Global Change Biology

Forests play a crucial role in mitigating climate change as primary terrestrial carbon sinks. While some studies suggest that global warming enhances forest productivity, a growing body of evidence highlights detrimental impact primarily driven by increased water stress. Yet the extent to which positive effects of climate change offset its negative impacts on tree species productivity remains unclear at large spatial extents. We assessed forest growth and mortality for the 21 most abundant tree species in Europe using National Forest Inventory data from more than 50,000 plots and 700,000 trees to disentangle the relative importance of climate and forest structure. Specifically, we examined how vapor pressure deficit (VPD) anomalies across species climatic edges and stand developmental stages affect forest growth and mortality occurrence and intensity (i.e. whether mortality occurred and the amount of basal area lost). Then, we aggregated the responses across species and separately for broad-leaved and needle-leaved species to assess whether forest growth and mortality differed between major functional groups. Although the importance of forest growth and mortality drivers varied markedly among species, climate had a stronger influence on mortality than on growth, particularly in needle-leaved species. Forest growth declined and mortality increased along VPD anomaly in most species and forests studied. Responses were most pronounced at arid species edges in early-stage broad-leaved forests and at wet edges in late-stage needle-leaved forests, where differences between functional groups were also highest. We evidence the need to parametrise species-specific models of forest growth and mortality across large spatial extents to better understand and predict effects of climate change on forest productivity. In addition, our results emphasize the importance of improving the understanding of forest mortality processes given the strong influence of climate on mortality, while also further studying vulnerable populations to climate change in arid edges of species distributions.

Winter warming is altering plant exposure to cold events, yet its effects on seasonal cold hardiness dynamics remain poorly understood. Here we quantified bud cold hardiness across four dormant seasons in a boreal peatland forest whole ecosystem warming experiment. Across a +0.00 to +9.00{degrees}C warming gradient, we semi-regularly measured cold hardiness in two overstory (Larix laricina and Picea mariana) and two understory species (Chamaedaphne calyculata and Rhododendron groenlandicum). Warming reduced cold hardiness in fall and spring by delaying acclimation and advancing deacclimation. However, risk was only increased in late winter and spring for three species. Warming reduced snow cover, increasing temperature variability and cold damage to understory shrubs. Together, our results show that cold damage risk depends on species traits, microclimate, and seasonal timing.

Climate change drives shifts in species composition, but turnover in many communities lags behind the current pace of change. Anticipating the impact of the resulting community-climate disequilibria on ecosystem functioning is critical. Present-day communities may already be out of equilibrium with climate, providing an opportunity to estimate the effects of disequilibrium before they become more widespread. We analyzed plant community composition and function data from [~]60,000 rangeland monitoring sites across the western US to measure how community-climate disequilibrium contributes to spatial and temporal variation in net primary productivity (NPP) - a key ecosystem function. We found that communities were already substantially out of equilibrium with climate and accounting for this disequilibrium helped explain patterns of NPP. Communities farthest from equilibrium were less productive than those that were closely matched with climate. Our findings suggest that future increases in community-climate disequilibrium may further impair ecosystem functioning.

