The role of seasonal timing and phenological shifts for species coexistence

Shifts in the phenologies of coexistence species are altering the temporal structure of natural communities worldwide. However, predicting how these changes affect the structure and long‐term dynamics of natural communities is challenging because phenology and coexistence theory have largely proceeded independently. Here, I propose a conceptual framework that incorporates seasonal timing of species interactions into a well‐studied competition model to examine how changes in phenologies influence long‐term dynamics of natural communities. Using this framework I demonstrate that persistence and coexistence conditions strongly depend on the difference in species’ mean phenologies and how this difference varies across years. Consequently, shifts in mean and interannual variation in relative phenologies of species can fundamentally alter the outcome of interactions and the potential for persistence and coexistence of competing species. These effects can be predicted by how per‐capita effects scale with differences in species’ phenologies. I outline how this approach can be parameterized with empirical systems and discuss how it fits within the context of current coexistence theory. Overall, this synthesis reveals that phenology of species interactions can play a crucial yet currently understudied role in driving coexistence and biodiversity patterns in natural systems and determine how species will respond to future climate change.     

A perspective on match/mismatch of phenology in community contexts

Climate change has significant impacts on phenology of various organisms in a species‐specific manner. Facing this problem, the match/mismatch hypothesis that phenological (a)synchrony with resource availability strongly influences recruitment success of a consumer population has recently received much attention. In this article, we discuss extending the conventional pairwise concept and demonstrate a community module‐based approach as an initial step for exploring community consequences of species‐specific phenological shifts caused by climate change. Our multispecies match/mismatch perspective leads to the prediction that phenological (a)synchrony among interacting species critically affects not only population recruitment of species but also key dynamical features of ecological communities such as trophic cascades, competitive hierarchies, and species coexistence. Explicit identification and consideration of species relationships is therefore desirable for a better understanding of seasonal community dynamics and thus community consequences of climate change‐induced phenological shifts.     

Resilience vs. historical contingency in microbial responses to environmental change

How soil processes such as carbon cycling will respond to future climate change depends on the responses of complex microbial communities, but most ecosystem models assume that microbial functional responses are resilient and can be predicted from simple parameters such as biomass and temperature. Here, we consider how historical contingencies might alter those responses because function depends on prior conditions or biota. Functional resilience can be driven by physiological, community or adaptive shifts; historical contingencies can result from the influence of historical environments or a combination of priority effects and biotic resistance. By modelling microbial population responses to environmental change, we demonstrate that historical environments can constrain soil function with the degree of constraint depending on the magnitude of change in the context of the prior environment. For example microbial assemblages from more constant environments were more sensitive to change leading to poorer functional acclimatisation compared to microbial assemblages from more fluctuating environments. Such historical contingencies can lead to deviations from expected functional responses to climate change as well as local variability in those responses. Our results form a set of interrelated hypotheses regarding soil microbial responses to climate change that warrant future empirical attention.     

Agriculture erases climate‐driven β‐diversity in Neotropical bird communities

Earth is experiencing multiple global changes that will, together, determine the fate of many species. Yet, how biological communities respond to concurrent stressors at local‐to‐regional scales remains largely unknown. In particular, understanding how local habitat conversion interacts with regional climate change to shape patterns in β‐diversity—differences among sites in their species compositions—is critical to forecast communities in the Anthropocene. Here, we study patterns in bird β‐diversity across land‐use and precipitation gradients in Costa Rica. We mapped forest cover, modeled regional precipitation, and collected data on bird community composition, vegetation structure, and tree diversity across 120 sites on 20 farms to answer three questions. First, do bird communities respond more strongly to changes in land use or climate in northwest Costa Rica? Second, does habitat conversion eliminate β‐diversity across climate gradients? Third, does regional climate control how communities respond to habitat conversion and, if so, how? After correcting for imperfect detection, we found that local land‐use determined community shifts along the climate gradient. In forests, bird communities were distinct between sites that differed in vegetation structure or precipitation. In agriculture, however, vegetation structure was more uniform, contributing to 7%–11% less bird turnover than in forests. In addition, bird responses to agriculture and climate were linked: agricultural communities across the precipitation gradient shared more species with dry than wet forest communities. These findings suggest that habitat conversion and anticipated climate drying will act together to exacerbate biotic homogenization.     

