Quantifying and assessing changes in biological diversity are central aspects of many ecological studies, yet accurate methods of estimating biological diversity from sampling data have been elusive. Hill numbers, or the effective number of species, are increasingly used to characterize the taxonomic, phylogenetic, or functional diversity of an assemblage. However, empirical estimates of Hill numbers, including species richness, tend to be an increasing function of sampling effort and, thus, tend to increase with sample completeness. Integrated curves based on sampling theory that smoothly link rarefaction (interpolation) and prediction (extrapolation) standardize samples on the basis of sample size or sample completeness and facilitate the comparison of biodiversity data. Here we extended previous rarefaction and extrapolation models for species richness (Hill number q D , where q = 0) to measures of taxon diversity incorporating relative abundance (i.e., for any Hill number q D , q > 0) and present a unified approach for both individual-based (abundance) data and sample-based (incidence) data. Using this unified sampling framework, we derive both theoretical formulas and analytic estimators for seamless rarefaction and extrapolation based on Hill numbers. Detailed examples are provided for the first three Hill numbers: q = 0 (species richness), q = 1 (the exponential of Shannon's entropy index), and q = 2 (the inverse of Simpson's concentration index). We developed a bootstrap method for constructing confidence intervals around Hill numbers, facilitating the comparison of multiple assemblages of both rarefied and extrapolated samples. The proposed estimators are accurate for both rarefaction and short-range extrapolation. For long-range extrapolation, the performance of the estimators depends on both the value of q and on the extrapolation range. We tested our methods on simulated data generated from species abundance models and on data from large species inventories. We also illustrate the formulas and estimators using empirical data sets from biodiversity surveys of temperate forest spiders and tropical ants.
The global decline in estuarine and coastal ecosystems (ECEs) is affecting a number of critical benefits, or ecosystem services. We review the main ecological services across a variety of ECEs, including marshes, mangroves, nearshore coral reefs, seagrass beds, and sand beaches and dunes. Where possible, we indicate estimates of the key economic values arising from these services, and discuss how the natural variability of ECEs impacts their benefits, the synergistic relationships of ECEs across seascapes, and management implications. Although reliable valuation estimates are beginning to emerge for the key services of some ECEs, such as coral reefs, salt marshes, and mangroves, many of the important benefits of seagrass beds and sand dunes and beaches have not been assessed properly. Even for coral reefs, marshes, and mangroves, important ecological services have yet to be valued reliably, such as cross-ecosystem nutrient transfer (coral reefs), erosion control (marshes), and pollution control (mangroves). An important issue for valuing certain ECE services, such as coastal protection and habitat-–fishery linkages, is that the ecological functions underlying these services vary spatially and temporally. Allowing for the connectivity between ECE habitats also may have important implications for assessing the ecological functions underlying key ecosystems services, such coastal protection, control of erosion, and habitat-–fishery linkages. Finally, we conclude by suggesting an action plan for protecting and/or enhancing the immediate and longer-term values of ECE services. Because the connectivity of ECEs across land-–sea gradients also influences the provision of certain ecosystem services, management of the entire seascape will be necessary to preserve such synergistic effects. Other key elements of an action plan include further ecological and economic collaborative research on valuing ECE services, improving institutional and legal frameworks for management, controlling and regulating destructive economic activities, and developing ecological restoration options.
ANOSIM, PERMANOVA, and the Mantel test are all resemblance-based permutation methods widely used in ecology. Here, we report the results of the first simulation study, to our knowledge, specifically designed to examine the effects of heterogeneity of multivariate dispersions on the rejection rates of these tests and on a classical MANOVA test (Pillai's trace). Increasing differences in dispersion among groups were simulated under scenarios of changing sample sizes, correlation structures, error distributions, numbers of variables, and numbers of groups for balanced and unbalanced one-way designs. The power of these tests to detect environmental impacts or natural large-scale biogeographic gradients was also compared empirically under simulations based on parameters derived from real ecological data sets. Overall, ANOSIM and the Mantel test were very sensitive to heterogeneity in dispersions, with ANOSIM generally being more sensitive than the Mantel test. In contrast, PERMANOVA and Pillai's trace were largely unaffected by heterogeneity for balanced designs. PERMANOVA was also unaffected by differences in correlation structure, unlike Pillai's trace. For unbalanced designs, however, all of the tests were (1) too liberal when the smaller group had greater dispersion and (2) overly conservative when the larger group had greater dispersion, especially ANOSIM and the Mantel test. For simulations based on real ecological data sets, PERMANOVA was generally, but not always, more powerful than the others to detect changes in community structure, and the Mantel test was usually more powerful than ANOSIM. Both the error distributions and the resemblance measure affected results concerning power. Differences in the underlying construction of these test statistics result in important differences in the nature of the null hypothesis they are testing, their sensitivity to heterogeneity, and their power to detect important changes in ecological communities. For balanced designs, PERMANOVA and PERMDISP can be used to rigorously identify location vs. dispersion effects, respectively, in the space of the chosen resemblance measure. ANOSIM and the Mantel test can be used as more "omnibus" tests, being sensitive to differences in location, dispersion or correlation structure among groups. Unfortunately, none of the tests (PERMANOVA, Mantel, or ANOSIM) behaved reliably for unbalanced designs in the face of heterogeneity.
