ABSTRACTClimate change is increasing human exposure to novel environments and generating serious practical challenges in human health, while the role of past climates in shaping hominin evolution remains a fascination. Models of human heat exchange vary from simple environmental indices to extremely detailed physiological calculations. Physiologically explicit models vary in their physical explicitness, and significant trade‐offs exist between model realism and computational speed. We presently lack agile models that are not so over‐parameterised that they are slow, that maintain generality across diverse and complex physical environments, and that have sufficient biological realism to capture human (and, more generally, hominin) diversity in physiology, body size and proportions, activity level, clothing, hair, and skin. Here we present a model (HomoTherm) to fill this gap, built upon the general endotherm model from the NicheMapR package for biophysical modelling in R. This steady‐state heat budget model is unique among existing open‐source models in that it solves for the metabolic rate, evaporation rate, skin temperature, and clothing temperature of a multi‐part (head, torso, and limbs) human of variable shape, size, or colour and at variable levels of physical activity. The model can handle complex microclimates, including environments that differ in downwelling and upwelling radiation, and connects directly with the microclimate modelling capabilities of NicheMapR. Because of its general nature, it can easily be adapted to model other hominins by changing proportions, fur properties, and any other known physiological trait. We illustrate the model's capabilities through comparisons with actual human responses in published empirical studies of indoor and outdoor exposures to heat and cold, and compare HomoTherm's performance with that of other models. Vignettes and an open‐source Shiny app facilitate the use of HomoTherm in addressing fundamental and applied problems in human thermal biology.

Soil organic carbon (SOC) is a key indicator of soil health and a crucial component of climate mitigation, making its reliable monitoring increasingly important. While Digital Soil Mapping (DSM) based on Machine Learning and Earth Observation (EO) data enables the generation of time series of spatially explicit SOC predictions, detecting temporal changes from these model predictions remains challenging due to the relatively large associated uncertainties. Although prediction uncertainties are now commonly reported, few studies have explicitly accounted for them when assessing SOC change. This study introduces a model-based signal-to-noise ratio (SNR) framework to assess the detectability of SOC change using both the state-first approach-modeling SOC states at each time point and then deriving change-and the change-first approach-modeling SOC change directly from repeated measurements. SNR is defined as the ratio of predicted SOC (concentration, g/kg) change to its modeled uncertainty, enabling evaluation of change-model reliability at pixel levels. Applied to repeated SOC observations from the pan-European Land Use and Coverage Area Frame Survey, this framework assesses the reliability of SOC change modeling across multiple land-cover types using Random Forest and Quantile Regression Forests. At the site level, prediction accuracy was poor and SNR values were consistently low. An illustrative aggregation analysis showed that spatial averaging improved SNR, supporting SOC change assessments at broader scales. However, further work is needed to incorporate land use and management information and to systematically examine how different aggregation schemes affect the results in various contexts, ensuring that aggregated outcomes remain meaningful and policy-relevant. As an internal metric based on model predictions and their estimated uncertainty, SNR provides a practical diagnostic of change-model confidence, especially when repeated ground-truth SOC measurements are not available. We advocate for routine SNR reporting to enhance the transparency and credibility of DSM-based SOC change monitoring.

Compound dry-hot events (CDHEs) are intensifying globally, positioning the Yellow River Basin (YRB) as a critical sentinel for understanding semi-arid ecosystem stability under climate change. This study investigates the spatiotemporal dynamics of vegetation resilience in the YRB (2001-2023) by integrating satellite-derived vegetation indices (NDVI), meteorological data, and Critical Slowing Down (CSD) indicators. Testing the hypothesis of a "Resilience Paradox," we reveal a counter-intuitive buffering mechanism: while high-intensity and prolonged CDHEs accelerated resilience loss, frequent but sublethal events significantly slowed this decline by triggering ecological memory and adaptive hardening. However, this buffering capacity is not limitless; mediation analysis identifies soil moisture as a strict boundary condition, meaning "training effects" fail in severely water-limited zones. Spatially, we delineate three functional management zones requiring distinct strategies: (1) conservation of the hydrological buffer in the water-abundant Source Region; (2) strict adherence to carrying capacity limits in the frequency-driven Loess Plateau to prevent tipping; and (3) active mitigation of prolonged stress in the agricultural Lower Reaches. By linking regional resilience mechanisms to global dryland dynamics, this study offers predictive insights for ecological restoration initiatives-such as the Great Green Wall-shifting the focus from maximizing biomass to sustaining functional persistence under future compound extremes.