Microbial communities regulate carbon and nitrogen (N) cycling, yet their long-term responses to chronic global changes remain unclear. Using 12 years of grassland litter samples from the Loma Ridge Global Change Experiment in Irvine, California, we tested whether interactions between experimental drought and N deposition, and previously observed temporal variability are driven by background climatic conditions, including precipitation and temperature. Consistent with short-term studies, drought and N addition had relatively small effects on bacterial community composition compared to pronounced seasonal and interannual variability, with drought-by-year interactions explaining more variation than drought alone. Seasonal shifts were largely driven by short-term fluctuations in rainfall and temperature, whereas the substantial interannual variability in community composition was not captured by site-level climate metrics. Contrary to expectations, drought effects were influenced more by background temperature than precipitation, with the strongest effects observed in cooler years. Lastly, a bacterial taxons sensitivity to climate variability under ambient conditions did not predict its response to chronic drought. Together, our findings show that bacterial responses to drought are temporally dynamic and influenced by background temperature, underscoring the need for long-term longitudinal studies of soil microbial communities to better predict microbial responses under future global change. ImportanceMicrobial responses to global change, particularly drought and nitrogen addition, are often inferred from short-term studies (< 2 years), yet natural temporal variability may overshadow experimental effects. Using a 12-year dataset of grassland leaf litter communities, we show that temporal variability, both seasonal and interannual, exert a stronger influence on bacterial community composition than chronic drought or nitrogen deposition. These findings challenge assumptions about the magnitude of drought effects, particularly in naturally drought-affected ecosystem such as California grasslands and highlight the importance of long-term datasets for predicting microbial responses to climate change. By demonstrating that bacterial communities are strongly shaped by background climatic variability (baseline precipitation and temperature independent of imposed chronic treatments) and may be buffered to sustained drought, this work improves forecasts of ecosystem responses and informs the design of global change experiments and restoration strategies in future research studies.

Snow algae darken snowpacks and accelerate melt worldwide. Although elevation strongly structures the physical conditions of mountain snowfields, its influence on snow algal traits and their effects on snowpack reflectance remains unclear. Here, we investigated snow algal composition, cellular traits, and optical properties in summer blooms across an elevational range of 1,059-3,423 m a.s.l. in the western United States, spanning two elevational gradients in the Cascade Range (CA, OR, WA) and the Rocky Mountains (UT, WY, MT). Across all samples (n = 294), snow albedo declined strongly with increasing algal cell density, indicating that total biomass, rather than pigment composition, is the dominant driver of albedo reduction. However, within Sanguina-dominated blooms (117 of 206 samples bloom samples identified across the dataset), neither relative abundance nor algal cell density varied systematically with elevation. Instead, mean cell size increased with elevation, while per-cell pigment concentrations declined, leading to higher astaxanthin:chlorophyll-a ratios driven primarily by reductions in chlorophyll-a per cell. These elevation-dependent shifts in cell size and pigment balance were consistent across both mountain ranges, indicating phenotypic acclimation to increasing environmental stress with elevation. Together, these findings link cellular-scale acclimation of a widespread snow alga to radiative processes shaping mountain snowpacks.

Forest regeneration depends not only on how many seeds trees produce, but on the physiological quality of those seeds. Yet while climate-driven shifts in seed quantity and masting have received sustained attention, the parallel question of whether climate change degrades seed quality remains poorly resolved. Using a nationwide dataset of seed mass and viability in European beech (Fagus sylvatica L.) collected between 1996 and 2024 (13,349 seed lots from 381 forest districts across Poland), with climate-quality analyses focused on 5,374 freshly harvested seed lots from 353 districts (2004-2023), we asked whether the two components of seed quality respond to different seasonal climatic windows, and whether harvest-year climate also shapes seed performance during long-term cold storage. Seed mass and seed viability were only weakly correlated (Spearmans {rho} = 0.15), acting as two independent dimensions of seed quality. Both revealed substantial temporal variation over the study period, but along distinct trajectories. Seed mass declined markedly between segmented-regression breakpoints in 2009 and 2019, more steeply at higher latitudes, coinciding spatially and temporally with the masting breakdown reported at the species northeastern range margin. Climatic associations were correspondingly divergent. Viability was positively associated with previous summer temperature, consistent with temperature-cued flower initiation, and negatively with spring temperature in the harvest year, plausibly reflecting thermal disruption of early embryogenesis. Seed mass showed no significant association with any seasonal climatic predictor, indicating control by slower or unmeasured processes. Storage duration progressively reduced viability, and this decline was further modulated by climate during seed development, with seeds developing under climatically suboptimal conditions losing viability faster. These results expose a hidden decoupling between seed quantity and seed quality under contemporary climate change, with direct consequences for forest regeneration and for ex situ conservation strategies that assume mast-year seeds will remain viable for decades.

