Publications

2025

1. When Do Trait-Based Higher Order Interactions and Individual Variation Promote Robust Species Coexistence?

   Gaurav Baruah, György Barabás, and Robert John

   Ecology and Evolution, 2025

   _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.71336

   Abs DOI

   Models on the effects of individual variation often focus on pairwise interactions, but communities could harbor both pairwise and higher order interactions (HOIs). Theoretical studies on HOIs, where a third species modulates pairwise species competition, tend to assign them at random, even though they could be mediated and structured by one-dimensional traits. Here, we consider two different classes of models of both pairwise and higher order trait-mediated interactions: competition alleviated by increasing trait distance, and hierarchical competition where species higher in the hierarchy exert more competition on those lower and vice versa. Combining these models with evolutionary dynamics based on quantitative genetics, we compare their impact on species diversity, community pattern, and robustness of coexistence. Regardless of individual variation, trait-mediated HOIs generally do not promote and often hinder species coexistence, but there are some notable exceptions to this. We present an analytical argument to make sense of these results and argue that while the effects of trait-based HOIs on diversity may appear confusing on the surface, we can understand what outcome to expect in any given scenario by looking at the shape of the effective interaction kernel that arises from the joint action of pairwise and HOI terms. In addition, we find that (i) communities structured by competitive trait hierarchies are highly vulnerable to external perturbations, regardless of HOIs, and (ii) trait-based HOIs with distance-dependent competition create the most robust communities, with minimal impact from individual variation, and (iii) both individual variation and HOIs consistently lead to a more even distribution of species traits than would occur by chance. These findings suggest that trait-mediated HOIs foster coexistence only under special conditions, raising the question of whether HOIs must involve multiple traits to positively affect coexistence in competitive communities.

2. Adaptive rewiring and temperature tolerance shape the architecture of plant-pollinator networks globally

   Gaurav Baruah and Meike J. Wittmann

   Oct 2025

   ISSN: 2692-8205 Pages: 2025.10.19.683289 Section: New Results

   Abs DOI

   Rising environmental temperatures are rapidly reshaping plant–pollinator communities by altering species traits and interaction patterns. We develop a simple eco-evolutionary model that integrates species-specific temperature tolerance curves with phenotype-based interaction dynamics. Across temperature gradients, species adaptively rewire, that is, they change their interaction partners. This rewiring is an emergent property of our model, driven by temperature-mediated selection and co-evolutionary trait matching. As temperature increases, our model predicts a consistent decline in network-level specialization, alongside increasing connectance and nestedness which are signatures of structural re-organization. These predictions are supported by empirical patterns from 165 plant–pollinator networks worldwide, where mean annual temperature correlates positively with connectance and nestedness, and negatively with network specialisation. Our findings suggest that temperature-driven trait evolution and emergent adaptive rewiring govern the assembly and architecture of mutualistic networks. By bridging dynamical eco-evolutionary theory with global empirical data, this work reveals the central role of trait-based processes in structuring biodiversity under ongoing and accelerating climate warming.

3. Behavioral variation affects persistence of an experimental food-chain

   Pragya Singh, Gaurav Baruah, and Caroline Müller

   Jul 2025

   ISSN: 2692-8205 Pages: 2025.07.04.663144 Section: New Results

   Abs DOI

   Intraspecific behavioral variation in prey could alter predator–prey interactions, yet its effects on temporal dynamics and food-web persistence remain underexplored. Pea aphids (Acyrthosiphon pisum) exhibit dropping behavior in response to predators like the seven-spot ladybird (Coccinella septempunctata). This response could be an effective anti-predator defense but could be costly in terms of energy expenditure and time not available for feeding. To investigate the impact of behavioral variation on food-chain persistence and dynamics, we used a tri-trophic experimental system with Vicia faba (plant), pea aphids (prey), and seven-spot ladybirds (predator), implementing three aphid behavioral treatments: droppers, non-droppers, and a mix of both droppers and non-droppers. To minimize genetic differences, we used clonal aphid populations across all treatments. We then tracked predator-prey population dynamics and species persistence over 25 days. Our results showed that aphid dropping behavior reduced food-chain persistence, with extinction risk significantly higher in dropper treatments than in the mix or non-dropper treatments. Ladybirds persisted across treatments, although they showed a steeper decline in abundance in the dropper treatment. In the mixed behavioral treatment, they had an intermediate persistence, suggesting a buffering effect of behavioral variation. Trophic food-chain state transitions also differed by treatment, with tri-trophic states most stable in the non-dropper, and least frequent in the dropper treatment. Furthermore, our results showed a trend of dropper treatments becoming more stable and robust towards the end of the experiment. These results demonstrate that prey behavior influences the persistence and dynamics of food-chains, with important implications for behavior-driven community dynamics.