Predicting phenology by integrating ecology,evolution and climate science

Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology – the timing of life‐history events. Phenology has well‐demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species’ reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.     

Climatic variables influence the temporal dynamics of an anuran metacommunity in a nonstationary way

Understanding the temporal dynamics of communities is crucial to predict how communities respond to climate change. Several factors can promote variation in phenology among species, including tracking of seasonal resources, adaptive responses to other species, demographic stochasticity, and physiological constraints. The activities of ectothermic vertebrates are sensitive to climatic variations due to the effect of temperature and humidity on species physiology. However, most studies on temporal dynamics have analyzed multi‐year data and do not have resolution to discriminate within‐year patterns that can determine community assembly cycles. Here, we tested the temporal stability and synchrony of calling activity and also how climatic variables influence anuran species composition throughout the year in a metacommunity in the Atlantic Forest of southern Brazil. Using a multivariate method, we described how the relationship between species composition and climatic variables changes through time. The metacommunity showed a weak synchronous spatial pattern, meaning that species responded independently to environmental variation. Interestingly, species composition exhibited a nonstationary response to climate, suggesting that climate affects species composition differently depending on the season. The species‐climate relationship was stronger during the spring, summer, and winter, mainly influenced by temperature, rainfall, and humidity. Thus, temporal community dynamics seem to be mediated by species life‐history traits, in which independent fluctuations promote community stability in temporally varying environments.     

Terrestrial insects and climate change: adaptive responses in key traits

Understanding and predicting how adaptation will contribute to species' resilience to climate change will be paramount to successfully managing biodiversity for conservation, agriculture, and human health‐related purposes. Making predictions that capture how species will respond to climate change requires an understanding of how key traits and environmental drivers interact to shape fitness in a changing world. Current trait‐based models suggest that low‐ to mid‐latitude populations will be most at risk, although these models focus on upper thermal limits, which may not be the most important trait driving species' distributions and fitness under climate change. In this review, we discuss how different traits (stress, fitness and phenology) might contribute and interact to shape insect responses to climate change. We examine the potential for adaptive genetic and plastic responses in these key traits and show that, although there is evidence of range shifts and trait changes, explicit consideration of what underpins these changes, be that genetic or plastic responses, is largely missing. Despite little empirical evidence for adaptive shifts, incorporating adaptation into models of climate change resilience is essential for predicting how species will respond under climate change. We are making some headway, although more data are needed, especially from taxonomic groups outside of Drosophila, and across diverse geographical regions. Climate change responses are likely to be complex, and such complexity will be difficult to capture in laboratory experiments. Moving towards well designed field experiments would allow us to not only capture this complexity, but also study more diverse species.     

Contemporary climate change in the Sonoran Desert favors cold‐adapted species

Impacts of long‐term climate shifts on the dynamics of intact communities within species ranges are not well understood. Here, we show that warming and drying of the Southwestern United States over the last 25 years has corresponded to a shift in the species composition of Sonoran Desert winter annuals, paradoxically favoring species that germinate and grow best in cold temperatures. Winter rains have been arriving later in the season, during December rather than October, leading to the unexpected result that plants are germinating under colder temperatures, shifting community composition to favor slow growing, water‐use efficient, cold‐adapted species. Our results demonstrate how detailed ecophysiological knowledge of individual species, combined with long‐term demographic data, can reveal complex and sometimes unexpected shifts in community composition in response to climate change. Further, these results highlight the potentially overwhelming impact of changes in phenology on the response of biota to a changing climate.     

