Showing papers in "Ecological Monographs in 2018"

Nutrient limitation of soil microbial processes in tropical forests

Abstract: Soil fungi and bacteria are the key players in the transformation and processing of carbon and nutrients in terrestrial ecosystems, yet controls on their abundance and activity are not well understood. Based on stoichiometric principles, soil microbial processes are expected to be limited by mineral nutrients, which are particularly scarce in often highly weathered tropical forest soils. Such limitation is directly relevant for the fate of soil carbon and global element cycles, but its extent and nature have never been assessed systematically across the tropical biome. Here, we address the relative importance of nitrogen, phosphorus and other nutrients in limiting soil microbial biomass and process rates in tropical forests. We conducted an in-depth literature review and a meta-analysis of the available nutrient addition experiments in tropical forests worldwide. Our synthesis showed predominant and general phosphorus limitation of a variety of microbial processes across tropical forests, and additional nitrogen limitation in tropical montane forests. The apparent widespread microbial phosphorus limitation needs to be accounted for in the understanding and prediction of biogeochemical cycles in tropical forests and their future functioning. Other mineral nutrients or carbon may modify the importance of phosphorus, but more experimental studies are urgently needed. This article is protected by copyright. All rights reserved.

Chesson's coexistence theory

Abstract: We give a comprehensive review of Chesson's coexistence theory, summarizing, for the first time, all its fundamental details in one single document. Our goal is for both theoretical and empirical ecologists to be able to use the theory to interpret their findings, and to get a precise sense of the limits of its applicability. To this end, we introduce an explicit handling of limiting factors, and a new way of defining the scaling factors that partition invasion growth rates into the different mechanisms contributing to coexistence. We explain terminology such as relative nonlinearity, storage effect, and growth‐density covariance, both in a formal setting and through their biological interpretation. We review the theory's applications and contributions to our current understanding of species coexistence. While the theory is very general, it is not well suited to all problems, so we carefully point out its limitations. Finally, we critique the paradigm of decomposing invasion growth rates into stabilizing and equalizing components: we argue that these concepts are useful when used judiciously, but have often been employed in an overly simplified way to justify false claims.

Model averaging in ecology: a review of Bayesian, information-theoretic, and tactical approaches for predictive inference

Abstract: In ecology, the true causal structure for a given problem is often not known, and several plausible models and thus model predictions exist. It has been claimed that using weighted averages of these models can reduce prediction error, as well as better reflect model selection uncertainty. These claims, however, are often demonstrated by isolated examples. Analysts must better understand under which conditions model averaging can improve predictions and their uncertainty estimates. Moreover, a large range of different model averaging methods exists, raising the question of how they differ in their behaviour and performance. Here, we review the mathematical foundations of model averaging along with the diversity of approaches available. We explain that the error in model‐averaged predictions depends on each model's predictive bias and variance, as well as the covariance in predictions between models, and uncertainty about model weights. We show that model averaging is particularly useful if the predictive error of contributing model predictions is dominated by variance, and if the covariance between models is low. For noisy data, which predominate in ecology, these conditions will often be met. Many different methods to derive averaging weights exist, from Bayesian over information‐theoretical to cross‐validation optimized and resampling approaches. A general recommendation is difficult, because the performance of methods is often context dependent. Importantly, estimating weights creates some additional uncertainty. As a result, estimated model weights may not always outperform arbitrary fixed weights, such as equal weights for all models. When averaging a set of models with many inadequate models, however, estimating model weights will typically be superior to equal weights. We also investigate the quality of the confidence intervals calculated for model‐averaged predictions, showing that they differ greatly in behaviour and seldom manage to achieve nominal coverage. Our overall recommendations stress the importance of non‐parametric methods such as cross‐validation for a reliable uncertainty quantification of model‐averaged predictions.

A guide to Bayesian model checking for ecologists

Abstract: Checking that models adequately represent data is an essential component of applied statistical inference. Ecologists increasingly use hierarchical Bayesian statistical models in their research. The appeal of this modeling paradigm is undeniable, as researchers can build and fit models that embody complex ecological processes while simultaneously controlling observation error. However, ecologists tend to be less focused on checking model assumptions and assessing potential lack-of-fit when applying Bayesian methods than when applying more traditional modes of inference such as maximum likelihood. There are also multiple ways of assessing the fit of Bayesian models, each of which has strengths and weaknesses. For instance, Bayesian p-values are relatively easy to compute, but are well known to be conservative, producing p-values biased toward 0.5. Alternatively, lesser known approaches to model checking, such as prior predictive checks, cross-validation probability integral transforms, and pivot discrepancy measures may produce more accurate characterizations of goodness-of-fit but are not as well known to ecologists. In addition, a suite of visual and targeted diagnostics can be used to examine violations of different model assumptions and lack-of-fit at different levels of the modeling hierarchy, and to check for residual temporal or spatial autocorrelation. In this review, we synthesize existing literature to guide ecologists through the many available options for Bayesian model checking. We illustrate methods and procedures with several ecological case studies, including i) analysis of simulated spatio-temporal count data, (ii) N-mixture models for estimating abundance and detection probability of sea otters from an aircraft, and (iii) hidden Markov modeling to describe attendance patterns of California sea lion mothers on a rookery. We find that commonly used procedures based on posterior predictive p-values detect extreme model inadequacy, but often do not detect more subtle cases of lack of fit. Tests based on cross-validation and pivot discrepancy measures (including the ``sampled predictive p-value'') appear to be better suited to model checking and to have better overall statistical performance. We conclude that model checking is an essential component of scientific discovery and learning that should accompany most Bayesian analyses presented in the literature.