4. Evolution of genetic variance and its consequences for eco-evolutionary responses in complex mutualistic networks

   Gaurav Baruah and Meike J. Wittmann

   Jun 2025

   Pages: 2024.12.25.630074 Section: New Results

   Abs DOI

   Rising temperatures threaten biodiversity and ecosystem resilience by disrupting phenological synchrony in plant–pollinator networks. These interactions, essential for ecosystem functioning, are sensitive to temperature shifts. We model species eco-evolutionary responses to an abrupt temperature increase, comparing evolution in mean trait alone versus evolution involving both the mean and genetic variance. We show that networks where species evolve in both their mean phenotype and genetic variance exhibit increased resilience to temperature shifts. Hyper-generalist species, engaged in extensive mutualistic interactions, accumulate greater genetic variance, thereby facilitating faster evolutionary rescue under strong selective pressures. Specialists also benefit by interacting with these hyper-generalists, which stabilize adaptation to new temperatures. We observe emergence in opposing selection pressures in complex networks that promote increases in genetic variance (“evolvability”), reducing trait lag, enabling faster adaptation, and increasing survival. Our findings highlight the role of evolving genetic variance and network architecture in mitigating plant–pollinator phenotypic mismatches under rising environmental temperatures. This study provides insights into the adaptive capacity of mutualistic networks, highlighting dynamic genetic variance changes as key to resilience amid accelerating climate warming. Our study highlights the importance of feedbacks between network topology and genetic architecture for conservation under climate change.

2024

1. Reviving collapsed plant–pollinator networks from a single species

   Gaurav Baruah and Meike Wittmann

   PLOS Biology, Oct 2024

   Abs DOI

   Mutualistic ecological networks can suddenly transition to undesirable states due to small changes in environmental conditions. Recovering from such a collapse can be difficult as restoring the original environmental conditions may be infeasible. Additionally, such networks can also exhibit a phenomenon known as hysteresis, whereby the system could exhibit multiple states under the same environmental conditions, implying that ecological networks may not recover. Here, we attempted to revive collapsed mutualistic networks to a high-functioning state from a single species, using concepts from signal propagation theory and an eco-evolutionary model based on network structures of 115 empirical plant–pollinator networks. We found that restoring the environmental conditions rarely aided in recovery of collapsed networks, but a positive relationship between recovering pollinator density and network nestedness emerged, which was qualitatively supported by empirical plant–pollinator restoration data. In contrast, network resurrection from a collapsed state in undesirable environmental conditions where restoration has minimal impacts could be readily achieved by perturbing a single species or a few species that controls the response of the dynamical networks. Additionally, nestedness in networks and a moderate amount of trait variation could aid in the revival of networks even in undesirable environmental conditions. Our work suggests that focus should be applied to a few species whose dynamics could be steered to resurrect entire networks from a collapsed state and that network architecture could play a crucial role in reviving collapsed plant–pollinator networks.

2. Predicting recoverability of collapsed food webs through perturbation and dimension reduction

   Swastik Patnaik and Gaurav Baruah

   Jul 2024

   Pages: 2024.07.09.602684 Section: New Results

   Abs DOI

   Biodiversity collapse, driven by escalating environmental changes, poses significant threats to ecosystem stability and the provision of essential ecosystem services. Understanding the recoverability of collapsed food webs thus is crucial for devising effective conservation strategies. This study delves into the theoretical exploration of the recoverability of food webs from a collapsed state. Through simple tools like dimension reduction, propagation of species-specific perturbation, and dynamical simulations, we explore whether simple tri-trophic food webs can be recovered from a collapsed state. Our study examines in detail the topological features of predator-prey food webs that could either facilitate or impede their recovery. We demonstrate that the recoverability of complex food webs can be predicted by using a simple dimension-reduced model, with certain structural factors that could constrain the full recovery of collapsed food webs. Furthermore, dynamic simulations also highlighted the significance of topological features such as connectance and the number of predator links in determining recoverability. Our dimension-reduced modeling framework offers insights into the feasibility of restoring entire complex predator-prey networks through species-specific interventions. This study contributes to a deeper understanding of ecosystem resilience and aids in the development of targeted conservation strategies.

