The ecology of differences: assessing community assembly with trait and evolutionary distances

Species enter and persist in local communities because of their ecological fit to local conditions, and recently, ecologists have moved from measuring diversity as species richness and evenness, to using measures that reflect species ecological differences. There are two principal approaches for quantifying species ecological differences: functional (trait‐based) and phylogenetic pairwise distances between species. Both approaches have produced new ecological insights, yet at the same time methodological issues and assumptions limit them. Traits and phylogeny may provide different, and perhaps complementary, information about species' differences. To adequately test assembly hypotheses, a framework integrating the information provided by traits and phylogenies is required. We propose an intuitive measure for combining functional and phylogenetic pairwise distances, which provides a useful way to assess how functional and phylogenetic distances contribute to understanding patterns of community assembly. Here, we show that both traits and phylogeny inform community assembly patterns in alpine plant communities across an elevation gradient, because they represent complementary information. Differences in historical selection pressures have produced variation in the strength of the trait‐phylogeny correlation, and as such, integrating traits and phylogeny can enhance the ability to detect assembly patterns across habitats or environmental gradients.     

Re‐approaching the small island effect

Aim To propose a new approach to the small island effect (SIE) and a simple mathematical procedure for the estimation of its upper limit. The main feature of the SIE is that below an upper size threshold an increase of species number with increase of area in small islands is not observed. Location Species richness patterns from different taxa and insular systems are analysed. Methods Sixteen different data sets from 12 studies are analysed. Path analysis was used for the estimation of the upper limit of the SIE. We studied each data set in order to detect whether there was a certain island size under which the direct effects of area were eliminated. This detection was carried out through the sequential exclusion of islands from the largest to the smallest. For the cases where an SIE was detected, a log‐log plot of species number against area is presented. The relationships between habitat diversity, species number and area are studied within the limits of the SIE. In previous studies only area was used for the detection of the SIE, whereas we also encompass habitat diversity, a parameter with well documented influence on species richness, especially at small scales. Results An SIE was detected in six out of the 16 studied cases. The upper limit of the SIE varies, depending on the characteristics of the taxon and the archipelago under study. In general, the values of the upper limit of the SIE calculated according to the approach undertaken in our study differ from the values calculated in previous studies. Main conclusions Although the classical species–area models have been used to estimate the upper limit of the SIE, we propose that the detection of this phenomenon should be undertaken independently from the species–area relationship, so that the net effects of area are calculated excluding the surrogate action of area on other variables, such as environmental heterogeneity. The SIE appears when and where area ceases to influence species richness directly. There are two distinct SIE patterns: (1) the classical SIE where both the direct and indirect effects of area are eliminated and (2) the cryptic SIE where area affects species richness indirectly. Our approach offers the opportunity of studying the different factors influencing biodiversity on small scales more accurately. The SIE cannot be considered a general pattern with fixed behaviour that can be described by the same model for different island groups and taxa. The SIE should be recognized as a genuine but idiosyncratic phenomenon.     

Critical review of NGS analyses for de novo genotyping multigene families

The genotyping of highly polymorphic multigene families across many individuals used to be a particularly challenging task because of methodological limitations associated with traditional approaches. Next‐generation sequencing (NGS) can overcome most of these limitations, and it is increasingly being applied in population genetic studies of multigene families. Here, we critically review NGS bioinformatic approaches that have been used to genotype the major histocompatibility complex (MHC) immune genes, and we discuss how the significant advances made in this field are applicable to population genetic studies of gene families. Increasingly, approaches are introduced that apply thresholds of sequencing depth and sequence similarity to separate alleles from methodological artefacts. We explain why these approaches are particularly sensitive to methodological biases by violating fundamental genotyping assumptions. An alternative strategy that utilizes ultra‐deep sequencing (hundreds to thousands of sequences per amplicon) to reconstruct genotypes and applies statistical methods on the sequencing depth to separate alleles from artefacts appears to be more robust. Importantly, the ‘degree of change’ (DOC) method avoids using arbitrary cut‐off thresholds by looking for statistical boundaries between the sequencing depth for alleles and artefacts, and hence, it is entirely repeatable across studies. Although the advances made in generating NGS data are still far ahead of our ability to perform reliable processing, analysis and interpretation, the community is developing statistically rigorous protocols that will allow us to address novel questions in evolution, ecology and genetics of multigene families. Future developments in third‐generation single molecule sequencing may potentially help overcome problems that still persist in de novo multigene amplicon genotyping when using current second‐generation sequencing approaches.     

