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Abstract Understanding ecosystem processes on our rapidly changing planet requires integration across spatial, temporal, and biological scales. We propose that spectral biology, using tools that enable near‐ to far‐range sensing by capturing the interaction of energy with matter across domains of the electromagnetic spectrum, will increasingly enable ecological insights across scales from cells to continents. Here, we focus on advances using spectroscopy in the visible to short‐wave infrared, chlorophyll fluorescence‐detecting systems, and optical laser scanning (light detection and ranging, LiDAR) to introduce the topic and special feature. Remote sensing using these tools, in conjunction with in situ measurements, can powerfully capture ecological and evolutionary processes in changing environments. These tools are amenable to capturing variation in life processes across biological scales that span physiological, evolutionary, and macroecological hierarchies. We point out key areas of spectral biology with high potential to advance understanding and monitoring of ecological processes across scales—particularly at large spatial extents—in the face of rapid global change. These include: the detection of plant and ecosystem composition, diversity, structure, and function as well as their relationships; detection of the causes and consequences of environmental stress, including disease and drought, for ecosystems; and detection of change through time in ecosystems over large spatial extents to discern variation in and mechanisms underlying their resistance, recovery, and resilience in the face of disturbance. We discuss opportunities for spectral biology to discover previously unseen variation and novel processes and to prepare the field of ecology for novel computational tools on the horizon with vast new capabilities for monitoring the ecology of our changing planet. 

ABSTRACT Litter decomposition is an important ecosystem process and global carbon flux that has been shown to be controlled by climate, litter quality, and microbial communities. Process‐based ecosystem models are used to predict responses of litter decomposition to climate change. While these models represent climate and litter quality effects on litter decomposition, they have yet to integrate empirical microbial community data into their parameterizations for predicting litter decomposition. To fill this gap, our research used a comprehensive leaf litterbag decomposition experiment at 10 temperate forest U.S. National Ecological Observatory Network (NEON) sites to calibrate (7 sites) and validate (3 sites) the MIcrobial‐MIneral Carbon Stabilization (MIMICS) model. MIMICS was calibrated to empirical decomposition rates and to their empirical drivers, including the microbial community (represented as the copiotroph‐to‐oligotroph ratio). We calibrate to empirical drivers, rather than solely rates or pool sizes, to improve the underlying drivers of modeled leaf litter decomposition. We then validated the calibrated model and evaluated the effects of calibration under climate change using the SSP 3–7.0 climate change scenario. We find that incorporating empirical drivers of litter decomposition provides similar, and sometimes better (in terms of goodness‐of‐fit metrics), predictions of leaf litter decomposition but with different underlying ecological dynamics. For some sites, calibration also increased climate change‐induced leaf litter mass loss by up to 5%, with implications for carbon cycle‐climate feedbacks. Our work also provides an example for integrating data on the relative abundance of bacterial functional groups into an ecosystem model using a novel calibration method to bridge empiricism and process‐based modeling, answering a call for the use of empirical microbial community data in process‐based ecosystem models. We highlight that incorporating mechanistic information into models, as done in this study, is important for improving confidence in model projections of ecological processes like litter decomposition under climate change. 

Abstract Effects of plant diversity on grassland productivity, or overyielding, are found to be robust to nutrient enrichment. However, the impact of cumulative nitrogen (N) addition (total N added over time) on overyielding and its drivers are underexplored. Synthesizing data from 15 multi-year grassland biodiversity experiments with N addition, we found that N addition decreases complementarity effects and increases selection effects proportionately, resulting in no overall change in overyielding regardless of N addition rate. However, we observed a convex relationship between overyielding and cumulative N addition, driven by a shift from complementarity to selection effects. This shift suggests diminishing positive interactions and an increasing contribution of a few dominant species with increasing N accumulation. Recognizing the importance of cumulative N addition is vital for understanding its impacts on grassland overyielding, contributing essential insights for biodiversity conservation and ecosystem resilience in the face of increasing N deposition. 

Abstract Improved understanding of bacterial community responses to multiple environmental filters over long time periods is a fundamental step to develop mechanistic explanations of plant–bacterial interactions as environmental change progresses.This is the first study to examine responses of grassland root‐associated bacterial communities to 15 years of experimental manipulations of plant species richness, functional group and factorial enrichment of atmospheric CO₂(eCO₂) and soil nitrogen (+N).Across the experiment, plant species richness was the strongest predictor of rhizobacterial community composition, followed by +N, with no observed effect of eCO₂. Monocultures of C₃and C₄grasses and legumes all exhibited dissimilar rhizobacterial communities within and among those groups. Functional responses were also dependent on plant functional group, where N₂‐fixation genes, NO₃₋‐reducing genes and P‐solubilizing predicted gene abundances increased under resource‐enriched conditions for grasses, but generally declined for legumes. In diverse plots with 16 plant species, the interaction of eCO₂+N altered rhizobacterial composition, while +N increased the predicted abundance of nitrogenase‐encoding genes, and eCO₂+N increased the predicted abundance of bacterial P‐solubilizing genes.Synthesis: Our findings suggest that rhizobacterial community structure and function will be affected by important global environmental change factors such as eCO₂, but these responses are primarily contingent on plant species richness and the selective influence of different plant functional groups. 