Diel Predator Activity Drives a Dynamic Landscape of Fear

Abstract: A "landscape of fear" (LOF) is a map that describes continuous spatial variation in an animal9s perception of predation risk. The relief on this map reflects, for example, places that an animal avoids to minimize risk. Although the LOF concept is a potential unifying theme in ecology that is often invoked to explain the ecological and conservation significance of fear, quantified examples of a LOF over large spatial scales are lacking as is knowledge about the daily dynamics of a LOF. Despite theory and data to the contrary, investigators often assume, implicitly or explicitly, that a LOF is a static consequence of a predator9s mere presence. We tested the prediction that a LOF in a large-scale, free-living system is a highly-dynamic map with "peaks" and "valleys" that alternate across the diel (24-hour) cycle in response to daily lulls in predator activity. We did so with extensive data from the case study of Yellowstone elk (Cervus elaphus) and wolves (Canis lupus) that was the original basis for the LOF concept. We quantified the elk LOF, defined here as spatial allocation of time away from risky places and times, across nearly 1000-km2 of northern Yellowstone National Park and found that it fluctuated with the crepuscular activity pattern of wolves, enabling elk to use risky places during wolf downtimes. This may help explain evidence that wolf predation risk has no effect on elk stress levels, body condition, pregnancy, or herbivory. The ability of free-living animals to adaptively allocate habitat use across periods of high and low predator activity within the diel cycle is an underappreciated aspect of animal behavior that helps explain why strong antipredator responses may trigger weak ecological effects, and why a LOF may have less conceptual and practical importance than direct killing.

Spatial autoregressive models for statistical inference from ecological data

Abstract: Ecological data often exhibit spatial pattern, which can be modeled as autocorrelation. Conditional autoregressive (CAR) and simultaneous autoregressive (SAR) models are network-based models (also known as graphical models) specifically designed to model spatially autocorrelated data based on neighborhood relationships. We identify and discuss six different types of practical ecological inference using CAR and SAR models, including: (1) model selection, (2) spatial regression, (3) estimation of autocorrelation, (4) estimation of other connectivity parameters, (5) spatial prediction, and (6) spatial smoothing. We compare CAR and SAR models, showing their development and connection to partial correlations. Special cases, such as the intrinsic autoregressive model (IAR), are described. Conditional autoregressive and SAR models depend on weight matrices, whose practical development uses neighborhood definition and row-standardization. Weight matrices can also include ecological covariates and connectivity structures, which we emphasize, but have been rarely used. Trends in harbor seals (Phoca vitulina) in southeastern Alaska from 463 polygons, some with missing data, are used to illustrate the six inference types. We develop a variety of weight matrices and CAR and SAR spatial regression models are fit using maximum likelihood and Bayesian methods. Profile likelihood graphs illustrate inference for covariance parameters. The same data set is used for both prediction and smoothing, and the relative merits of each are discussed. We show the nonstationary variances and correlations of a CAR model and demonstrate the effect of row-standardization. We include several take-home messages for CAR and SAR models, including (1) choosing between CAR and IAR models, (2) modeling ecological effects in the covariance matrix, (3) the appeal of spatial smoothing, and (4) how to handle isolated neighbors. We highlight several reasons why ecologists will want to make use of autoregressive models, both directly and in hierarchical models, and not only in explicit spatial settings, but also for more general connectivity models.

The unrealized potential of herbaria for global change biology

Abstract: Plant and fungal specimens in herbaria are becoming primary resources for investigating how plant phenology and geographic distributions shift with climate change, greatly expanding inferences across spatial, temporal, and phylogenetic dimensions. However, these specimens contain a wealth of additional data-including nutrients, defensive compounds, herbivore damage, disease lesions, and signatures of physiological processes-that capture ecological and evolutionary responses to the Anthropocene but which are less frequently utilized. Here, we outline the diversity of herbarium data, global change topics to which they have been applied, and new hypotheses they could inform. We find that herbarium data have been used extensively to study impacts of climate change and invasive species, but that such data are less commonly used to address other drivers of biodiversity loss, including habitat conversion, pollution, and overexploitation. In addition, we note that fungal specimens are under-explored relative to vascular plants. To facilitate broader application of plant and fungal specimens in global change research, we outline the limitations of these data and modern sampling and statistical tools that may be applied to surmount challenges they present. Using a case study of insect herbivory, we illustrate how novel herbarium data may be employed to test hypotheses for which few data exist, despite potentially large biases. With the goal of positioning herbaria as hubs for global change research, we suggest future research directions and curation priorities.

Biodiverse cities: the nursery industry, homeowners, and neighborhood differences drive urban tree composition

Abstract: In arid and semiarid regions, where few if any trees are native, city trees are largely human planted. Societal factors such as resident preferences for tree traits, nursery offerings, and neighborhood characteristics are potentially key drivers of urban tree community composition and diversity, however, they remain critically understudied. We investigated patterns of urban tree structure in residential neighborhoods of the Salt Lake Valley, Utah, combining biological variables, such as neighborhood and plant nursery tree species and trait composition, and sociological data comprised of resident surveys and U.S. Census data. We sampled nine neighborhoods that varied in household income and age of homes. We found more tree species were offered in locally owned nurseries compared with mass merchandiser stores and yard trees at private residences were more diverse than public street trees in the same neighborhoods. There were significant differences among neighborhoods in street and yard tree composition. Newer neighborhoods differed from older neighborhoods in street tree species composition and trait diversity, while neighborhoods varying in affluence differed in yard tree composition. Species richness of yard trees was positively correlated with neighborhood household income, while species richness of street trees was negatively correlated with home age of neighborhood residences. Tree traits differed across neighborhoods of varying ages, suggesting different tree availability and preferences over time. Last, there was a positive correlation between resident preferences for tree attributes and the number of trees that had those attributes both in residential yards and in nursery offerings. Strong relationships between social variables and urban tree composition provides evidence that resident preferences and nursery offerings affect patterns of biodiversity in cities across Salt Lake Valley. These findings can be applied toward efforts to increase taxonomic and functional diversity of city trees in semiarid regions in ways that will also provide ecosystem services of most interest to residents.

