Organization of macroalgal assemblages in the Northeast Pacific: the assumption of homogeneity and the illusion of generality

Evidence for the geographic generality of the causes of intertidal zonation and the indirect effects of a keystone predator, the sea otter, on subtidal kelp assemblages was examined. Most research on intertidal algal assemblages has been done at a few protected sites where zonation is distinct. Surveys of wave-exposed intertidal sites in central and northern California show that assemblage structure is highly variable. This indicates that our present understanding of assemblage organization, including the effects of mussel-algal interactions, may not be widely applicable. Surveys of kelp forest habitat along the entire coast of California suggest that deforestation by sea urchins is uncommon in the absence of sea otters. These examples indicate that the generality of commonly accepted causes of algal assemblage structure in the Northeast Pacific may be an illusion based on assumptions of environmental homogeneity.     

物种分布区范围地理格局的Rapoport法则

Rapoport法则最初是关于物种分布的纬度位置与纬度分布宽度的关系的假说, 被认为是宏观生态学的重要假说之一。Rapoport法则提出以后引发了广泛的实证检验和理论探讨, 并扩展到海拔和海洋深度梯度的分析。对Rapoport法则的检验发展了多种算法, 包括基于中域效应模型的比较分析法, 提出了气候变异性等多种机理解释, 并建立了物种分布区范围格局与物种丰富度格局、分布边界限制等重要宏观生态学现象之间的联系。关于该法则的普适性仍存在明显的意见分歧, 但分析和检验方法被认为是影响结果的重要因素, 方法的改进将是这一领域今后研究的关键。本文主要从Rapoport法则的概念、检验方法、机理性解释, 关于其普适性的争论及其与物种丰富度格局的关系等方面, 综述这一领域的研究进展。     

Community assembly, stability and signatures of dynamical constraints on food web structure

To understand the dynamics of natural species communities, a major challenge is to quantify the relationship between their assembly, stability, and underlying food web structure. To this end, two complementary aspects of food web structure can be related to community stability: sign structure, which refers to the distributions of trophic links irrespective of interaction strengths, and interaction strength structure, which refers to the distributions of interaction strengths with or without consideration of sign structure. In this paper, using data from a set of relatively well documented community food webs, I show that natural communities generally exhibit a sign structure that renders their stability sensitive to interaction strengths. Using a Lotka-Volterra type population dynamical model, I then show that in such communities, individual consumer species with high values of a measure of their total biomass acquisition rate, which I term “weighted generality”, tend to undermine community stability. Thus consumer species’ trophic modules (a species and all its resource links) should be “selected” through repeated immigrations and extinctions during assembly into configurations that increase the probability of stable coexistence within the constraints of the community's trophic sign structure. The presence of such constraints can be detected by the incidence and strength of certain non-random structural characteristics. These structural signatures of dynamical constraints are readily measurable, and can be used to gauge the importance of interaction-driven dynamical constraints on communities during and after assembly in natural communities.     

The development of animal personality: relevance,concepts and perspectives

Recent studies of animal personality have focused on its proximate causation and its ecological and evolutionary significance, but have mostly ignored questions about its development, although an understanding of the latter is highly relevant to these other questions. One possible reason for this neglect is confusion about many of the concepts and terms that are necessary to study the development of animal personality. Here, we provide a framework for studying personality development that focuses on the properties of animal personality, and considers how and why these properties may change over time. We specifically focus on three dimensions of personality: (1) contextual generality at a given age or time, (2) temporal consistency in behavioural traits and in relationships between traits, and (3) the effects of genes and experience on the development of personality at a given age or life stage. We advocate using a new approach, contextual reaction norms, to study the contextual generality of personality traits at the level of groups, individuals and genotypes, show how concepts and terms borrowed from the literature on personality development in humans can be used to study temporal changes in personality at the level of groups and individuals, and demonstrate how classical developmental reaction norms can provide insights into the ways that genes and experiential factors interact across ontogeny to affect the expression of personality traits. In addition, we discuss how correlations between the effects of genes and experience on personality development can arise as a function of individuals' control over their own environment, via niche‐picking or niche‐construction. Using this framework, we discuss several widely held assumptions about animal personality development that still await validation, identify neglected methodological issues, and describe a number of promising new avenues for future research.     

