Search

Spatially continuous data on functional diversity will improve our ability to predict global change impacts on ecosystem properties. We applied methods that combine imaging spectroscopy and foliar traits to estimate remotely sensed functional diversity in tropical forests across an Amazon-to-Andes elevation gradient (215 to 3537 m). We evaluated the scale dependency of community assembly processes and examined whether tropical forest productivity could be predicted by remotely sensed functional diversity. Functional richness of the community decreased with increasing elevation. Scale-dependent signals of trait convergence, consistent with environmental filtering, play an important role in explaining the range of trait variation within each site and along elevation. Single- and multitrait remotely sensed measures of functional diversity were important predictors of variation in rates of net and gross primary productivity. Our findings highlight the potential of remotely sensed functional diversity to inform trait-based ecology and trait diversity-ecosystem function linkages in hyperdiverse tropical forests.

Much ecological research aims to explain how climate impacts biodiversity and ecosystem-level processes through functional traits that link environment with individual performance. However, the specific climatic drivers of functional diversity across space and time remain unclear due largely to limitations in the availability of paired trait and climate data. We compile and analyze a global forest dataset using a method based on abundance-weighted trait moments to assess how climate influences the shapes of whole-community trait distributions. Our approach combines abundance-weighted metrics with diverse climate factors to produce a comprehensive catalog of trait-climate relationships that differ dramatically-27% of significant results change in sign and 71% disagree on sign, significance, or both-from traditional species-weighted methods. We find that (i) functional diversity generally declines with increasing latitude and elevation, (ii) temperature variability and vapor pressure are the strongest drivers of geographic shifts in functional composition and ecological strategies, and (iii) functional composition may currently be shifting over time due to rapid climate warming. Our analysis demonstrates that climate strongly governs functional diversity and provides essential information needed to predict how biodiversity and ecosystem function will respond to climate change.

Microbes affect the global carbon cycle that influences climate change and are in turn influenced by environmental change. Here, we use data from a long‐term whole‐ecosystem warming experiment at a boreal peatland to answer how temperature and CO2 jointly influence communities of abundant, diverse, yet poorly understood, non‐fungi microbial Eukaryotes (protists). These microbes influence ecosystem function directly through photosynthesis and respiration, and indirectly, through predation on decomposers (bacteria and fungi). Using a combination of high‐throughput fluid imaging and 18S amplicon sequencing, we report large climate‐induced, community‐wide shifts in the community functional composition of these microbes (size, shape, and metabolism) that could alter overall function in peatlands. Importantly, we demonstrate a taxonomic convergence but a functional divergence in response to warming and elevated CO2 with most environmental responses being contingent on organismal size: warming effects on functional composition are reversed by elevated CO2 and amplified in larger microbes but not smaller ones. These findings show how the interactive effects of warming and rising CO2 levels could alter the structure and function of peatland microbial food webs—a fragile ecosystem that stores upwards of 25% of all terrestrial carbon and is increasingly threatened by human exploitation. [ABSTRACT FROM AUTHOR]

Mixotrophs are ubiquitous and integral to microbial food webs, but their impacts on the dynamics and functioning of broader ecosystems are largely unresolved.Here, we show that mixotrophy produces a unique type of food web module that exhibits unusual ecological dynamics, with surprising consequences for carbon flux under warming. We develop a generalizable model of a mixotrophic food web module that incorporates dynamic switching between phototrophy and phagotrophy to assess ecological dynamics and total system CO2 flux.We find that warming switches mixotrophic systems between alternative stable carbon states—including a phototrophy‐dominant carbon sink state, a phagotrophy‐dominant carbon source state and cycling between these two. Moreover, warming always shifts this mixotrophic system from a carbon sink state to a carbon source state, but a coordinated increase in nutrients can erase early warning signals of this transition and expand hysteresis.This suggests that mixotrophs can generate critical carbon tipping points under warming that will be more abrupt and less reversible when combined with increased nutrient levels, having widespread implications for ecosystem functioning in the face of rapid global change. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Climate change is affecting how energy and matter flow through ecosystems, thereby altering global carbon and nutrient cycles. Microorganisms play a fundamental role in carbon and nutrient cycling and are thus an integral link between ecosystems and climate. Here, we highlight a major black box hindering our ability to anticipate ecosystem climate responses: viral infections within complex microbial food webs. We show how understanding and predicting ecosystem responses to warming could be challenging—if not impossible—without accounting for the direct and indirect effects of viral infections on different microbes (bacteria, archaea, fungi, protists) that together perform diverse ecosystem functions. Importantly, understanding how rising temperatures associated with climate change influence viruses and virus-host dynamics is crucial to this task, yet is severely understudied. In this perspective, we (i) synthesize existing knowledge about virus-microbe-temperature interactions and (ii) identify important gaps to guide future investigations regarding how climate change might alter microbial food web effects on ecosystem functioning. To provide real-world context, we consider how these processes may operate in peatlands—globally significant carbon sinks that are threatened by climate change. We stress that understanding how warming affects biogeochemical cycles in any ecosystem hinges on disentangling complex interactions and temperature responses within microbial food webs. [ABSTRACT FROM AUTHOR]