Fire-induced deforestation in drought-prone Mediterranean forests: drivers and unknowns from leaves to communities

Abstract: Over the past 15 years, 3 million hectares of forests have been converted into shrublands or grasslands in the Mediterranean countries of the European Union. Fire and drought are the main drivers underlying this deforestation. Here we present a conceptual framework for the process of fire‐induced deforestation based on the interactive effects of fire and drought across three hierarchical scales: resistance in individuals, resilience in populations, and transitions to a new state. At the individual plant level, we review the traits that confer structural and physiological resistance, as well as allow for resprouting capacity: deforestation can be initiated when established individuals succumb to fire. After individuals perish, the second step toward deforestation requires a limited resilience from the population, that is, a reduced ability of that species to regenerate after fire. If individuals die after fire and the population fails to recover, then a transition to a new state will occur. We document trade‐offs between drought survival and fire survival, as embolism resistance is negatively correlated with fire tolerance in conifers and leaf shedding or drought deciduousness, a process that decreases water consumption at the peak of the dry season, temporally increases crown flammability. Propagule availability and establishment control resilience after mortality, but different hypotheses make contrasting predictions on the drivers of post‐fire establishment. Mycorrhizae play an additional role in modulating the response by favoring recovery through amelioration of the nutritional and water status of resprouts and new germinants. So far, resprouter species such as oaks have provided a buffer against deforestation in forests dominated by obligate seeder trees, when present in high enough density in the understory. While diversifying stands with resprouters is often reported as advantageous for building resilience, important knowledge gaps exist on how floristic composition interacts with stand flammability and on the “resprouter exhaustion syndrome,” a condition where pre‐fire drought stress, or short fire return intervals, seriously restrict post‐fire resprouting. Additional attention should be paid to the onset of novel fire environments in previously fire‐free environments, such as high altitude forests, and management actions need to accommodate this complexity to sustain Mediterranean forests under a changing climate.

Litter chemistry influences decomposition through activity of specific microbial functional guilds

Abstract: Niche differentiation among species is a key mechanism by which biodiversity may be linked to ecosystem function. We tested a set of widely invoked hypotheses about the extent of niche differentiation in one of the most diverse communities on Earth, decomposer microorganisms, by measuring their response to changes in three abundant litter resources: lignin, cellulose, and nitrogen (N). To do this, we used the model system Arabidopsis thaliana to manipulate lignin, cellulose, and N availability and then used high‐throughput sequencing to measure the response of microbial communities during decay. Resequencing the decomposer communities after incubation of decomposed litter with pure substrates showed that groups of species had unique substrate use profiles, such that species organized into functional “guilds” of decomposers that were associated with individual litter chemicals. Low concentrations of lignin, cellulose, or N in the litter caused unique shifts in decomposer community composition after 1 yr of decay. Low cellulose plants had low levels of fungi in all decomposer guilds, low lignin plants had high levels of fungi in all decomposer guilds, and low N plants had low levels of fungi in decomposer guilds associated with sucrose and lignin. The relative abundance of decomposer guilds correlated with the total loss of individual litter chemicals during litter decay in the field. In addition, N fertilization shifted decomposer communities during both the early and later stages of decay to those dominated by decomposers in the cellulose guild. Our results contrast the assumption that major carbon (C) and N degradation mechanisms are uniform across whole decomposer communities and instead suggest that decomposition arises from complementarity among groups of metabolically distinct taxa.

Field tests of a general ectotherm niche model show how water can limit lizard activity and distribution

Abstract: Mechanistic forecasts of how species will respond to climate change are highly desired but difficult to achieve. Because processes at different scales are explicit in such models, careful assessments of their predictive abilities can provide valuable insights that will be relevant to functionally similar species. However, there are surprisingly few comprehensive field tests of mechanistic niche models in the literature. We applied a general, thermodynamically grounded modeling framework to determine the fundamental niche of an extremely well-studied herbivorous ectotherm, the sleepy lizard Tiliqua rugosa. We then compared the model predictions with detailed long-term field observations that included sub-hourly data on microclimate, activity levels, home ranges, and body temperatures as well as annual to decadal patterns of body condition and growth. Body temperature predictions inferred from gridded climatic data were within 10% of empirically observed values and explained >70% of observed daytime activity patterns across all lizards. However, some periods of activity restriction were explained by predicted desiccation level rather than by temperature, and metabolically driven activity requirements were much lower than potential activity time. Decadal trajectories of field growth and body condition could also be explained to within 10% of observed values, with the variance in trajectories being attributable to whether individuals had access to permanent water. Continent-wide applications of the model partly captured the inland distribution limit, but only after accounting for water limitations. Predicted changes in habitat suitability under six climate change scenarios were generally positive within the species’ current range, but varied strongly with predicted rainfall. Temperature is regarded as the major factor that will restrict the distribution and abundance of lizards and other terrestrial ectotherms under climate change. Yet our findings show how water can be more important than temperature in constraining the activity, habitat requirements, and distribution limits of terrestrial ectotherms. Our results demonstrate the feasibility of first-principles computation of the climatic limits on terrestrial animals from gridded environmental data, providing a coherent picture for how species will respond to climate change at different scales of space and time.

Partitioning assimilatory nitrogen uptake in streams: an analysis of stable isotope tracer additions across continents

Abstract: Headwater streams remove, transform, and store inorganic nitrogen (N) delivered from surrounding watersheds, but excessive N inputs from human activity can saturate removal capacity. Most research has focused on quantifying N removal from the water column over short periods and in individual reaches, and these ecosystem-scale measurements suggest that assimilatory N uptake accounts for most N removal. However, cross-system comparisons addressing the relative role of particular biota responsible for incorporating inorganic N into biomass are lacking. Here we assess the importance of different primary uptake compartments on reach-scale ammonium (NH4+-N) uptake and storage across a wide range of streams varying in abundance of biota and local environmental factors. We analyzed data from 17 15N-NH4 tracer addition experiments globally, and found that assimilatory N uptake by autotrophic compartments (i.e., epilithic biofilm, filamentous algae, bryophytes/macrophytes) was higher but more variable than for heterotrophic microorganisms colonizing detrital organic matter (i.e., leaves, small wood, and fine particles). Autotrophic compartments played a disproportionate role in N uptake relative to their biomass, although uptake rates were similar when we rescaled heterotrophic assimilatory N uptake associated only with live microbial biomass. Assimilatory NH4+-N uptake, either estimated as removal from the water column or from the sum uptake of all individual compartments, was four times higher in open- than in closed-canopy streams. Using Bayesian Model Averaging, we found that canopy cover and gross primary production (GPP) controlled autotrophic assimilatory N uptake while ecosystem respiration (ER) was more important for the heterotrophic contribution. The ratio of autotrophic to heterotrophic N storage was positively correlated with metabolism (GPP:ER), which was also higher in open- than in closed-canopy streams. Our analysis shows riparian canopy cover influences the relative abundance of different biotic uptake compartments and thus GPP:ER. As such, the simple categorical variable of canopy cover explained differences in assimilatory N uptake among streams at the reach scale, as well as the relative roles of autotrophs and heterotrophs in N storage. Finally, this synthesis links cumulative N uptake by stream biota to reach-scale N demand and provides a mechanistic and predictive framework for estimating and modeling N cycling in other streams. This article is protected by copyright. All rights reserved.

