Showing papers in "Ecology in 2008"

New multidimensional functional diversity indices for a multifaceted framework in functional ecology.

Abstract: Functional diversity is increasingly identified as an important driver of ecosystem functioning. Various indices have been proposed to measure the functional diversity of a community, but there is still no consensus on which are most suitable. Indeed, none of the existing indices meets all the criteria required for general use. The main criteria are that they must be designed to deal with several traits, take into account abundances, and measure all the facets of functional diversity. Here we propose three indices to quantify each facet of functional diversity for a community with species distributed in a multidimensional functional space: functional richness (volume of the functional space occupied by the community), functional evenness (regularity of the distribution of abundance in this volume), and functional divergence (divergence in the distribution of abundance in this volume). Functional richness is estimated using the existing convex hull volume index. The new functional evenness index is based on the minimum spanning tree which links all the species in the multidimensional functional space. Then this new index quantifies the regularity with which species abundances are distributed along the spanning tree. Functional divergence is measured using a novel index which quantifies how species diverge in their distances (weighted by their abundance) from the center of gravity in the functional space. We show that none of the indices meets all the criteria required for a functional diversity index, but instead we show that the set of three complementary indices meets these criteria. Through simulations of artificial data sets, we demonstrate that functional divergence and functional evenness are independent of species richness and that the three functional diversity indices are independent of each other. Overall, our study suggests that decomposition of functional diversity into its three primary components provides a meaningful framework for its quantification and for the classification of existing functional diversity indices. This decomposition has the potential to shed light on the role of biodiversity on ecosystem functioning and on the influence of biotic and abiotic filters on the structure of species communities. Finally, we propose a general framework for applying these three functional diversity indices.

Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed.

Abstract: Our meta-analysis of 126 nitrogen addition experiments evaluated nitrogen (N) limitation of net primary production (NPP) in terrestrial ecosystems. We tested the hypothesis that N limitation is widespread among biomes and influenced by geography and climate. We used the response ratio (R approximately equal ANPP(N)/ANPP(ctrl)) of aboveground plant growth in fertilized to control plots and found that most ecosystems are nitrogen limited with an average 29% growth response to nitrogen (i.e., R = 1.29). The response ratio was significant within temperate forests (R = 1.19), tropical forests (R = 1.60), temperate grasslands (R = 1.53), tropical grasslands (R = 1.26), wetlands (R = 1.16), and tundra (R = 1.35), but not deserts. Eight tropical forest studies had been conducted on very young volcanic soils in Hawaii, and this subgroup was strongly N limited (R = 2.13), which resulted in a negative correlation between forest R and latitude. The degree of N limitation in the remainder of the tropical forest studies (R = 1.20) was comparable to that of temperate forests, and when the young Hawaiian subgroup was excluded, forest R did not vary with latitude. Grassland response increased with latitude, but was independent of temperature and precipitation. These results suggest that the global N and C cycles interact strongly and that geography can mediate ecosystem response to N within certain biome types.

Forward selection of explanatory variables

Abstract: This paper proposes a new way of using forward selection of explanatory variables in regression or canonical redundancy analysis. The classical forward selection method presents two problems: a highly inflated Type I error and an overestimation of the amount of explained variance. Correcting these problems will greatly improve the performance of this very useful method in ecological modeling. To prevent the first problem, we propose a two-step procedure. First, a global test using all explanatory variables is carried out. If, and only if, the global test is significant, one can proceed with forward selection. To prevent overestimation of the explained variance, the forward selection has to be carried out with two stopping criteria: (1) the usual alpha significance level and (2) the adjusted coefficient of multiple determination (Ra(2)) calculated using all explanatory variables. When forward selection identifies a variable that brings one or the other criterion over the fixed threshold, that variable is rejected, and the procedure is stopped. This improved method is validated by simulations involving univariate and multivariate response data. An ecological example is presented using data from the Bryce Canyon National Park, Utah, U.S.A.

Using circuit theory to model connectivity in ecology, evolution, and conservation.

Abstract: Connectivity among populations and habitats is important for a wide range of ecological processes. Understanding, preserving, and restoring connectivity in complex landscapes requires connectivity models and metrics that are reliable, efficient, and process based. We introduce a new class of ecological connectivity models based in electrical circuit theory. Although they have been applied in other disciplines, circuit-theoretic connectivity models are new to ecology. They offer distinct advantages over common analytic connectivity models, including a theoretical basis in random walk theory and an ability to evaluate contributions of multiple dispersal pathways. Resistance, current, and voltage calculated across graphs or raster grids can be related to ecological processes (such as individual movement and gene flow) that occur across large population networks or landscapes. Efficient algorithms can quickly solve networks with millions of nodes, or landscapes with millions of raster cells. Here we review basic circuit theory, discuss relationships between circuit and random walk theories, and describe applications in ecology, evolution, and conservation. We provide examples of how circuit models can be used to predict movement patterns and fates of random walkers in complex landscapes and to identify important habitat patches and movement corridors for conservation planning.

