Summary The relationship between species richness and ecosystem function, as measured by productivity or biomass, is of long‐standing theoretical and practical interest in ecology. This is especially true for forests, which represent a majority of global biomass, productivity and biodiversity. Here, we conduct an analysis of relationships between tree species richness, biomass and productivity in 25 forest plots of area 8–50 ha from across the world. The data were collected using standardized protocols, obviating the need to correct for methodological differences that plague many studies on this topic. We found that at very small spatial grains (0.04 ha) species richness was generally positively related to productivity and biomass within plots, with a doubling of species richness corresponding to an average 48% increase in productivity and 53% increase in biomass. At larger spatial grains (0.25 ha, 1 ha), results were mixed, with negative relationships becoming more common. The results were qualitatively similar but much weaker when we controlled for stem density: at the 0.04 ha spatial grain, a doubling of species richness corresponded to a 5% increase in productivity and 7% increase in biomass. Productivity and biomass were themselves almost always positively related at all spatial grains. Synthesis. This is the first cross‐site study of the effect of tree species richness on forest biomass and productivity that systematically varies spatial grain within a controlled methodology. The scale‐dependent results are consistent with theoretical models in which sampling effects and niche complementarity dominate at small scales, while environmental gradients drive patterns at large scales. Our study shows that the relationship of tree species richness with biomass and productivity changes qualitatively when moving from scales typical of forest surveys (0.04 ha) to slightly larger scales (0.25 and 1 ha). This needs to be recognized in forest conservation policy and management.

A fundamental challenge in ecology is to understand the mechanisms that govern patterns of relative species abundance. Previous numerical simulations have suggested that complex niche-structured models produce species abundance distributions (SADs) that are qualitatively similar to those of very simple neutral models that ignore differences between species. However, in the absence of an analytical treatment of niche models, one cannot tell whether the two classes of model produce the same patterns via similar or different mechanisms. We present an analytical proof that, in the limit as diversity becomes large, a strong niche model give rises to exactly the same asymptotic form of SAD as the neutral model, and we verify the analytical predictions for a Panamanian tropical forest data set. Our results strongly suggest that neutral processes drive patterns of relative species abundance in high-diversity ecological communities, even when strong niche structure exists. However, neutral theory cannot explain what generates high diversity in the first place, and it may not be valid in low-diversity communities. Our results also confirm that neutral theory cannot be used to infer an absence of niche structure or to explain ecosystem function.community ecology | neutral theory | niche theory | relative species abundance distributions | biodiversity I n community ecology, niche theory and neutral theory are two major families of theoretical models that aim to explain patterns of biodiversity observed in nature (1, 2). Niche theory, which has a long history of development (3-5), assumes that different species are regulated by different environmental factors and proposes that diversity arises from spatial and temporal environmental heterogeneity (6). Neutral theory, which was developed more recently from the theory of island biogeography (7), assumes that species are equivalent and proposes that diversity arises from a balance between immigration, speciation, and extinction (8-10). An important metric of biodiversity is the species abundance distribution (SAD), which describes the relative abundances of different species within an ecological community. Neutral models predict SADs that closely match observations from tropical rainforests and other ecosystems (9, 11). These SADs are characterized by log-series distributions at large scales and by zero-sum multinomials (which are shaped like log-normal distributions) at smaller scales. Interestingly, simulations of more complex niche-structured models can produce similar qualitative patterns (1, 12). However, simulations alone cannot tell us whether the two theories produce these similar patterns via different mechanisms or whether neutral processes generate patterns of relative species abundance that are, in fact, robust to niche structure.In this article, we construct an analytical framework to provide a definitive answer to the question of why different models predict similar patterns of relative species abundance. We base our analysis on the standard spatially implicit mod...

Long-term surveys of entire communities of species are needed to measure fluctuations in natural populations and elucidate the mechanisms driving population dynamics and community assembly. We analysed changes in abundance of over 4000 tree species in 12 forests across the world over periods of 6-28 years. Abundance fluctuations in all forests are large and consistent with population dynamics models in which temporal environmental variance plays a central role. At some sites we identify clear environmental drivers, such as fire and drought, that could underlie these patterns, but at other sites there is a need for further research to identify drivers. In addition, cross-site comparisons showed that abundance fluctuations were smaller at species-rich sites, consistent with the idea that stable environmental conditions promote higher diversity. Much community ecology theory emphasises demographic variance and niche stabilisation; we encourage the development of theory in which temporal environmental variance plays a central role.