3. Stability, resilience and eco-evolutionary feedbacks of mutualistic networks to rising temperature

   Gaurav Baruah and Tim Lakämper

   Journal of Animal Ecology, 2024

   _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2656.14118

   Abs DOI

   Ecological networks comprising of mutualistic interactions can suddenly transition to undesirable states, such as collapse, due to small changes in environmental conditions such as a rise in local environmental temperature. However, little is known about the capacity of such interaction networks to adapt to a rise in temperature and the occurrence of critical transitions. Here, combining quantitative genetics and mutualistic dynamics in an eco-evolutionary framework, we evaluated the stability and resilience of mutualistic networks to critical transitions as environmental temperature increases. Specifically, we modelled the dynamics of an optimum trait that determined the tolerance of species to local environmental temperature as well as to species interaction. We then evaluated the impact of individual trait variation and evolutionary dynamics on the stability of feasible equilibria, the occurrence of threshold temperatures at which community collapses, and the abruptness of such community collapses. We found that mutualistic network architecture, that is the size of the community and the arrangement of species interactions, interacted with evolutionary dynamics to impact the onset of network collapses. Some networks had more capacity to track the rise in temperatures than others and thereby increased the threshold temperature at which the networks collapsed. However, such a result was modulated by the amount of heritable trait variation species exhibited, with high trait variation in the mean optimum phenotypic trait increasing the environmental temperature at which networks collapsed. Furthermore, trait variation not only increased the onset of temperatures at which networks collapsed but also increased the local stability of feasible equilibria. Our study argued that mutualistic network architecture interacts with species evolutionary dynamics and increases the capacity of networks to adapt to changes in temperature and thereby delayed the occurrence of community collapses.

2023

1. Transitions and its indicators in mutualistic meta-networks: effects of network topology, size of metacommunities and species dispersal

   Gaurav Baruah

   Evolutionary Ecology, Aug 2023

   Abs DOI

   Gradual changes in the environment could cause dynamical ecological networks to suddenly shift from one state to an alternative state. When this happens ecosystem functions and services provided by ecological networks get disrupted. We, however, know very little about how the topology of such interaction networks can play a role in the transition of ecological networks when spatial interactions come into play. In the event of such unwanted transitions, little is known about how statistical metrics used to inform such impending transitions, measured at the species-level or at the community-level could relate to network architecture and the size of the metacommunity. Here, using hundred and one empirical plant-pollinator networks in a spatial setting, I evaluated the impact of network topology and spatial scale of species interactions on transitions, and on statistical metrics used as predictors to forecast such transitions. Using generalized Lotka-Volterra equations in a meta-network framework, I show that species dispersal rate and the size of the metacommunity can impact when a transition can occur. In addition, forecasting such unwanted transitions of meta-networks using statistical metrics of instability was also consequently dependent on the topology of the network, species dispersal rate, and the size of the metacommunity. The results indicated that the plant-pollinator meta-networks that could exhibit stronger statistical signals before collapse than others were dependent on their network architecture and on the spatial scale of species interactions.