Effects of climate change on phenology, frost damage, and floral abundance of montane wildflowers

Abstract: The timing of life history traits is central to lifetime fitness and nowhere is this more evident or well studied as in the phenology of flowering in governing plant reproductive success. Recent changes in the timing of environmental events attributable to climate change, such as the date of snowmelt at high altitudes, which initiates the growing season, have had important repercussions for some common perennial herbaceous wildflower species. The phenology of flowering at the Rocky Mountain Biological Laboratory (Colorado, USA) is strongly influenced by date of snowmelt, which makes this site ideal for examining phenological responses to climate change. Flower buds of Delphinium barbeyi, Erigeron speciosus, and Helianthella quinquenervis are sensitive to frost, and the earlier beginning of the growing season in recent years has exposed them to more frequent mid-June frost kills. From 1992 to 1998, on average 36.1% of Helianthella buds were frosted, but for 1999-2006 the mean is 73.9%; in only one year since 1998 have plants escaped all frost damage. For all three of these perennial species, there is a significant relationship between the date of snowmelt and the abundance of flowering that summer. Greater snowpack results in later snowmelt, later beginning of the growing season, and less frost mortality of buds. Microhabitat differences in snow accumulation, snowmelt patterns, and cold air drainage during frost events can be significant; an elevation difference of only 12 m between two plots resulted in a temperature difference of almost 28C in 2006 and a difference of 37% in frost damage to buds. The loss of flowers and therefore seeds can reduce recruitment in these plant populations, and affect pollinators, herbivores, and seed predators that previously relied on them. Other plant species in this environment are similarly susceptible to frost damage so the negative effects for recruitment and for consumers dependent on flowers and seeds could be widespread. These findings point out the paradox of increased frost damage in the face of global warming, provide important insights into the adaptive significance of phenology, and have general implications for flowering plants throughout the region and anywhere climate change is having similar impacts.

Consequences of dominance: a review of evenness effects on local and regional ecosystem processes

Abstract: The composition of communities is strongly altered by anthropogenic manipulations of biogeochemical cycles, abiotic conditions, and trophic structure in all major ecosystems. Whereas the effects of species loss on ecosystem processes have received broad attention, the consequences of altered species dominance for emergent properties of communities and ecosystems are poorly investigated. Here we propose a framework guiding our understanding of how dominance affects species interactions within communities, processes within ecosystems, and dynamics on regional scales. Dominance (or the complementary term, evenness) reflects the distribution of traits in a community, which in turn affects the strength and sign of both intraspecifc and interspecific interactions. Consequently, dominance also mediates the effect of such interactions on species coexistence. We review the evidence for the fact that dominance directly affects ecosystem functions such as process rates via species identity (the dominant trait) and evenness (the frequency distribution of traits), and indirectly alters the relationship between process rates and species richness. Dominance also influences the temporal and spatial variability of aggregate community properties and compositional stability (invasibility). Finally, we propose that dominance affects regional species coexistence by altering metacommunity dynamics. Local dominance leads to high beta diversity, and rare species can persist because of source-sink dynamics, but anthropogenically induced environmental changes result in regional dominance and low beta diversity, reducing regional coexistence. Given the rapid anthropogenic alterations of dominance in many ecosystems and the strong implications of these changes, dominance should be considered explicitly in the analysis of consequences of altered biodiversity.

Primary production and rain use efficiency across a precipitation gradient on the Mongolia Plateau.

Abstract: Understanding how the aboveground net primary production (ANPP) of arid and semiarid ecosystems of the world responds to variations in precipitation is crucial for assessing the impacts of climate change on terrestrial ecosystems. Rain-use efficiency (RUE) is an important measure for acquiring this understanding. However, little is known about the response pattern of RUE for the largest contiguous natural grassland region of the world, the Eurasian Steppe. Here we investigated the spatial and temporal patterns of ANPP and RUE and their key driving factors based on a long-term data set from 21 natural arid and semiarid ecosystem sites across the Inner Mongolia steppe region in northern China. Our results showed that, with increasing mean annual precipitation (MAP), (1) ANPP increased while the interannual variability of ANPP declined, (2) plant species richness increased and the relative abundance of key functional groups shifted predictably, and (3) RUE increased in space across different ecosystems but decreased with increasing annual precipitation within a given ecosystem. These results clearly indicate that the patterns of both ANPP and RUE are scale dependent, and the seemingly conflicting patterns of RUE in space vs. time suggest distinctive underlying mechanisms, involving interactions among precipitation, soil N, and biotic factors. Also, while our results supported the existence of a common maximum RUE, they also indicated that its value could be substantially increased by altering resource availability, such as adding nitrogen. Our findings have important implications for understanding and predicting ecological impacts of global climate change and for management practices in arid and semiarid ecosystems in the Inner Mongolia steppe region and beyond.