The steady upward trend in the use of model selection and Bayesian methods in ecological research has made it clear that both approaches to inference are important for modern analysis of models and data. However, in teaching Bayesian methods and in working with our research colleagues, we have noticed a general dissatisfaction with the available literature on Bayesian model selection and multimodel inference. Students and researchers new to Bayesian methods quickly find that the published advice on model selection is often preferential in its treatment of options for analysis, frequently advocating one particular method above others. The recent appearance of many articles and textbooks on Bayesian modeling has provided welcome background on relevant approaches to model selection in the Bayesian framework, but most of these are either very narrowly focused in scope or inaccessible to ecologists. Moreover, the methodological details of Bayesian model selection approaches are spread thinly throughout the literature, appearing in journals from many different fields. Our aim with this guide is to condense the large body of literature on Bayesian approaches to model selection and multimodel inference and present it specifically for quantitative ecologists as neutrally as possible. We also bring to light a few important and fundamental concepts relating directly to model selection that seem to have gone unnoticed in the ecological literature. Throughout, we provide only a minimal discussion of philosophy, preferring instead to examine the breadth of approaches as well as their practical advantages and disadvantages. This guide serves as a reference for ecologists using Bayesian methods, so that they can better understand their options and can make an informed choice that is best aligned with their goals for inference.
A predictive understanding of the ecological impacts of nonnative species has been slow to develop, owing largely to an apparent dearth of clearly defined hypotheses and the lack of a broad theoretical framework. The context dependency of impact has fueled the perception that meaningful generalizations are nonexistent. Here, we identified and reviewed 19 testable hypotheses that explain temporal and spatial variation in impact. Despite poor validation of most hypotheses to date, evidence suggests that each can explain at least some impacts in some situations. Several hypotheses are broad in scope (applying to plants and animals in virtually all contexts) and some of them, intriguingly, link processes of colonization and impact. Collectively, these hypotheses highlight the importance of the functional ecology of the nonnative species and the structure, diversity, and evolutionary experience of the recipient community as general determinants of impact; thus, they could provide the foundation for a theoretical framework for understanding and predicting impact. Further substantive progress toward this goal requires explicit consideration of within-taxon and across-taxa variation in the per capita effect of invaders, and analyses of complex interactions between invaders and their biotic and abiotic environments.
The recent warming in the Arctic is affecting a broad spectrum of physical, ecological, and human/cultural systems that may be irreversible on century time scales and have the potential to cause rapid changes in the earth system. The response of the carbon cycle of the Arctic to changes in climate is a major issue of global concern, yet there has not been a comprehensive review of the status of the contemporary carbon cycle of the Arctic and its response to climate change. This review is designed to clarify key uncertainties and vulnerabilities in the response of the carbon cycle of the Arctic to ongoing climatic change. While it is clear that there are substantial stocks of carbon in the Arctic, there are also significant uncertainties associated with the magnitude of organic matter stocks contained in permafrost and the storage of methane hydrates beneath both subterranean and submerged permafrost of the Arctic. In the context of the global carbon cycle, this review demonstrates that the Arctic plays an important role in the global dynamics of both CO₂ and CH₄ . Studies suggest that the Arctic has been a sink for atmospheric CO₂ of between 0 and 0.8 Pg C/yr in recent decades, which is between 0% and 25% of the global net land/ocean flux during the 1990s. The Arctic is a substantial source of CH₄ to the atmosphere (between 32 and 112 Tg CH₄/yr), primarily because of the large area of wetlands throughout the region. Analyses to date indicate that the sensitivity of the carbon cycle of the Arctic during the remainder of the 21st century is highly uncertain. To improve the capability to assess the sensitivity of the carbon cycle of the Arctic to projected climate change, we recommend that (1) integrated regional studies be conducted to link observations of carbon dynamics to the processes that are likely to influence those dynamics, and (2) the understanding gained from these integrated studies be incorporated into both uncoupled and fully coupled carbon-climate modeling efforts.
