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Results for “Ecology”

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bioRxiv2019

Dormancy dynamics and dispersal contribute to soil microbiome resilience

In disturbance ecology, stability is composed of resistance to change and resilience towards recovery after the disturbance subsides. Two key microbial mechanisms that can support microbiome stability include dormancy and dispersal. Specifically, microbial populations that are sensitive to disturbance can be re-seeded by local dormant pools of viable and reactivated cells, or by immigrants dispersed from regional metacommunities. However, it is difficult to quantify the contributions of these mechanisms to stability without, first, distinguishing the active from inactive membership, and, second, distinguishing the populations recovered by local resuscitation from those recovered by dispersed immigrants. Here, we investigate the contributions of dormancy dynamics (activation and inactivation), and dispersal to soil microbial community resistance and resilience. We designed a replicated, 45-week time-series experiment to quantify the responses of the active soil microbial community to a thermal press disturbance, including control mesocosms, disturbed mesocosms without dispersal, and disturbed mesocosms with dispersal after the release of the stressor. Communities were sensitive within one week of warming. Though the disturbed mesocosms did not fully recover within 29 weeks, resuscitation of thermotolerant taxa was key for community transition during the press, and both resuscitation of opportunistic taxa and immigration contributed to community resilience. Also, mesocosms with dispersal were more resilient than mesocosms without. This work advances the mechanistic understanding of how microbiomes respond to disturbances in their environment.

ecology↗

bioRxiv2019

PalaeoChip Arctic1.0: An optimised eDNA targeted enrichment approach to reconstructing past environments

Ancient environmental DNA has been established as a viable biomolecular proxy for tracking taxonomic presence through time in a local environment, even in the total absence of primary tissues. It is thought that sedimentary ancient DNA (sedaDNA) survives through mineral binding. And while these organo-mineral complexes likely facilitate long-term preservation, they also challenge our ability to release and isolate target molecules. Two limitations in sedaDNA extraction impede many palaeoenvironmental reconstructions: the post-extraction carryover of enzymatic inhibitors, and sedaDNA loss when attempting to reduce inhibitor co-elution. Here, we present an optimised eDNA targeted enrichment approach for reconstructing past environments. Our new extraction protocol with targeted enrichment averages a 14.6-fold increase in on-target plant and animal DNA compared to a commercial soil extraction kit, and a 22.6-fold increase compared to a PCR metabarcoding approach. To illustrate the effectiveness of the PalaeoChip Arctic1.0 protocol, we present results of plant and animal presence from permafrost samples and discuss new potential evidence for the late survival (ca. 9685 BP) of mammoth (Mammuthus sp.) and horse (Equus sp.) in the Klondike Region of Yukon, Canada. This approach translates to a more diverse and sensitive dataset with increased sequencing efficiency of ecologically informative sedaDNA.

ecology↗

bioRxiv2019

Can endogenous fluctuations persist in high-diversity ecosystems?

When can complex ecological interactions drive an entire ecosystem into a persistent non-equilibrium state, where species abundances keep fluctuating without going to extinction? We show that high-diversity spatially-extended systems, in which conditions vary somewhat between spatial locations, can exhibit chaotic dynamics which persist for extremely long times. We develop a theoretical framework, based on dynamical mean-field theory, to quantify the conditions under which these fluctuating states exist, and predict their properties. We uncover parallels with the persistence of externally-perturbed ecosystems, such as the role of perturbation strength, synchrony and correlation time. But uniquely to endogenous fluctuations, these properties arise from the species dynamics themselves, creating feedback loops between perturbation and response. A key result is that the fluctuation amplitude and species diversity are tightly linked, in particular fluctuations enable dramatically more species to coexist than at equilibrium in the very same system. Our findings highlight crucial differences between well-mixed and spatially-extended systems, with implications for experiments and their ability to reproduce natural dynamics. They shed light on the maintenance of biodiversity, and the strength and synchrony of fluctuations observed in natural systems.

ecology↗

bioRxiv2019

Thinking like a naturalist: enhancing computer vision of citizen science images by harnessing contextual data