Statistical methods in spatial genetics

The joint analysis of spatial and genetic data is rapidly becoming the norm in population genetics. More and more studies explicitly describe and quantify the spatial organization of genetic variation and try to relate it to underlying ecological processes. As it has become increasingly difficult to keep abreast with the latest methodological developments, we review the statistical toolbox available to analyse population genetic data in a spatially explicit framework. We mostly focus on statistical concepts but also discuss practical aspects of the analytical methods, highlighting not only the potential of various approaches but also methodological pitfalls.     

Managing Nordic boreal forest landscapes for biodiversity: ecological and economic perspectives

More conservation-oriented forest management practices have been implemented recently in the Nordic countries. The goal of this ecological forest landscape management is to reconcile the commercial harvesting of boreal forests with biodiversity conservation. Management aims at maintaining viable populations of the full array of naturally occurring species in an area while still keeping the timber flow as maximal as possible. Basic ecological tools of managing landscape for biodiversity are (1) to mimic natural disturbance regimes, (2) to set aside areas in permanent or temporary nature reserves, and (3) to enhance dispersal of organisms by creating habitat corridors and stepping stones. The ecological basis of this management system is not well founded, and much more empirical and theoretical research is needed to justify and further develop forest landscape management. It has also proved difficult to assess the economic consequences of more conservation-oriented forest management because the market economy largely fails to give value to forest products other than fibre. Considerable methodological development in the valuation of non-timber goods has occurred in recent years, but there is still much controversy over the justification of the valuation procedure in principle. It seems that both economic and moral approaches to the issue of valuation are inseparable from the choices and decisions we have to make about ecological systems. Perhaps the most fruitful outcome can be achieved by using moral and economic arguments in parallel.     

Changes in home range sizes and population densities of carnivore species along the natural to urban habitat gradient

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Local and regional species richness in communities of surface-dwelling grassland Collembola: indication of species saturation

The relationship of local (LSR) versus regional species richness (RSR) provides an insight into patterns of species diversity. We examined communities of surface-dwelling Collembola in ten differently sized, temperate dry grasslands. To register genuine manifestations of saturation or proportional sampling, accurate determination of species pools is essential. Therefore. we applied the first-order jackknife as a species-richness estimator for LSR and introduce here a method for defining a range within which the real RSR probably lies. Our data exhibited similar levels of local Collembolan species richness across all regions, largely independent of regional richness. This curvilinear relationship between LSR and RSR indicates that a limit is present for the number of species that can locally coexist, suggesting local interactions and community saturation. We discuss several conditions that may cause pseudo-proportionality or pseudosaturation, i.e. artificial relationships between LSR and RSR, Furthermore, we test the LSR-RSR relationship for possible effects of autocorrelation.     

Exploring the Function-Location Nexus: Using Multiple Lines of Evidence in Defining the Subcellular Location of Plant Proteins

Defining the function of all proteins in an organism is one of the major objectives for biology in the coming decades. Here, we assess approaches used to determine subcellular protein location and discuss the relationship between protein location and function. It is important to recognize that targeting, accumulation, and the site of function are not necessarily interchangeable terms with respect to defining the location of a protein. Some proteins have tightly defined locations, whereas others have low specificity targeting and complex accumulation patterns. Location may be essential for function in some cases, but it may be much less important for other proteins. There is no single approach that can be considered entirely adequate for defining the in vivo location of all proteins. By combining approaches that assess targeting and accumulation of proteins, more confidence can be gained about localization. The strengths and weaknesses of different localization technologies are summarized, and some guidelines for performing combined targeting and accumulation assays are outlined.     