Are functional traits good predictors of demographic rates? evidence from five neotropical forests

Abstract: A central goal of comparative plant ecology is to understand how functional traits vary among species and to what extent this variation has adaptive value. Here we evaluate relationships between four functional traits (seed volume, specific leaf area, wood density, and adult stature) and two demographic attributes (diameter growth and tree mortality) for large trees of 240 tree species from five Neotropical forests. We evaluate how these key functional traits are related to survival and growth and whether similar relationships between traits and demography hold across different tropical forests. There was a tendency for a trade-off between growth and survival across rain forest tree species. Wood density, seed volume, and adult stature were significant predictors of growth and/or mortality. Both growth and mortality rates declined with an increase in wood density. This is consistent with greater construction costs and greater resistance to stem damage for denser wood. Growth and mortality rates also declined as seed volume increased. This is consistent with an adaptive syndrome in which species tolerant of low resource availability (in this case shade-tolerant species) have large seeds to establish successfully and low inherent growth and mortality rates. Growth increased and mortality decreased with an increase in adult stature, because taller species have a greater access to light and longer life spans. Specific leaf area was, surprisingly, only modestly informative for the performance of large trees and had ambiguous relationships with growth and survival. Single traits accounted for 9-55% of the interspecific variation in growth and mortality rates at individual sites. Significant correlations with demographic rates tended to be similar across forests and for phylogenetically independent contrasts as well as for cross-species analyses that treated each species as an independent observation. In combination, the morphological traits explained 41% of the variation in growth rate and 54% of the variation in mortality rate, with wood density being the best predictor of growth and mortality. Relationships between functional traits and demographic rates were statistically similar across a wide range of Neotropical forests. The consistency of these results strongly suggests that tropical rain forest species face similar trade-offs in different sites and converge on similar sets of solutions.

Continuous-time correlated random walk model for animal telemetry data.

Abstract: We propose a continuous-time version of the correlated random walk model for animal telemetry data. The continuous-time formulation allows data that have been nonuniformly collected over time to be modeled without subsampling, interpolation, or aggregation to obtain a set of locations uniformly spaced in time. The model is derived from a continuous-time Ornstein-Uhlenbeck velocity process that is integrated to form a location process. The continuous-time model was placed into a state-space framework to allow parameter estimation and location predictions from observed animal locations. Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are possible. A harbor seal data set was analyzed with a model that incorporates the proportion of each hour spent on land. Also, a northern fur seal pup data set was analyzed with a random drift component to account for directed travel and ocean currents.

Testing the species traits-environment relationships: the fourth-corner problem revisited.

Abstract: Functional ecology aims at determining the relationships between species traits and environmental variables in order to better understand biological processes in ecosystems. From a methodological point of view, this biological objective calls for a method linking three data matrix tables: a table L with abundance or presence-absence values for species at a series of sites, a table R with variables describing the environmental conditions of the sites, and a table Q containing traits (e.g., morphological or behavioral attributes) of the species. Ten years ago, the fourth-corner method was proposed to measure and test the relationships between species traits and environmental variables using tables R, L, and Q simultaneously. In practice, this method is rarely used. The major reasons for this lack of interest are the restriction of the original method and program to presence-absence data in L and to the analysis of a single trait and a single environmental variable at a time. Moreover, ecologists often have problems in choosing a permutation model among the four originally proposed. In this paper, we revisit the fourth-corner method and propose improvements to the original approach. First, we present an extension to measure the link between species traits and environmental variables when the ecological community is described by abundance data. A new multivariate fourth-corner statistic is also proposed. Then, using numerical simulations, we discuss and evaluate the existing testing procedures. A new two-step testing procedure is presented. We hope that these elements will help ecologists use the best possible methodology to analyze this type of ecological problem.

Novel weapons: invasive plant suppresses fungal mutualists in america but not in its native europe

Abstract: Why some invasive plant species transmogrify from weak competitors at home to strong competitors abroad remains one of the most elusive questions in ecology. Some evidence suggests that disproportionately high densities of some invaders are due to the release of biochemicals that are novel, and therefore harmful, to naive organisms in their new range. So far, such evidence has been restricted to the direct phytotoxic effects of plants on other plants. Here we found that one of North America's most aggressive invaders of undisturbed forest understories, Alliaria petiolata (garlic mustard) and a plant that inhibits mycorrhizal fungal mutualists of North American native plants, has far stronger inhibitory effects on mycorrhizas in invaded North American soils than on mycorrhizas in European soils where A. petiolata is native. This antifungal effect appears to be due to specific flavonoid fractions in A. petiolata extracts. Furthermore, we found that suppression of North American mycorrhizal fungi by A. petiolata corresponds with severe inhibition of North American plant species that rely on these fungi, whereas congeneric European plants are weakly affected. These results indicate that phytochemicals, benign to resistant mycorrhizal symbionts in the home range, may be lethal to naive native mutualists in the introduced range and indirectly suppress the plants that rely on them.

