A long-term experimental test of the dynamic equilibrium model of species diversity.

The dynamic equilibrium model of species diversity predicts that ecosystem productivity interacts with disturbance to determine how many species coexist. However, a robust test of this model requires manipulations of productivity and disturbance over a sufficient timescale to allow competitive exclusion, and such long-term experimental tests of this hypothesis are rare. Here we use long-term (27 years), large-scale (8 × 50-m plots), factorial manipulations of soil resource availability and sheep grazing intensity (disturbance) in grasslands to test the dynamic equilibrium model. As predicted by the model, increased productivity not only reduced plant species richness, but also moderated the effects of grazing intensity, shifting them from negative to neutral with increasing productivity. Reductions in species richness with productivity were associated with dominance by faster growing (i.e. high specific leaf area) and taller plants. Conversely, grazing favoured shorter plants and this effect became stronger with greater productivity, consistent with the view that grazing can lead to weaker asymmetric competition for light. Our study shows that the dynamic equilibrium model can help to explain changes in plant species richness following long-term increases in soil resource availability and grazing pressure, two fundamental drivers of change in grasslands worldwide.

Further Considerations on the Debate Over Herbivore Optimization Theory.

Criticism of the basis and use of the herbivore optimization theory is discussed. It is argued here that evidence from theory and agricultural practice support the view that compensation and overcompensation of total primary production can occur in plant populations and communities subjected to grazing. However, whether this will occur depends on specific circumstances. Modeling and carefully designed field studies should be used to determine the responses of rangeland systems under a variety of environmental conditions and grazing intensities.

Hidden treatments in ecological experiments: re-evaluating the ecosystem function of biodiversity.

Interactions between biotic and abiotic processes complicate the design and interpretation of ecological experiments. Separating causality from simple correlation requires distinguishing among experimental treatments, experimental responses, and the many processes and properties that are correlated with either the treatments or the responses, or both. When an experimental manipulation has multiple components, but only one of them is identified as the experimental treatment, erroneous conclusions about cause and effect relationships are likely because the actual cause of any observed response may be ignored in the interpretation of the experimental results. This unrecognized cause of an observed response can be considered a "hidden treatment." Three types of hidden treatments are potential problems in biodiversity experiments: (1) abiotic conditions, such as resource levels, or biotic conditions, such as predation, which are intentionally or unintentionally altered in order to create differences in species numbers for "diversity" treatments; (2) non-random selection of species with particular attributes that produce treatment differences that exceed those due to "diversity" alone; and (3) the increased statistical probability of including a species with a dominant negative or positive effect (e.g., dense shade, or nitrogen fixation) in randomly selected groups of species of increasing number or "diversity." In each of these cases, treatment responses that are actually the result of the "hidden treatment" may be inadvertently attributed to variation in species diversity. Case studies re-evaluating three different types of biodiversity experiments demonstrate that the increases found in such ecosystem properties as productivity, nutrient use efficiency, and stability (all of which were attributed to higher levels of species diversity) were actually caused by "hidden treatments" that altered plant biomass and productivity.

How does pedogenesis drive plant diversity?

Some of the most species-rich plant communities occur on ancient, strongly weathered soils, whereas those on recently developed soils tend to be less diverse. Mechanisms underlying this well-known pattern, however, remain unresolved. Here, we present a conceptual model describing alternative mechanisms by which pedogenesis (the process of soil formation) might drive plant diversity. We suggest that long-term soil chronosequences offer great, yet largely untapped, potential as 'natural experiments' to determine edaphic controls over plant diversity. Finally, we discuss how our conceptual model can be evaluated quantitatively using structural equation modeling to advance multivariate theories about the determinants of local plant diversity. This should help us to understand broader-scale diversity patterns, such as the latitudinal gradient of plant diversity.

Comment on "Productivity is a poor predictor of plant species richness".

Adler et al. (Reports, 23 September 2011, p. 1750) reported "weak and variable" relationships between productivity and species richness and dispute the "humped-back" model (HBM) of plant diversity. We show that their analysis lacks sufficient high-productivity sites, ignores litter, and excludes anthropogenic sites. If corrected, the data set of Adler et al. would apparently yield strong HBM support.