Sexual selection and speciation: the comparative evidence revisited

The spectacular diversity in sexually selected traits in the animal kingdom has inspired the hypothesis that sexual selection can promote species divergence. In recent years, several studies have attempted to test this idea by correlating species richness with estimates of sexual selection across phylogenies. These studies have yielded mixed results and it remains unclear whether the comparative evidence can be taken as generally supportive. Here, we conduct a meta‐analysis of the comparative evidence and find a small but significant positive overall correlation between sexual selection and speciation rate. However, we also find that effect size estimates are influenced by methodological choices. Analyses that included deeper phylogenetic nodes yielded weaker correlations, and different proxies for sexual selection showed different relationships with species richness. We discuss the biological and methodological implications of these findings. We argue that progress requires more representative sampling and justification of chosen proxies for sexual selection and speciation rate, as well as more mechanistic approaches.     

Guidelines for a priori grouping of species in hierarchical community models

Recent methodological advances permit the estimation of species richness and occurrences for rare species by linking species‐level occurrence models at the community level. The value of such methods is underscored by the ability to examine the influence of landscape heterogeneity on species assemblages at large spatial scales. A salient advantage of community‐level approaches is that parameter estimates for data‐poor species are more precise as the estimation process “borrows” from data‐rich species. However, this analytical benefit raises a question about the degree to which inferences are dependent on the implicit assumption of relatedness among species. Here, we assess the sensitivity of community/group‐level metrics, and individual‐level species inferences given various classification schemes for grouping species assemblages using multispecies occurrence models. We explore the implications of these groupings on parameter estimates for avian communities in two ecosystems: tropical forests in Puerto Rico and temperate forests in northeastern United States. We report on the classification performance and extent of variability in occurrence probabilities and species richness estimates that can be observed depending on the classification scheme used. We found estimates of species richness to be most precise and to have the best predictive performance when all of the data were grouped at a single community level. Community/group‐level parameters appear to be heavily influenced by the grouping criteria, but were not driven strictly by total number of detections for species. We found different grouping schemes can provide an opportunity to identify unique assemblage responses that would not have been found if all of the species were analyzed together. We suggest three guidelines: (1) classification schemes should be determined based on study objectives; (2) model selection should be used to quantitatively compare different classification approaches; and (3) sensitivity of results to different classification approaches should be assessed. These guidelines should help researchers apply hierarchical community models in the most effective manner.     

Spatiotemporal landscape genetics: Investigating ecology and evolution through space and time

Genetic time‐series data from historical samples greatly facilitate inference of past population dynamics and species evolution. Yet, although climate and landscape change are often touted as post‐hoc explanations of biological change, our understanding of past climate and landscape change influences on evolutionary processes is severely hindered by the limited application of methods that directly relate environmental change to species dynamics through time. Increased integration of spatiotemporal environmental and genetic data will revolutionize the interpretation of environmental influences on past population processes and the quantification of recent anthropogenic impacts on species, and vastly improve prediction of species responses under future climate change scenarios, yielding widespread revelations across evolutionary biology, landscape ecology and conservation genetics. This review encourages greater use of spatiotemporal landscape genetic analyses that explicitly link landscape, climate and genetic data through time by providing an overview of analytical approaches for integrating historical genetic and environmental data in five key research areas: population genetic structure, demography, phylogeography, metapopulation connectivity and adaptation. We also include a tabular summary of key methodological information, suggest approaches for mitigating the particular difficulties in applying these techniques to ancient DNA and palaeoclimate data, and highlight areas for future methodological development.     