O_LIThe accurate identification of species in images submitted by citizen scientists is currently a bottleneck for many data uses. Machine learning tools offer the potential to provide rapid, objective and scalable species identification for the benefit of many aspects of ecological science. Currently, most approaches only make use of image pixel data for classification. However, an experienced naturalist would also use a wide variety of contextual information such as the location and date of recording.\nC_LIO_LIHere, we examine the automated identification of ladybird (Coccinellidae) records from the British Isles submitted to the UK Ladybird Survey, a volunteer-led mass participation recording scheme. Each image is associated with metadata; a date, location and recorder ID, which can be cross-referenced with other data sources to determine local weather at the time of recording, habitat types and the experience of the observer. We built multi-input neural network models that synthesise metadata and images to identify records to species level.\nC_LIO_LIWe show that machine learning models can effectively harness contextual information to improve the interpretation of images. Against an image-only baseline of 48.2%, we observe a 9.1 percentage-point improvement in top-1 accuracy with a multi-input model compared to only a 3.6% increase when using an ensemble of image and metadata models. This suggests that contextual data is being used to interpret an image, beyond just providing a prior expectation. We show that our neural network models appear to be utilising similar pieces of evidence as human naturalists to make identifications.\nC_LIO_LIMetadata is a key tool for human naturalists. We show it can also be harnessed by computer vision systems. Contextualisation offers considerable extra information, particularly for challenging species, even within small and relatively homogeneous areas such as the British Isles. Although complex relationships between disparate sources of information can be profitably interpreted by simple neural network architectures, there is likely considerable room for further progress. Contextualising images has the potential to lead to a step change in the accuracy of automated identification tools, with considerable benefits for large scale verification of submitted records.\nC_LI

ecology↗

bioRxiv2019

Predicting the global mammalian viral sharing network using phylogeography

Understanding interspecific viral transmission is key to understanding viral ecology and evolution, disease spillover into humans, and the consequences of global change. Prior work has demonstrated that macroecological factors drive viral sharing in some mammalian groups, but analyses have never attempted to predict viral sharing in a pan-mammalian context. Here we show that host phylogenetic similarity and geographic range overlap are strong, nonlinear predictors of viral sharing among species across the entire mammal class. Using these traits, we predict global viral sharing patterns across 4196 mammal species and show that our simulated network successfully predicts viral sharing and reservoir host status using internal validation and an external dataset. We predict high rates of mammalian viral sharing in the tropics, particularly among rodents and bats, and that within- and between-order sharing differs geographically and taxonomically. Our results emphasize the importance of macroecological factors in shaping mammalian viral communities, and provide a robust, general model to predict viral host range and guide pathogen surveillance and conservation efforts.

ecology↗

bioRxiv2019

An agent-based model of insect resistance management and mitigation for Bt maize: A social science perspective

Managing and mitigating agricultural pest resistance to control technologies is a complex system in which biological and social factors spatially and dynamically interact. We build a spatially explicit population genetics model for the evolution of pest resistance to Bt toxins by the insect Ostrinia nubilalis and an agent-based model of Bt maize adoption, emphasizing the importance of social factors. The farmer adoption model for Bt maize weighed both individual profitability and adoption decisions of neighboring farmers to mimic the effects of economic incentives and social networks. The model was calibrated using aggregate adoption data for Wisconsin. Simulation experiments with the model provide insights into mitigation policies for a high-dose Bt maize technology once resistance emerges in a pest population. Mitigation policies evaluated include increased refuge requirements for all farms, localized bans on Bt maize where resistance develops, areawide applications of insecticidal sprays on resistant populations, and taxes on Bt maize seed for all farms. Evaluation metrics include resistance allele frequency, pest population density, farmer adoption of Bt maize and economic surplus generated by Bt maize.\n\nBased on economic surplus, the results suggest that refuge requirements should remain the foundation of resistance management and mitigation for high-dose Bt maize technologies. For shorter planning horizons (< 16 years), resistance mitigation strategies did not improve economic surplus from Bt maize. Social networks accelerated the emergence of resistance, making the optimal policy intervention for longer planning horizons rely more on increased refuge requirements and less on insecticidal sprays targeting resistant pest populations. Overall, the importance social factors play in these results implies more social science research, including agent-based models, would contribute to developing better policies to address the evolution of pest resistance.\n\nAuthor SummaryBt maize has been a valuable technology used by farmers for more than two decades to control pest damage to crops. Using Bt maize, however, leads to pest populations evolving resistance to Bt toxins so that benefits decrease. As a result, managing and mitigating resistance has been a serious concern for policymakers balancing the current and future benefits for many stakeholders. While the evolution of insect resistance is a biological phenomenon, human activities also play key roles in agricultural landscapes with active pest management, yet social science research on resistance management and mitigation policies has generally lagged biological research. Hence, to evaluate policy options for resistance mitigation for this complex biological and social system, we build an agent-based model that integrates key social factors into insect ecology in a spatially and dynamically explicit way. We demonstrate the significance of social factors, particularly social networks. Based on an economic surplus criterion, our results suggest that refuge requirements should remain the foundation of resistance mitigation policies for high-dose Bt technologies, rather than localized bans, areawide insecticide sprays, or taxes on Bt maize seed.

