength of the relationship.

Leaf mechanical resistance in plant trait databases: comparing the results of two common measurement methods.

BACKGROUND AND AIMS: The influence of leaf mechanical properties on local ecosystem processes, such as trophic transfer, decomposition and nutrient cycling, has resulted in a growing interest in including leaf mechanical resistance in large-scale databases of plant functional traits. 'Specific work to shear' and 'force to tear' are two properties commonly used to describe mechanical resistance (toughness or strength) of leaves. Two methodologies have been widely used to measure them across large datasets. This study aimed to assess correlations and standardization between the two methods, as measured by two widely used apparatuses, in order to inter-convert existing data in those global datasets. METHODS: Specific work to shear (W(SS)) and force to tear (FT) were measured in leaves of 72 species from south-eastern Australia. The measurements were made including and excluding midribs. Relationships between the variables were tested by Spearman correlations and ordinary least square regressions. KEY RESULTS: A positive and significant correlation was found between the methods, but coefficients varied according to the inclusion or exclusion of the midrib in the measurements. Equations for prediction varied according to leaf venation pattern. A positive and significant (r = 0·90, P < 0·0001) correlation was also found between W(SS) values for fresh and rehydrated leaves, which is considered to be of practical relevance. CONCLUSIONS: In the context of broad-scale ecological hypotheses and used within the constraints recommended here, leaf mechanical resistance data obtained with both methodologies could be pooled together into a single coarser variable, using the equations provided in this paper. However, more detailed datasets of FT cannot be safely filled in with estimations based on W(SS), or vice versa. In addition, W(SS) values of green leaves can be predicted with good accuracy from W(SS) of rehydrated leaves of the same species.

Plant ecology. Worldwide evidence of a unimodal relationship between productivity and plant species richness.

The search for predictions of species diversity across environmental gradients has challenged ecologists for decades. The humped-back model (HBM) suggests that plant diversity peaks at intermediate productivity; at low productivity few species can tolerate the environmental stresses, and at high productivity a few highly competitive species dominate. Over time the HBM has become increasingly controversial, and recent studies claim to have refuted it. Here, by using data from coordinated surveys conducted throughout grasslands worldwide and comprising a wide range of site productivities, we provide evidence in support of the HBM pattern at both global and regional extents. The relationships described here provide a foundation for further research into the local, landscape, and historical factors that maintain biodiversity.

Global patterns of leaf mechanical properties.

Leaf mechanical properties strongly influence leaf lifespan, plant-herbivore interactions, litter decomposition and nutrient cycling, but global patterns in their interspecific variation and underlying mechanisms remain poorly understood. We synthesize data across the three major measurement methods, permitting the first global analyses of leaf mechanics and associated traits, for 2819 species from 90 sites worldwide. Key measures of leaf mechanical resistance varied c. 500-800-fold among species. Contrary to a long-standing hypothesis, tropical leaves were not mechanically more resistant than temperate leaves. Leaf mechanical resistance was modestly related to rainfall and local light environment. By partitioning leaf mechanical resistance into three different components we discovered that toughness per density contributed a surprisingly large fraction to variation in mechanical resistance, larger than the fractions contributed by lamina thickness and tissue density. Higher toughness per density was associated with long leaf lifespan especially in forest understory. Seldom appreciated in the past, toughness per density is a key factor in leaf mechanical resistance, which itself influences plant-animal interactions and ecosystem functions across the globe.