A hierarchical perspective of plant diversity.

Predictive models of plant diversity have typically focused on either a landscape's capacity for richness (equilibrium models), or on the processes that regulate competitive exclusion, and thus allow species to coexist (nonequilibrium models). Here, we review the concepts and purposes of a hierarchical, multiscale model of the controls of plant diversity that incorporates the equilibrium model of climatic favorability at macroscales, nonequilibrium models of competition at microscales, and a mixed model emphasizing environmental heterogeneity at mesoscales. We evaluate the conceptual model using published data from three spatially nested datasets: (1) a macroscale analysis of ecoregions in the continental and western U.S.; (2) a mesoscale study in California; and (3) a microscale study in the Siskiyou Mountains of Oregon and California. At the macroscale (areas from 3889 km2 to 638,300 km2), climate (actual evaporation) was a strong predictor of tree diversity (R2 = 0.80), as predicted by the conceptual model, but area was a better predictor for vascular plant diversity overall (R2 = 0.38), which suggests different types of plants differ in their sensitivity to climatic controls. At mesoscales (areas from 1111 km2 to 15,833 km2), climate was still an important predictor of richness (R2 = 0.52), but, as expected, topographic heterogeneity explained an important share of the variance (R2 = 0.19) showed positive correlations with diversity of trees, shrubs, and annual and perennial herbs, and was the primary predictor of shrub and annual plant species richness. At microscales (0.1 ha plots), spatial patterns of diversity showed a clear unimodal pattern along a climate-driven productivity gradient and a negative relationship with soil fertility. The strong decline in understory and total diversity at the most productive sites suggests that competitive controls, as predicted, can override climatic controls at this scale. We conclude that this hierarchical, multiscale model provides a sound basis to understand and analyze plant species diversity. Specifically, future research should employ the principles in this paper to explore climatic controls on species richness of different life forms, better quantify environmental heterogeneity in landscapes, and analyze how these large-scale factors interact with local nonequilibrium dynamics to maintain plant diversity.

Use of individual-based forest succession models to link physiological whole-tree models to landscape-scale ecosystem models.

Models of the spatial and temporal dynamics of forests that are based on competition between individual plants can be used to predict changes in the abundance of different tree species that result from natural succession or environmental change. These individual-based models can be designed to take into account important physiological and chemical properties of individual species, and thus provide a mechanism for scaling up the predictions of whole-plant physiological process models to intermediate-scale patterns in ecosystems and landscapes. Because plant species differ greatly in such properties as carbon fixation and evapotranspiration rates, models that predict species composition could provide information on the distribution of parameter values used as input for large-scale (e.g., "big leaf") models of regional vegetation-atmosphere interactions.

Carbon management and biodiversity.

International efforts to mitigate human-caused changes in the Earth's climate are considering a system of incentives (debits and credits) that would encourage specific changes in land use that can help to reduce the atmospheric concentration of carbon dioxide. The two primary land-based activities that would help to minimize atmospheric carbon dioxide are carbon storage in the terrestrial biosphere and the efficient substitution of biomass fuels and bio-based products for fossil fuels and energy-intensive products. These two activities have very different land requirements and different implications for the preservation of biodiversity and the maintenance of other ecosystem services. Carbon sequestration in living forests can be pursued on lands with low productivity, i.e. on lands that are least suitable for agriculture or intensive forestry, and are compatible with the preservation of biodiversity over large areas. In contrast, intensive harvest-and-use systems for biomass fuels and products generally need more productive land to be economically viable. Intensive harvest-and-use systems may compete with agriculture or they may shift intensive land uses onto the less productive lands that currently harbor most of the Earth's biodiversity. Win-win solutions for carbon dioxide control and biodiversity are possible, but careful evaluation and planning are needed to avoid practices that reduce biodiversity with little net decrease in atmospheric carbon dioxide. Planning is more complex on a politically subdivided Earth where issues of local interest, national sovereignty, and equity come into play.