Humans, unlike any other multicellular species in Earth's history, have emerged as a global force that is transforming the ecology of an entire planet. It is no longer possible to understand, predict, or successfully manage ecological pattern, process, or change without understanding why and how humans reshape these over the long term. Here, a general causal theory is presented to explain why human societies gained the capacity to globally alter the patterns, processes, and dynamics of ecology and how these anthropogenic alterations unfold over time and space as societies themselves change over human generational time. Building on existing theories of ecosystem engineering, niche construction, inclusive inheritance, cultural evolution, ultrasociality, and social change, this theory of anthroecological change holds that sociocultural evolution of subsistence regimes based on ecosystem engineering, social specialization, and non-kin exchange, or "sociocultural niche construction," is the main cause of both the long-term upscaling of human societies and their unprecedented transformation of the biosphere. Human sociocultural niche construction can explain, where classic ecological theory cannot, the sustained transformative effects of human societies on biogeography, ecological succession, ecosystem processes, and the ecological patterns and processes of landscapes, biomes, and the biosphere. Anthroecology theory generates empirically testable hypotheses on the forms and trajectories of long-term anthropogenic ecological change that have significant theoretical and practical implications across the subdisciplines of ecology and conservation. Though still at an early stage of development, anthroecology theory aligns with and integrates established theoretical frameworks including social-ecological systems, social metabolism, countryside biogeography, novel ecosystems, and anthromes. The "fluxes of nature" are fast becoming "cultures of nature." To investigate, understand, and address the ultimate causes of anthropogenic ecological change, not just the consequences, human sociocultural processes must become as much a part of ecological theory and practice as biological and geophysical processes are now. Strategies for achieving this goal and for advancing ecological science and conservation in an increasingly anthropogenic biosphere are presented.
Species spatial distributions are the result of population demography, behavioral traits, and species interactions in spatially heterogeneous environmental conditions. Hence the composition of species assemblages is an integrative response variable, and its variability can be explained by the complex interplay among several structuring factors. The thorough analysis of spatial variation in species assemblages may help infer processes shaping ecological communities. We suggest that ecological studies would benefit from the combined use of the classical statistical models of community composition data, such as constrained or unconstrained multivariate analyses of site-by-species abundance tables, with rapidly emerging and diversifying methods of spatial pattern analysis. Doing so allows one to deal with spatially explicit ecological models of beta diversity in a biogeographic context through the multiscale analysis of spatial patterns in original species data tables, including spatial characterization of fitted or residual variation from environmental models. We summarize here the recent progress for specifying spatial features through spatial weighting matrices and spatial eigenfunctions in order to define spatially constrained or scale-explicit multivariate analyses. Through a worked example on tropical tree communities, we also show the potential of the overall approach to identify significant residual spatial patterns that could arise from the omission of important unmeasured explanatory variables or processes.
Elemental stoichiometry constitutes an inherent link between biogeochemistry and the structure and processes within food webs, and thus is at the core of ecosystem functioning. Stoichiometry allows for spanning different levels of biological organization, from cellular metabolism to ecosystem structure and nutrient cycling, and is therefore particularly useful for establishing links between different ecosystem compartments. We review elemental carbon : nitrogen : phosphorus (C:N:P) ratios in terrestrial ecosystems (from vegetation, leaf litter, woody debris, and dead roots, to soil microbes and organic matter). While the stoichiometry of the plant, litter, and soil compartments of ecosystems is well understood, heterotrophic microbial communities, which dominate the soil food web and drive nutrient cycling, have received increasing interest in recent years. This review highlights the effects of resource stoichiometry on soil microorganisms and decomposition, specifically on the structure and function of heterotrophic microbial communities and suggests several general patterns. First, latitudinal gradients of soil and litter stoichiometry are reflected in microbial community structure and function. Second, resource stoichiometry may cause changes in microbial interactions and community dynamics that lead to feedbacks in nutrient availability. Third, global change alters the C:N, C:P, and N:P ratios of primary producers, with repercussions for microbial decomposer communities and critical ecosystem services such as soil fertility. We argue that ecological stoichiometry provides a framework to analyze and predict such global change effects at various scales.