2. Transitions and its indicators in mutualistic meta-networks: effects of network topology, size of metacommunities and species dispersal

   Gaurav Baruah

   Evolutionary Ecology, Aug 2023

   Abs DOI

   Gradual changes in the environment could cause dynamical ecological networks to suddenly shift from one state to an alternative state. When this happens ecosystem functions and services provided by ecological networks get disrupted. We, however, know very little about how the topology of such interaction networks can play a role in the transition of ecological networks when spatial interactions come into play. In the event of such unwanted transitions, little is known about how statistical metrics used to inform such impending transitions, measured at the species-level or at the community-level could relate to network architecture and the size of the metacommunity. Here, using hundred and one empirical plant-pollinator networks in a spatial setting, I evaluated the impact of network topology and spatial scale of species interactions on transitions, and on statistical metrics used as predictors to forecast such transitions. Using generalized Lotka-Volterra equations in a meta-network framework, I show that species dispersal rate and the size of the metacommunity can impact when a transition can occur. In addition, forecasting such unwanted transitions of meta-networks using statistical metrics of instability was also consequently dependent on the topology of the network, species dispersal rate, and the size of the metacommunity. The results indicated that the plant-pollinator meta-networks that could exhibit stronger statistical signals before collapse than others were dependent on their network architecture and on the spatial scale of species interactions.

2022

1. The impact of individual variation on abrupt collapses in mutualistic networks

   Gaurav Baruah

   Ecology Letters, 2022

   _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/ele.13895

   Abs DOI

   Individual variation is central to species involved in complex interactions with others in an ecological system. Such ecological systems could exhibit tipping points in response to changes in the environment, consequently leading to abrupt transitions to alternative, often less desirable states. However, little is known about how individual trait variation could influence the timing and occurrence of abrupt transitions. Using 101 empirical mutualistic networks, I model the eco-evolutionary dynamics of such networks in response to gradual changes in strength of co-evolutionary interactions. Results indicated that individual variation facilitates the timing of transition in such networks, albeit slightly. In addition, individual variation significantly increases the occurrence of large abrupt transitions. Furthermore, topological network features also positively influence the occurrence of such abrupt transitions. These findings argue for understanding tipping points using an eco-evolutionary perspective to better forecast abrupt transitions in ecological systems.

2. Community structure determines the predictability of population collapse

   Gaurav Baruah, Arpat Ozgul, and Christopher F. Clements

   Journal of Animal Ecology, 2022

   _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2656.13769

   Abs DOI

   Early warning signals (EWS) are phenomenological tools that have been proposed as predictors of the collapse of biological systems. Although a growing body of work has shown the utility of EWS based on either statistics derived from abundance data or shifts in phenotypic traits such as body size, so far this work has largely focused on single species populations. However, to predict reliably the future state of ecological systems, which inherently could consist of multiple species, understanding how reliable such signals are in a community context is critical. Here, reconciling quantitative trait evolution and Lotka–Volterra equations, which allow us to track both abundance and mean traits, we simulate the collapse of populations embedded in mutualistic and multi-trophic predator–prey communities. Using these simulations and warning signals derived from both population- and community-level data, we showed the utility of abundance-based EWS, as well as metrics derived from stability-landscape theory (e.g. width and depth of the basin of attraction), were fundamentally linked. Thus, the depth and width of such stability-landscape curves could be used to identify which species should exhibit the strongest EWS of collapse. The probability a species displays both trait and abundance-based EWS was dependent on its position in a community, with some species able to act as indicator species. In addition, our results also demonstrated that in general trait-based EWS were less reliable in comparison with abundance-based EWS in forecasting species collapses in our simulated communities. Furthermore, community-level abundance-based EWS were fairly reliable in comparison with their species-level counterparts in forecasting species-level collapses. Our study suggests a holistic framework that combines abundance-based EWS and metrics derived from stability-landscape theory that may help in forecasting species loss in a community context.

3. Evolutionary effects of individual variation and dimensionality of higher-order interactions on robustness of species coexistence