The food web perspective on aquatic biofilms

Abstract: Biofilms, the complex communities of microbiota that live in association with aquatic interfaces, are considered to be hotspots of microbial life in many aquatic ecosystems. Although the importance of attached algae and bacteria is widely recognized, the role of the highly abundant biofilm-dwelling micrograzers (i.e., heterotrophic protists and small metazoans) is poorly understood. Studies often highlight the resistance of bacterial biofilms to grazing within the microbial food web and therefore argue that the micrograzers have a modulating role (i.e., have effects on biofilm phenotype) rather than a direct trophic role within biofilms. In the present review, we show that this view comes too short, and we establish a conceptual framework of biofilm food webs consisting of three major elements. (1) Energy pathways and subsidization from plankton. As inhabitants of interfaces, biofilm-dwelling grazers potentially access both planktonic organisms and surface-associated organisms. They can play an important role in importing planktonic production into the biofilm food web and thus in the coupling of the planktonic and benthic food webs. Nevertheless, specialized grazers are also able to utilize significant amounts of autochthonous biofilm production. (2) Horizontal complexity of the basal food web. While bacteria and algae within biofilms are edible in general, food quality and accessibility of both bacteria and algae can differ considerably between different prey phenotypes occurring during biofilm formation with respect to morphology, chemical defense, and nutrient stoichiometry. Instead of considering bacteria and algae within biofilms to be generally resistant to feeding by micrograzers, we suggest considering a horizontal food-quality axis to be at the base of biofilm food webs. This food quality gradient is probably associated with increasing costs for the micrograzers. (3) Vertical food web complexity and food chain length. In addition to the consumption of bacteria and algae, many predatory micrograzers exist within biofilm food webs. With the help of video microscopy, we were able to demonstrate the existence of a complex food web with several trophic levels within biofilms. Our conceptual framework should assist in integrating food web concepts and processes into whole-biofilm budgets and in understanding food-web-related interactions within biofilms.

Age × stage-classified demographic analysis: a comprehensive approach

Abstract: This paper presents a comprehensive theory for the demographic analysis of populations in which individuals are classified by both age and stage. The earliest demographic models were age classified. Ecologists adopted methods developed by human demographers and used life tables to quantify survivorship and fertility of cohorts and the growth rates and structures of populations. Later, motivated by studies of plants and insects, matrix population models structured by size or stage were developed. The theory of these models has been extended to cover all the aspects of age‐classified demography and more. It is a natural development to consider populations classified by both age and stage. A steady trickle of results has appeared since the 1960s, analyzing one or another aspect of age × stage‐classified populations, in both ecology and human demography. Here, we use the vec‐permutation formulation of multistate matrix population models to incorporate age‐ and stage‐specific vital rates into demographic analysis. We present cohort results for the life table functions (survivorship, mortality, and fertility), the dynamics of intra‐cohort selection, the statistics of longevity, the joint distribution of age and stage at death, and the statistics of life disparity. Combining transitions and fertility yields a complete set of population dynamic results, including population growth rates and structures, net reproductive rate, the statistics of lifetime reproduction, and measures of generation time. We present a complete analysis of a hypothetical model species, inspired by poecilogonous marine invertebrates that produce two kinds of larval offspring. Given the joint effects of age and stage, many familiar demographic results become multidimensional, so calculations of marginal and mixture distributions are an important tool. From an age‐classified point of view, stage structure is a form of unobserved heterogeneity. From a stage‐classified point of view, age structure is unobserved heterogeneity. In an age × stage‐classified model, variance in demographic outcomes can be partitioned into contributions from both sources. Because these models are formulated as matrices, they are amenable to a complete sensitivity analysis. As more detailed and longer longitudinal studies are developed, age × stage‐classified demography will become more common and more important.

Constructing and evaluating a continent-wide migratory songbird network across the annual cycle

Abstract: Determining how migratory animals are spatially connected between breeding and nonbreeding periods is essential for predicting the effects of environmental change and for developing optimal conservation strategies. Yet, despite recent advances in tracking technology, we lack comprehensive information on the spatial structure of migratory networks across a species’ range, particularly for small-bodied, long-distance migratory animals. We constructed a migratory network for a songbird and used network-based metrics to characterize the spatial structure and prioritize regions for conservation. The network was constructed using year-round movements derived from 133 archival light-level geolocators attached to Tree Swallows (Tachycineta bicolor) originating from 12 breeding sites across their North American breeding range. From these breeding sites, we identified 10 autumn stopover nodes (regions) in North America, 13 non-breeding nodes located around the Gulf of Mexico, Mexico, Florida, and the Caribbean, and 136 unique edges (migratory routes) connecting nodes. We found strong migratory connectivity between breeding and autumn stopover sites and moderate migratory connectivity between the breeding and non-breeding sites. We identified three distinct “communities” of nodes that corresponded to western, central, and eastern North American flyways. Several regions were important for maintaining network connectivity, with South Florida and Louisiana as the top ranked non-breeding nodes and the Midwest as the top ranked stopover node. We show that migratory songbird networks can have both a high degree of mixing between seasons yet still show regionally distinct migratory flyways. Such information will be crucial for accurately predicting factors that limit and regulate migratory songbirds throughout the annual cycle. Our study highlights how network-based metrics can be valuable for identifying overall network structure and prioritizing specific regions within a network for conserving a wide variety of migratory animals.