Historical climate‐change influences modularity and nestedness of pollination networks

The structure of species interaction networks is important for species coexistence, community stability and exposure of species to extinctions. Two widespread structures in ecological networks are modularity, i.e. weakly connected subgroups of species that are internally highly interlinked, and nestedness, i.e. specialist species that interact with a subset of those species with which generalist species also interact. Modularity and nestedness are often interpreted as evolutionary ecological structures that may have relevance for community persistence and resilience against perturbations, such as climate‐change. Therefore, historical climatic fluctuations could influence modularity and nestedness, but this possibility remains untested. This lack of research is in sharp contrast to the considerable efforts to disentangle the role of historical climate‐change and contemporary climate on species distributions, richness and community composition patterns. Here, we use a global database of pollination networks to show that historical climate‐change is at least as important as contemporary climate in shaping modularity and nestedness of pollination networks. Specifically, on the mainland we found a relatively strong negative association between Quaternary climate‐change and modularity, whereas nestedness was most prominent in areas having experienced high Quaternary climate‐change. On islands, Quaternary climate‐change had weak effects on modularity and no effects on nestedness. Hence, for both modularity and nestedness, historical climate‐change has left imprints on the network structure of mainland communities, but had comparably little effect on island communities. Our findings highlight a need to integrate historical climate fluctuations into eco‐evolutionary hypotheses of network structures, such as modularity and nestedness, and then test these against empirical data. We propose that historical climate‐change may have left imprints in the structural organisation of species interactions in an array of systems important for maintaining biological diversity.     

Using bioacoustics to examine shifts in songbird phenology

Monitoring patterns in biodiversity and phenology have become increasingly important given accelerating levels of anthropogenic change. Long‐term monitoring programs have reported earlier occurrence of spring activity, reflecting species response to climate change. Although tracking shifts in spring migration represents a valuable approach to monitoring community‐level consequences of climate change, robust long‐term observations are challenging and costly. Audio recordings and metrics of bioacoustic activity could provide an effective method for monitoring changes in songbird activity and broader biotic interactions. We used 3 years of spring and fall recordings at six sites in Glacier Bay National Park, Alaska, an area experiencing rapid warming and glacial retreat, to examine the utility of bioacoustics to detect changes in songbird phenology. We calculated the Acoustic Complexity Index (ACI), an algorithm representing an index of bird community complexity. Abrupt changes in ACI values from winter to spring corresponded to spring transition, suggesting that ACI may be an effective, albeit coarse metric to detect the arrival of migrating songbirds. The first peak in ACI shifted from April 16 to April 11 from 2012 to 2014. Changes in ACI were less abrupt in the fall due to weather events, suggesting spring recordings are better suited to indicate phenology. To ensure changes in ACI values were detecting real changes in songbird activity, we explored the relationship between ACI and song of three species: varied thrush   (Ixoreus naevius), Pacific wren (Troglodytes pacificus), and ruby‐crowned kinglet (Regulus calendula). ACI was positively related to counts of all species, but most markedly with song of the varied thrush, the most common species in our recordings and a known indicator of forest ecosystem health. We conclude that acoustic recordings paired with bioacoustic indices may be a useful method of monitoring shifts in songbird communities due to climate change and other sources of anthropogenic disturbance.     

Variable flowering phenology and pollinator use in a community suggest future phenological mismatch