   Gaurav Baruah, György Barabás, and Robert John

   Dec 2022

   Pages: 2022.12.22.521465 Section: New Results

   Abs DOI

   Although the eco-evolutionary effects of individual variation for species coexistence are still widely debated, theoretical evidence appears to support a negative impact on coexistence. Mechanistic models of eco-evolutionary effects of individual variation focus largely on pairwise interactions, while the dynamics of communities where both pairwise and higher-order interactions (HOIs) are pervasive are not known. In addition, most studies have focused on effects of high dimensional HOIs on species coexistence when in reality such HOIs could be highly structured and low-dimensional, as species interactions could primarily be mediated through phenotypic traits. Here, combining quantitative genetics and Lotka-Volterra equations, we explored the eco-evolutionary effects of individual variation on the patterns of species coexistence in a competitive community dictated by pairwise interactions and HOIs. Specifically, we compare six different models in which HOIs were modelled to be trait-mediated (low-dimensional) or random (high-dimensional) and evaluated its impact on robustness of species coexistence in the presence of different levels of individual variation. Across the six different models, we found that individual variation did not promote species coexistence, irrespective of whether interactions were pairwise or were of higher-order. However, individual trait variation could stabilize communities to external perturbation more so when interactions were of higher order. When compared across models, species coexistence is promoted when HOIs strengthen pairwise intraspecific competition more so than interspecific competition, and when HOIs act in a hierarchical manner. Additionally, across the models, we found that species’ traits tend to cluster together when individual variation in the community was low. We argue that, while individual variation can influence community patterns in many different ways, they more often lead to fewer species coexisting together.

2021

1. Higher order interactions and species coexistence

   Pragya Singh and Gaurav Baruah

   Theoretical Ecology, Mar 2021

   Abs DOI

   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 not known. Here, using generalized Lotka-Volterra model, we derive a general rule for species coexistence modulated by HOIs. We show that where pairwise species interactions fail to promote species coexistence in regions of extreme fitness differences, negative HOIs that intensify pairwise competition, however, can promote coexistence provided that HOIs strengthen intraspecific competition more than interspecific competition. In contrast, positive HOIs that alleviate pairwise competition can stabilize coexistence across a wide range of fitness differences, irrespective of differences in strength of inter- and intraspecific competition. In addition, we extend our three-species analytical result to multispecies communities and show, using simulations, that multispecies coexistence is possible provided that strength of negative intraspecific HOIs is higher than interspecific HOIs. Our work sheds light on the underlying mechanisms through which HOIs can maintain species diversity.

2. Effect of habitat quality and phenotypic variation on abundance- and trait-based early warning signals of population collapses

   Gaurav Baruah, Christopher F. Clements, and Arpat Ozgul

   Oikos, 2021

   _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/oik.07925

   Abs DOI

   Loss of resilience in population numbers in response to environmental perturbations may be predicted with statistical metrics called early warning signals (EWS) that are derived from abundance time series. These signals, however, have been shown to have limited success, leading to the development of trait-based EWS that are based on information collected from phenotypic traits such as body size. Experimental work assessing the efficacy of EWS under varying ecological and environmental factors are rare. In addition, disentangling how such warning signals are affected under varying ecological and environmental factors is key to their application in biological conservation. Here, we experimentally test how different rates of environmental forcing (i.e. warming) and varying ecological factors (i.e. habitat quality and phenotypic diversity) affected population stability and predictive power of early warning signals of population collapse. We analyzed population density and body size time series data from three phenotypically different populations of a protozoan ciliate Askenasia volvox in two levels of habitat quality subjected to three different treatments of warming (i.e. no warming, fast warming and slow warming). We then evaluated how well abundance- and trait-based EWS predicted population collapses under different levels of phenotypic diversity, habitat quality and warming treatments. Our results suggest that habitat quality and warming treatments had more profound effects than phenotypic diversity had on both population stability and on the performance of abundance-based signals of population collapse. In addition, trait-based EWS generally performed well, were reliable and more robust in forecasting population collapse than abundance-based EWS, regardless of variation in environmental and ecological factors. Our study points towards the development of a predictive framework that includes information from phenotypic traits such as body size as an indicator of loss of resilience of ecological systems in response to environmental perturbations.

2020

1. Effect of time series length and resolution on abundance- and trait-based early warning signals of population declines