Nutrient remobilization in tree foliage as affected by soil nutrients and leaf life span

Abstract: Nutrient remobilization is a key process in nutrient conservation in plants and in nutrient cycling in ecosystems. To predict the productivity of terrestrial ecosystems, we thus need to improve our understanding of the factors that control remobilization. We studied the remobilization rates of several major nutrients (N, P, S, K, Ca, and Mg) in 102 forest ecosystems representing large environmental gradients at the country scale (France). Total amounts or availability of nutrients in soils were correlated with nutrient remobilization: the larger the soil nutrient pool, the lower the remobilization rate (e.g., P remobilization decreased with increasing total or extractable inorganic P in soils). Soil type and soil parent material influenced nutrient remobilization indirectly through their effect on soil nutrients. Nutrient remobilization was also affected by the quality of soil organic matter (C:N and C:P ratios) and K‐Ca‐Mg antagonisms. In addition to soil properties, plant‐related parameters (nutrient concentrations in foliage and leaf life span) and climate variables (e.g., precipitation and actual evapotranspiration) were also correlated with nutrient remobilization. Using multivariate analysis, we found that soil nutrient richness and the life span of the leaf were generally the two most important factors controlling nutrient remobilization. As a whole, the nutrient remobilization rate is regulated by soil nutrients through negative feedback. This general ecological pattern is modulated by ecophysiological constraints of plants, mainly leaf life span or the capability of plants to move Ca through the phloem sap.

Long-term research in ecology and evolution: a survey of challenges and opportunities

Abstract: Long-term research in ecology and evolution (LTREE) is considered fundamental for understanding complex ecological and evolutionary dynamics. However, others have argued for revision of LTREE efforts given perceived limitations in current research priorities and approaches. Yet most arguments about the benefits and failings of LTREE could be argued to reflect the views of only the limited number of scientists who have authored reports on the field, and not the wider community of ecological and evolutionary scientists. To more systematically and quantitatively assess the views of the community on LTREE contributions and future activities, we conducted and here report the results of a survey of ecological and evolutionary scientists at primarily U.S.-based institutions, completed by 1,179 respondents. The survey objectives were to (1) identify and prioritize research questions that are important to address through long-term, ecological field experiments and (2) understand the role that these experiments might play in generating and applying ecological and evolutionary knowledge. Almost 80% (n = 936) of respondents said that long-term experiments had contributed “a great deal” to ecological understanding. Compared to other research approaches (e.g., short-term, single-site, modeling, or lab), there was overwhelming support that multi-site, long-term research was very important for advancing theory, and that both observational and experimental approaches were required. Respondents identified a wide range of research questions for LTREE to address. The most common topic was the impact of global change (n = 1,352), likely because these processes play out over many years, requiring LTREE approaches to fully understand. Another recurrent theme was the potential of LTREE approaches to build evolutionary understanding across all levels of ecological organization. Critical obstacles preventing some scientists from engaging in LTREE included short-term funding mechanisms and fewer publications, whereas the longer-term value for advancing knowledge and an individual’s career were widely recognized. Substantive advances in understanding ecological and evolutionary dynamics then seem likely to be made through engagement in long-term observational and experimental research. However, wider engagement seems dependent on a more supportive research environment and funding structure, through increased institutional acknowledgement of the contributions of long-term research, and greater program support during the establishment and maintenance of research.

Anthropogenic N deposition increases soil C storage by reducing the relative abundance of lignolytic fungi

Abstract: Atmospheric nitrogen (N) deposition has increased dramatically since preindustrial times and continues to increase across many regions of the Earth. In temperate forests, this agent of global change has increased soil carbon (C) storage, but the mechanisms underlying this response are not understood. One long‐standing hypothesis proposed to explain the accumulation of soil C proposes that higher inorganic N availability may suppress both the activity and abundance of fungi that decay lignin and other polyphenols in soil. In field studies, elevated rates of N deposition have reduced the activity of enzymes mediating lignin decay, but a decline in the abundance of lignolytic fungi has not been definitively documented to date. Here, we tested the hypothesis that elevated rates of anthropogenic N deposition reduce the abundance of lignolytic fungi. We conducted a field experiment in which we compared fungal communities colonizing low‐lignin, high‐lignin, and wood substrates in a northern hardwood forest that is part of a long‐term N deposition experiment. We reasoned that if lignolytic fungi decline under experimental N deposition, this effect should be most evident among fungi colonizing high‐lignin and wood substrates. Using molecular approaches, we provide evidence that anthropogenic N deposition reduces the relative abundance of lignolytic fungi on both wood and a high‐lignin substrate. Furthermore, experimental N deposition increased total fungal abundance on a low‐lignin substrate, reduced fungal abundance on wood, and had no significant effect on fungal abundance on a high‐lignin substrate. We simultaneously examined these responses in the surrounding soil and forest floor, in which we did not observe significant reductions in the relative abundance of lignolytic fungi or in the size of the fungal community; however, we did detect a change in community composition in the forest floor that appears to be driven by a shift away from lignolytic fungi and towards cellulolytic fungi. Our results provide direct evidence that reductions in the abundance of lignolytic fungi are part of the mechanism by which anthropogenic N deposition increases soil C storage.