Anthropogenic increases in temperature and nutrient loads will likely impact food web structure and stability. Although their independent effects have been reasonably well studied, their joint effects—particularly on coupled ecological and phenotypic dynamics—remain poorly understood. Here we experimentally manipulated temperature and nutrient levels in microbial food webs and used time-series analysis to quantify the strength of reciprocal effects between ecological and phenotypic dynamics across trophic levels. We found that (1) joint—often interactive—effects of temperature and nutrients on ecological dynamics are more common at higher trophic levels, (2) temperature and nutrients interact to shift the relative strength of top-down versus bottom-up control, and (3) rapid phenotypic change mediates observed ecological responses to changes in temperature and nutrients. Our results uncover how feedback between ecological and phenotypic dynamics mediate food web responses to environmental change. This suggests important but previously unknown ways that temperature and nutrients might jointly control the rapid eco-phenotypic feedback that determine food web dynamics in a changing world. [ABSTRACT FROM AUTHOR]

Biomass dynamics capture information on population dynamics and ecosystem‐level processes (e.g., changes in production over time). Understanding how rising temperatures associated with global climate change influence biomass dynamics is thus a pressing issue in ecology. The total biomass of a species depends on its density and its average mass. Consequently, disentangling how biomass dynamics responds to increasingly warm and variable temperatures ultimately depends on understanding how temperature influences both density and mass dynamics. Here, we address this issue by keeping track of experimental microbial populations growing to carrying capacity for 15 days at two different temperatures, and in the presence and absence of temperature variability. We develop a simple mathematical expression to partition the contribution of changes in density and mass to changes in biomass and assess how temperature responses in either one influence biomass shifts. Moreover, we use time‐series analysis (Convergent Cross Mapping) to address how temperature and temperature variability influence reciprocal effects of density on mass and vice versa. We show that temperature influences biomass through its effects on density and mass dynamics, which have opposite effects on biomass and can offset each other. We also show that temperature variability influences biomass, but that effect is independent of any effects on density or mass dynamics. Last, we show that reciprocal effects of density and mass shift significantly across temperature regimes, suggesting that rapid and environment‐dependent eco‐phenotypic dynamics underlie biomass responses. Overall, our results connect temperature effects on population and phenotypic dynamics to explain how biomass responds to temperature regimes, thus shedding light on processes at play in cosmopolitan and abundant microbes as the world experiences increasingly warm and variable temperatures. [ABSTRACT FROM AUTHOR]

Assessing the impacts of anthropogenic degradation and climate change on global carbon cycling is hindered by a lack of clear, flexible and easy‐to‐use productivity models along with scarce trait and productivity data for parameterizing and testing those models. We provide a simple solution: a mechanistic framework (RS‐CFM) that combines remotely‐sensed foliar‐trait and canopy‐structural data with trait‐based metabolic theory to efficiently map productivity at large spatial scales. We test this framework by quantifying net primary productivity (NPP) at high‐resolution (0.01‐ha) in hyper‐diverse Peruvian tropical forests (30040 hectares) along a 3322‐m elevation gradient. Our analysis captures hotspots and elevational shifts in productivity more accurately and in greater detail than alternative empirical‐ and process‐based models that use plant functional types. This result exposes how high‐resolution, location‐specific variation in traits and light competition drive variability in productivity, opening up possibilities to fully harness remote sensing data and reliably scale up from traits to map global productivity in a more direct, efficient and cost‐effective manner. [ABSTRACT FROM AUTHOR]