   A. A. Arkilanian, C. F. Clements, A. Ozgul, and 1 more author

   Ecology, 2020

   _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.3040

   Abs DOI

   Natural populations are increasingly threatened with collapse at the hands of anthropogenic effects. Predicting population collapse with the help of generic early warning signals (EWS) may provide a prospective tool for identifying species or populations at highest risk. However, pattern-to-process methods such as EWS have a multitude of challenges to overcome to be useful, including the low signal-to-noise ratio of ecological systems and the need for high quality time series data. The inclusion of trait dynamics with EWS has been proposed as a more robust tool to predict population collapse. However, the length and resolution of available time series are highly variable from one system to another, especially when generation time is considered. As yet, it remains unknown how this variability with regards to generation time will alter the efficacy of EWS. Here we take both a simulation- and experimental-based approach to assess the impacts of relative time series length and resolution on the forecasting ability of EWS. We show that EWS’ performance decreases with decreasing time-series length. However, there was no evident decrease in EWS performance as resolution decreased. Our simulations suggest a relative time series length between 10 and five generations as a minimum requirement for accurate forecasting by abundance-based EWS. However, when trait information is included alongside abundance-based EWS, we find positive signals at lengths one-half of what was required without them. We suggest that, in systems where specific traits are known to affect demography, trait data should be monitored and included alongside abundance data to improve forecasting reliability.

2. Eco-evolutionary processes underlying early warning signals of population declines

   Gaurav Baruah, Christopher F. Clements, and Arpat Ozgul

   Journal of Animal Ecology, 2020

   _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2656.13097

   Abs DOI

   Environmental change can impact the stability of ecological systems and cause rapid declines in populations. Abundance-based early warning signals have been shown to precede such declines, but detection prior to wild population collapses has had limited success, leading to the development of warning signals based on shifts in distribution of fitness-related traits such as body size. The dynamics of population abundances and traits in response to external environmental perturbations are controlled by a range of underlying factors such as reproductive rate, genetic variation and plasticity. However, it remains unknown how such ecological and evolutionary factors affect the stability landscape of populations and the detectability of abundance and trait-based early warning signals. Here, we apply a trait-based demographic approach and investigate both trait and population dynamics in response to gradual and increasing changes in the environment. We explore a range of ecological and evolutionary constraints under which stability of a population may be affected. We show both analytically and with simulations that strength of abundance- and trait-based warning signals are affected by ecological and evolutionary factors. Finally, we show that combining trait- and abundance-based information improves our ability to predict population declines. Our study suggests that the inclusion of trait dynamic information alongside generic warning signals should provide more accurate forecasts of the future state of biological systems.

2019

1. When Do Shifts in Trait Dynamics Precede Population Declines?

   Gaurav Baruah, Christopher F. Clements, Frédéric Guillaume, and 1 more author

   The American Naturalist, May 2019

   Abs DOI

   Predicting population responses to environmental change is an ongoing challenge in ecology. Studies investigating the links between fitness-related phenotypic traits and demography have shown that trait dynamic responses to environmental change can sometimes precede population dynamic responses and thus can be used as an early warning signal. However, it is still unknown under which ecological and evolutionary circumstances shifts in fitness-related traits can precede population responses to environmental perturbation. Here, we take a trait-based demographic approach and investigate both trait and population dynamics in a density-regulated population in response to a gradual change in the environment. We explore the ecological and evolutionary constraints under which shifts in fitness-related traits precede a decline in population size. We show both analytically and with experimental data that under medium to slow rates of environmental change, shifts in a trait value can precede population decline. We further show the positive influence of environmental predictability, net reproductive rate, plasticity, and genetic variation on shifts in trait dynamics preceding potential population declines. These results still hold under nonconstant genetic variation and environmental stochasticity. Our study highlights ecological and evolutionary circumstances under which a fitness-related trait can be used as an early warning signal of an impending population decline.

2018

1. Tundra Trait Team: A database of plant traits spanning the tundra biome

   Anne D. Bjorkman, Isla H. Myers-Smith, Sarah C. Elmendorf, and 102 more authors

   Global Ecology and Biogeography, 2018

   _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/geb.12821

   Abs DOI

   Motivation The Tundra Trait Team (TTT) database includes field-based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade-offs, trait–environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable contained The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (\textgreater 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grain Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub-Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grain All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software format csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.