Ecological and methodological drivers of species’ distribution and phenology responses to climate change

Climate change is shifting species’ distribution and phenology. Ecological traits, such as mobility or reproductive mode, explain variation in observed rates of shift for some taxa. However, estimates of relationships between traits and climate responses could be influenced by how responses are measured. We compiled a global data set of 651 published marine species’ responses to climate change, from 47 papers on distribution shifts and 32 papers on phenology change. We assessed the relative importance of two classes of predictors of the rate of change, ecological traits of the responding taxa and methodological approaches for quantifying biological responses. Methodological differences explained 22% of the variation in range shifts, more than the 7.8% of the variation explained by ecological traits. For phenology change, methodological approaches accounted for 4% of the variation in measurements, whereas 8% of the variation was explained by ecological traits. Our ability to predict responses from traits was hindered by poor representation of species from the tropics, where temperature isotherms are moving most rapidly. Thus, the mean rate of distribution change may be underestimated by this and other global syntheses. Our analyses indicate that methodological approaches should be explicitly considered when designing, analysing and comparing results among studies. To improve climate impact studies, we recommend that (1) reanalyses of existing time series state how the existing data sets may limit the inferences about possible climate responses; (2) qualitative comparisons of species’ responses across different studies be limited to studies with similar methodological approaches; (3) meta‐analyses of climate responses include methodological attributes as covariates; and (4) that new time series be designed to include the detection of early warnings of change or ecologically relevant change. Greater consideration of methodological attributes will improve the accuracy of analyses that seek to quantify the role of climate change in species’ distribution and phenology changes.     

The ecological and evolutionary implications of merging different types of networks

Interactions among species drive the ecological and evolutionary processes in ecological communities. These interactions are effectively key components of biodiversity. Studies that use a network approach to study the structure and dynamics of communities of interacting species have revealed many patterns and associated processes. Historically these studies were restricted to trophic interactions, although network approaches are now used to study a wide range of interactions, including for example the reproductive mutualisms. However, each interaction type remains studied largely in isolation from others. Merging the various interaction types within a single integrative framework is necessary if we want to further our understanding of the ecological and evolutionary dynamics of communities. Dividing the networks up is a methodological convenience as in the field the networks occur together in space and time and will be linked by shared species. Herein, we outline a conceptual framework for studying networks composed of more than one type of interaction, highlighting key questions and research areas that would benefit from their study.     

Experimental evidence of long‐term reproductive costs in a colonial nesting seabird

Trade‐offs between current and future reproduction are central to the evolution of life histories. Experiments that manipulate brood size provide an effective approach to investigating future costs of current reproduction. Most manipulative studies to date, however, have addressed only the short‐term effects of brood size manipulation. Our goal was to determine whether survival or breeding costs of reproduction in a long‐lived species manifest beyond the subsequent breeding season. To this end, we investigated long‐term survival and breeding effects of a multi‐year reproductive cost experiment conducted on black‐legged kittiwakes Rissa tridactyla, a long‐lived colonial nesting seabird. We used multi‐state capture–recapture modeling to assess hypotheses regarding the role of experimentally reduced breeding effort and other factors, including climate phase and colony size and productivity, on future survival and breeding probabilities during the 16‐yr period following the experiment. We found that forced nest failures had a positive effect on breeding probability over time, but had no effect on long‐term survival. This apparent canalization of survival suggests that adult survival is the most important parameter influencing fitness in this long‐lived species, and that adults should pay reproductive costs in ways that do not compromise this critical life history parameter. When declines in adult survival rate are observed, they may indicate populations of conservation concern.     

Hare's affairs: Lessons learnt from a noninvasive genetic monitoring for tracking mountain hare individuals

Systematic monitoring of individuals and their abundance over time has become an important tool to provide information for conservation. For genetic monitoring studies, noninvasive sampling has emerged as a valuable approach, particularly so for elusive or rare animals. Here, we present the 5‐year results of an ongoing noninvasive genetic monitoring of mountain hares (Lepus timidus) in a protected area in the Swiss Alps. We used nuclear microsatellites and a sex marker to identify individuals and assign species to noninvasively collected feces samples. Through including a marker for sex identification, we were able to assess sex ratio changes and sex‐specific demographic parameters over time. Male abundance in the area showed high fluctuations and apparent survival for males was lower than for females. Generally, males and females showed only little temporary migration into and out of the study area. Additionally, using genotyped tissue samples from mountain hares, European hares (Lepus europaeus) and their hybrids, we were able to provide evidence for the first occurrence of a European hare in the study area at an elevation of 2,300 m a.s.l. in spring 2016. For future monitoring studies, we suggest to include complementary analysis methods to reliably infer species identities of the individuals analyzed and, thus, not only monitor mountain hare individual abundance, but also assess the potential threats given through competitive exclusion by and hybridization with the European hare.     