ecology↗

bioRxiv2019

Development and application of eDNA-based tools for the conservation of white-clawed crayfish

O_LIeDNA-based methods represent non-invasive and cost-effective approaches for species monitoring and their application as a conservation tool has rapidly increased within the last decade. Currently, they are primarily used to determine the presence/absence of invasive, endangered or commercially important species, but they also hold potential to contribute to an improved understanding of the ecological interactions that drive species distribution. However, this next step of eDNA-based applications requires a thorough method development. C_LIO_LIWe developed an eDNA assay for the white-clawed crayfish (Austropotamobius pallipes), a flagship species of conservation in the UK. Multiple subsequent in-situ and ex-situ validation tests aimed at improving method performance allowed us to apply eDNA-based surveys to evaluate interactions between white-clawed crayfish, crayfish plague and invasive signal crayfish. C_LIO_LIThe assay performed well in terms of specificity (no detection of non-target DNA) and sensitivity, which was higher than more established traditional species survey methods. Quantification of species biomass was, however, less reliable. C_LIO_LIComparison of eDNA sampling methods (precipitation vs. various filtration approaches) revealed that optimal sampling method differed across environments and might depend on inhibitor concentrations. C_LIO_LIFinally, we applied our methodology together with established assays for crayfish plague and the invasive signal crayfish and demonstrated their significant interactions in a UK river system. C_LIO_LIOur analysis highlights the importance of thorough methodological development of eDNA-based assays. Only a critical evaluation of methodological strengths and weaknesses will allow us to capitalise on the full potential of eDNA-based methods and use them as decision support tools in environmental monitoring and conservation practices. C_LI

ecology↗

bioRxiv2019

Effects of forest management on the phenology of early-flowering understory herbs

Many organisms respond to anthropogenic environmental change through shifts in their phenology. In plants, flowering is largely driven by temperature, and therefore affected by climate change. However, on smaller scales climatic conditions are also influenced by other factors, including habitat structure. A group of plants with a particularly distinct phenology are the understorey herbs in temperate forests. In these forests, management alters tree species composition and stand structure and, as a consequence, light conditions and microclimate. Forest management should thus also affect the phenology of understorey herbs. To test this, we recorded the flowering phenology of 20 early-flowering herbs on 100 forest plots varying in management intensity, from near-natural to intensely managed forests, in Central and Southern Germany. We found that in forest stands with a high management intensity the plants flowered on average about two weeks later than in unmanaged forests. This was largely because management also affected microclimate (e.g. spring temperatures of 5.9 {degrees}C in managed coniferous, 6.7 in managed deciduous and 7.0 {degrees}C in unmanaged deciduous plots), which in turn affected phenology, with plants flowering later on colder and moister forest stands (+4.5 days per -1{degrees}C and 2.7 days per 10 % humidity increase). Among forest characteristics, the main tree species as well as the age, overall crown projection area, structural complexity and spatial distribution of trees had the greatest influence on microclimate. Our study demonstrates that forest management alters plant phenology, with potential far-reaching consequences for the ecology and evolution of understorey communities. More generally, our study suggests that besides climate change other drivers of environmental change, too, can influence the phenology of organisms.

ecology↗

bioRxiv2019

Local human movement patterns and land use impact exposure to zoonotic malaria in Malaysian Borneo

Human movement into insect vector and wildlife reservoir habitats determines zoonotic disease risks; however, few data are available to quantify the impact of land use on pathogen transmission. Here, we utilise GPS tracking devices and novel applications of ecological methods to develop fine-scale models of human space use relative to land cover to assess exposure to the zoonotic malaria Plasmodium knowlesi in Malaysian Borneo. Combining data with spatially explicit models of mosquito biting rates, we demonstrate the role of individual heterogeneities in local space use in disease exposure. At a community level, our data indicate that areas close to both secondary forest and houses have the highest probability of human P. knowlesi exposure, providing quantitative evidence for the importance of ecotones. Despite higher biting rates in forests, incorporating human movement space use into exposure estimates illustrates the importance of intensified interactions between pathogens, insect vectors and people around habitat edges.