Background Increasingly accessible satellite imagery provides scalable measures of the built and natural environment relevant to population health. However, whether such imagery can capture subnational variation in mortality and life expectancy remains unclear. We therefore assessed its predictive value for regional mortality and life expectancy across OECD regions. Methods We conducted an ecological, cross-sectional prediction study using 2023 data from OECD Territorial Level 3 (TL3) regions. Annual cloud-masked composites from the Harmonized Landsat and Sentinel-2 collection were processed in the Google Earth Engine, tiled at 224 x 224 pixels, and encoded with the pretrained Prithvi foundation model to derive region-level satellite embeddings. For each outcome, we trained LightGBM regressors for a country-only baseline, a satellite-only model, a combined model (country + satellite), and a final contextual model that additionally included prespecified socioeconomic and environmental covariates. Performance was evaluated using 10-fold outer cross-validation with held-out test folds; R2 was the primary metric. Results The analytic sample comprised 2,414 OECD TL3 regions across 38 countries, for which 939,959 satellite image tiles were processed. In paired bootstrap comparisons, adding satellite features to country indicators improved predictive performance for all outcomes, with incremental R2 ranging from 0.097 to 0.233. The final contextual model achieved R2 values of 0.78 (95% CI, 0.74-0.81) for crude mortality, 0.87 (0.84-0.89) for age-adjusted mortality, 0.86 (0.82-0.88) for infant mortality, and 0.76 (0.69-0.84) for life expectancy. In SHAP analyses, the aggregated satellite image effect consistently ranked among the top predictors across outcomes. Conclusion Satellite imagery captures subnational environmental heterogeneity relevant to regional mortality and life expectancy beyond country identity alone. Earth observation may therefore provide a scalable, complementary data source for characterizing geographic disparities in population health.

Accelerated warming at high elevations is having a disproportionate impact on alpine species. While assessments of climate vulnerability require quantifying the ecological and evolutionary components of adaptive capacity, such assessments are rare, especially in alpine systems. We leverage recent advances in population and landscape genomics to assess how variation in spatial heterogeneity and population connectivity across alpine systems influences adaptive capacity, using the North American Rosy-Finch species complex as a model system. In doing so, we clarify taxonomic relationships across the complex and identify one new ESU, the Sierra Nevada Rosy-Finch, based on its combined ecological and evolutionary distinctiveness. We then illustrate how combining genomic analyses with ecological data can improve estimates of adaptive capacity, sensitivity, and exposure and ultimately clarify climate vulnerability. Overall, our integrative analyses revealed that more isolated lineages, such as the Sierra Nevada Rosy-Finch, have lower adaptive capacity and face disproportionately high risks from climate change. This work highlights how conservation strategies that account for the multidimensional aspects of adaptive capacity can improve estimates of climate vulnerability.

