Understanding how landscape characteristics affect biodiversity patterns and ecological processes at local and landscape scales is critical for mitigating effects of global environmental change. In this review, we use knowledge gained from human-modified landscapes to suggest eight hypotheses, which we hope will encourage more systematic research on the role of landscape composition and configuration in determining the structure of ecological communities, ecosystem functioning and services. We organize the eight hypotheses under four overarching themes. Section A: ‘landscape moderation of biodiversity patterns’ includes (1) the landscape species pool hypothesis—the size of the landscape-wide species pool moderates local (alpha) biodiversity, and (2) the dominance of beta diversity hypothesis—landscapemoderated dissimilarity of local communities determines landscape-wide biodiversity and overrides negative local effects of habitat fragmentation on biodiversity. Section B: ‘landscape moderation of population dynamics’ includes (3) the cross-habitat spillover hypothesis—landscape-moderated spillover of energy, resources and organisms across habitats, including between managed and natural ecosystems, influences landscape-wide community structure and associated processes and (4) the landscape-moderated concentration and dilution hypothesis—spatial and temporal changes in landscape composition can cause transient concentration or dilution of populationswith functional consequences. Section C: ‘landscape moderation of functional trait selection’ includes (5) the landscape-moderated functional trait selection hypothesis—landscape moderation of species trait selection shapes the functional role and trajectory of community assembly, and (6) the landscape-moderated insurance hypothesis—landscape complexity provides spatial and temporal insurance, i.e. high resilience and stability of ecological processes in changing environments. Section D: ‘landscape constraints on conservation management’ includes (7) the intermediate landscape-complexity hypothesis—landscapemoderated effectiveness of local conservation management is highest in structurally simple, rather than in cleared (i.e. extremely simplified) or in complex landscapes, and (8) the landscape-moderated biodiversity versus ecosystem service management hypothesis—landscape-moderated biodiversity conservation to optimize functional diversity and related ecosystem services will not protect endangered species. Shifting our research focus from local to landscape-moderated effects on biodiversity will be critical to developing solutions for future biodiversity and ecosystem service management.
Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km 2 to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: ( i ) integrating pairwise dependencies, ( ii ) using integrative predictors, and ( iii ) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.
Repeatability (more precisely the common measure of repeatability, the intra-class correlation coefficient, ICC) is an important index for quantifying the accuracy of measurements and the constancy of phenotypes. It is the proportion of phenotypic variation that can be attributed to between-subject (or between-group) variation. As a consequence, the non-repeatable fraction of phenotypic variation is the sum of measurement error and phenotypic flexibility. There are several ways to estimate repeatability for Gaussian data, but there are no formal agreements on how repeatability should be calculated for non-Gaussian data (e.g. binary, proportion and count data). In addition to point estimates, appropriate uncertainty estimates (standard errors and confidence intervals) and statistical significance for repeatability estimates are required regardless of the types of data. We review the methods for calculating repeatability and the associated statistics for Gaussian and non-Gaussian data. For Gaussian data, we present three common approaches for estimating repeatability: correlation-based, analysis of variance (ANOVA)-based and linear mixed-effects model (LMM)-based methods, while for non-Gaussian data, we focus on generalised linear mixed-effects models (GLMM) that allow the estimation of repeatability on the original and on the underlying latent scale. We also address a number of methods for calculating standard errors, confidence intervals and statistical significance; the most accurate and recommended methods are parametric bootstrapping, randomisation tests and Bayesian approaches. We advocate the use of LMM- and GLMM-based approaches mainly because of the ease with which confounding variables can be controlled for. Furthermore, we compare two types of repeatability (ordinary repeatability and extrapolated repeatability) in relation to narrow-sense heritability. This review serves as a collection of guidelines and recommendations for biologists to calculate repeatability and heritability from both Gaussian and non-Gaussian data.
Stable isotope analysis has emerged as one of the primary means for examining the structure and dynamics of food webs, and numerous analytical approaches are now commonly used in the field. Techniques range from simple, qualitative inferences based on the isotopic niche, to Bayesian mixing models that can be used to characterize food‐web structure at multiple hierarchical levels. We provide a comprehensive review of these techniques, and thus a single reference source to help identify the most useful approaches to apply to a given data set. We structure the review around four general questions: (1) what is the trophic position of an organism in a food web?; (2) which resource pools support consumers?; (3) what additional information does relative position of consumers in isotopic space reveal about food‐web structure?; and (4) what is the degree of trophic variability at the intrapopulation level? For each general question, we detail different approaches that have been applied, discussing the strengths and weaknesses of each. We conclude with a set of suggestions that transcend individual analytical approaches, and provide guidance for future applications in the field.