ecology↗

bioRxiv2019

A Maxent modelling with a geospatial approach for the Habitat suitability of Flamingos in an Evanescing Ramsar site (Sambhar Lake, India) over the changing climatic scenarios

Wetlands play a crucial role in the biosphere and provide numerous services. They performed multiple functions such as groundwater recharge, water purification, conservation of biological resources, act as a carbon sink and habitat of amphibians and birds. A Ramsar site-the Sambhar Lake is one of the largest inland saline wetland present in the arid region of Rajasthan, India has unique habitat suitability for the winter avifauna migrants like flamingoes and falcons. The occurrence of suitable climatic conditions and food availability like brine shrimps (Artemia salina) attracts flocks of migratory birds. From the last three decades, Sambhar Lake has been continuously facing degradation due to anthropogenic activities, which disturb Lakes natural ecology and existence. These cause disturbances in habitat suitability of migratory birds in the Sambhar Lake, which leads to a reduction of population density of migratory birds. Therefore, this study aimed to assess the degradation and vulnerability of Sambhar Lake and the habitat suitability of migratory birds using Maxent Habitat Suitability model. This model provides a platform to integrate the birds occurrence data with the bioclimatic variables using remote sensing and Geographical Information System, and provides birds habitat suitability as well as predicts future birds occurrence scenarios. Landsat-5 and Sentinel-2 imagery for the year 1996 and 2019 respectively were used in this study. Four indicators such as LULC NDWI, MSI and SABI depicts the environmental condition of the Sambhar Lake. Output form Maxent model reveals that the Sambhar lake area with increasing anthropogenic activities has become unsuitable for flamingos. A remarkable loss of breeding sites of animal, particularly avian fauna (flamingos) is seen in the recent years due to different types of threats posed on the Ramsar site. Increase in Salt crust and Vegetation area from 36.8055 to 123.837 Sq. Km. and 26.5347 to 36.857 Sq. Km. respectively have taken place. While a decrease in saline water area from 88.8309 to 19.3256 Sq. Km has been observed, within the vicinity of Sambhar Lake as clearly shown through LULC map. The future prediction of the distribution of species in the region for the year 2050 shows that the most suitable regions will be near to Jhapok and nearby waters of Salt Lake City as the drains from the city opens in the lake where the flamingoes get Algae in the form of food. Active steps are needed for the lake conservation to reduce the risks of migratory birds population.

ecology↗

bioRxiv2019

Short-term effects of GPS collars on the activity, behavior, and adrenal response of scimitar-horned oryx (Oryx dammah)

GPS collars have revolutionized the field of animal ecology, providing detailed information on animal movement and the habitats necessary for species survival. GPS collars also have the potential to cause adverse effects ranging from mild irritation to severe tissue damage, reduced fitness, and death. The impact of GPS collars on the behavior, stress, or activity, however, have rarely been tested on study species prior to release. The objective of our study was to provide a comprehensive assessment of the short-term effects of GPS collars fitted on scimitar-horned oryx (Oryx dammah), an extinct-in-the-wild antelope once widely distributed across Sahelian grasslands in North Africa. We conducted behavioral observations, assessed fecal glucocorticoid metabolites (FGM), and evaluated high-resolution data from tri-axial accelerometers. Using a series of non-standard regression models, we illustrate clear but short-term effects to animals fitted with GPS collars. Behavioral observations highlighted a significant increase in the amount of headshaking from pre-treatment levels, returning below baseline levels during the post-treatment period (>3 days post-collaring). Similarly, FGM concentrations (i.e., stress hormones) increased after GPS collars were fitted on animals but returned to pre-collaring levels within 5 days of collaring. Lastly, tri-axial accelerometers, collecting data at eight positions per second, indicated a > 480 percent increase in the amount of hourly headshaking immediately after collaring. This post-collaring increase in headshaking was estimated to decline in magnitude within 4 hours after GPS collar fitting. These effects constitute a handling and/or habituation response (model dependent), with animals showing short-term responses in activity, behavior, and stress that dissipated within several hours to several days of being fitted with GPS collars. Importantly, none of our analyses indicated any long-term effects that would have more pressing animal welfare concerns.

ecology↗

bioRxiv2019

Evolutionary rescue is determined by differential selection on demographic rates and density dependence.