Global warming and flowering times in thoreau's concord: a community perspective

Abstract: As a result of climate change, many plants are now flowering measurably earlier than they did in the past. However, some species' flowering times have changed much more than others. Data at the community level can clarify the variation in flowering responses to climate change. In order to determine how North American species' flowering times respond to climate, we analyzed a series of previously unstudied records of the dates of first flowering for over 500 plant taxa in Concord, Massachusetts, USA. These records began with six years of observations by the famous naturalist Henry David Thoreau from 1852 to 1858, continued with 16 years of observations by the botanist Alfred Hosmer in 1878 and 1888-1902, and concluded with our own observations in 2004, 2005, and 2006. From 1852 through 2006, Concord warmed by 2.4 degrees C due to global climate change and urbanization. Using a subset of 43 common species, we determined that plants are now flowering seven days earlier on average than they did in Thoreau's times. Plant flowering times were most correlated with mean temperatures in the one or two months just before flowering and were also correlated with January temperatures. Summer-flowering species showed more interannual variation in flowering time than did spring-flowering species, but the flowering times of spring-flowering species correlated more strongly to mean monthly temperatures. In many cases, such as within the genera Betula and Solidago, closely related, co-occurring species responded to climate very differently from one another. The differences in flowering responses to warming could affect relationships in plant communities as warming continues. Common St. John's wort (Hypericum perforatum) and highbush blueberry (Vaccinium corymbosum) are particularly responsive to changes in climate, are common across much of the United States, and could serve as indicators of biological responses to climate change. We discuss the need for researchers to be aware, when using data sets involving multiple observers, of how varying methodologies, sample sizes, and sampling intensities affect the results. Finally, we emphasize the importance of using historical observations, like those of Thoreau and Hosmer, as sources of long-term data and to increase public awareness of biological responses to climate change.

Evaluating signatures of glacial refugia for north atlantic benthic marine taxa

Abstract: A goal of phylogeography is to relate patterns of genetic differentiation to potential historical geographic isolating events. Quaternary glaciations, particularly the one culminating in the Last Glacial Maximum ;21 ka (thousands of years ago), greatly affected the distributions and population sizes of temperate marine species as their ranges retreated southward to escape ice sheets. Traditional genetic models of glacial refugia and routes of recolonization include these predictions: low genetic diversity in formerly glaciated areas, with a small number of alleles/haplotypes dominating disproportionately large areas, and high diversity including ''private'' alleles in glacial refugia. In the Northern Hemisphere, low diversity in the north and high diversity in the south are expected. This simple model does not account for the possibility of populations surviving in relatively small northern periglacial refugia. If these periglacial populations experienced extreme bottlenecks, they could have the low genetic diversity expected in recolonized areas with no refugia, but should have more endemic diversity (private alleles) than recently recolonized areas. This review examines evidence of putative glacial refugia for eight benthic marine taxa in the temperate North Atlantic. All data sets were reanalyzed to allow direct comparisons between geographic patterns of genetic diversity and distribution of particular clades and haplotypes including private alleles. We contend that for marine organisms the genetic signatures of northern periglacial and southern refugia can be distinguished from one another. There is evidence for several periglacial refugia in northern latitudes, giving credence to recent climatic reconstructions with less extensive glaciation.

What can we learn from resource pulses

Abstract: An increasing number of studies in a wide range of natural systems have investigated how pulses of resource availability influence ecological processes at individual, population, and community levels. Taken together, these studies suggest that some common processes may underlie pulsed resource dynamics in a wide diversity of systems. Developing a common framework of terms and concepts for the study of resource pulses may facilitate greater synthesis among these apparently disparate systems. Here, we propose a general definition of the resource pulse concept, outline some common patterns in the causes and consequences of resource pulses, and suggest a few key questions for future investigations. We define resource pulses as episodes of increased resource availability in space and time that combine low frequency (rarity), large magnitude (intensity), and short duration (brevity), and emphasize the importance of considering resource pulses at spatial and temporal scales relevant to specific resource-consumer interactions. Although resource pulses are uncommon events for consumers in specific systems, our review of the existing literature suggests that pulsed resource dynamics are actually widespread phenomena in nature. Resource pulses often result from climatic and environmental factors, processes of spatiotemporal accumulation and release, outbreak population dynamics, or a combination of these factors. These events can affect life history traits and behavior at the level of individual consumers, numerical responses at the population level, and indirect effects at the community level. Consumers show strategies for utilizing ephemeral resources opportunistically, reducing resource variability by averaging over larger spatial scales, and tolerating extended interpulse periods of reduced resource availability. Resource pulses can also create persistent effects in communities through several mechanisms. We suggest that the study of resource pulses provides opportunities to understand the dynamics of many specific systems, and may also contribute to broader ecological questions at individual, population, and community levels.