Early warning signals precede cyanobacterial blooms in multiple whole-lake experiments

Abstract: Ecosystem regime shifts are abrupt changes from one dynamical state to another, such as the shift from a clear-water state to an algal bloom state in lakes. These transitions are hard to forecast but theory suggests that early warning indicators can predict impending regime shifts that may allow for management intervention to prevent or mitigate an unwanted change. The efficacy of early warning indicators has been demonstrated in modeling and laboratory experiments, but rarely in the field, where environmental drivers are numerous and interacting. It is unclear if early warning indicators are observable or timely enough to allow for intervention under these conditions. We performed six whole-lake experimental nutrient additions to test the utility of early warning indicators for predicting the regime shift from a clear-water state to a cyanobacteria-dominated state. The lakes were monitored for increases in resilience indicators including rises in standard deviation and autocorrelation of algal pigments and dissolved oxygen saturation. A statistical method, quickest detection, determined when resilience indicators in manipulated lakes deviated substantially from those in a reference ecosystem. Blooms occurred in five of the six lake-years. Although there was substantial variability in bloom size and timing, at least one indicator foreshadowed the peak chlorophyll a concentration in all instances. Early warnings occurred 1–57 d prior to a bloom, which in some instances, may allow managers to notify the public or intervene to prevent blooms. The resilience indicators generally identified changes in resilience over time within a lake and also ranked large differences in resilience among lakes. Our findings suggest that resilience indicators can be useful for classifying ecosystems on a landscape and across time with respect to proximity to a critical threshold.

Upscaling biodiversity: Estimating the species-area relationship from small samples

Abstract: The challenge of biodiversity upscaling, estimating the species richness of a large area from scattered local surveys within it, has attracted increasing interest in recent years, producing a wide range of competing approaches. Such methods, if successful, could have important applications to multi‐scale biodiversity estimation and monitoring. Here we test 19 techniques using a high quality plant data set: the GB Countryside Survey 1999, detailed surveys of a stratified random sample of British landscapes. In addition to the full data set, a set of geographical and statistical subsets was created, allowing each method to be tested on multiple data sets with different characteristics. The predictions of the models were tested against the “true” species–area relationship for British plants, derived from contemporaneously surveyed national atlas data. This represents a far more ambitious test than is usually employed, requiring 5–10 orders of magnitude in upscaling. The methods differed greatly in their performance; while there are 2,326 focal plant taxa recorded in the focal region, up‐scaled species richness estimates ranged from 62 to 11,593. Several models provided reasonably reliable results across the 16 test data sets: the Shen and He and the Ulrich and Ollik models provided the most robust estimates of total species richness, with the former generally providing estimates within 10% of the true value. The methods tested proved less accurate at estimating the shape of the species–area relationship (SAR) as a whole; the best single method was Hui's Occupancy Rank Curve approach, which erred on average by <20%. A hybrid method combining a total species richness estimate (from the Shen and He model) with a downscaling approach (the Sizling model) proved more accurate in predicting the SAR (mean relative error 15.5%) than any of the pure upscaling approaches tested. There remains substantial room for improvement in upscaling methods, but our results suggest that several existing methods have a high potential for practical application to estimating species richness at coarse spatial scales. The methods should greatly facilitate biodiversity estimation in poorly studied taxa and regions, and the monitoring of biodiversity change at multiple spatial scales.

Genetic variation determines which feedbacks drive and alter predator–prey eco-evolutionary cycles

Abstract: Evolution can alter the ecological dynamics of communities, but the effects depend on the magnitudes of standing genetic variation in the evolving species. Using an eco-coevolutionary predator–prey model, I identify how the magnitudes of prey and predator standing genetic variation determine when ecological, evolutionary, and eco-evolutionary feedbacks influence system stability and the phase lags in predator–prey cycles. Here, feedbacks are defined by subsystems, i.e., the dynamics of a subset of the components of the whole system when the other components are held fixed; ecological (evolutionary) feedbacks involve the direct and indirect effects between population densities (species traits) and eco-evolutionary feedbacks involve the direct and indirect effects between population densities and traits. When genetic variation is low in both species, ecological feedbacks and eco-evolutionary feedbacks involving either the predator or the prey trait have the strongest effects on system stability, when genetic variation is high in one species, evolutionary and eco-evolutionary feedbacks involving that species’ trait have the strongest effects, and, when genetic variation is high in both species, evolutionary feedbacks involving one or both traits and eco-coevolutionary feedbacks involving both traits have the strongest effects. I present the biological conditions under which each feedback can destabilize the whole system and cause predator–prey cycles. Predator–prey cycles can also arise when all feedbacks are stabilizing. This counterintuitive outcome occurs when feedbacks involving many variables are more stabilizing than feedbacks involving fewer variables or vice versa. I also identify how the indirect effects of prey and predator density on the predator dynamics (mediated by evolutionary responses in one or both species) alter the phase lags in predator–prey cycles. I present conditions under which the trait-mediated indirect effects introduce delays that cause the lag between prey and predator peaks to increase. This work explains and unifies empirical and theoretical studies on how predator–prey coevolution alters the dynamics of predator–prey systems and how those effects depend on the magnitudes of prey and predator standing genetic variation.

Species turnover and invasion of dominant freshwater invertebrates alter biodiversity–ecosystem-function relationship

Abstract: Freshwater ecosystems rely on allochthonous resources. Integration of these subsidies depends on diversity of both terrestrial resources and aquatic shredder and decomposer communities, but the diversity effects on leaf litter breakdown and decomposition are less clear in aquatic than terrestrial ecosystems. We need a better understanding of this relationship because aquatic communities are rapidly changing with species invasions and anthropogenic impacts. Here, we experimentally disentangled the effects of leaf and shredder richness on leaf litter breakdown by macroinvertebrates in mesocosm experiments using three species of amphipods, a dominant guild of crustaceans in European freshwater ecosystems. Increased leaf richness led to lower-than-predicted leaf consumption by native shredders, with mixed evidence of resource-switching or prioritization of preferred food items within a leaf mix. Higher shredder species richness never promoted leaf consumption rates compared to predictions from relevant single-species experiments, and instead sometimes substantially decreased leaf consumption. We then conducted a meta-analysis of leaf litter consumption rates by seven widely distributed amphipod species (the three used in the experiments and four additional species). As expected based on our own experiments, nonnative amphipod species generally had lower biomass- adjusted leaf litter consumption rates, although their larger body size led to higher per-individual leaf consumption rates. Contamination of the water by metals, pesticides, and other chemicals additionally significantly decreased leaf litter consumption by multiple native and nonnative species compared to unpolluted systems. While the meta-analysis suggested that litter consumption, and thus breakdown, would decline if native shredders are replaced by nonnative heterospecifics, complete species replacement is not the only outcome following immigration in a meta-community context. Our experiments suggest that breakdown rates could remain reasonably high where native species coexist with nonnative arrivals. Experiments that neglect the ecological realism of species coexistence will necessarily mischaracterize effects on ecosystem functioning.