Recent anthropogenic climate change is strongly associated with average shifts toward earlier seasonal timing of activity (phenology) in temperate-zone species. Shifts in phenology have the potential to alter ecological interactions, to the detriment of one or more interacting species. Recent models predict that detrimental phenological mismatch may increasingly occur between plants and their pollinators. One way to test this prediction is to examine data from ecological communities that experience large annual weather fluctuations. Taking this approach, we analyzed interactions over a four-year period among 132 plant species and 665 pollinating insect species within a Mediterranean community. For each plant species we recorded onset and duration of flowering and number of pollinator species. Flowering onset varied among years, and a year of earlier flowering of a species tended to be a year of fewer species pollinating its flowers. This relationship was attributable principally to early-flowering species, suggesting that shifts toward earlier phenology driven by climate change may reduce pollination services due to phenological mismatch. Earlier flowering onset of a species also was associated with prolonged flowering duration, but it is not certain that this will counterbalance any negative effects of lower pollinator species richness on plant reproductive success. Among plants with different life histories, annuals were more severely affected by flowering–pollinator mismatches than perennials. Specialized plant species (those attracting a smaller number of pollinator species) did not experience disproportionate interannual fluctuations in phenology. Thus they do not appear to be faced with disproportionate fluctuations in pollinator species richness, contrary to the expectation that specialists are at greatest risk of losing mutualistic interactions because of climate change.     

Predicting insect phenology across space and time

Many species appear to be undergoing shifts in phenology, arising from climate change. To predict the direction and magnitude of future changes requires an understanding of how phenology depends on climatic variation. Species show large‐scale spatial variation in phenology (affected by differentiation among populations) as well as variation in phenology from year‐to‐year at the same site (affected predominantly by local plasticity). Teasing apart spatial and temporal variation in phenology should allow improved predictions of phenology under climate change. This study is the first to quantify large‐scale spatial and temporal variation in the entire emergence pattern of species, and to test the relationships found by predicting future data. We use data from up to 33 years of permanent transect records of butterflies in the United Kingdom to fit and test models for 15 butterfly species. We use generalized additive models to model spatial and temporal variation in the distribution of adult butterflies over the season, allowing us to capture changes in the timing of emergence peaks, relative sizes of peaks and/or number of peaks in a single analysis. We develop these models using data for 1973–2000, and then use them to predict phenologies from 2001 to 2006. For six of our study species, a model with only spatial variation in phenology is the best predictor of the future, implying that these species have limited plasticity. For the remaining nine species, the best predictions come from a model with both spatial and temporal variation in phenology; for four of these, growing degree‐days have similar effects over space and time, implying high levels of plasticity. The results show that statistical phenology models can be used to predict phenology shifts in a second time period, suggesting that it should be feasible to project phenologies under climate change scenarios, at least over modest time scales.     

Spatial predictions at the community level: from current approaches to future frameworks

A fundamental goal of ecological research is to understand and model how processes generate patterns so that if conditions change, changes in the patterns can be predicted. Different approaches have been proposed for modelling species assemblage, but their use to predict spatial patterns of species richness and other community attributes over a range of spatial and temporal scales remains challenging. Different methods emphasize different processes of structuring communities and different goals. In this review, we focus on models that were developed for generating spatially explicit predictions of communities, with a particular focus on species richness, composition, relative abundance and related attributes. We first briefly describe the concepts and theories that span the different drivers of species assembly. A combination of abiotic processes and biotic mechanisms are thought to influence the community assembly process. In this review, we describe four categories of drivers: (i) historical and evolutionary, (ii) environmental, (iii) biotic, and (iv) stochastic. We discuss the different modelling approaches proposed or applied at the community level and examine them from different standpoints, i.e. the theoretical bases, the drivers included, the source data, and the expected outputs, with special emphasis on conservation needs under climate change. We also highlight the most promising novelties, possible shortcomings, and potential extensions of existing methods. Finally, we present new approaches to model and predict species assemblages by reviewing promising ‘integrative frameworks’ and views that seek to incorporate all drivers of community assembly into a unique modelling workflow. We discuss the strengths and weaknesses of these new solutions and how they may hasten progress in community‐level modelling.     