Dispersal costs can be classified into energetic, time, risk and opportunity costs and may be levied directly or deferred during departure, transfer and settlement. They may equally be incurred during life stages before the actual dispersal event through investments in special morphologies. Because costs will eventually determine the performance of dispersing individuals and the evolution of dispersal, we here provide an extensive review on the different cost types that occur during dispersal in a wide array of organisms, ranging from micro‐organisms to plants, invertebrates and vertebrates. In general, costs of transfer have been more widely documented in actively dispersing organisms, in contrast to a greater focus on costs during departure and settlement in plants and animals with a passive transfer phase. Costs related to the development of specific dispersal attributes appear to be much more prominent than previously accepted. Because costs induce trade‐offs, they give rise to covariation between dispersal and other life‐history traits at different scales of organismal organisation. The consequences of ( i ) the presence and magnitude of different costs during different phases of the dispersal process, and ( ii ) their internal organisation through covariation with other life‐history traits, are synthesised with respect to potential consequences for species conservation and the need for development of a new generation of spatial simulation models.
Many birds and mammals drastically reduce their energy expenditure during times of cold exposure, food shortage, or drought, by temporarily abandoning euthermia, i.e. the maintenance of high body temperatures. Traditionally, two different types of heterothermy, i.e. hypometabolic states associated with low body temperature (torpor), have been distinguished: daily torpor, which lasts less than 24 h and is accompanied by continued foraging, versus hibernation, with torpor bouts lasting consecutive days to several weeks in animals that usually do not forage but rely on energy stores, either food caches or body energy reserves. This classification of torpor types has been challenged, suggesting that these phenotypes may merely represent extremes in a continuum of traits. Here, we investigate whether variables of torpor in 214 species (43 birds and 171 mammals) form a continuum or a bimodal distribution. We use Gaussian‐mixture cluster analysis as well as phylogenetically informed regressions to quantitatively assess the distinction between hibernation and daily torpor and to evaluate the impact of body mass and geographical distribution of species on torpor traits. Cluster analysis clearly confirmed the classical distinction between daily torpor and hibernation. Overall, heterothermic endotherms tend to be small; hibernators are significantly heavier than daily heterotherms and also are distributed at higher average latitudes (∼35°) than daily heterotherms (∼25°). Variables of torpor for an average 30 g heterotherm differed significantly between daily heterotherms and hibernators. Average maximum torpor bout duration was >30‐fold longer, and mean torpor bout duration >25‐fold longer in hibernators. Mean minimum body temperature differed by ∼13°C, and the mean minimum torpor metabolic rate was ∼35% of the basal metabolic rate ( BMR ) in daily heterotherms but only 6% of BMR in hibernators. Consequently, our analysis strongly supports the view that hibernators and daily heterotherms are functionally distinct groups that probably have been subject to disruptive selection. Arguably, the primary physiological difference between daily torpor and hibernation, which leads to a variety of derived further distinct characteristics, is the temporal control of entry into and arousal from torpor, which is governed by the circadian clock in daily heterotherms, but apparently not in hibernators.
Freshwater mussels of the Order Unionida provide important ecosystem functions and services, yet many of their populations are in decline. We comprehensively review the status of the 16 currently recognized species in Europe, collating for the first time their life‐history traits, distribution, conservation status, habitat preferences, and main threats in order to suggest future management actions. In northern, central, and eastern Europe, a relatively homogeneous species composition is found in most basins. In southern Europe, despite the lower species richness, spatially restricted species make these basins a high conservation priority. Information on freshwater mussels in Europe is unevenly distributed with considerable differences in data quality and quantity among countries and species. To make conservation more effective in the future, we suggest greater international cooperation using standardized protocols and methods to monitor and manage European freshwater mussel diversity. Such an approach will not only help conserve this vulnerable group but also, through the protection of these important organisms, will offer wider benefits to freshwater ecosystems.