ABSTRACT Stomata control plant water loss and photosynthetic carbon gain. Developing more generalized and accurate stomatal models is essential for earth system models and predicting responses under novel environmental conditions associated with global change. Plant optimality theories offer one promising approach, but most such theories assume that stomatal conductance maximizes photosynthetic net carbon assimilation subject to some cost orconstraintof water. We move beyond this approach by developing a new, generalized optimality theory of stomatal conductance, optimizing any non‐foliar proxy that requires water and carbon reserves, like growth, survival, and reproduction. We overcome two prior limitations. First, we reconcile the computational efficiency ofinstantaneousoptimization with a more biologically meaningfuldynamic feedbackoptimization over plant lifespans. Second, we incorporatenon‐steady‐statephysics in the optimization to account for the temporal changes in the water, carbon, and energy storage within a plant and its environment that occur over the timescales that stomata act, contrary to previous theories. Our optimal stomatal conductance compares well to observations from seedlings, saplings, and mature trees from field and greenhouse experiments. Our model predicts predispositions to mortality during the 2018 European drought and captures realistic responses to environmental cues, including the partial alleviation of heat stress by evaporative cooling and the negative effect of accumulating foliar soluble carbohydrates, promoting closure under elevated CO₂. We advance stomatal optimality theory by incorporating generalized evolutionary fitness proxies and enhance its utility without compromising its realism, offering promise for future models to more realistically and accurately predict global carbon and water fluxes. 

Abstract In the past few decades, there has been an evolution in our understanding of soil organic matter (SOM) dynamics from one of inherent biochemical recalcitrance to one deriving from plant‐microbe‐mineral interactions. This shift in understanding has been driven, in part, by influential conceptual frameworks which put forth hypotheses about SOM dynamics. Here, we summarize several focal conceptual frameworks and derive from them six controls related to SOM formation, (de)stabilization, and loss. These include: (a) physical inaccessibility; (b) organo‐mineral and ‐metal stabilization; (c) biodegradability of plant inputs; (d) abiotic environmental factors; (e) biochemical reactivity and diversity; and (f) microbial physiology and morphology. We then review the empirical evidence for these controls, their model representation, and outstanding knowledge gaps. We find relatively strong empirical support and model representation of abiotic environmental factors but disparities between data and models for biochemical reactivity and diversity, organo‐mineral and ‐metal stabilization, and biodegradability of plant inputs, particularly with respect to SOM destabilization for the latter two controls. More empirical research on physical inaccessibility and microbial physiology and morphology is needed to deepen our understanding of these critical SOM controls and improve their model representation. The SOM controls are highly interactive and also present some inconsistencies which may be reconciled by considering methodological limitations or temporal and spatial variation. Future conceptual frameworks must simultaneously refine our understanding of these six SOM controls at various spatial and temporal scales and within a hierarchical structure, while incorporating emerging insights. This will advance our ability to accurately predict SOM dynamics. 

Summary Allocation of leaf phosphorus (P) among different functional fractions represents a crucial adaptive strategy for optimizing P use. However, it remains challenging to monitor the variability in leaf P fractions and, ultimately, to understand P‐use strategies across diverse plant communities.We explored relationships between five leaf P fractions (orthophosphate P, P_i; lipid P, P_L; nucleic acid P, P_N; metabolite P, P_M; and residual P, P_R) and 11 leaf economic traits of 58 woody species from three biomes in China, including temperate, subtropical and tropical forests. Then, we developed trait‐based models and spectral models for leaf P fractions and compared their predictive abilities.We found that plants exhibiting conservative strategies increased the proportions of P_Nand P_M, but decreased the proportions of P_iand P_L, thus enhancing photosynthetic P‐use efficiency, especially under P limitation. Spectral models outperformed trait‐based models in predicting cross‐site leaf P fractions, regardless of concentrations (R² = 0.50–0.88 vs 0.34–0.74) or proportions (R² = 0.43–0.70 vs 0.06–0.45).These findings enhance our understanding of leaf P‐allocation strategies and highlight reflectance spectroscopy as a promising alternative for characterizing large‐scale leaf P fractions and plant P‐use strategies, which could ultimately improve the physiological representation of the plant P cycle in land surface models. 