ForestGEO is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types. ForestGEO's mission is to advance understanding of the diversity and dynamics of forests and to strengthen global capacity for forest science research. ForestGEO is unique among forest plot networks in its large-scale plot dimensions, censusing of all stems ≥1 cm in diameter, inclusion of tropical, temperate and boreal forests, and investigation of additional biotic (e.g., arthropods) and abiotic (e.g., soils) drivers, which together provide a holistic view of forest functioning. The 71 FDPs in 27 countries include approximately 7.33 million living trees and about 12,000 species, representing 20% of the world's known tree diversity. With >1300 published papers, ForestGEO researchers have made significant contributions in two fundamental areas: species coexistence and diversity, and ecosystem functioning. Specifically, defining the major biotic and abiotic controls on the distribution and coexistence of species and functional types and on variation in species' demography has led to improved understanding of how the multiple dimensions of forest diversity are structured across space and time and how this diversity relates to the processes controlling the role of forests in the Earth system. Nevertheless, knowledge gaps remain that impede our ability to predict how forest diversity and function will respond to climate change and other stressors. Meeting these global research challenges requires major advances in standardizing taxonomy of tropical species, resolving the main drivers of forest dynamics, and integrating plotbased ground and remote sensing observations to scale up estimates of forest diversity and function, coupled with improved predictive models. However, they cannot be met without greater financial commitment to sustain the long-term research of ForestGEO and other forest plot networks, greatly expanded scientific capacity across the world's forested nations, and increased collaboration and integration among research networks and disciplines addressing forest science.

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The coexistence of many species within ecological communities poses a long‐standing theoretical puzzle. Modern coexistence theory (MCT) and related techniques explore this phenomenon by examining the chance of a species population growing from rarity in the presence of all other species. The mean growth rate when rare, E[r], is used in MCT as a metric that measures persistence properties (like invasibility or time to extinction) of a population. Here we critique this reliance on E[r] and show that it fails to capture the effect of temporal random abundance variations on persistence properties. The problem becomes particularly severe when an increase in the amplitude of stochastic temporal environmental variations leads to an increase in E[r], since at the same time it enhances random abundance fluctuations and the two effects are inherently intertwined. In this case, the chance of invasion and the mean extinction time of a population may even go down as E[r] increases.

We evaluated the utility of combining metapopulation models with landscape-level forest-dynamics models to assess the sustainability of forest management practices. We used the Brown Creeper (Certhia americana) in the boreal forests of northern Ontario as a case study. We selected the Brown Creeper as a potential indicator of sustainability because it is relatively common in the region but is dependent on snags and old trees for nesting and foraging; hence, it may be sensitive to timber harvesting. For the modeling we used RAMAS Landscape, a software package that integrates RAMAS GIS, population-modeling software, and LAN-DIS, forest-dynamics modeling software. Predictions about the future floristic composition and structure of the landscape under a variety of management and natural disturbance scenarios were derived using LANDIS. We modeled eight alternative forest management scenarios, ranging in intensity from no timber harvesting and a natural fire regime to intensive timber harvesting with salvage logging after fire. We predicted the response of the Brown Creeper metapopulation over a 160-year period and used future population size and expected minimum population size to compare the sustainability of the various management scenarios. The modeling methods were easy to apply and model predictions were sensitive to the differences among management scenarios, indicating that these methods may be useful for assessing and ranking the sustainability of forest management options. Primary concerns about the method are the practical difficulties associated with incorporating fire stochasticity in prediction uncertainty and the number of model assumptions that must be made and tested with sensitivity analysis. We wrote new software to help quantify the contribution of landscape stochasticity to model prediction uncertainty. Utilización de Modelos Metapoblacionales en Paisajes Dinámicos para el Manejo Sustentable de BosquesResumen: Evaluamos la conveniencia de combinar modelos metapoblacionales con modelos de dinámica de bosques a nivel de paisaje para estimar la sustentabilidad de las prácticas de manejo de bosques. Como estudio de caso utilizamos a Certhia americana en bosques boreales del norte de Ontario. Seleccionamos a Certhia americana como un indicador potencial de sustentabilidad porque es relativamente común en la región pero depende de tocones y deárboles viejos para anidar y forrajear, por ello puede ser sensible a la cosecha de madera. Para el modelo utilizamos RAMAS Landscape, un paquete de software que integra a RAMAS GIS (software para modelar poblaciones) y a LANDIS (software para modelar la dinámica de bosques). Utilizando LANDSIS derivamos predicciones de la composición y estructura florística del paisaje bajo una variedad de escenarios de manejo y perturbaciones naturales. Modelamos ocho escenarios alternativos de manejo de bosques, que variaron en intensidad desde la no cosecha de madera y un régimen natural de fuego hasta la cosecha intensiva de madera con corte deárboles después de incendios. Pred...

In the classic spatially implicit formulation of Hubbell's neutral theory of biodiversity a local community receives immigrants from a metacommunity operating on a relatively slow timescale, and dispersal into the local community is governed by an immigration parameter m. A current problem with neutral theory is that m lacks a clear biological interpretation. Here, we derive analytical expressions that relate the immigration parameter m to the geometry of the plot defining the local community and the parameters of a dispersal kernel. Our results facilitate more rigorous and extensive tests of the neutral theory: we conduct a test of neutral theory by comparing estimates of m derived from fits to empirical species abundance distributions to those derived from dispersal kernels and find acceptable correspondence; and we generate a new prediction of neutral theory by investigating how the shapes of species abundance distributions change theoretically as the spatial scale of observation changes. We also discuss how our main analytical results can be used to assess the error in the mean-field approximations associated with spatially implicit formulations of neutral theory.