Fungi play key roles in ecosystems as mutualists, pathogens, and decomposers. Current estimates of global species richness are highly uncertain, and the importance of stochastic vs. deterministic forces in the assembly of fungal communities is unknown. Molecular studies have so far failed to reach saturated, comprehensive estimates of fungal diversity. To obtain a more accurate estimate of global fungal diversity, we used a direct molecular approach to census diversity in a boreal ecosystem with precisely known plant diversity, and we carefully evaluated adequacy of sampling and accuracy of species delineation. We achieved the first exhaustive enumeration of fungi in soil, recording 1002 taxa in this system. We show that the fungus:plant ratio in Picea mariana forest soils from interior Alaska is at least 17:1 and is regionally stable. A global extrapolation of this ratio would suggest 6 million species of fungi, as opposed to leading estimates ranging from 616000 to 1.5 million. We also find that closely related fungi often occupy divergent niches. This pattern is seen in fungi spanning all major functional guilds and four phyla, suggesting a major role of deterministic niche partitioning in community assembly. Extinctions and range shifts are reorganizing biodiversity on Earth, yet our results suggest that 98% of fungi remain undescribed and that many of these species occupy unique niches.
Community assembly processes are thought to shape the mean, spread, and spacing of functional trait values within communities. Two broad categories of assembly processes have been proposed: first, a habitat filter that restricts the range of viable strategies and second, a partitioning of microsites and/or resources that leads to a limit to the similarity of coexisting species. The strength of both processes may be dependent on conditions at a particular site and may change along an abiotic gradient. We sampled environmental variables and plant communities in 44 plots across the varied topography of a coastal California landscape. We characterized 14 leaf, stem, and root traits for 54 woody plant species, including detailed intraspecific data for two traits with the goal of understanding the connection between traits and assembly processes in a variety of environmental conditions. We examined the within-community mean, range, variance, kurtosis, and other measures of spacing of trait values. In this landscape, there was a topographically mediated gradient in water availability. Across this gradient we observed strong shifts in both the plot-level mean trait values and the variation in trait values within communities. Trends in trait means with the environment were due largely to species turnover, with intraspecific shifts playing a smaller role. Traits associated with a vertical partitioning of light showed a greater range and variance on the wet soils, while nitrogen per area, which is associated with water use efficiency, showed a greater spread on the dry soils. We found strong nonrandom patterns in the trait distributions consistent with expectations based on trait-mediated community assembly. There was a significant reduction in the range of six out of 11 leaf and stem functional trait values relative to a null model. For specific leaf area (SLA) we found a significant even spacing of trait values relative to the null model. For seed size we found a more platykurtic distribution than expected. These results suggest that both a habitat filter and a limit to the similarity of coexisting species can simultaneously shape the distribution of traits and the assembly of local plant communities.
About one-third of North America is forested. These forests are of incalculable value to human society in terms of harvested resources and ecosystem services and are sensitive to disturbance regimes. Epidemics of forest insects and diseases are the dominant sources of disturbance to North American forests. Here we review current understanding of climatic effects on the abundance of forest insects and diseases in North America, and of the ecological and socioeconomic impacts of biotic disturbances. We identified 27 insects (6 nonindigenous) and 22 diseases (9 nonindigenous) that are notable agents of disturbance in North American forests. The distribution and abundance of forest insects and pathogens respond rapidly to climatic variation due to their physiological sensitivity to temperature, high mobility, short generation times, and high reproductive potential. Additionally, climate affects tree defenses, tree tolerance, and community interactions involving enemies, competitors, and mutualists of insects and diseases. Recent research affirms the importance of milder winters, warmer growing seasons, and changes in moisture availability to the occurrence of biotic disturbances. Predictions from the first U.S. National Climate Assessment of expansions in forest disturbances from climate change have been upheld, in some cases more rapidly and dramatically than expected. Clear examples are offered by recent epidemics of spruce beetles in Alaska, mountain pine beetle in high-elevation five-needle pine forests of the Rocky Mountains, and southern pine beetle in the New Jersey Pinelands. Pathogens are less studied with respect to climate, but some are facilitated by warmer and wetter summer conditions. Changes in biotic disturbances have broad consequences for forest ecosystems and the services they provide to society. Climatic effects on forest insect and disease outbreaks may foster further changes in climate by influencing the exchange of carbon, water, and energy between forests and the atmosphere. Climate-induced changes in forest productivity and disturbance create opportunities as well as vulnerabilities (e.g., increases in productivity in many areas, and probably decreases in disturbance risks in some areas). There is a critical need to better understand and predict the interactions among climate, forest productivity, forest disturbance, and the socioeconomic relations between forests and people.