Multiple functions increase the importance of biodiversity for overall ecosystem functioning

Abstract: Biodiversity is proposed to be important for the rate of ecosystem functions. Most biodiversity-ecosystem function studies, however, consider only one response variable at a time, and even when multiple variables are examined they are analyzed separately. This means that a very important aspect of biodiversity is overlooked: the possibility for different species to carry out different functions at any one time. We propose a conceptual model to explore the effects of species loss on overall ecosystem functioning, where overall functioning is defined as the joint effect of many ecosystem functions. We show that, due to multifunctional complementarity among species, overall functioning is more susceptible to species loss than are single functions. Modeled relationships between species richness and overall ecosystem functioning using five empirical data sets on monocultures reflected the range of effects of species loss on multiple functions predicted by the model. Furthermore, an exploration of the correlations across functions and the degree of redundancy within functions revealed that multifunctional redundancy was generally lower than single-function redundancy in these empirical data sets. We suggest that by shifting the focus to the variety of functions maintained by a diversity of species, the full importance of biodiversity for the functioning of ecosystems can be uncovered. Our results are thus important for conservation and management of biota and ecosystem services.

Temporal dynamics in a pollination network.

Abstract: Despite a strong current interest in ecological networks, the bulk of studies are static descriptions of the structure of networks, and very few analyze their temporal dynamics. Yet, understanding network dynamics is important in order to relate network patterns to ecological processes. We studied the day-to-day dynamics of an arctic pollination interaction network over two consecutive seasons. First, we found that new species entering the network tend to interact with already well-connected species, although there are deviations from this trend due, for example, to morphological mismatching between plant and pollinator traits and nonoverlapping phenophases of plant and pollinator species. Thus, temporal dynamics provides a mechanistic explanation for previously reported network patterns such as the heterogeneous distribution of number of interactions across species. Second, we looked for the ecological properties most likely to be mediating this dynamical process and found that both abundance and phenophase length were important determinants of the number of links per species.

Revisiting the classics: considering nonconsumptive effects in textbook examples of predator–prey interactions

Abstract: Predator effects on prey dynamics are conventionally studied by measuring changes in prey abundance attributed to consumption by predators. We revisit four classic examples of predator-prey systems often cited in textbooks and incorporate subsequent studies of nonconsumptive effects of predators (NCE), defined as changes in prey traits (e.g., behavior, growth, development) measured on an ecological time scale. Our review revealed that NCE were integral to explaining lynx-hare population dynamics in boreal forests, cascading effects of top predators in Wisconsin lakes, and cascading effects of killer whales and sea otters on kelp forests in nearshore marine habitats. The relative roles of consumption and NCE of wolves on moose and consequent indirect effects on plant communities of Isle Royale depended on climate oscillations. Nonconsumptive effects have not been explicitly tested to explain the link between planktonic alewives and the size structure of the zooplankton, nor have they been invoked to attribute keystone predator status in intertidal communities or elsewhere. We argue that both consumption and intimidation contribute to the total effects of keystone predators, and that characteristics of keystone consumers may differ from those of predators having predominantly NCE. Nonconsumptive effects are often considered as an afterthought to explain observations inconsistent with consumption-based theory. Consequently, NCE with the same sign as consumptive effects may be overlooked, even though they can affect the magnitude, rate, or scale of a prey response to predation and can have important management or conservation implications. Nonconsumptive effects may underlie other classic paradigms in ecology, such as delayed density dependence and predator-mediated prey coexistence. Revisiting classic studies enriches our understanding of predator-prey dynamics and provides compelling rationale for ramping up efforts to consider how NCE affect traditional predator-prey models based on consumption, and to compare the relative magnitude of consumptive and NCE of predators.

Longevity can buffer plant and animal populations against changing climatic variability

Abstract: Both means and year-to-year variances of climate variables such as temperature and precipitation are predicted to change. However, the potential impact of changing climatic variability on the fate of populations has been largely unexamined. We analyzed multiyear demographic data for 36 plant and animal species with a broad range of life histories and types of environment to ask how sensitive their long-term stochastic population growth rates are likely to be to changes in the means and standard deviations of vital rates (survival, reproduction, growth) in response to changing climate. We quantified responsiveness using elasticities of the long-term population growth rate predicted by stochastic projection matrix models. Short-lived species (insects and annual plants and algae) are predicted to be more strongly (and negatively) affected by increasing vital rate variability relative to longer-lived species (perennial plants, birds, ungulates). Taxonomic affiliation has little power to explain sensitivity to increasing variability once longevity has been taken into account. Our results highlight the potential vulnerability of short-lived species to an increasingly variable climate, but also suggest that problems associated with short-lived undesirable species (agricultural pests, disease vectors, invasive weedy plants) may be exacerbated in regions where climate variability decreases.

Tree recruitment in an empty forest.