The pentose phosphate pathway (PPP) is a fundamental component of cellular metabolism. The PPP is important to maintain carbon homoeostasis, to provide precursors for nucleotide and amino acid biosynthesis, to provide reducing molecules for anabolism, and to defeat oxidative stress. The PPP shares reactions with the Entner-Doudoroff pathway and Calvin cycle and divides into an oxidative and non-oxidative branch. The oxidative branch is highly active in most eukaryotes and converts glucose 6-phosphate into carbon dioxide, ribulose 5-phosphate and NADPH. The latter function is critical to maintain redox balance under stress situations, when cells proliferate rapidly, in ageing, and for the 'Warburg effect' of cancer cells. The non-oxidative branch instead is virtually ubiquitous, and metabolizes the glycolytic intermediates fructose 6-phosphate and glyceraldehyde 3-phosphate as well as sedoheptulose sugars, yielding ribose 5-phosphate for the synthesis of nucleic acids and sugar phosphate precursors for the synthesis of amino acids. Whereas the oxidative PPP is considered unidirectional, the non-oxidative branch can supply glycolysis with intermediates derived from ribose 5-phosphate and vice versa, depending on the biochemical demand. These functions require dynamic regulation of the PPP pathway that is achieved through hierarchical interactions between transcriptome, proteome and metabolome. Consequently, the biochemistry and regulation of this pathway, while still unresolved in many cases, are archetypal for the dynamics of the metabolic network of the cell. In this comprehensive article we review seminal work that led to the discovery and description of the pathway that date back now for 80 years, and address recent results about genetic and metabolic mechanisms that regulate its activity. These biochemical principles are discussed in the context of PPP deficiencies causing metabolic disease and the role of this pathway in biotechnology, bacterial and parasite infections, neurons, stem cell potency and cancer metabolism.
The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub‐disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub‐disciplines hampers potential meta‐analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo‐diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information. Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo‐diversity metrics based on their mathematical form within these three dimensions and identify ‘anchor’ representatives: for α‐diversity metrics these are PD (Faith's phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices.
The ecological impacts of nighttime light pollution have been a longstanding source of concern, accentuated by realized and projected growth in electrical lighting. As human communities and lighting technologies develop, artificial light increasingly modifies natural light regimes by encroaching on dark refuges in space, in time, and across wavelengths. A wide variety of ecological implications of artificial light have been identified. However, the primary research to date is largely focused on the disruptive influence of nighttime light on higher vertebrates, and while comprehensive reviews have been compiled along taxonomic lines and within specific research domains, the subject is in need of synthesis within a common mechanistic framework. Here we propose such a framework that focuses on the cross‐factoring of the ways in which artificial lighting alters natural light regimes (spatially, temporally, and spectrally), and the ways in which light influences biological systems, particularly the distinction between light as a resource and light as an information source. We review the evidence for each of the combinations of this cross‐factoring. As artificial lighting alters natural patterns of light in space, time and across wavelengths, natural patterns of resource use and information flows may be disrupted, with downstream effects to the structure and function of ecosystems. This review highlights: ( i ) the potential influence of nighttime lighting at all levels of biological organisation (from cell to ecosystem); ( ii ) the significant impact that even low levels of nighttime light pollution can have; and ( iii ) the existence of major research gaps, particularly in terms of the impacts of light at population and ecosystem levels, identification of intensity thresholds, and the spatial extent of impacts in the vicinity of artificial lights.
DNA barcoding is currently a widely used and effective tool that enables rapid and accurate identification of plant species; however, none of the available loci work across all species. Because single‐locus DNA barcodes lack adequate variations in closely related taxa, recent barcoding studies have placed high emphasis on the use of whole‐chloroplast genome sequences which are now more readily available as a consequence of improving sequencing technologies. While chloroplast genome sequencing can already deliver a reliable barcode for accurate plant identification it is not yet resource‐effective and does not yet offer the speed of analysis provided by single‐locus barcodes to unspecialized laboratory facilities. Here, we review the development of candidate barcodes and discuss the feasibility of using the chloroplast genome as a super‐barcode. We advocate a new approach for DNA barcoding that, for selected groups of taxa, combines the best use of single‐locus barcodes and super‐barcodes for efficient plant identification. Specific barcodes might enhance our ability to distinguish closely related plants at the species and population levels.
