Global Change Biology最新文献

Climate extremes such as droughts are expected to increase in frequency and intensity with global change. Therefore, it is important to map and predict ecosystem responses to such extreme events to maintain ecosystem functions and services. Alongside abiotic factors, biotic factors such as the proportion of needle and broadleaf trees were found to affect forest drought responses, corroborating results from biodiversity–ecosystem functioning (BEF) experiments. Yet it remains unclear to what extent the behavior of non-experimental systems at large scales corresponds to the relationships discovered in BEF experiments. Using remote sensing, the trait-based functional diversity of forest ecosystems can be directly quantified. We investigated the relationship between remotely sensed functional richness and evenness and forest drought responses using data from temperate mixed forests in Switzerland, which experienced an extremely hot and dry summer in 2018. We used Sentinel-2 satellite data to assess aspects of functional diversity and quantified drought response in terms of resistance, recovery, and resilience from 2017 to 2020 in a scalable approach. We then analyzed the BEF relationship between functional diversity measures and drought response for different aggregation levels of richness and evenness of three physiological canopy traits (chlorophyll, carotenoid/chlorophyll ratio, and equivalent water thickness). Forest stands with greater trait richness were more resistant and resilient to the drought event, and the relationship of trait evenness with resistance or resilience was hump-shaped or negative, respectively. These results suggest forest functional diversity can support forests in such drought responses via a mixture of complementarity and dominance effects, the first indicated by positive richness effects and the second by negative evenness effects. Our results link ecosystem functioning and biodiversity at large scales and provide new insights into the BEF relationships in non-experimental forest ecosystems.

Coastal freshwater wetlands are critical ecosystems for both local and global carbon cycles, sequestering substantial carbon while also emitting methane (CH₄) due to anoxic conditions. Estuarine freshwater wetlands face unique challenges from fluctuating water levels, which influence water quality, vegetation, and carbon cycling. However, the response of CH₄ fluxes and their drivers to altered hydrology and vegetation remains unclear, hindering mechanistic modeling. To address these knowledge gaps, we studied an estuarine freshwater wetland in the Great Lakes region, where rising water levels led to a vegetation shift from emergent Typha dominance in 2015–2016 to floating-leaved species in 2020–2022. Using eddy covariance flux measurements during the peak growing season (June–September) of both periods, we observed a 60% decrease in CH₄ emissions, from 81 ± 4 g C m⁻² in 2015–2016 to 31 ± 3 g C m⁻² in 2020–2022. This decline was driven by two main factors: (1) higher water levels, which suppressed ebullitive fluxes via increased hydrostatic pressure and extended CH₄ residence time, enhancing oxidation potential in the water column; and (2) reduced CH₄ conductance through plants. Net carbon dioxide (CO₂) uptake decreased by 90%, from −267 ± 26 g C m⁻² in 2015–2016 to −27 ± 49 g C m⁻² in 2020–2022. Additionally, diel CH₄ flux patterns shifted, with a distinct morning peak observed in 2015–2016 but absent in 2020–2022, suggesting changes in plant-mediated transport and a potential decoupling from photosynthesis. The dominant factors influencing CH₄ fluxes shifted from water temperature and gross primary productivity in 2015–2016 to atmospheric pressure in 2020–2022, suggesting an increased role of ebullition as a primary transport pathway. Our results demonstrate that changes in water levels and vegetation can substantially alter CH₄ and CO₂ fluxes in coastal freshwater wetlands, underscoring the critical role of hydrological shifts in driving carbon dynamics in these ecosystems.

There are still large uncertainties on the relationships between microbial carbon use efficiency and soil organic carbon across (1) different carbon use efficiency estimation methods, (2) various temporal, spatial and biological scales, and (3) multiple climate change scenarios. These uncertainties call for further efforts to re-examine the relationships between carbon use efficiency and soil organic carbon to better represent microbial processes in the current modelling frameworks.

High spatial or temporal variability in community composition makes it challenging for natural resource managers to predict ecosystem trajectories at scales relevant to management. This is commonly the case in nearshore marine environments, where the frequency and intensity of disturbance events vary at the sub-kilometer to meter scale, creating a patchwork of successional stages within a single ecosystem. The successional stage of a community impacts its stability, recovery potential, and trajectory over time in predictable ways. Here we demonstrate the value of successional theory for interpreting fine-scale community heterogeneity using Hawaiian coral reefs as a case study. We tracked benthic community dynamics on 36 forereefs over a 6-year period (2017–2023) that captures impacts from high surf events, a marine heatwave, and unprecedented shifts in human behavior due to the COVID-19 pandemic. We document high spatial variation in benthic community composition that was only partially explained by island and environmental regime. Through hierarchical clustering, we identify three distinct community types that appear to represent different successional stages of reef development. Reefs belonging to the same community type exhibited similar rates of change in coral cover and structural complexity over time, more so than reefs located on the same island. Importantly, communities that were indicative of early succession (low coral cover reefs dominated by stress-tolerant corals) were most likely to experience an increase in coral cover over time, while later-stage successional communities were more likely to experience coral decline. Our findings highlight the influence of life history and successional stage on community trajectories. Accounting for these factors, not simply overall coral cover, is essential for designing effective management interventions. Site-specific management that accounts for a community's unique composition and history of disturbance is needed to effectively conserve these important ecosystems.

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 or constraint of 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 of instantaneous optimization with a more biologically meaningful dynamic feedback optimization over plant lifespans. Second, we incorporate non-steady-state physics 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.