2. Impacts of seven years of experimental warming and nutrient addition on neighbourhood species interactions and community structure in two contrasting alpine plant communities

   Gaurav Baruah, Ulf Molau, Annika K. Jägerbrand, and 1 more author

   Ecological Complexity, Jan 2018

   Abs DOI

   Global change is predicted to have major impacts on alpine and arctic ecosystems. Plant fitness and growth will be determined by how plants interact with each other at smaller scales. Local-scale neighbourhood interactions may be altered by environmental pertubations, which could fundamentally affect community structure. This study examined the effects of seven years of experimental warming and nutrient addition on overall changes in the community structure and patterns of interspecific interaction between neighbouring plant species in two contrasting alpine plant communities, mesic meadow and poor heath, in subarctic Sweden. We used a network approach to quantify the dissimilarity of plant interaction networks and the average number of interspecific neighbourhood interactions over time in response to different environmental perturbations. The results revealed that combined warming and nutrient addition had significant negative effects on how dissimilar plant interaction networks were over time compared with the control. Moreover, plant–plant neighbourhood interaction networks were more dissimilar over time in nutrient-poor heath than in nutrient-rich mesic meadow. In addition, nutrient addition alone and combined nutrient addition and warming significantly affected neighbourhood species interactions in both plant communities. Surprisingly, changes in interspecific neighbourhood interactions over time in both communities were very similar, suggesting that the nutrient-poor heath is as robust to experimental environmental perturbation as the mesic meadow. Comparisons of changes in neighbouring species interactions with changes in evenness and richness at the same scale, in order to determine whether diversity drove such changes in local-scale interaction patterns, provided moderate evidence that diversity was behind the changes in local-scale interspecific neighbourhood interactions. This implied that species might interact at smaller scales than those at which community measures were made. Overall, these results demonstrated that global change involving increased nutrient deposition and warming is likely to affect species interactions and alter community structure in plant communities, whether rich or poor in nutrients and species.

2017

1. Community and species-specific responses of plant traits to 23 years of experimental warming across subarctic tundra plant communities

   Gaurav Baruah, Ulf Molau, Yang Bai, and 1 more author

   Scientific Reports, May 2017

   Number: 1

   Abs DOI

   To improve understanding of how global warming may affect competitive interactions among plants, information on the responses of plant functional traits across species to long-term warming is needed. Here we report the effect of 23 years of experimental warming on plant traits across four different alpine subarctic plant communities: tussock tundra, Dryas heath, dry heath and wet meadow. Open-top chambers (OTCs) were used to passively warm the vegetation by 1.5–3 °C. Changes in leaf width, leaf length and plant height of 22 vascular plant species were measured. Long-term warming significantly affected all plant traits. Overall, plant species were taller, with longer and wider leaves, compared with control plots, indicating an increase in biomass in warmed plots, with 13 species having significant increases in at least one trait and only three species having negative responses. The response varied among species and plant community in which the species was sampled, indicating community-warming interactions. Thus, plant trait responses are both species- and community-specific. Importantly, we show that there is likely to be great variation between plant species in their ability to maintain positive growth responses over the longer term, which might cause shifts in their relative competitive ability.

1. Plant metabolites modulate social networks and lifespan in a sawfly

   Pragya Singh, Leon Brueggemann, Steven Janz, and 3 more authors

   Journal of Animal Ecology

   _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2656.14189

   Abs DOI

   Social interactions influence disease spread, information flow and resource allocation across species, yet heterogeneity in social interaction frequency and its fitness consequences are still poorly understood. Additionally, the role of exogenous chemicals, such as non-nutritive plant metabolites that are utilised by several animal species, in shaping social networks remains unclear. Here, we investigated how non-nutritive plant metabolites impact social interactions and the lifespan of the turnip sawfly, Athalia rosae. Adult sawflies acquire neo-clerodane diterpenoids (‘clerodanoids’) from non-food plants and this can serve as a defence against predation and increase mating success. We found intraspecific variation in clerodanoids in natural populations and laboratory-reared individuals. Clerodanoids could also be acquired from conspecifics that had prior access to the plant metabolites, which led to increased agonistic social interactions. Network analysis indicated increased social interactions in sawfly groups where some or all individuals had prior access to clerodanoids, while groups with no prior access had fewer interactions. The frequency of social interactions was influenced by the clerodanoid status of the focal individual and that of other conspecifics. Finally, we observed a shorter lifespan in adults with prior clerodanoid access when grouped with individuals without prior access, suggesting that social interactions to obtain clerodanoids have fitness costs. Our findings highlight the role of intraspecific variation in the acquisition of non-nutritional plant metabolites in shaping social networks. This variation influences individual fitness and social interactions, thereby shaping the individualised social niche.