Biodiversity is unevenly distributed on Earth and hotspots of biodiversity are often associated with areas that have undergone orogenic activity during recent geological history (i.e. tens of millions of years). Understanding the underlying processes that have driven the accumulation of species in some areas and not in others may help guide prioritization in conservation and may facilitate forecasts on ecosystem services under future climate conditions. Consequently, the study of the origin and evolution of biodiversity in mountain systems has motivated growing scientific interest. Despite an increasing number of studies, the origin and evolution of diversity hotspots associated with the Qinghai‐Tibetan Plateau ( QTP ) remains poorly understood. We review literature related to the diversification of organisms linked to the uplift of the QTP . To promote hypothesis‐based research, we provide a geological and palaeoclimatic scenario for the region of the QTP and argue that further studies would benefit from providing a complete set of complementary analyses (molecular dating, biogeographic, and diversification rates analyses) to test for a link between organismic diversification and past geological and climatic changes in this region. In general, we found that the contribution of biological interchange between the QTP and other hotspots of biodiversity has not been sufficiently studied to date. Finally, we suggest that the biological consequences of the uplift of the QTP would be best understood using a meta‐analysis approach, encompassing studies on a variety of organisms (plants and animals) from diverse habitats (forests, meadows, rivers), and thermal belts (montane, subalpine, alpine, nival). Since the species diversity in the QTP region is better documented for some organismic groups than for others, we suggest that baseline taxonomic work should be promoted.
Understanding how communities of living organisms assemble has been a central question in ecology since the early days of the discipline. Disentangling the different processes involved in community assembly is not only interesting in itself but also crucial for an understanding of how communities will behave under future environmental scenarios. The traditional concept of assembly rules reflects the notion that species do not co‐occur randomly but are restricted in their co‐occurrence by interspecific competition. This concept can be redefined in a more general framework where the co‐occurrence of species is a product of chance, historical patterns of speciation and migration, dispersal, abiotic environmental factors, and biotic interactions, with none of these processes being mutually exclusive. Here we present a survey and meta‐analyses of 59 papers that compare observed patterns in plant communities with null models simulating random patterns of species assembly. According to the type of data under study and the different methods that are applied to detect community assembly, we distinguish four main types of approach in the published literature: species co‐occurrence, niche limitation, guild proportionality and limiting similarity. Results from our meta‐analyses suggest that non‐random co‐occurrence of plant species is not a widespread phenomenon. However, whether this finding reflects the individualistic nature of plant communities or is caused by methodological shortcomings associated with the studies considered cannot be discerned from the available metadata. We advocate that more thorough surveys be conducted using a set of standardized methods to test for the existence of assembly rules in data sets spanning larger biological and geographical scales than have been considered until now. We underpin this general advice with guidelines that should be considered in future assembly rules research. This will enable us to draw more accurate and general conclusions about the non‐random aspect of assembly in plant communities.
Global increases in environmental noise levels – arising from expansion of human populations, transportation networks, and resource extraction – have catalysed a recent surge of research into the effects of noise on wildlife. Synthesising a coherent understanding of the biological consequences of noise from this literature is challenging. Taxonomic groups vary in auditory capabilities. A wide range of noise sources and exposure levels occur, and many kinds of biological responses have been observed, ranging from individual behaviours to changes in ecological communities. Also, noise is one of several environmental effects generated by human activities, so researchers must contend with potentially confounding explanations for biological responses. Nonetheless, it is clear that noise presents diverse threats to species and ecosystems and salient patterns are emerging to help inform future natural resource‐management decisions. We conducted a systematic and standardised review of the scientific literature published from 1990 to 2013 on the effects of anthropogenic noise on wildlife, including both terrestrial and aquatic studies. Research to date has concentrated predominantly on E uropean and N orth A merican species that rely on vocal communication, with approximately two‐thirds of the data set focussing on songbirds and marine mammals. The majority of studies documented effects from noise, including altered vocal behaviour to mitigate masking, reduced abundance in noisy habitats, changes in vigilance and foraging behaviour, and impacts on individual fitness and the structure of ecological communities. This literature survey shows that terrestrial wildlife responses begin at noise levels of approximately 40 dBA , and 20% of papers documented impacts below 50 dBA . Our analysis highlights the utility of existing scientific information concerning the effects of anthropogenic noise on wildlife for predicting potential outcomes of noise exposure and implementing meaningful mitigation measures. Future research directions that would support more comprehensive predictions regarding the magnitude and severity of noise impacts include: broadening taxonomic and geographical scope, exploring interacting stressors, conducting larger‐scale studies, testing mitigation approaches, standardising reporting of acoustic metrics, and assessing the biological response to noise‐source removal or mitigation. The broad volume of existing information concerning the effects of anthropogenic noise on wildlife offers a valuable resource to assist scientists, industry, and natural‐resource managers in predicting potential outcomes of noise exposure.