Accelerated rates of climate change are expected to either lead to populations adapting and persisting, or suffering extinction. Traditionally ecological models make extinction predictions based on how environmental change alters the intrinsic growth rate (r). However, these often ignore potential for evolutionary rescue, or to avoid extinction via adaptive evolution. Moreover, the environment may impose selective pressure on specific demographic rates (birth and death) rather than directly on r (the difference between the birth and death rates). Therefore, when we consider the potential for evolutionary rescue, populations with the same r can have different abilities to persist amidst environmental change. We cant adequately understand evolutionary rescue without accounting for demography, and interactions between density dependence and environmental change. Using stochastic birth-death population models, we found evolutionary rescue more likely when environmental change alters birth rather than the death rate. Furthermore, species that evolve via density dependent selection are less vulnerable to extinction than species that undergo selection independent of population density. Resolving the key demographic factors affected by environmental change can lead to an understanding of how populations evolve to avoid extinction. By incorporating these considerations into our models we can better predict how species will respond to climate change.

ecology↗

bioRxiv2019

Partitioning plant spectral diversity into alpha and beta components

Plant spectral diversity -- how plants differentially interact with solar radiation -- is an integrator of plant chemical, structural, and taxonomic diversity that can be remotely sensed. We propose to measure spectral diversity as spectral variance, which allows the partitioning of the spectral diversity of a region, called spectral gamma ({gamma}) diversity, into additive alpha (; within communities) and beta ({beta}; among communities) components. Our method calculates the contributions of individual bands or spectral features to spectral{gamma} -, {beta}-, and -diversity, as well as the contributions of individual plant communities to spectral diversity. We present two case studies illustrating how our approach can identify \"hotspots\" of spectral -diversity within a region, and discover spectrally unique areas that contribute strongly to {beta}-diversity. Partitioning spectral diversity and mapping its spatial components has many applications for conservation since high local diversity and distinctiveness in composition are two key criteria used to determine the ecological value of ecosystems.

ecology↗

bioRxiv2019

Unifying ecosystem resistance, resilience, and recovery from extreme stress into a single statistical framework

Natural communities and ecosystems are currently experiencing unprecedented rates of environmental and biotic change. While gradual shifts in average conditions, such as rising mean air temperatures, can significantly alter ecosystem function, ecologists recently acknowledged that the most damaging consequences of global change will probably emanate from both a higher prevalence and increased intensity of extreme climatic stress events. Given the potential ecological and societal ramifications of more frequent disturbances, it is imperative that we identify which ecosystems are most vulnerable to global change by accurately quantifying ecosystem responses to extreme stress. Unfortunately, the lack of a standardized method for estimating ecosystem sensitivity to drought makes drawing general conclusions difficult. There is a need for estimates of resistance/resilience/legacy effects that are free of observation error, not biased by stochasticity in production or rainfall, and standardizes stress magnitude among many disparate ecosystems relative to normal interannual variability. Here, I propose a statistical framework that estimates all three components of ecosystem response to stress using standardized language (resistance, resilience, recovery, and legacy effects) while resolving all of the issues described above. Coupling autoregressive time series with exogenous predictors (ARX) models with impulse response functions (IRFs) allows researchers to statistically subject all ecosystems to similar levels of stress, estimate legacy effects, and obtain a standardized estimate of ecosystem resistance and resilience to drought free from observation error and stochastic processes inherent in raw data. This method will enable researchers to rigorously compare resistance and resilience among locations using long-term time series, thereby improving our knowledge of ecosystem responses to extreme stress.

ecology↗

bioRxiv2019

Relative growth of invasive and indigenous tilapiine cichlid fishes in Tanzania

Non-native species have been widely distributed across Africa for the enhancement of capture fisheries, but it can be unclear what benefits in terms of fisheries production the non-native species bring over native species. Here we compared the relative growth rate of sympatric populations of introduced Oreochromis niloticus (Nile tilapia) to indigenous Oreochromis jipe (Jipe tilapia) at three impoundments in Northern Tanzania. Using scale increments as a proxy for growth, we found that O. niloticus had an elevated growth rate relative to O. jipe, with the greatest O. niloticus growth rates being evident in the Nyumba ya Mungu reservoir. These results help explain why O. niloticus may be a superior competitor to native species in some circumstances. However, further introductions of this non-native species should be undertaken with caution given potential for negative ecological impacts on threatened indigenous tilapia species.