Despite a long history of the study of tropical forests, uncertainty about the importance of different ecological processes in shaping tropical tree species distributions persists. Trait- and phylogenetic-based tests of community assembly provide a powerful way to detect community assembly processes but have seldom been applied to the same community. Both methods are well suited to testing how the relative importance of different ecological processes changes with spatial scale. Here we apply both methods to the Yasuní Forest Dynamics Plot, a 25-ha Amazonian forest with >1100 tree species. We found evidence for habitat filtering from both trait and phylogenetic methods from small (25 m 2 ) to intermediate (10 000 m 2 ) spatial scales. Trait-based methods detected even spacing of strategies, a pattern consistent with niche partitioning or enemy-mediated density dependence, at smaller spatial scales (25-400 m 2 ). Simulation modeling of community assembly processes suggests that low statistical power to detect even spacing of traits at larger spatial scales may contribute to the observed patterns. Trait and phylogenetic methods tended to identify the same areas of the forest as being subject to habitat filtering. Phylogenetic community tests, which are far less data-intensive than trait-based methods, captured much of the same filtering patterns detected by trait-based methods but often failed to detect even-spacing patterns apparent in trait data. Taken together, it appears that both habitat associations and niche differentiation shape species co-occurrence patterns in one of the most diverse forests in the world at a range of small and intermediate spatial scales.
Nutrient resorption in plants influences nutrient availability and cycling and is a key process in biogeochemical models. Improved estimates of resorption parameters are needed for predicting long-term primary productivity and for improving such models. Currently, most models assume a value of 50% resorption for nitrogen (N) and phosphorus (P) and lack resorption data for other nutrients and for specific vegetation types. We provide global estimates of resorption efficiencies and nutrient concentrations for carbon (C), N, and P and the first global-scale estimates for essential nutrients such as potassium (K), calcium (Ca), and magnesium (Mg). We also examine leaf mass loss during senescence (LML) globally and for different plant types, thus defining a mass loss correction factor (MLCF) needed to quantify unbiased resorption values. We used a global meta-analysis of 86 studies and ∼1000 data points across climates for green and senesced leaves in six plant types: ferns, forbs, graminoids, conifers, and evergreen and deciduous woody angiosperms. In general, N and P resorption differed significantly from the commonly used global value of 50% (62.1%, 64.9%, respectively; P < 0.05). Ca, C, and Mg showed lower average resorptions of 10.9%, 23.2%, and 28.6%, respectively, while K had the highest resorption, at 70.1%. We also found that resorption of all nutrients except Ca depended on leaf nutrient-status; globally, C, N, P, K, and Mg showed a decrease in resorption with increased nutrient status. On average, global leaf mass loss was 24.2%. Overall, our resorption data differ substantially from commonly assumed values and should help improve ecological theory and biogeochemical and land-surface models.