Are niche‐based species distribution models transferable in space?

Aim To assess the geographical transferability of niche‐based species distribution models fitted with two modelling techniques. Location Two distinct geographical study areas in Switzerland and Austria, in the subalpine and alpine belts. Methods Generalized linear and generalized additive models (GLM and GAM) with a binomial probability distribution and a logit link were fitted for 54 plant species, based on topoclimatic predictor variables. These models were then evaluated quantitatively and used for spatially explicit predictions within (internal evaluation and prediction) and between (external evaluation and prediction) the two regions. Comparisons of evaluations and spatial predictions between regions and models were conducted in order to test if species and methods meet the criteria of full transferability. By full transferability, we mean that: (1) the internal evaluation of models fitted in region A and B must be similar; (2) a model fitted in region A must at least retain a comparable external evaluation when projected into region B, and vice‐versa; and (3) internal and external spatial predictions have to match within both regions. Results The measures of model fit are, on average, 24% higher for GAMs than for GLMs in both regions. However, the differences between internal and external evaluations (AUC coefficient) are also higher for GAMs than for GLMs (a difference of 30% for models fitted in Switzerland and 54% for models fitted in Austria). Transferability, as measured with the AUC evaluation, fails for 68% of the species in Switzerland and 55% in Austria for GLMs (respectively for 67% and 53% of the species for GAMs). For both GAMs and GLMs, the agreement between internal and external predictions is rather weak on average (Kulczynski's coefficient in the range 0.3–0.4), but varies widely among individual species. The dominant pattern is an asymmetrical transferability between the two study regions (a mean decrease of 20% for the AUC coefficient when the models are transferred from Switzerland and 13% when they are transferred from Austria). Main conclusions The large inter‐specific variability observed among the 54 study species underlines the need to consider more than a few species to test properly the transferability of species distribution models. The pronounced asymmetry in transferability between the two study regions may be due to peculiarities of these regions, such as differences in the ranges of environmental predictors or the varied impact of land‐use history, or to species‐specific reasons like differential phenotypic plasticity, existence of ecotypes or varied dependence on biotic interactions that are not properly incorporated into niche‐based models. The lower variation between internal and external evaluation of GLMs compared to GAMs further suggests that overfitting may reduce transferability. Overall, a limited geographical transferability calls for caution when projecting niche‐based models for assessing the fate of species in future environments.     

Evaluation of six process‐based forest growth models using eddy‐covariance measurements of CO2 and H2O fluxes at six forest sites in Europe

Reliable models are required to assess the impacts of climate change on forest ecosystems. Precise and independent data are essential to assess this accuracy. The flux measurements collected by the EUROFLUX project over a wide range of forest types and climatic regions in Europe allow a critical testing of the process‐based models which were developed in the LTEEF project. The ECOCRAFT project complements this with a wealth of independent plant physiological measurements. Thus, it was aimed in this study to test six process‐based forest growth models against the flux measurements of six European forest types, taking advantage of a large database with plant physiological parameters. The reliability of both the flux data and parameter values itself was not under discussion in this study. The data provided by the researchers of the EUROFLUX sites, possibly with local corrections, were used with a minor gap‐filling procedure to avoid the loss of many days with observations. The model performance is discussed based on their accuracy, generality and realism. Accuracy was evaluated based on the goodness‐of‐fit with observed values of daily net ecosystem exchange, gross primary production and ecosystem respiration (gC m^?2 d^?1), and transpiration (kg H₂O m^?2 d^?1). Moreover, accuracy was also evaluated based on systematic and unsystematic errors. Generality was characterized by the applicability of the models to different European forest ecosystems. Reality was evaluated by comparing the modelled and observed responses of gross primary production, ecosystem respiration to radiation and temperature. The results indicated that: Accuracy. All models showed similar high correlation with the measured carbon flux data, and also low systematic and unsystematic prediction errors at one or more sites of flux measurements. The results were similar in the case of several models when the water fluxes were considered. Most models fulfilled the criteria of sufficient accuracy for the ability to predict the carbon and water exchange between forests and the atmosphere. Generality. Three models of six could be applied for both deciduous and coniferous forests. Furthermore, four models were applied both for boreal and temperate conditions. However, no severe water‐limited conditions were encountered, and no year‐to‐year variability could be tested. Realism. Most models fulfil the criterion of realism that the relationships between the modelled phenomena (carbon and water exchange) and environment are described causally. Again several of the models were able to reproduce the responses of measurable variables such as gross primary production (GPP), ecosystem respiration and transpiration to environmental driving factors such as radiation and temperature. Stomatal conductance appears to be the most critical process causing differences in predicted fluxes of carbon and water between those models that accurately describe the annual totals of GPP, ecosystem respiration and transpiration. As a conclusion, several process‐based models are available that produce accurate estimates of carbon and water fluxes at several forest sites of Europe. This considerable accuracy fulfils one requirement of models to be able to predict the impacts of climate change on the carbon balance of European forests. However, the generality of the models should be further evaluated by expanding the range of testing over both time and space. In addition, differences in behaviour between models at the process level indicate requirement of further model testing, with special emphasis on modelling stomatal conductance realistically.     