Abiotic and biotic predictors of macroecological patterns in bird and butterfly coloration

Abstract: Animal color phenotypes are invariably influenced by both their biotic community and the abiotic environments. A host of hypotheses have been proposed for how variables such as solar radiation, habitat shadiness, primary productivity, temperature, rainfall, and community diversity might affect animal color traits. However, while individual factors have been linked to coloration in specific contexts, little is known about which factors are most important across broad taxonomic and geographic scales. Using data collected from 570 species of birds and 424 species of butterflies from Australia, which inhabit an area spanning a latitudinal range of 35° and covering deserts, tropical and temperate forests, savannas, and heathlands, we test multiple hypotheses from the coloration literature and assess their relative importance. We show that bird and butterfly species exhibit more reflective and less saturated colors in better-lit environments, a pattern that is robust across an array of variables expected to influence the intensity or quality of ambient light in an environment. Both taxa display more diverse colors in regions with greater net primary production and longer growing seasons. Models that included variables related to energy inputs and resources in ecosystems have better explanatory power for bird and butterfly coloration overall than do models that included community diversity metrics. However, the diversity of the bird community in an environment was the single most powerful predictor of color pattern variation in both birds and butterflies. We observed strong similarities across taxa in the covariance between color and environmental factors, suggesting the presence of fundamental macroecological drivers of visual appearance across disparate taxa.

Multiscale variation in drought controlled historical forest fire activity in the boreal forests of eastern Fennoscandia

Abstract: Forest fires are a key disturbance in boreal forests, and characteristics of fire regimes are among the most important factors explaining the variation in forest structure and species composition. The occurrence of fire is connected with climate, but earlier, mostly local-scale studies in the northern European boreal forests have provided little insight into fire–climate relationship before the modern fire suppression period. Here, we compiled annually resolved fire history, temperature, and precipitation reconstructions from eastern Fennoscandia from the mid-16th century to the end of the 19th century, a period of strong human influence on fires. We used synchrony of fires over the network of 25 fire history reconstructions as a measure of climatic forcing on fires. We examined the relationship between fire occurrence and climate (summer temperature, precipitation, and a drought index summarizing the influence of variability in temperature and precipitation) across temporal scales, using a scale space multiresolution correlation approach and Bayesian inference that accounts for the annually varying uncertainties in climate reconstructions. At the annual scale, fires were synchronized during summers with low precipitation, and most clearly during drought summers. A scale-derivative analysis revealed that fire synchrony and climate varied at similar, roughly decadal scales. Climatic variables and fire synchrony showed varying correlation strength and credibility, depending on the climate variable and the time period. In particular, precipitation emerged as a credible determinant of fire synchrony also at these time scales, despite the large uncertainties in precipitation reconstruction. The findings explain why fire occurrence can be high during cold periods (such as from the mid-17th to early-18th century), and stresses the notion that future fire frequency will likely depend to a greater extent on changes in precipitation than temperature alone. We showed, for the first time, the importance of climate as a decadal-scale driver of forest fires in the European boreal forests, discernible even during a period of strong human influence on fire occurrence. The fire regime responded both to anomalously dry summers, but also to decadal-scale climate changes, demonstrating how climatic variability has shaped the disturbance regimes in the northern European boreal forests over various time scales.

Ecological autocatalysis: A central principle in ecosystem organization?

Abstract: Ecosystems comprise flows of energy and materials, structured by organisms and their interactions. Important generalizations have emerged in recent decades about conversions by organisms of energy (metabolic theory of ecology) and materials (ecological stoichiometry). However, these new insights leave a key question about ecosystems inadequately addressed: are there basic organizational principles that explain how the interaction structure among species in ecosystems arises? Here we integrate recent contributions to the understanding of how ecosystem organization emerges through ecological autocatalysis (EA), in which species mutually benefit through self-reinforcing circular interaction structures. We seek to generalize the concept of EA by integrating principles from community and ecosystem ecology. We discuss evidence suggesting that ecological autocatalysis is facilitated by resource competition and natural selection, both central principles in community ecology. Furthermore, we suggest that pre-emptive resource competition by consumers and plant resource diversity drive the emergence of autocatalytic loops at the ecosystem level. Subsequently, we describe how interactions between such autocatalytic loops can explain pattern and processes observed at the ecosystem scale, and summarize efforts to model different aspect of the phenomenon. We conclude that EA is a central principle that forms the backbone of the organization in systems ecology, analogous to autocatalytic loops in systems chemistry.

Testing the intermittent upwelling hypothesis: upwelling, downwelling, and subsidies to the intertidal zone

Abstract: The Intermittent Upwelling Hypothesis (IUH) posits that subsidies of larvae and phytoplankton to intertidal communities should vary unimodally along a gradient of upwelling from persistent upwelling to persistent downwelling with most subsidies occurring where upwelling is of intermediate strength and intermittent. Furthermore, the hypothesis states that larvae and phytoplankton are transported far offshore by strong, persistent upwelling and fail to subsidize nearshore communities, whereas weak upwelling or downwelling reduces nutrients for phytoplankton production limiting food for larvae and nearshore communities. We review studies conducted at sea and onshore and reanalyze published data to test the IUH and evaluate alternative hypotheses. To test the hypothesis, we examine five predictions that must hold if the IUH is true. (1) Larvae should inhabit the surface Ekman layer where they are transported offshore during upwelling. Larvae of many intertidal taxa occur deeper in the water column where currents flow shoreward during upwelling. (2) Larvae of nearshore species should occur farther offshore during upwelling than during relaxation or downwelling. Larvae of many nearshore species remain within several kilometers of shore during both conditions. (3) Larval settlement in intertidal communities should be lower during upwelling than relaxation or downwelling. Daily larval settlement has not observed to be higher during relaxation or downwelling events; settlement has most often been seen to vary with the fortnightly tidal cycle likely due to onshore larval transport by internal tides. (4) Larval settlement and recruitment in intertidal communities should be lower in areas of strong, persistent upwelling than where upwelling is weaker and less persistent. Recruitment of mussels and barnacles to artificial and natural substrates did not vary with the strength of upwelling, but did vary inversely with two measures of desiccation potential, and directly with indicators of surf zone hydrodynamics; larval recruitment was higher where surf zones were more dissipative with rip currents. (5) Phytoplankton subsidies to nearshore communities should be highest where upwelling is moderate and intermittent. Like larval subsidies, phytoplankton subsidies varied spatially with surf zone hydrodynamics rather than upwelling. This reconsideration of the evidence for the IUH finds the hypothesis unsupported.