Streams and rivers can substantially modify organic carbon (OC) inputs from terrestrial landscapes, and much of this processing is the result of microbial respiration. While carbon dioxide (CO2) is the major end-product of ecosystem respiration, methane (CH4) is also present in many fluvial environments even though methanogenesis typically requires anoxic conditions that may be scarce in these systems. Given recent recognition of the pervasiveness of this greenhouse gas in streams and rivers, we synthesized existing research and data to identify patterns and drivers of CH4, knowledge gaps, and research opportunities. This included examining the history of lotie CH4 research, creating a database of concentrations and fluxes (MethDB) to generate a global-scale estimate of fluvial CH4 efflux, and developing a conceptual framework and using this framework to consider how human activities may modify fluvial CH4 dynamics. Current understanding of CH4 in streams and rivers has been strongly influenced by goals of understanding OC processing and quantifying the contribution of CH4 to ecosystem C fluxes. Less effort has been directed towards investigating processes that dictate in situ CH4 production and loss. CH4 makes a meager contribution to watershed or landscape C budgets, but streams and rivers are often significant CH4 sources to the atmosphere across these same spatial extents. Most fluvial systems are supersaturated with CH4 and we estimate an annual global emission of 26.8 Tg CH4, equivalent to ∼15-40% of wetland and lake effluxes, respectively. Less clear is the role of CH4 oxidation, methanogenesis, and total anaerobic respiration to whole ecosystem production and respiration. Controls on CH4 generation and persistence can be viewed in terms of proximate controls that influence methanogenesis (organic matter, temperature, alternative electron acceptors, nutrients) and distal geomorphic and hydrologie drivers. Multiple controls combined with its extreme redox status and low solubility result in high spatial and temporal variance of CH4 in fluvial environments, which presents a substantial challenge for understanding its larger-scale dynamics. Further understanding of CH4 production and consumption, anaerobic metabolism, and ecosystem energetics in streams and rivers can be achieved through more directed studies and comparison with knowledge from terrestrial, wetland, and aquatic disciplines.
Functional diversity is the diversity of species traits in ecosystems. This concept is increasingly used in ecological research, yet its formal definition and measurements are currently under discussion. As the overall behavior and consistency of functional diversity indices have not been described so far, the novice user risks choosing an inaccurate index or a set of redundant indices to represent functional diversity. In our study we closely examine functional diversity indices to clarify their accuracy, consistency, and independence. Following current theory, we categorize them into functional richness, evenness, or divergence indices. We considered existing indices as well as new indices developed in this study. The new indices aimed at remedying the weaknesses of currently used indices (e.g., by taking into account intraspecific variability). Using virtual data sets, we test (1) whether indices respond to community changes as expected from their category and (2) whether the indices within each category are consistent and independent of indices from other categories. We also test the accuracy of methods proposed for the use of categorical traits. Most classical functional richness indices either failed to describe functional richness or were correlated with functional divergence indices. We therefore recommend using the new functional richness indices that consider intraspecific variability and thus empty space in the functional niche space. In contrast, most functional evenness and divergence indices performed well with respect to all proposed tests. For categorical variables, we do not recommend blending discrete and real-valued traits (except for indices based on distance measures) since functional evenness and divergence have no transposable meaning for discrete traits. Nonetheless, species diversity indices can be applied to categorical traits (using trait levels instead of species) in order to describe functional richness and equitability.
Plants store large amounts of non-structural carbohydrates (NSC). While multiple functions of NSC have long been recognized, the interpretation of NSC seasonal dynamics is often based on the idea that stored NSC is a reservoir of carbon that fluctuates depending on the balance between supply via photosynthesis and demand for growth and respiration (the source–sink dynamics concept). Consequently, relatively high NSC concentrations in some plants have been interpreted to reflect excess supply relative to demand. An alternative view, however, is that NSC accumulation reflects the relatively high NSC levels required for plant survival; an important issue that remains highly controversial. Here, we assembled a new global database to examine broad patterns of seasonal NSC variation across organs (leaves, stems, and belowground), plant functional types (coniferous, drought-deciduous angiosperms, winter deciduous angiosperms, evergreen angiosperms, and herbaceous) and biomes (boreal, temperate, Mediterranean, and tropical). We compiled data from 121 studies, including seasonal measurements for 177 species under natural conditions. Our results showed that, on average, NSC account for ~10% of dry plant biomass and are highest in leaves and lowest in stems, whereas belowground organs show intermediate concentrations. Total NSC, starch, and soluble sugars (SS) varied seasonally, with a strong depletion of starch during the growing season and a general increase during winter months, particularly in boreal and temperate biomes. Across functional types, NSC concentrations were highest and most variable in herbaceous species and in conifer needles. Conifers showed the lowest stem and belowground NSC concentrations. Minimum NSC values were relatively high (46% of seasonal maximums on average for total NSC) and, in contrast to average values, were similar among biomes and functional types. Overall, although starch depletion was relatively common, seasonal depletion of total NSC or SS was rare. These results are consistent with a dual view of NSC function: whereas starch acts mostly as a reservoir for future use, soluble sugars perform immediate functions (e.g., osmoregulation) and are kept above some critical threshold. If confirmed, this dual function of NSC will have important implications for the way we understand and model plant carbon allocation and survival under stress.