Copyright of Functional Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Understanding the processes that influence range expansions during climate warming is paramount for predicting population extirpations and preparing for the arrival of non-native species. While climate warming occurs over a background of variation due to cyclical processes and irregular events, the temporal structure of the thermal environment is largely ignored when forecasting the dynamics of non-native species. Ecological theory predicts that high levels of temporal autocorrelation in the environment - relatedness between conditions occurring in close temporal proximity - will favor populations that would otherwise have an average negative growth rate by increasing the duration of favorable environmental periods. Here, we invoke such theory to explain the success of biological invasions and evaluate the hypothesis that sustained periods of high environmental temperature can act synergistically with increases in mean temperature to favor the establishment of non-native species. We conduct a 60-day field mesocosm experiment to measure the population dynamics of the non-native cladoceran zooplankter Daphnia lumholtzi and a native congener Daphnia pulex in ambient temperature environments (control), warmed with recurrent periods of high environmental temperatures (uncorrelated-warmed), or warmed with sustained periods of high environmental temperatures (autocorrelated-warmed), such that both warmed treatments exhibited the same mean temperature but exhibited different temporal structures of their thermal environments. Maximum D. lumholtzi densities in the warmed-autocorrelated treatment were threefold and eightfold higher relative to warmed-uncorrelated and control treatments, respectively. Yet, D. lumholtzi performed poorly across all experimental treatment(s) relative to D. pulex and were undetectable (by) the end of the experiment. Using mathematical models, we show that this increase in performance can occur alongside increasing temporal autocorrelation and should occur over a broad range of warming scenarios. These results provide both empirical and theoretical evidence that the temporal structure of the environment can influence the performance of species undergoing range expansions due to climate warming. [ABSTRACT FROM AUTHOR]

The impact of temporal variation in the environment, specifically the amount of temporal autocorrelation, on population processes is of growing interest in ecology and evolutionary biology. It was recently discovered that temporal autocorrelation in the environment can significantly increase the abundance of populations that would otherwise have low, or even negative long-term growth rates (via so-called 'inflationary effects'), provided that immigration from another source prevents extinction. Here we use a mathematical model to ask whether inflationary effects can also increase population persistence without immigration if different phenotypes within that population partition growth over time and buffer each other from extinction via mutation. Using a combination of analytical and numerical methods, we find that environmental autocorrelation can inflate the abundance of phenotypes that would otherwise be excluded from the population, provided that phenotypes are sufficiently different in their use of the environment. This inflation of abundance at the phenotypic level also generates an inflation of abundance at the population level. Remarkably, intraspecific inflationary effects can increase both phenotypic and whole population abundance even if one or all phenotypes are maladapted to the environment, as long as mutations prevent phenotypic extinction during periods of poor environmental conditions. Given the prevalence of temporally autocorrelated environmental variables in nature, intraspecific inflationary effects have the potential to be of widespread importance for population persistence as well as the maintenance of intraspecific diversity. [ABSTRACT FROM AUTHOR]

Microbes affect the global carbon cycle that influences climate change and are in turn influenced by environmental change. Here, we use data from a long-term whole-ecosystem warming experiment at a boreal peatland to answer how temperature and CO 2 jointly influence communities of abundant, diverse, yet poorly understood, non-fungi microbial Eukaryotes (protists). These microbes influence ecosystem function directly through photosynthesis and respiration, and indirectly, through predation on decomposers (bacteria and fungi). Using a combination of high-throughput fluid imaging and 18S amplicon sequencing, we report large climate-induced, community-wide shifts in the community functional composition of these microbes (size, shape, and metabolism) that could alter overall function in peatlands. Importantly, we demonstrate a taxonomic convergence but a functional divergence in response to warming and elevated CO 2 with most environmental responses being contingent on organismal size: warming effects on functional composition are reversed by elevated CO 2 and amplified in larger microbes but not smaller ones. These findings show how the interactive effects of warming and rising CO 2 levels could alter the structure and function of peatland microbial food webs-a fragile ecosystem that stores upwards of 25% of all terrestrial carbon and is increasingly threatened by human exploitation., (© 2024 John Wiley & Sons Ltd.)

Predicting food web structure in future climates is a pressing goal of ecology. These predictions may be impossible without a solid understanding of the factors that structure current food webs. The most fundamental aspect of food web structure-the relationship between the number of links and species-is still poorly understood. Some species interactions may be physically or physiologically 'forbidden'-like consumption by non-consumer species-with possible consequences for food web structure. We show that accounting for these 'forbidden interactions' constrains the feasible link-species space, in tight agreement with empirical data. Rather than following one particular scaling relationship, food webs are distributed throughout this space according to shared biotic and abiotic features. Our study provides new insights into the long-standing question of which factors determine this fundamental aspect of food web structure.