Old‐growth tropical forests are being extensively deforested and fragmented worldwide. Yet forest recovery through succession has led to an expansion of secondary forests in human‐modified tropical landscapes ( HMTLs ). Secondary forests thus emerge as a potential repository for tropical biodiversity, and also as a source of essential ecosystem functions and services in HMTLs . Such critical roles are controversial, however, as they depend on successional, landscape and socio‐economic dynamics, which can vary widely within and across landscapes and regions. Understanding the main drivers of successional pathways of disturbed tropical forests is critically needed for improving management, conservation, and restoration strategies. Here, we combine emerging knowledge from tropical forest succession, forest fragmentation and landscape ecology research to identify the main driving forces shaping successional pathways at different spatial scales. We also explore causal connections between land‐use dynamics and the level of predictability of successional pathways, and examine potential implications of such connections to determine the importance of secondary forests for biodiversity conservation in HMTLs . We show that secondary succession ( SS ) in tropical landscapes is a multifactorial phenomenon affected by a myriad of forces operating at multiple spatio‐temporal scales. SS is relatively fast and more predictable in recently modified landscapes and where well‐preserved biodiversity‐rich native forests are still present in the landscape. Yet the increasing variation in landscape spatial configuration and matrix heterogeneity in landscapes with intermediate levels of disturbance increases the uncertainty of successional pathways. In landscapes that have suffered extensive and intensive human disturbances, however, succession can be slow or arrested, with impoverished assemblages and reduced potential to deliver ecosystem functions and services. We conclude that: ( i ) succession must be examined using more comprehensive explanatory models, providing information about the forces affecting not only the presence but also the persistence of species and ecological groups, particularly of those taxa expected to be extirpated from HMTLs ; ( ii ) SS research should integrate new aspects from forest fragmentation and landscape ecology research to address accurately the potential of secondary forests to serve as biodiversity repositories; and ( iii ) secondary forest stands, as a dynamic component of HMTLs , must be incorporated as key elements of conservation planning; i.e. secondary forest stands must be actively managed (e.g. using assisted forest restoration) according to conservation goals at broad spatial scales.
Well‐designed and effectively managed networks of marine reserves can be effective tools for both fisheries management and biodiversity conservation. Connectivity, the demographic linking of local populations through the dispersal of individuals as larvae, juveniles or adults, is a key ecological factor to consider in marine reserve design, since it has important implications for the persistence of metapopulations and their recovery from disturbance. For marine reserves to protect biodiversity and enhance populations of species in fished areas, they must be able to sustain focal species (particularly fishery species) within their boundaries, and be spaced such that they can function as mutually replenishing networks whilst providing recruitment subsidies to fished areas. Thus the configuration (size, spacing and location) of individual reserves within a network should be informed by larval dispersal and movement patterns of the species for which protection is required. In the past, empirical data regarding larval dispersal and movement patterns of adults and juveniles of many tropical marine species have been unavailable or inaccessible to practitioners responsible for marine reserve design. Recent empirical studies using new technologies have also provided fresh insights into movement patterns of many species and redefined our understanding of connectivity among populations through larval dispersal. Our review of movement patterns of 34 families (210 species) of coral reef fishes demonstrates that movement patterns (home ranges, ontogenetic shifts and spawning migrations) vary among and within species, and are influenced by a range of factors (e.g. size, sex, behaviour, density, habitat characteristics, season, tide and time of day). Some species move <0.1–0.5 km (e.g. damselfishes, butterflyfishes and angelfishes), <0.5–3 km (e.g. most parrotfishes, goatfishes and surgeonfishes) or 3–10 km (e.g. large parrotfishes and wrasses), while others move tens to hundreds (e.g. some groupers, emperors, snappers and jacks) or thousands of kilometres (e.g. some sharks and tuna). Larval dispersal distances tend to be <5–15 km, and self‐recruitment is common. Synthesising this information allows us, for the first time, to provide species, specific advice on the size, spacing and location of marine reserves in tropical marine ecosystems to maximise benefits for conservation and fisheries management for a range of taxa. We recommend that: ( i ) marine reserves should be more than twice the size of the home range of focal species (in all directions), thus marine reserves of various sizes will be required depending on which species require protection, how far they move, and if other effective protection is in place outside reserves; ( ii ) reserve spacing should be <15 km, with smaller reserves spaced more closely; and ( iii ) marine reserves should include habitats that are critical to the life history of focal species (e.g. home ranges, nursery grounds, migration corridors and spawning aggregations), and be located to accommodate movement patterns among these. We also provide practical advice for practitioners on how to use this information to design, evaluate and monitor the effectiveness of marine reserve networks within broader ecological, socioeconomic and management contexts.