Leveraging nature's backup plans to incorporate interspecific interactions and resilience into restoration

Interspecific interactions are important structuring forces in ecological communities. Interactions can be disturbed when species are lost from a community. When interactions result in fitness gains for at least one participating organism, that organism may experience reduced fitness as a result of interaction disturbance. However, many species exhibit traits that enable individuals to persist and reproduce in spite of such disruptions, resulting in resilience to interaction disturbance. Such traits can result in interaction generalization, phenotypic and behavioral plasticity, and adaptive capacity. We discuss examples of these traits and use case studies to illustrate how restoration practitioners can use a trait‐based approach to examine species of concern, identify traits that are associated with interspecific interactions and are relevant to resilience, and target such traits in restoration. Restoration activities that bolster interaction resilience could include, for example, reintroducing or supporting specific functional groups or managing abiotic conditions to reduce interaction dependence by at‐risk species (e.g. providing structural complexity offering shelter and cover). Resilience may also be an important consideration in species selection for restoration. Establishment of resilient species, able to persist after interaction disturbance, may be essential to restoring to a functioning ecological community. Once such species are present, they could help support more specialized species that lack resilience traits, such as many species of concern. Understanding the conditions under which processes linked to resilience may enable species to persist and communities to reform following interaction disturbance is a key application of community ecology to ecological restoration.     

Predicting invasion success in complex ecological networks

A central and perhaps insurmountable challenge of invasion ecology is to predict which combinations of species and habitats most effectively promote and prevent biological invasions. Here, we integrate models of network structure and nonlinear population dynamics to search for potential generalities among trophic factors that may drive invasion success and failure. We simulate invasions where 100 different species attempt to invade 150 different food webs with 15–26 species and a wide range (0.06–0.32) of connectance. These simulations yield 11 438 invasion attempts by non-basal species, 47 per cent of which are successful. At the time of introduction, whether or not the invader is a generalist best predicts final invasion success; however, once the invader establishes itself, it is best distinguished from unsuccessful invaders by occupying a lower trophic position and being relatively invulnerable to predation. In general, variables that reflect the interaction between an invading species and its new community, such as generality and trophic position, best predict invasion success; however, for some trophic categories of invaders, fundamental species traits, such as having the centre of the feeding range low on the theoretical niche axis (for non-omnivorous and omnivorous herbivores), or the topology of the food web (for tertiary carnivores), best predict invasion success. Across all invasion scenarios, a discriminant analysis model predicted successful and failed invasions with 76.5 per cent accuracy for properties at the time of introduction or 100 per cent accuracy for properties at the time of establishment. More generally, our results suggest that tackling the challenge of predicting the properties of species and habitats that promote or inhibit invasions from food web perspective may aid ecologists in identifying rules that govern invasions in natural ecosystems.