Summary Leaf dark respiration (R_d) acclimates to environmental changes. However, the magnitude, controls and time scales of acclimation remain unclear and are inconsistently treated in ecosystem models.We hypothesized thatR_dand Rubisco carboxylation capacity (V_cmax) at 25°C (R_d,25,V_cmax,25) are coordinated so thatR_d,25variations supportV_cmax,25at a level allowing full light use, withV_cmax,25reflecting daytime conditions (for photosynthesis), andR_d,25/V_cmax,25reflecting night‐time conditions (for starch degradation and sucrose export). We tested this hypothesis temporally using a 5‐yr warming experiment, and spatially using an extensive field‐measurement data set. We compared the results to three published alternatives:R_d,25declines linearly with daily average prior temperature;R_dat average prior night temperatures tends towards a constant value; andR_d,25/V_cmax,25is constant.Our hypothesis accounted for more variation in observedR_d,25over time (R² = 0.74) and space (R² = 0.68) than the alternatives. Night‐time temperature dominated the seasonal time‐course ofR_d, with an apparent response time scale ofc.2 wk.V_cmaxdominated the spatial patterns.Our acclimation hypothesis results in a smaller increase in globalR_din response to rising CO₂and warming than is projected by the two of three alternative hypotheses, and by current models. 

Abstract AimUnderstanding the mechanisms promoting resilience in plant communities is crucial in times of increasing disturbance and global environmental change. Here, we present the first meta‐analysis evaluating the relationship between functional diversity and resilience of plant communities. Specifically, we tested whether the resilience of plant communities is positively correlated with interspecific trait variation (following the niche complementarity hypothesis) and the dominance of acquisitive and small‐size species (following the mass ratio hypothesis), and for the context‐dependent effects of ecological and methodological differences across studies. LocationGlobal. Time Period2004–2021. Major Taxa StudiedVascular plants. MethodsWe compiled a dataset of 69 independent sites from 26 studies that have quantified resilience. For each site, we calculated functional diversity indices based on the floristic composition and functional traits of the plant community (obtained from the TRY database) which we correlated with resilience of biomass and floristic composition. After transforming correlation coefficients to Fisher'sZ‐scores, we conducted a hierarchical meta‐analysis, using a multilevel random‐effects model that accounted for the non‐independence of multiple effect sizes and the effects of ecological and methodological moderators. ResultsIn general, we found no positive functional diversity–resilience relationships of grand mean effect sizes. In contrast to our expectations, we encountered a negative relationship between resilience and trait variety, especially in woody ecosystems, whereas there was a positive relationship between resilience and the dominance of acquisitive species in herbaceous ecosystems. Finally, the functional diversity–resilience relationships were strongly affected by both ecological (biome and disturbance properties) and methodological (temporal scale, study design and resilience metric) characteristics. Main ConclusionsWe rejected our hypothesis of a general positive functional diversity–resilience relationship. In addition to strong context dependency, we propose that idiosyncratic effects of single resident species present in the communities before the disturbances and biological legacies could play major roles in the resilience of terrestrial plant communities. 

Abstract Legumes are an important component of plant diversity that modulate nitrogen (N) cycling in many terrestrial ecosystems. Limited knowledge of legume effects on soil N cycling and its response to global change factors and plant diversity hinders a general understanding of whether and how legumes broadly regulate the response of soil N availability to those factors. In a 17‐year study of perennial grassland species grown under ambient and elevated (+180 ppm) CO₂and ambient and enriched (+4 g N m⁻² year⁻¹) N environments, we compared pure legume plots with plots dominated by or including other herbaceous functional groups (and containing one or four species) to assess the effect of legumes on N cycling (net N mineralization rate and inorganic N pools). We also examined the effects of numbers of legume species (from zero to four) in four‐species mixed plots on soil N cycling. We hypothesized that legumes would increase N mineralization rates most in those treatments with the greatest diversity and the greatest relative limitation by and competition for N. Results partially supported these hypotheses. Plots with greater dominance by legumes had greater soil nitrate concentrations and mineralization rates. Higher species richness significantly increased the impact of legumes on soil N metrics, with 349% and 505% higher mineralization rates and nitrate concentrations in four‐species plots containing legumes compared to legume‐free four‐species plots, in contrast to 185% and 129% greater values, respectively, in pure legume than nonlegume monoculture plots. N‐fertilized plots had greater legume effects on soil nitrate, but lower legume effects on net N mineralization. In contrast, neither elevated CO₂nor its interaction with legumes affected net N mineralization. These results indicate that legumes markedly influence the response of soil N cycling to some, but not all, global change drivers.