The discovery that an individual may be constrained, and even behave sub‐optimally, because of its personality type has fundamental implications for understanding individual‐ to group‐level processes. Despite recent interest in the study of animal personalities within behavioural ecology, the field is fraught with conceptual and methodological difficulties inherent in any young discipline. We review the current agreement of definitions and methods used in personality studies across taxa and systems, and find that current methods risk misclassifying traits. Fortunately, these problems have been faced before by other similar fields during their infancy, affording important opportunities to learn from past mistakes. We review the tools that were developed to overcome similar methodological problems in psychology. These tools emphasise the importance of attempting to measure animal personality traits using multiple tests and the care that needs to be taken when interpreting correlations between personality traits or their tests. Accordingly, we suggest an integrative theoretical framework that incorporates these tools to facilitate a robust and unified approach in the study of animal personality.
Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly, NHST does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. All biologists should be ultimately interested in biological importance, which may be assessed using the magnitude of an effect, but not its statistical significance. Therefore, we advocate presentation of measures of the magnitude of effects (i.e. effect size statistics) and their confidence intervals (CIs) in all biological journals. Combined use of an effect size and its CIs enables one to assess the relationships within data more effectively than the use of p values, regardless of statistical significance. In addition, routine presentation of effect sizes will encourage researchers to view their results in the context of previous research and facilitate the incorporation of results into future meta-analysis, which has been increasingly used as the standard method of quantitative review in biology. In this article, we extensively discuss two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta-analysis. However, our focus on these standardised effect size statistics does not mean unstandardised effect size statistics (e.g. mean difference and regression coefficient) are less important. We provide potential solutions for four main technical problems researchers may encounter when calculating effect size and CIs: (1) when covariates exist, (2) when bias in estimating effect size is possible, (3) when data have non-normal error structure and/or variances, and (4) when data are non-independent. Although interpretations of effect sizes are often difficult, we provide some pointers to help researchers. This paper serves both as a beginner's instruction manual and a stimulus for changing statistical practice for the better in the biological sciences.
Winter is a key driver of individual performance, community composition, and ecological interactions in terrestrial habitats. Although climate change research tends to focus on performance in the growing season, climate change is also modifying winter conditions rapidly. Changes to winter temperatures, the variability of winter conditions, and winter snow cover can interact to induce cold injury, alter energy and water balance, advance or retard phenology, and modify community interactions. Species vary in their susceptibility to these winter drivers, hampering efforts to predict biological responses to climate change. Existing frameworks for predicting the impacts of climate change do not incorporate the complexity of organismal responses to winter. Here, we synthesise organismal responses to winter climate change, and use this synthesis to build a framework to predict exposure and sensitivity to negative impacts. This framework can be used to estimate the vulnerability of species to winter climate change. We describe the importance of relationships between winter conditions and performance during the growing season in determining fitness, and demonstrate how summer and winter processes are linked. Incorporating winter into current models will require concerted effort from theoreticians and empiricists, and the expansion of current growing‐season studies to incorporate winter.
Connectivity is classically considered an emergent property of landscapes encapsulating individuals' flows across space. However, its operational use requires a precise understanding of why and how organisms disperse. Such movements, and hence landscape connectivity, will obviously vary according to both organism properties and landscape features. We review whether landscape connectivity estimates could gain in both precision and generality by incorporating three fundamental outcomes of dispersal theory. Firstly, dispersal is a multi‐causal process; its restriction to an ‘escape reaction’ to environmental unsuitability is an oversimplification, as dispersing individuals can leave excellent quality habitat patches or stay in poor‐quality habitats according to the relative costs and benefits of dispersal and philopatry. Secondly, species, populations and individuals do not always react similarly to those cues that trigger dispersal, which sometimes results in contrasting dispersal strategies. Finally, dispersal is a major component of fitness and is thus under strong selective pressures, which could generate rapid adaptations of dispersal strategies. Such evolutionary responses will entail spatiotemporal variation in landscape connectivity. We thus strongly recommend the use of genetic tools to: ( i ) assess gene flow intensity and direction among populations in a given landscape; and ( ii ) accurately estimate landscape features impacting gene flow, and hence landscape connectivity. Such approaches will provide the basic data for planning corridors or stepping stones aiming at (re)connecting local populations of a given species in a given landscape. This strategy is clearly species‐ and landscape‐specific. But we suggest that the ecological network in a given landscape could be designed by stacking up such linkages designed for several species living in different ecosystems. This procedure relies on the use of umbrella species that are representative of other species living in the same ecosystem.