According to data from the USDA's Risk Management Agency, crop insurance indemnities related to precipitation, hurricanes, excess moisture, and field inundation have totaled approximately $3.65 billion across Illinois, Indiana, and Iowa over the past decade. Of this amount, an estimated $924 million (25.31%) was attributed to losses that occurred in the spring months. Cover crops and conservation tillage have been recommended as best management practices to mitigate financial impacts by reducing nutrient losses from erosion, runoff, and greenhouse gas (GHG) emissions, preventing disease and physical plant damage, and enhancing field access through improved landscape drainage. However, further intensification of field inundation events is projected in these three states as we approach the midcentury, which may lessen the mitigative capacity of these practices. Few studies have tested the resilience of these land management practices to intensifying field inundation. We propose a framework that integrates guiding research questions and field experiments to determine whether the mitigative capacity of cover crops and conservation tillage keeps pace with intensifying field inundation events. We also explore agricultural biologicals, precision agriculture, the introduction of perennial crops, and drainage management as measures to address inefficiencies associated with the mitigative capacity of cover crops and conservation tillage that may be identified during experimentation. This effort expands recommended best management practices and provides stakeholders with more options in an uncertain future due to climate change.

Global warming is altering spring phenology in temperate forests, with important consequences for tree survival, growth, and ecological interactions. However, temperature requirements for dormancy release and budburst vary among populations adapted to different climatic conditions, complicating predictions of spring phenology across broad geographic regions. Here, we quantified the chilling and forcing requirements of three deciduous tree species (Fagus sylvatica, Quercus robur, and Tilia cordata) using four provenances per species spanning a latitudinal gradient from Spain to Poland. Saplings were overwintered under either ambient or warmed open-top chambers and were transferred monthly from November to February to a climate chamber under constant forcing conditions. We found that reduced chilling due to earlier transfer substantially delayed budburst, with T. cordata showing the highest chilling requirement, followed by F. sylvatica, whereas Q. robur exhibited the lowest. We detected both co- and counter-gradient patterns of genetic variation in budburst timing. In Q. robur and, to a lower extent, in T. cordata, Polish provenances budburst later than Spanish ones, while German and Swiss populations were intermediate (co-gradient). In contrast, F. sylvatica showed the opposite pattern with the Spanish provenance tending to budburst latest and the Polish one earliest (counter-gradient). These differences likely reflect genetic differentiation in chilling and forcing requirements among provenances, likely driven by variation in frost risk at their sites of origin. Importantly, insufficient chilling significantly reduced budburst success by 25%-85% across species, with the strongest effect in T. cordata, where success fell below 10% in saplings transferred in November or December across all provenances, potentially constraining canopy development and impairing growth and reproduction. These findings underscore the critical role of winter chilling in regulating budburst timing and canopy development, as well as provenance-specific adaptation, suggesting that species adapted to low chilling might be candidates for assisted migration under rapid climate warming.