From early life to senescence: individual heterogeneity in a long‐lived seabird

Abstract: Although population studies have long assumed that all individuals of a given sex and age are identical, ignoring among-individual differences may strongly bias our perception of eco-evolutionary processes. Individual heterogeneity, often referred to as individual quality, has received increasing research attention in the last decades. However, there are still substantial gaps in our current knowledge. For example, there is little information on how individual heterogeneity influences various life-history traits simultaneously, and studies describing individual heterogeneity in wild populations are generally not able to jointly identify possible sources of this variation. Here, based on a mark–recapture data set of 9,685 known-aged Wandering Albatrosses (Diomedea exulans), we investigated the existence of individual quality over the entire life cycle of this species, from early life to senescence. Using finite mixture models, we investigated the expression of individual heterogeneity in various demographic traits, and examined the origin of these among-individual differences by considering the natal environmental conditions. We found that some individuals consistently outperformed others during most of their life. In old age, however, the senescence rate was stronger in males that showed high demographic performance at younger ages. Variation in individual quality seemed strongly affected by extrinsic factors experienced during the ontogenetic period. We found that individuals born in years with high population density tended to have lower performances during their lifespan, suggesting delayed density dependence effects through individual quality. Our study showed that among-individual differences could be important in structuring individual life history trajectories, with substantial consequences at higher ecological levels such as population dynamics.

Linking fishing pressure with ecosystem thresholds and food web stability on coral reefs

Abstract: Managing fisheries for ecosystem resilience is essential, but practical guidance is limited by food-web complexity. Processes, mechanisms, and thresholds associated with ecosystem overfishing were investigated by combining traditional concepts in fisheries biology with recent advances in food-web modeling. Diverse coral-reef food webs were simplified by grouping species into guilds based on the way they capture, store, and transfer energy, rather than taxonomically, as is traditionally done. Biomass fluxes between the guilds were then quantified using an allometric trophic model. The model was calibrated by linking parameters describing growth, predation, and competition with known body size and metabolic constraints, and then adjusting the base rate of parameters to match fish biomass estimates from a “pristine” coral reef system. The calibrated model was then tested by replacing equilibrium fish biomasses with observations from fished systems across the Pacific, spanning nine islands and numerous major-reef habitats. Encouraging relationships were found between predicted algal accumulation and field observations, and between modelled and observed guild restructuring. In terms of food-web ecology, “pristine” food webs were characterized by asynchronous population dynamics between the guilds (i.e., offsetting fluctuations), which maximized their persistence and the net accumulation of biomass within food webs. Beneficial, offsetting fluctuations were driven by the contrasting roles of density dependence, apparent competition, and predation. Fishing for predators synchronized the population fluctuations between the guilds, resulting in larger amplitudes (i.e., highs and lows), and a growing dominance of small herbivores. Continued fishing for large herbivores eventually led to an inflection point where algal biomass accumulated exponentially, revealing an ecosystem-based fisheries benchmark. Management targets that maximized fisheries yields while controlling for algal accumulation required simultaneous exploitation across the guilds; a significant challenge because maximum yields of predators, large herbivores, and small herbivores were magnitudes of order apart. This strategy also represented a departure from modern commercial fisheries policies that place catch quotas on entire fish families taxonomically, committing systems to smaller fish, higher biomass turnover, and undesirable algal accumulation. Moving forward, the model provided a flexible and adaptable framework to consider economic and ecosystem objectives of fisheries simultaneously, ultimately balancing resilient food webs against higher fisheries productivity.

Spatially explicit modeling and prediction of shrub cover increase near Umiujaq, Nunavik

Abstract: A circumpolar increase in shrub growth and cover has been underway in Arctic and subarctic ecosystems for the last few decades, but there is considerable spatial heterogeneity in this shrubification process. Although topography, hydrology, and edaphic factors are known to influence shrubification patterns, a better understanding of the landscape‐scale factors driving this phenomenon is needed to accurately predict its impacts on ecosystem function. In this study, we generated land cover change models in order to identify variables driving shrub cover increase near Umiujaq (Quebec, Canada). Using land cover maps from 1990/1994 and 2010, we modeled observed changes using two contrasting conceptual approaches: binomial modeling of transitions to shrub dominance and multinomial modeling of all land cover transitions. Models were used to generate spatially explicit predictions of transition to shrub dominance in the near future as well as long‐term predictions of the abundance of different land cover types. Model predictions were validated using both field data and current Landsat‐derived trends of normalized difference vegetation index (NDVI) increase in the region in order to assess their consistency with observed patterns of change. We found that both variables related to topography and to vegetation were useful in modeling land cover changes occurring near Umiujaq. Shrubs tended to preferentially colonize low‐elevation areas and moderate slopes, while their cover was more likely to increase in the vicinity of existing shrub patches. Deterministic realizations of the spatially explicit models of land cover change had a good predictive capability, although they performed better at predicting the proportion of different cover types than at predicting the precise location of the changes. Binomial models performed as well as multinomial models, indicating that neglecting land cover changes other than shrubification does not result in decreased prediction accuracy. The predicted probabilities of shrub increase in the region were consistent with patterns of change inferred from field data, but only partly supported by recent local increases in NDVI. Our findings increase the current understanding of the factors driving shrubification, while warranting further research on its impacts on ecosystem function and on the link between land cover changes and shifts in remotely sensed vegetation indices.