The Canadian Arctic Archipelago (CAA) is warming at an unprecedented rate, leading to sea ice loss and glacial retreat. Marine-terminating (tidewater) glaciers can fuel summertime marine productivity by delivering nutrient-rich deep waters via upwelling to the surface ocean. While the impact of glacier-induced upwelling has been well-studied in the context of phytoplankton and primary productivity, its effects on broader marine microbial communities remain poorly understood. We investigated how glacier-driven upwelling shapes marine microbial (bacterial and archaeal) communities across a series of sites in the CAA. At upwelling sites, the upper 50 m of the water column exhibited elevated nutrient concentrations and physical characteristics that resembled deeper waters, which were associated with differences in microbial community composition relative to non-upwelling sites. Our results indicate that upwelling influences microbial communities in surface waters in two ways. It directly introduces typically deeper-water-associated taxa into surface waters and reshapes ecological niches by enhancing nutrient supply and stimulating primary production, indirectly driving changes in microbial communities. The enrichment of Candidatus Nitrosopumilus, a deep water nitrifier, likely affects nitrogen cycling and raises the possibility of active nitrification in surface waters. Likewise, the increased abundance of taxa known to be associated with phytoplankton-derived organic matter in upwelling regions suggests an enhanced capacity to process organic matter generated from elevated primary productivity. Ultimately, as tidewater glaciers continue to retreat, the resulting changes in the glacially-driven upwelling regime will likely shift marine microbial communities towards assemblages adapted to less productive ecosystems, with implications for nutrient cycling in these systems. ImportanceClimate change has a disproportionate impact on the Arctic, with rising temperatures causing increased marine-terminating glacier retreat and changes in the marine water column structure. The consequent loss of the ability of these glaciers to upwell deep water to the surface ocean results in a reduction of nutrient delivery and mixing in these ecosystems. Previous work has highlighted the importance of marine-terminating glaciers in sustaining phytoplankton productivity during the summer season through this delivery of deep-water nutrients to the surface ocean. The impact of glacially-induced upwelling on marine bacterial and archaeal communities, however, remains underexplored. We found that in regions with glacially-driven upwelling, the surface ocean showed enrichment of phytoplankton-associated taxa and nitrifiers commonly associated with deep waters. This work underscores the role of glacially-driven upwelling in structuring both microbial communities and nutrient cycling, suggesting that glacier loss could reshape community composition and biogeochemical processes in a rapidly changing Arctic.

Global marine heatwaves have devastated tropical coral reefs, and further mortality is projected under ongoing climate change. Identifying thermally tolerant coral colonies is therefore a priority for conservation, restoration, and research. Portable acute heat stress assays (e.g., CBASS) enable rapid, standardized estimates of coral thermal tolerance under field conditions. However, it remains unresolved whether such experimentally derived metrics (ED5, ED50, DW) predict bleaching and mortality in situ. Here, we quantified acute thermal tolerance metrics for 2,068 coral colonies across 12 common Indo-Pacific species, six months prior to an unprecedented heat stress event in northeastern Peninsular Malaysia and compared experimentally derived ED and DW values to subsequent bleaching severity and mortality in the field. Experimental thermal tolerance metrics explained only a limited proportion of variation in bleaching outcomes and survival. Predictive power varied among species and was higher in slow-growing species. Our findings suggest that while acute heat stress assays capture substantial variation in coral thermal tolerance, their ability to predict in situ outcomes is context-dependent and diminishes under severe thermal stress. Ultimately, in situ coral bleaching under severe heat stress may reduce the discriminatory capacity of acute assay-derived tolerance metrics.

Mediterranean forest restoration depends critically on autumn seedling outplanting and establishment, a period increasingly threatened by delayed and irregular precipitation. Although critical, drought at moderate temperatures, decoupled from summer heat stress, remains poorly characterized in terms of plant physiology and root microbiome responses. In the present study we simulated a short but severe drought under moderate air temperatures (5-25{degrees}C) in Pinus halepensis Mill. seedlings to examine the independent effects of water deficit on physiology and root-associated microbial communities. Drought reduced stomatal conductance to one-third of control values and induced a decoupling between stomatal conductance and net photosynthesis upon rewatering. This decoupling is rather due to the residual hydraulic and biochemical limitations rather than transpirational cooling demands. Drought-treated seedlings diverged into distinct phenotypic classes differing in recovery capacity, with a subset failing to recover despite being phenotypically identical to the controls. Root microbiome restructuring was phenotype-dependent and differed between active and resident fractions: bacterial richness and evenness increased while bacterial assembly shifted progressively toward determinism with increasing phenotype severity (29% to 37%), whereas fungal communities shifted toward stochastic drift (up to 89%). Functionally, drought disrupted symbiotic associations and drove a shift toward a fungal saprotrophic lifestyle. Network analyses revealed displacement of Rhizobium from its central hub position, reducing connectivity and compromising functional resilience. These results demonstrate that short, severe drought at moderate temperatures fundamentally affect plant-microbiome interactions through phenotype-dependent assembly processes, with direct consequences for seedling establishment and Mediterranean reforestation under climate change.