Abstract: To assess how the decimation of large vertebrates by hunting alters recruitment processes in a tropical forest, we compared the sapling cohorts of two structurally and compositionally similar forests in the Rio Manu floodplain in southeastern Peru. Large vertebrates were severely depleted at one site, Boca Manu (BM), whereas the other, Cocha Cashu Biological Station (CC), supported an intact fauna. At both sites we sampled small (� 1 m tall, ,1 cm dbh) and large (� 1 cm and ,10 cm dbh) saplings in the central portion of 4-ha plots within which all trees � 10 cm dbh were mapped and identified. This design ensured that all conspecific adults within at least 50 m (BM) or 55 m (CC) of any sapling would have known locations. We used the Janzen-Connell model to make five predictions about the sapling cohorts at BM with respect to CC: (1) reduced overall sapling recruitment, (2) increased recruitment of species dispersed by abiotic means, (3) altered relative abundances of species, (4) prominence of large-seeded species among those showing depressed recruitment, and (5) little or no tendency for saplings to cluster closer to adults at BM. Our results affirmed each of these predictions. Interpreted at face value, the evidence suggests that few species are demographically stable at BM and that up to 28% are increasing and 72% decreasing. Loss of dispersal function allows species dispersed abiotically and by small birds and mammals to substitute for those dispersed by large birds and mammals. Although we regard these conclusions as preliminary, over the long run, the observed type of directional change in tree composition is likely to result in biodiversity loss and negative feedbacks on both the animal and plant communities. Our results suggest that the best, and perhaps only, way to prevent compositional change and probable loss of diversity in tropical tree communities is to prohibit hunting.

Janzen‐connell effects are widespread and strong enough to maintain diversity in grasslands

Abstract: Crop rotation schemes are believed to work by preventing specialist soil-borne pests from depressing the future yields of similar crops. In ecology, such negative plant-soil feedbacks may be viewed as a type of Janzen-Connell effect, which promotes species coexistence and diversity by preventing the same species from repeatedly occupying a particular site. In a controlled greenhouse experiment with 24 plant species and using soils from established field monocultures, we reveal community-wide soil-based Janzen-Connell effects between the three major functional groups of plants in temperate European grasslands. The effects are much stronger and more prevalent if plants are grown in interspecific competition. Using several soil treatments (gamma irradiation, activated carbon, fungicide, fertilizer) we show that the mechanism of the negative feedback is the buildup of soil pathogens which reduce the competitive ability of nearly all species when grown on soils they have formerly occupied. We further show that the magnitude of the change in competitive outcome is sufficient to stabilize observed fitness differences between functional groups in reasonably large communities. The generality and strength of this negative feedback suggests that Janzen-Connell effects have been underestimated as drivers of plant diversity in temperate ecosystems.

Climate change can cause spatial mismatch of trophically interacting species

Abstract: Climate change is one of the most influential drivers of biodiversity. Species-specific differences in the reaction to climate change can become particularly important when interacting species are considered. Current studies have evidenced temporal mismatching of interacting species at single points in space, and recently two investigations showed that species interactions are relevant for their future ranges. However, so far we are not aware that the ranges of interacting species may become substantially spatially mismatched. We developed separate ecological-niche models for a monophagous butterfly (Boloria titania) and its larval host plant (Polygonum bistorta) based on monthly interpolated climate data, land-cover classes, and soil data at a 10'-grid resolution. We show that all of three chosen global-change scenarios, which cover a broad range of potential developments in demography, socio-economics, and technology during the 21st century from moderate to intermediate to maximum change, will result in a pronounced spatial mismatch between future niche spaces of these species. The butterfly may expand considerably its future range (by 124-258%) if the host plant has unlimited dispersal, but it could lose 52-75% of its current range if the host plant is not able to fill its projected ecological niche space, and 79-88% if the butterfly also is assumed to be highly dispersal limited. These findings strongly suggest that climate change has the potential to disrupt trophic interactions because co-occurring species do not necessarily react in a similar manner to global change, having important consequences at ecological and evolutionary time scales.

What do interaction network metrics tell us about specialization and biological traits

Abstract: The structure of ecological interaction networks is often interpreted as a product of meaningful ecological and evolutionary mechanisms that shape the degree of specialization in community associations. However, here we show that both unweighted network metrics (connectance, nestedness, and degree distribution) and weighted network metrics (interaction evenness, interaction strength asymmetry) are strongly constrained and biased by the number of observations. Rarely observed species are inevitably regarded as "specialists," irrespective of their actual associations, leading to biased estimates of specialization. Consequently, a skewed distribution of species observation records (such as the lognormal), combined with a relatively low sampling density typical for ecological data, already generates a "nested" and poorly "connected" network with "asymmetric interaction strengths" when interactions are neutral. This is confirmed by null model simulations of bipartite networks, assuming that partners associate randomly in the absence of any specialization and any variation in the correspondence of biological traits between associated species (trait matching). Variation in the skewness of the frequency distribution fundamentally changes the outcome of network metrics. Therefore, interpretation of network metrics in terms of fundamental specialization and trait matching requires an appropriate control for such severe constraints imposed by information deficits. When using an alternative approach that controls for these effects, most natural networks of mutualistic or antagonistic systems show a significantly higher degree of reciprocal specialization (exclusiveness) than expected under neutral conditions. A higher exclusiveness is coherent with a tighter coevolution and suggests a lower ecological redundancy than implied by nested networks.