Integrating molecular and morphological approaches for characterizing parasite cryptic species: implications for parasitology

Herein we review theoretical and methodological considerations important for finding and delimiting cryptic species of parasites (species that are difficult to recognize using traditional systematic methods). Applications of molecular data in empirical investigations of cryptic species are discussed from an historical perspective, and we evaluate advantages and disadvantages of approaches that have been used to date. Developments concerning the theory and practice of species delimitation are emphasized because theory is critical to interpretation of data. The advantages and disadvantages of different molecular methodologies, including the number and kind of loci, are discussed relative to tree-based approaches for detecting and delimiting cryptic species. We conclude by discussing some implications that cryptic species have for research programmes in parasitology, emphasizing that careful attention to the theory and operational practices involved in finding, delimiting, and describing new species (including cryptic species) is essential, not only for fully characterizing parasite biodiversity and broader aspects of comparative biology such as systematics, evolution, ecology and biogeography, but to applied research efforts that strive to improve development and understanding of epidemiology, diagnostics, control and potential eradication of parasitic diseases.     

Environmental changes define ecological limits to species richness and reveal the mode of macroevolutionary competition

Co‐dependent geological and climatic changes obscure how species interact in deep time. The interplay between these environmental factors makes it hard to discern whether ecological competition exerts an upper limit on species richness. Here, using the exceptional fossil record of Cenozoic Era macroperforate planktonic foraminifera, we assess the evidence for alternative modes of macroevolutionary competition. Our models support an environmentally dependent macroevolutionary form of contest competition that yields finite upper bounds on species richness. Models of biotic competition assuming unchanging environmental conditions were overwhelmingly rejected. In the best‐supported model, temperature affects the per‐lineage diversification rate, while both temperature and an environmental driver of sediment accumulation defines the upper limit. The support for contest competition implies that incumbency constrains species richness by restricting niche availability, and that the number of macroevolutionary niches varies as a function of environmental changes.     

Comparing species interaction networks along environmental gradients

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co‐variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant–hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis‐based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients.     

Analysing ecological networks of species interactions

Network approaches to ecological questions have been increasingly used, particularly in recent decades. The abstraction of ecological systems – such as communities – through networks of interactions between their components indeed provides a way to summarize this information with single objects. The methodological framework derived from graph theory also provides numerous approaches and measures to analyze these objects and can offer new perspectives on established ecological theories as well as tools to address new challenges. However, prior to using these methods to test ecological hypotheses, it is necessary that we understand, adapt, and use them in ways that both allow us to deliver their full potential and account for their limitations. Here, we attempt to increase the accessibility of network approaches by providing a review of the tools that have been developed so far, with – what we believe to be – their appropriate uses and potential limitations. This is not an exhaustive review of all methods and metrics, but rather, an overview of tools that are robust, informative, and ecologically sound. After providing a brief presentation of species interaction networks and how to build them in order to summarize ecological information of different types, we then classify methods and metrics by the types of ecological questions that they can be used to answer from global to local scales, including methods for hypothesis testing and future perspectives. Specifically, we show how the organization of species interactions in a community yields different network structures (e.g., more or less dense, modular or nested), how different measures can be used to describe and quantify these emerging structures, and how to compare communities based on these differences in structures. Within networks, we illustrate metrics that can be used to describe and compare the functional and dynamic roles of species based on their position in the network and the organization of their interactions as well as associated new methods to test the significance of these results. Lastly, we describe potential fruitful avenues for new methodological developments to address novel ecological questions.