The mineralization of nitrogen and phosphorus from plant residues provides an important input of inorganic nutrients to the soil, which can be taken up by plants. The dynamics of nutrient mineralization or immobilization during decomposition are controlled by different biological and physical factors. Decomposers sequester carbon and nutrients from organic substrates and exchange inorganic nutrients with the environment to maintain their stoichiometric balance. Additionally, physical losses of organic compounds from leaching and other processes may alter the nutrient content of litter. In this work, we extend a stoichiometric model of litter nitrogen mineralization to include (1) phosphorus mineralization, (2) physical losses of organic nutrients, and (3) chemical heterogeneity of litter substrates. The enhanced model provides analytical mineralization curves for nitrogen and phosphorus as well as critical litter carbon: nutrient ratios (the carbon: nutrient ratios below which net nutrient release occurs) as a function of the elemental composition of the decomposers, their carbon-use efficiency, and the rate of physical loss of organic compounds. The model is used to infer the critical litter carbon: nutrient ratios from observed nitrogen and phosphorus dynamics in about 2600 litterbag samplings from 21 decomposition data sets spanning artic to tropical ecosystems. At the beginning of decomposition, nitrogen and phosphorus tend to be immobilized in boreal and temperate climates (i.e., both C:N and C:P critical ratios are lower than the initial ratios), while in tropical areas nitrogen is generally released and phosphorus may be either immobilized or released, regardless of the typically low phosphorus concentrations. The critical carbon: nutrient ratios we observed were found to increase with initial litter carbon: nutrient ratios, indicating that decomposers adapt to low-nutrient conditions by reducing their carbon-use efficiency. This stoichiometric control on nutrient dynamics appears ubiquitous across climatic regions and ecosystems, although other biological and physical processes also play important roles in litter decomposition. In tropical humid conditions, we found high critical C:P ratios likely due to high leaching and low decomposer phosphorus concentrations. In general, the compound effects of stoichiometric constraints and physical losses explain most of the variability in critical carbon: nutrient ratios and dynamics of nutrient immobilization and release at the global scale.
The use of structural equation modeling (SEM) is often motivated by its utility for investigating complex networks of relationships, but also because of its promise as a means of representing theoretical concepts using latent variables. In this paper, we discuss characteristics of ecological theory and some of the challenges for proper specification of theoretical ideas in structural equation models (SE models). In our presentation, we describe some of the requirements for classical latent variable models in which observed variables (indicators) are interpreted as the effects of underlying causes. We also describe alternative model specifications in which indicators are interpreted as having causal influences on the theoretical concepts. We suggest that this latter nonclassical specification (which involves another variable type—the composite) will often be appropriate for ecological studies because of the multifaceted nature of our theoretical concepts. In this paper, we employ the use of meta-models to aid the translation of theory into SE models and also to facilitate our ability to relate results back to our theories. We demonstrate our approach by showing how a synthetic theory of grassland biodiversity can be evaluated using SEM and data from a coastal grassland. In this example, the theory focuses on the responses of species richness to abiotic stress and disturbance, both directly and through intervening effects on community biomass. Models examined include both those based on classical forms (where each concept is represented using a single latent variable) and also ones in which the concepts are recognized to be multifaceted and modeled as such. To address the challenge of matching SE models with the conceptual level of our theory, two approaches are illustrated, compositing and aggregation. Both approaches are shown to have merits, with the former being preferable for cases where the multiple facets of a concept have widely differing effects in the system and the latter being preferable where facets act together consistently when influencing other parts of the system. Because ecological theory characteristically deals with concepts that are multifaceted, we expect the methods presented in this paper will be useful for ecologists wishing to use SEM.