ecology↗

bioRxiv2019

Forest canopy resists plant invasions: a case study of Chromolaena odorata in sub-tropical Sal (Shorea robusta) forests of Nepal

Invasive Alien Species cause tremendous ecological and economic damage in agriculture, forestry, aquatic ecosystems, and pastoral resources. They are one of the major threats to biodiversity conservation. Understanding the spatial pattern of invasive species and disentangling the biophysical drivers of invasion at forest stand level is essential for managing invasive species in forest ecosystems and the wider landscape. However, forest-level and species-specific information on invasive species abundance and area of extent is largely lacking. In this context, we analysed the cover of one of the worlds worst invasive plant species Chromolaena odorata in Sal (Shorea robusta Gaertn.) forest in central Nepal. Vegetation was sampled in four community-managed forests using 0.01 ha square quadrats, covering forest edge to the interior. Chromolaena cover, floral richness, tree density, forest canopy cover, shrub cover, and tree basal area were measured in each plot. We also estimated the level of disturbance in plots, and calculated distance from the plot to the nearest road. We also explored forest and invasive species management practices in community forests.\n\nChromolaena cover was found to be negatively correlated with forest canopy cover, distance to the nearest road, angle of slope and shrub cover. Canopy cover had the greatest effect on the Chromolaena cover. Chromolaena cover did not show any pattern along native species richness gradients. In conclusion, forest canopy cover is the overriding biotic covariate affecting Chromolaena cover in Sal forests. The practical application of our results in managing Chromolaena in forest ecosystems is discussed.

ecology↗

bioRxiv2019

Higher order interactions and coexistence theory

Higher order interactions (HOIs) have been suggested to stabilize diverse ecological communities. However, their role in maintaining species coexistence from the perspective of modern coexistence theory is unknown. Here, using a three-species Lotka-Volterra model, we derive a general rule for species coexistence modulated by HOIs. We show that negative HOIs that intensify pairwise competition, can promote coexistence across a wide range of fitness differences, provided that HOIs strengthen intraspecific competition more than interspecific competition. In contrast, positive HOIs that alleviate pairwise competition can also stabilize coexistence across a wide range of fitness differences, irrespective of differences in strength of inter- and intraspecific competition. Furthermore, we extend our three-species analytical result to multispecies competitive community and show, using simulations, that feasible multispecies coexistence is possible provided that strength of negative intraspecific HOIs is higher than interspecific HOIs. In addition, multispecies communities, however, become unstable with positive HOIs as such higher-order interactions could lead to disproportionately infeasible growth rates. This work provides crucial insights on the underlying mechanisms that could maintain species diversity and links HOIs with modern coexistence theory.

ecology↗

bioRxiv2019

Climatic sensitivity of species’ vegetative and reproductive phenology in a Hawaiian montane wet forest

Understanding the way tropical tree phenology (i.e., the timing and amount of seed and leaf production) responds to climate is vital for predicting how climate change may alter ecological functioning of tropical forests. We examined the effects of temperature, rainfall, and photosynthetically active radiation (PAR) on seed and leaf phenology in a montane wet forest on Hawaii using monthly data collected over [~]6 years. We expected that species phenologies were more sensitive to temperature and PAR than to rainfall at this wet tropical site because rainfall is not limiting. Seed production declined with increasing temperatures for two foundational species in Hawaiian forests (Acacia koa and Metrosideros polymorpha). Seed production also declined with rainfall for two species, and greater PAR for one species. One species showed relatively flat responses to climate. Community-level leaf phenology was not strongly seasonal. Unlike seed phenology, we found no effect of temperature on leaf phenology. However, leaf fall increased with rainfall. Climatic factors explained a low to moderate proportion of variance for both seed and leaf litterfall, thus the impact of future climate change on this forest will depend on how climate change interacts with other factors such as daylength, biotic, and/or evolutionary constraints. Our results nonetheless provide insight into how climate change may differentially affect different species with potential consequences for shifts in species distributions and community composition.

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