Projecting marine species range shifts from only temperature can mask climate vulnerability

Climate change is causing range shifts in many marine species, with implications for biodiversity and fisheries. Previous research has mainly focused on how species' ranges will respond to changing ocean temperatures, without accounting for other environmental covariates that could affect future distribution patterns. Here, we integrate habitat suitability modeling approaches, a high‐resolution global climate model projection, and detailed fishery‐independent and ‐dependent faunal datasets from one of the most extensively monitored marine ecosystems—the U.S. Northeast Shelf. We project the responses of 125 species in this region to climate‐driven changes in multiple oceanographic factors (e.g., ocean temperature, salinity, sea surface height) and seabed characteristics (i.e., rugosity and depth). Comparing model outputs based on ocean temperature and seabed characteristics to those that also incorporated salinity and sea surface height (proxies for primary productivity and ocean circulation features), we explored how an emphasis on ocean temperature in projecting species' range shifts can impact assessments of species' climate vulnerability. We found that multifactor habitat suitability models performed better in explaining and predicting species historical distribution patterns than temperature‐based models. We also found that multifactor models provided more concerning assessments of species' future distribution patterns than temperature‐based models, projecting that species' ranges will largely shift northward and become more contracted and fragmented over time. Our results suggest that using ocean temperature as a primary determinant of range shifts can significantly alter projections, masking species' climate vulnerability, and potentially forestalling proactive management.     

Community‐wide changes in intertaxonomic temporal co‐occurrence resulting from phenological shifts

Global climate change is known to affect the assembly of ecological communities by altering species' spatial distribution patterns, but little is known about how climate change may affect community assembly by changing species' temporal co‐occurrence patterns, which is highly likely given the widely observed phenological shifts associated with climate change. Here, we analyzed a 29‐year phenological data set comprising community‐level information on the timing and span of temporal occurrence in 11 seasonally occurring animal taxon groups from 329 local meteorological observatories across China. We show that widespread shifts in phenology have resulted in community‐wide changes in the temporal overlap between taxa that are dominated by extensions, and that these changes are largely due to taxa's altered span of temporal occurrence rather than the degree of synchrony in phenological shifts. Importantly, our findings also suggest that climate change may have led to less phenological mismatch than generally presumed, and that the context under which to discuss the ecological consequences of phenological shifts should be expanded beyond asynchronous shifts.     

Predicting species‐specific responses of fungi to climatic variation using historical records

Although striking changes have been documented in plant and animal phenology over the past century, less is known about how the fungal kingdom's phenology has been changing. A few recent studies have documented changes in fungal fruiting in Europe in the last few decades, but the geographic and taxonomic extent of these changes, the mechanisms behind these changes, and their relationships to climate are not well understood. Here, we analyzed herbarium data of 274 species of fungi from Michigan to test the hypotheses that fruiting times of fungi depend on annual climate and that responses depend on taxonomic and functional groups. We show that the fungal community overall fruits later in warmer and drier years, which has led to a shift toward later fruiting dates for autumn‐fruiting species, consistent with existing evidence. However, we also show that these effects are highly variable among species and are partly explained by basic life‐history characteristics. Resulting differences in climate sensitivities are expected to affect community structure as climate changes. This study provides a unique picture of the climate dependence of fungal phenology in North America and an approach for quantifying how individual species and broader fungal communities will respond to ongoing climate change.     

Species and community responses to short‐term climate manipulation: Microarthropods in the sub‐Antarctic

Abstract: Both species and community‐level investigations are important for understanding the biotic impacts of climate change, because current evidence suggests that individual species responses are idiosyncratic. However, few studies of climate change impacts have been conducted on entire terrestrial arthropod communities living in the same habitat in the southern Hemisphere, and the effects of precipitation changes on them are particularly poorly understood. Here we investigate the species‐ and community‐level responses of microarthropods inhabiting a keystone plant species, on sub‐Antarctic Marion Island, to experimental reduction in precipitation, warming and shading. These climate manipulations were chosen based on observed climate trends and predicted indirect climate change impacts on this system. The dry‐warm and shade inducing treatments that were imposed effected significant species‐ and community‐level responses after a single year. Although the strongest community‐level trends included a dramatic decline in springtail abundance and total biomass under the dry‐warm and shade treatments, species responses were generally individualistic, that is, springtails responded differently to mites, and particular mite and springtail species responded differently to each other. Our results therefore provide additional support for the dynamic rather than static model for community responses to climate change, in the first such experiment in the sub‐Antarctic. In conclusion, these results show that an ongoing decline in precipitation and increase in temperature is likely to have dramatic direct and indirect effects on this microarthropod community. Moreover, they indicate that while at a broad scale it may be possible to make generalizations regarding species responses to climate change, these generalizations are unlikely to translate into predictable effects at the community level.     