Humans are altering the composition of biological communities through a variety of activities that increase rates of species invasions and species extinctions, at all scales, from local to global. These changes in components of the Earth's biodiversity cause concern for ethical and aesthetic reasons, but they also have a strong potential to alter ecosystem properties and the goods and services they provide to humanity. Ecological experiments, observations, and theoretical developments show that ecosystem properties depend greatly on biodiversity in terms of the functional characteristics of organisms present in the ecosystem and the distribution and abundance of those organisms over space and time. Species effects act in concert with the effects of climate, resource availability, and disturbance regimes in influencing ecosystem properties. Human activities can modify all of the above factors; here we focus on modification of these biotic controls. The scientific community has come to a broad consensus on many aspects of the relationship between biodiversity and ecosystem functioning, including many points relevant to management of ecosystems. Further progress will require integration of knowledge about biotic and abiotic controls on ecosystem properties, how ecological communities are structured, and the forces driving species extinctions and invasions. To strengthen links to policy and management, we also need to integrate our ecological knowledge with understanding of the social and economic constraints of potential management practices. Understanding this complexity, while taking strong steps to minimize current losses of species, is necessary for responsible management of Earth's ecosystems and the diverse biota they contain. Based on our review of the scientific literature, we are certain of the following conclusions: 1) Species' functional characteristics strongly influence ecosystem properties. Functional characteristics operate in a variety of contexts, including effects of dominant species, keystone species, ecological engineers, and interactions among species (e.g., competition, facilitation, mutualism, disease, and predation). Relative abundance alone is not always a good predictor of the ecosystem-level importance of a species, as even relatively rare species (e.g., a keystone predator) can strongly influence pathways of energy and material flows. 2) Alteration of biota in ecosystems via species invasions and extinctions caused by human activities has altered ecosystem goods and services in many well-documented cases. Many of these changes are difficult, expensive, or impossible to reverse or fix with technological solutions. 3) The effects of species loss or changes in composition, and the mechanisms by which the effects manifest themselves, can differ among ecosystem properties, ecosystem types, and pathways of potential community change. 4) Some ecosystem properties are initially insensitive to species loss because (a) ecosystems may have multiple species that carry out similar functional roles, (b) some species may contribute relatively little to ecosystem properties, or (c) properties may be primarily controlled by abiotic environmental conditions. 5) More species are needed to insure a stable supply of ecosystem goods and services as spatial and temporal variability increases, which typically occurs as longer time periods and larger areas are considered. We have high confidence in the following conclusions: 1) Certain combinations of species are complementary in their patterns of resource use and can increase average rates of productivity and nutrient retention. At the same time, environmental conditions can influence the importance of complementarity in structuring communities. Identification of which and how many species act in a complementary way in complex communities is just beginning. 2) Susceptibility to invasion by exotic species is strongly influenced by species composition and, under similar environmental conditions, generally decreases with increasing species richness. However, several other factors, such as propagule pressure, disturbance regime, and resource availability also strongly influence invasion success and often override effects of species richness in comparisons across different sites or ecosystems. 3) Having a range of species that respond differently to different environmental perturbations can stabilize ecosystem process rates in response to disturbances and variation in abiotic conditions. Using practices that maintain a diversity of organisms of different functional effect and functional response types will help preserve a range of management options. Uncertainties remain and further research is necessary in the following areas: 1) Further resolution of the relationships among taxonomic diversity, functional diversity, and community structure is important for identifying mechanisms of biodiversity effects. 2) Multiple trophic levels are common to ecosystems but have been understudied in biodiversity/ecosystem functioning research. The response of ecosystem properties to varying composition and diversity of consumer organisms is much more complex than responses seen in experiments that vary only the diversity of primary producers. 3) Theoretical work on stability has outpaced experimental work, especially field research. We need long-term experiments to be able to assess temporal stability, as well as experimental perturbations to assess response to and recovery from a variety of disturbances. Design and analysis of such experiments must account for several factors that covary with species diversity. 4) Because biodiversity both responds to and influences ecosystem properties, understanding the feedbacks involved is necessary to integrate results from experimental communities with patterns seen at broader scales. Likely patterns of extinction and invasion need to be linked to different drivers of global change, the forces that structure communities, and controls on ecosystem properties for the development of effective management and conservation strategies. 5) This paper focuses primarily on terrestrial systems, with some coverage of freshwater systems, because that is where most empirical and theoretical study has focused. While the fundamental principles described here should apply to marine systems, further study of that realm is necessary. Despite some uncertainties about the mechanisms and circumstances under which diversity influences ecosystem properties, incorporating diversity effects into policy and management is essential, especially in making decisions involving large temporal and spatial scales. Sacrificing those aspects of ecosystems that are difficult or impossible to reconstruct, such as diversity, simply because we are not yet certain about the extent and mechanisms by which they affect ecosystem properties, will restrict future management options even further. It is incumbent upon ecologists to communicate this need, and the values that can derive from such a perspective, to those charged with economic and policy decision-making.