On estimating the exponent of power-law frequency distributions

Abstract: Power-law frequency distributions characterize a wide array of natural phenomena. In ecology, biology, and many physical and social sciences, the exponents of these power laws are estimated to draw inference about the processes underlying the phenomenon, to test theoretical models, and to scale up from local observations to global patterns. Therefore, it is essential that these exponents be estimated accurately. Unfortunately, the binning-based methods traditionally used in ecology and other disciplines perform quite poorly. Here we discuss more sophisticated methods for fitting these exponents based on cumulative distribution functions and maximum likelihood estimation. We illustrate their superior performance at estimating known exponents and provide details on how and when ecologists should use them. Our results confirm that maximum likelihood estimation outperforms other methods in both accuracy and precision. Because of the use of biased statistical methods for estimating the exponent, the conclusions of several recently published papers should be revisited.

Separating habitat invasibility by alien plants from the actual level of invasion

Abstract: Habitats vary considerably in the level of invasion (number or proportion of alien plant species they contain), which depends on local habitat properties, propagule pressure, and climate. To determine the invasibility (susceptibility to invasions) of different habitats, it is necessary to factor out the effects of any confounding variables such as propagule pressure and climate on the level of invasion. We used 20 468 vegetation plots from 32 habitats in the Czech Republic to compare the invasibility of different habitats. Using regression trees, the proportion of alien plants, including archaeophytes (prehistoric to medieval invaders) and neophytes (recent invaders), was related to variables representing habitat properties, propagule pressure, and climate. The propagule pressure was expressed as the proportion of surrounding urban and industrial or agricultural land, human population density, distance from a river, and history of human colonization in the region. Urban and industrial land use had a positive effect on the proportion of both archaeophytes and neophytes. Agricultural land use, higher population density, and longer history of human impact positively affected the proportion of archaeophytes. Disturbed human-made habitats with herbaceous vegetation were most invaded by both groups of aliens. Neophytes were also relatively common in disturbed woody vegetation, such as broad-leaved plantations, forest clearings, and riverine scrub. These habitats also had the highest proportion of aliens after removing the effect of propagule pressure and climate, indicating that they are not only the most invaded, but also most invasible. These habitats experience recurrent disturbances and are rich, at least temporarily, in available nutrients, which supports the hypothesis that fluctuating resources are the major cause of habitat invasibility. The least invaded habitats were mires and alpine-subalpine grasslands and scrub. After removing the effect of propagule pressure and climate, some habitats actually invaded at an intermediate level had very low proportions of aliens. This indicates that these habitats (e.g., dry, wet, and saline grasslands, base-rich fens, and broad-leaved deciduous woodlands) are resistant to invasion.

Landscape constraints on functional diversity of birds and insects in tropical agroecosystems.

Abstract: In this paper, we analyze databases [corrected] on birds and insects to assess patterns of functional diversity in human-dominated landscapes in the tropics. A perspective from developed landscapes is essential for understanding remnant natural ecosystems, because most species experience their surroundings at spatial scales beyond the plot level, and spillover between natural and managed ecosystems is common. Agricultural bird species have greater habitat and diet breadth than forest species. Based on a global data base, bird assemblages in tropical agroforest ecosystems were composed of disproportionately more frugivorous and nectarivorous, but fewer insectivorous bird species compared with forest. Similarly, insect predators of plant-feeding arthropods were more diverse in Ecuadorian agroforest and forest compared with rice and pasture, while, in Indonesia, bee diversity was also higher in forested habitats. Hence, diversity of insectivorous birds and insect predators as well as bee pollinators declined with agricultural transformation. In contrast, with increasing agricultural intensification, avian pollinators and seed dispersers initially increase then decrease in proportion. It is well established that the proximity of agricultural habitats to forests has a strong influence on the functional diversity of agroecosystems. Community similarity is higher among agricultural systems than in natural habitats and higher in simple than in complex landscapes for both birds and insects, so natural communities, low-intensity agriculture, and heterogeneous landscapes appear to be critical in the preservation of beta diversity. We require a better understanding of the relative role of landscape composition and the spatial configuration of landscape elements in affecting spillover of functionally important species across managed and natural habitats. This is important for data-based management of tropical human-dominated landscapes sustaining the capacity of communities to reorganize after disturbance and to ensure ecological functioning.

A hierarchical model for spatial capture–recapture data

Abstract: Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture–recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.