Theory predicts that demographic performance should peak at the core of species ranges and decrease toward their limits. Yet, empirical correlations between population growth rate and species distribution remain weak for most tree species. Part of the problem may arise from the difficulty of integrating multiple demographic processes across the complex life cycle of a forest, and from the significant variability among individuals and locations. It remains unclear if the mismatch between performance and distribution arises from modelling limitations or if climate is simply a poor predictor of species performance across distributions. Here, rather than asking whether demographic performance correlates with species distributions, we ask how climate and competition jointly shape population growth rate for 31 tree species across eastern North America. By combining flexible nonlinear hierarchical models for growth, survival, and recruitment with explicit uncertainty propagation, we use Integral Projection Models to address key gaps in previous studies. Perturbation analyses revealed that population growth rate was consistently more sensitive to mean annual temperature than to conspecific or heterospecific competition across all species. We further examined how sensitivities to climate and competition varied across species thermal ranges. The dominance of climate over competition increased toward both cold and hot range limits, while sensitivity to competition generally declined from cold to hot limits. Notably, these patterns emerged along the continental thermal gradient shared across species rather than within each species individual range, suggesting that range-edge demographic responses may arise as a community-level phenomenon. Across species, the largest source of variability remained the local plot conditions captured by random effects, likely reflecting differences in soil conditions, drainage, and disturbance history. Together, these results may provide a mechanistic pathway underlying the performance declines predicted by range-limit theories, and offer a basis for understanding how forest populations and communities may reorganize in response to ongoing climate change and shifting disturbance regimes.

Coral reefs deliver vital services via a complex three-dimensional framework sustained by the balance between calcium carbonate production and erosion, or the net carbonate budget state. In many tropical western Atlantic reefs, ecological decline has reduced carbonate production, yielding near-neutral or negative budgets. Yet some reefs retain high coral cover and, theoretically, should also have high net positive budgets, yet often show modest carbonate accumulation. We used the remote reef of Cayo Arenas in the Campeche Bank, Gulf of Mexico, to test whether in reefs under suboptimal (variable) environmental conditions, high coral production is offset by robust bioeroder communities, producing neutral budgets. At 14 sites, we quantified carbonate producers and bioeroders to estimate gross production, bioerosion, and net budget states. Despite relatively high live coral cover, mean net carbonate budgets were approximately neutral. Crucially, this neutrality arose not from depressed biological activity (as in degraded reefs) but from an active equilibrium: vigorous carbonate production coupled with substantial bioerosion. These reefs, therefore, represent a contemporary, functional reef state in net stasis. Distinguishing active-neutral from impoverishment-neutral regimes is critical for predicting reef trajectories under environmental change and for targeting management, although near-stasis emerging from high carbonate turnover can appear functionally intact yet operate with limited buffering capacity against net carbonate loss.

Winter can affect animal population dynamics by limiting resource availability and increasing energetic costs of movement caused by deep snow. Given the rapid alteration of snowpack properties due to climate change, quantifying how snow characteristics influence reproduction and physical condition is critical. We evaluated how snow cover duration, depth, and density affect spring body mass, reproduction probability, and subsequent autumn body mass of bighorn sheep (Ovis canadensis) using 45 years of individual-based data at Ram Mountain, Alberta, Canada, along with historical snow records reconstructed via the SNOWPACK model. Using Bayesian structural equation modeling, we quantified the direct and indirect effects of snow across different sex and age classes. Long and deep snow covers reduced spring body mass across all demographic groups, with yearlings, especially males, losing up to 0.12 kg per additional cm of snow depth. Harsh snow conditions reduced the probability of reproduction for adult females and generated a compensatory indirect effect on mass by avoiding the energetic costs of reproduction. In contrast, yearlings showed no compensatory responses and entered the following autumn in poor condition (up to 14% lighter for males and 8% for females following the deepest snow years). The impact of snow density on autumn mass of adult males was density-dependent, shifting from beneficial at low density (+0.09 kg per kg/m3) to detrimental at high density (-0.04 kg per kg/m3). The effects of snow conditions generate persistent, context-dependent carry-over effects across seasons. Our study suggests that distinct demographic groups rely on different mechanisms to cope with environmental constraints, highlighting complex, time-lagged consequences of changing winter climate on alpine herbivore populations.