How phenological tracking shapes species and communities in non-stationary environments

Climate change alters the environments of all species. Predicting species responses requires understanding how species track environmental change, and how such tracking shapes communities. Growing empirical evidence suggests that how species track phenologically – how an organism shifts the timing of major biological events in response to the environment – is linked to species performance and community structure. Such research tantalizingly suggests a potential framework to predict the winners and losers of climate change, and the future communities we can expect. But developing this framework requires far greater efforts to ground empirical studies of phenological tracking in relevant ecological theory. Here we review the concept of phenological tracking in empirical studies and through the lens of coexistence theory to show why a community-level perspective is critical to accurate predictions with climate change. While much current theory for tracking ignores the importance of a multi-species context, basic community assembly theory predicts that competition will drive variation in tracking and trade-offs with other traits. We highlight how existing community assembly theory can help understand tracking in stationary and non-stationary systems. But major advances in predicting the species- and community-level consequences of climate change will require advances in theoretical and empirical studies. We outline a path forward built on greater efforts to integrate priority effects into modern coexistence theory, improved empirical estimates of multivariate environmental change, and clearly defined estimates of phenological tracking and its underlying environmental cues.     

Competitive and demographic leverage points of community shifts under climate warming

Accelerating rates of climate change and a paucity of whole-community studies of climate impacts limit our ability to forecast shifts in ecosystem structure and dynamics, particularly because climate change can lead to idiosyncratic responses via both demographic effects and altered species interactions. We used a multispecies model to predict which processes and species'' responses are likely to drive shifts in the composition of a space-limited benthic marine community. Our model was parametrized from experimental manipulations of the community. Model simulations indicated shifts in species dominance patterns as temperatures increase, with projected shifts in composition primarily owing to the temperature dependence of growth, mortality and competition for three critical species. By contrast, warming impacts on two other species (rendering them weaker competitors for space) and recruitment rates of all species were of lesser importance in determining projected community changes. Our analysis reveals the importance of temperature-dependent competitive interactions for predicting effects of changing climate on such communities. Furthermore, by identifying processes and species that could disproportionately leverage shifts in community composition, our results contribute to a mechanistic understanding of climate change impacts, thereby allowing more insightful predictions of future biodiversity patterns.     

Movement‐mediated community assembly and coexistence

Organismal movement is ubiquitous and facilitates important ecological mechanisms that drive community and metacommunity composition and hence biodiversity. In most existing ecological theories and models in biodiversity research, movement is represented simplistically, ignoring the behavioural basis of movement and consequently the variation in behaviour at species and individual levels. However, as human endeavours modify climate and land use, the behavioural processes of organisms in response to these changes, including movement, become critical to understanding the resulting biodiversity loss. Here, we draw together research from different subdisciplines in ecology to understand the impact of individual‐level movement processes on community‐level patterns in species composition and coexistence. We join the movement ecology framework with the key concepts from metacommunity theory, community assembly and modern coexistence theory using the idea of micro–macro links, where various aspects of emergent movement behaviour scale up to local and regional patterns in species mobility and mobile‐link‐generated patterns in abiotic and biotic environmental conditions. These in turn influence both individual movement and, at ecological timescales, mechanisms such as dispersal limitation, environmental filtering, and niche partitioning. We conclude by highlighting challenges to and promising future avenues for data generation, data analysis and complementary modelling approaches and provide a brief outlook on how a new behaviour‐based view on movement becomes important in understanding the responses of communities under ongoing environmental change.