Arthropod assemblages are best predicted by plant species composition

Abstract: Insects and spiders comprise more than two-thirds of the Earth's total species diversity. There is wide concern, however, that the global diversity of arthropods may be declining even more rapidly than the diversity of vertebrates and plants. For adequate conservation planning, ecologists need to understand the driving factors for arthropod communities and devise methods that provide reliable predictions when resources do not permit exhaustive ground surveys. Which factor most successfully predicts arthropod community structure is still a matter of debate, however. The purpose of this study was to identify the factor best predicting arthropod assemblage composition. We investigated the species composition of seven functionally different arthropod groups (epigeic spiders, grasshoppers, ground beetles, weevils, hoppers, hoverflies, and bees) at 47 sites in The Netherlands comprising a range of seminatural grassland types and one heathland type. We then compared the actual arthropod composition with predictions based on plant species composition, vegetation structure, environmental data, flower richness, and landscape composition. For this we used the recently published method of predictive co-correspondence analysis, and a predictive variant of canonical correspondence analysis, depending on the type of predictor data. Our results demonstrate that local plant species composition is the most effective predictor of arthropod assemblage composition, for all investigated groups. In predicting arthropod assemblages, plant community composition consistently outperforms both vegetation structure and environmental conditions (even when the two are combined), and also performs better than the surrounding landscape. These results run against a common expectation of vegetation structure as the decisive factor. Such expectations, however, have always been biased by the fact that until recently no methods existed that could use an entire (plant) species composition in the explanatory role. Although more recent experimental diversity work has reawakened interest in the role of plant species, these studies still have not used (or have not been able to use) entire species compositions. They only consider diversity measures, both for plant and insect assemblages, which may obscure relationships. The present study demonstrates that the species compositions of insect and plant communities are clearly linked.

Global potential net primary production predicted from vegetation class, precipitation, and temperature

Abstract: Net primary production (NPP), the difference between CO2 fixed by photosynthesis and CO2 lost to autotrophic respiration, is one of the most important components of the carbon cycle. Our goal was to develop a simple regression model to estimate global NPP using climate and land cover data. Approximately 5600 global data points with observed mean annual NPP, land cover class, precipitation, and temperature were compiled. Precipitation was better correlated with NPP than temperature, and it explained much more of the variability in mean annual NPP for grass- or shrub-dominated systems (r 2 ¼ 0.68) than for tree-dominated systems (r 2 ¼ 0.39). For a given precipitation level, tree- dominated systems had significantly higher NPP (;100-150 g Cm � 2 � yr � 1 ) than non-tree- dominated systems. Consequently, previous empirical models developed to predict NPP based on precipitation and temperature (e.g., the Miami model) tended to overestimate NPP for non-tree-dominated systems. Our new model developed at the National Center for Ecological Analysis and Synthesis (the NCEAS model) predicts NPP for tree-dominated systems based on precipitation and temperature; but for non-tree-dominated systems NPP is solely a function of precipitation because including a temperature function increased model error for these systems. Lower NPP in non-tree-dominated systems is likely related to decreased water and nutrient use efficiency and higher nutrient loss rates from more frequent fire disturbances. Late 20th century aboveground and total NPP for global potential native vegetation using the NCEAS model are estimated to be ;28 Pg and ;46 Pg C/yr, respectively. The NCEAS model estimated an ;13% increase in global total NPP for potential vegetation from 1901 to 2000 based on changing precipitation and temperature patterns.

Plant-soil microorganism interactions: heritable relationship between plant genotype and associated soil microorganisms.

Abstract: Although soil microbial communities are known to play crucial roles in the cycling of nutrients in forest ecosystems and can vary by plant species, how microorganisms respond to the subtle gradients of plant genetic variation is just beginning to be appreciated. Using a model Populus system in a common garden with replicated clones of known genotypes, we evaluated microbial biomass and community composition as quantitative traits. Two main patterns emerged. (1) Plant genotype influenced microbial biomass nitrogen in soils under replicated genotypes of Populus angustifolia ,F 1, and backcross hybrids, but not P. fremontii. Genotype explained up to 78% of the variation in microbial biomass as indicated by broad-sense heritability estimates (i.e., clonal repeatability). A second estimate of microbial biomass (total phospholipid fatty acid) was more conservative and showed significant genotype effects in P. angustifolia and backcross hybrids. (2) Plant genotype significantly influenced microbial community composition, explaining up to 70% of the variation in community composition within P. angustifolia genotypes alone. These findings suggest that variation in above- and belowground traits of individual plant genotypes can alter soil microbial dynamics, and suggests that further investigations of the evolutionary implications of genetic feedbacks are warranted.

Animal movements in heterogeneous landscapes: identifying profitable places and homogeneous movement bouts.

Abstract: Because of the heterogeneity of natural landscapes, animals have to move through various types of areas that are more or less suitable with respect to their current needs. The locations of the profitable places actually used, which may be only a subset of the whole set of suitable areas available, are usually unknown, but can be inferred from movement analysis by assuming that these places correspond to the limited areas where the animals spend more time than elsewhere. Identifying these intensively used areas makes it possible, through subsequent analyses, to address both how they are distributed with respect to key habitat features, and the underlying behavioral mechanisms used to find these areas and capitalize on such habitats. We critically reviewed the few previously published methods to detect changes in movement behavior likely to occur when an animal enters a profitable place. As all of them appeared to be too narrowly tuned to specific situations, we designed a new, easy-to-use method based on the time spent in the vicinity of successive path locations. We used computer simulations to show that our method is both quite general and robust to noisy data.