Subalpine forests in the Alps are fragile ecosystems that play a crucial role in regional water resources and the local climate. These ecosystems are ecologically significant due to their unique biodiversity and vulnerability to climate change. While several components of the hydrological balance have been studied, the interplay between catchment-scale processes and plot-scale drivers such as fog presence and forest age remains insufficiently understood. To address this, we investigated the hydrological balance of a subalpine coniferous forest catchment at the Renon site in the Italian Alps, integrating observations across spatial scales. The study area includes a mosaic of mature and younger regrowth forest, where both interannual and seasonal variability in precipitation and fog presence are pronounced. At the catchment scale, we quantified above-canopy precipitation, evapotranspiration (ET, measured via eddy covariance at the ICOS tower), stream discharge, and soil moisture dynamics. Within the catchment, we characterised water partitioning using sap flow sensors for tree transpiration, throughfall and stemflow collectors with rain gauges above and below the canopy and epiphyte sampling. Mixed fog-rain events frequently coincided with higher throughfall. However, these changes had a minor effect on soil water storage and catchment discharge in the annual water balance, which was nearly closed. At the plot scale, our results show that tree transpiration was higher in the younger forest structure, while canopy interception is a dominant process in water partitioning in the older forest structure, where lichen abundance likely enhances interception. This study highlights the importance of multi-scale monitoring in temperate mountain forests, where forest age influences water partitioning, and fog presence, though not directly quantified, can still contribute to reducing evaporative processes. Such contributions may gain importance under changing climate conditions, albeit less prominently than in tropical or subtropical cloud forests.

Genomic forecasting approaches based on genotype-environment associations (GEAs) are increasingly used to estimate genomic offsets (GOs), which predict population maladaptation and extinction risk under current or future climatic conditions. Despite their widespread use, only a subset of studies have evaluated how accurately GOs predict (mal)adaptation, limiting their interpretation and application in policy and management. Here, we used GEA analyses to estimate GOs for past, present, and future climates in Lycaeides butterflies, focusing on the causes of variation in GOs among populations and their relationships with demographic parameters inferred from population genomic data. Using multivariate linear regression and genotyping-by-sequencing data from 42 Lycaeides populations (922 butterflies), we found that mean annual temperature, cumulative annual precipitation, and hybridization history together explained 47.6% of variation in genome-wide allele frequencies. Genomic offsets differed substantially among populations and across past, present, and future climates, with evidence for increasing maladaptation under more distant future climate scenarios. We found no relationship between GOs for present climates and contemporary effective population size. In contrast, genetic diversity, which reflects long-term effective population size, and local rates of gene flow together explained 27.3% of variation in contemporary GOs. Populations with higher genetic diversity and more gene flow exhibited lower GOs, consistent with the hypothesis that genetic diversity enhances adaptive capacity and that gene flow may introduce adaptive alleles. Overall, our results support the utility of GO predictions, particularly when validated with independent measures of adaptation, while cautioning against simplistic interpretations of GO as a direct measure of maladaptation in conservation and management contexts.

As global temperatures rise, ecological communities are increasingly dominated by warm-affiliated species, a process known as community warming or thermophilisation. Yet, why different taxa exhibit different rates of community warming remains unclear. Habitat composition and structure are likely drivers of this variation, as the ecological consequences of warming are filtered by local environmental conditions. Using over 40 years of monitoring data spanning terrestrial (birds, insects, plants) and freshwater (phytoplankton) communities, we show that habitat structure determines how strongly communities track warming. Forest cover systematically slows thermophilisation by reducing communities sensitivity to temperature change, whereas habitat heterogeneity has weak and variable effects that differ among ecosystems. Together, these results demonstrate that uneven thermophilisation arises from habitat-mediated differences in how communities respond to a shared climatic signal. Incorporating these effects is essential for improving predictions of biodiversity change under ongoing climate warming.

Changing climates are reshaping animal populations, but our understanding of how demographic trends are shaped by individual responses to local environmental conditions is often limited to long-term studies with restricted spatial scales. Increasing evidence suggests that climatic extremes exert differential selection pressures across environments, often leading to nonstationary biological responses among populations. Participatory science (i.e. citizen science) observations can detect this variation at large geographic scales, but analyses of these data often lack insight into the individual-level responses that are required to explain the origins of such variation. Here we present a new research framework that uses long-term data to validate, then inform analyses of participatory science data to measure reproductive responses to environmental variation across large geographic scales. We use this approach to investigate how reproduction in a montane-adapted songbird, the mountain chickadee (Poecile gambeli), varies across elevations and latitudes in response to extreme scarcity and extreme accumulation of snow throughout the Sierra Nevada Mountains in North America. Chickadee reproduction in lower and higher elevation populations was often differentially impacted by drought and deluge snowfall extremes, but these relationships varied across latitudes. Reproductive performance in the northern Sierra Nevada was negatively affected by snow deluge conditions at high elevations, whereas snow drought conditions reduced reproductive output at low elevations. These relationships changed in the central Sierras where drought conditions negatively impacted both elevations, but deluge conditions improved reproductive performance at both low and high elevations. Reproduction in the southern Sierra Nevada was less affected by spring snow levels, likely due to the lower snow accumulation and earlier snowmelt in this region. These results emphasize the power of long-term studies to inform and interpret participatory science data in order to better understand how animal responses to environmental extremes vary across large geographic scales.

Northern peatlands store large carbon stocks but are sensitive to disturbance. Hydrology, vegetation, herbivory and snow conditions may affect the soil microorganisms driving methane (CH) and nitrous oxide (N2O) cycling. We investigated how reindeer exclusion and snow depth (increased and reduced relative to ambient) manipulations (ongoing for three seasons) influenced archaeal and bacterial communities in a boreal rich fen. Metagenomic (MG) and metatranscriptomic (MT) sequencing were combined with pore-water chemistry and CH flux measurements to link the microbiome to ecosystem processes. Microbial communities differed between outside and inside the exclosure. However, these patterns primarily reflected underlying hydrological variation. Slightly wetter inside plots showed higher expression of denitrification genes (norB, nosZ) and lower (nirS+nirK)/nosZ ratios, indicating greater potential for complete denitrification to N2 instead of N2O. Methane dynamics were mainly associated with vegetation: plots associated with Carex rostrata exhibited lower pmoA/mcrA ratios and elevated CH fluxes. Snow manipulations had subtle effects: reduced snow depth decreased the expression of taxa dependent on microbial interactions, while the effect to the investigated metabolic marker genes was small. Overall hydrology, leading to variations in redox conditions and nutrient availability, together with vegetation appeared as the primary drivers on microbial greenhouse gas processes in this peatland.

Recurring patterns in biosphere dynamics are anchored in daily and seasonal oscillations in abiotic variables driven by Earths obliquity, rotation, and orbit. While circadian and annual biotic cycles are well studied, persistent supra- or subannual cycles in biotic systems are rarely documented globally. Here, we apply a machine learning approach to DNA metabarcoding time series and detect a biotic semi-annual cycle expressed across aquatic communities in temperate regions across taxonomic domains. We propose that this dynamic reflects a semi-annual mode in insolation and is suppressed under conditions of limited nutrients or sunlight. Our results suggest photoautotrophs are central for the aetiology of the biotic SAM, while demonstrating that it is a community-level phenomena not attributable to single species. The regularity of the biotic SAM suggests value for anticipating less predictable ecological events, including phytoplankton blooms. Overall, our results highlight Earth system-scale forcing of local dynamics and reinforce coupling patterns.