Converting cropland to planted forests improves soil organic carbon (SOC) and total nitrogen (TN) storage while contributing to climate change mitigation, primarily through the regulation of belowground organisms and mineral protection such as calcium (Ca). However, the mechanistic pathways linking exchangeable Ca2+, soil micro-food web interactions, and nutrient accumulation under warming remain unclear. Here, we investigated their potential roles in driving the accumulation of mineral-associated organic matter (MAOM), SOC, and TN in planted forests compared with croplands under warming conditions. Planted forests exhibited higher MAOM, SOC, and TN than cropland and had stronger coupling between carbon and nitrogen. Warming increased MAOM, SOC, and TN in planted forests but reduced SOC in cropland. Compared to cropland, planted forests displayed elevated levels of soil exchangeable Ca2+, microbial necromass carbon and nitrogen, stronger Ca-microbial and multi-trophic associations. Warming further amplified positive Ca-microbial (e.g., bacteria and fungi) and cross-trophic associations (e.g., nematode-bacteria, nematode-fungi, nematode-protist, and omnivore-predator-bacteria/fungi) in planted forests by increasing plant productivity, litter biomass, and soil exchangeable Ca2+, whereas cropland showed limited responsiveness to temperature changes. In planted forests, soil exchangeable Ca2+ was positively correlated with Ca-microbial and cross-trophic associations, microbial necromass carbon and nitrogen, and the contents of MAOM, SOC, and TN. These relationships were absent in cropland. Notably, cross-trophic associations rather than microbial abundance or diversity, with significant modulation by soil exchangeable Ca2+, had the strongest positive relationship with MAOM, SOC, and TN accumulation in planted forests. Collectively, our findings lead to the hypothesis that warming promotes SOC and TN storage in planted forests by jointly strengthening exchangeable Ca2+, Ca-microbial and cross-trophic interactions. These results highlight the potential importance of multi-trophic interactions and Ca-mediated processes in stabilizing microbial necromass and fostering carbon and nitrogen preservation during vegetation restoration in response to warming.

Nitrogen deposition often promotes plant invasions and can arise from multiple sources. However, it remains unclear whether native legumes facilitate invasive plants directly through biotic nitrogen transfer or indirectly via soil microbial mediation. It is also unknown how exogenous nitrogen addition influences these facilitative effects. To address these questions, we combined evidence from a greenhouse experiment and global meta-analysis. The greenhouse experiment tested the effects of neighboring plants (a native nitrogen-fixing legume Albizia julibrissin; a native non-nitrogen-fixing legume Styphnolobium japonicum; or a conspecific) on the growth of invasive Rhus typhina and its native congener R. chinensis. Within-pot membrane treatments were used to obstruct microbial and nitrogen movement between focal and neighboring plants, with and without added nitrogen. The total biomass of invasive R. typhina increased when grown with the nitrogen-fixing legume compared with conspecific neighbors, but not when grown with the non-nitrogen-fixing legume. Positive effects of the nitrogen-fixing legume on R. typhina were suppressed when nitrogen transfer or soil microbial movement was obstructed by membranes. Exogenous nitrogen addition did not alter the growth of invasive R. typhina or its interactions with legumes. The biomass of native R. chinensis did not differ among neighboring plant treatments, indicating that facilitation by legumes favored the invasive species. The global meta-analysis of 268 effect sizes from 46 studies of the effects of legumes on neighboring plants also revealed that native legumes enhanced invasive plants' performance. Together, our findings recognize nitrogen-fixing legumes as overlooked facilitators of plant invasion, operating through both nutrient and microbial mediated pathways. These findings highlight a paradox in which native species can act as "turncoats," accelerating invasion and reshaping plant communities under global change.

Forest canopy, air temperatures and air humidity ( , , and ) play a central rol in regulating energy and gas exchange between vegetation and the atmosphere. Although often treated as independent drivers of canopy processes, and are dynamically coupled to via surface energy fluxes and atmospheric boundary layer (ABL) development. We investigated how plant physiology mediates this coupling. Using data from a tropical ecosystem, we studied a process-based forest model dynamically coupled with an ABL growth model to simulate diurnal interactions between the canopy and the atmosphere. We systematically varied plant traits related to water use and thermal regulation to assess their effects on coupling and feedback. We focused on three metrics: the slope of the relationship, the peak of reached during the day and the lag between the maximum and , indicating hysteresis. Conservative water use, by reducing transpiration, leads to greater canopy warming, which intensifies sensible heat flux and accelerates ABL growth. This, in turn, raises near-surface air temperature and vapor pressure deficit (VPD), amplifying thermal and water stress. In contrast, greater water use enhances evaporative cooling and slows ABL development, thereby moderating these feedback. Surprisingly, the slope of the relationship is quite insensitive to plant water-use syndromes. This insight extends beyond modeling. Empirical studies often treat and VPD as independent drivers of transpiration, photosynthesis, or stomatal conductance. Our results challenge this assumption, showing that these variables are influenced by plant function itself. is not a passive outcome but an active mediator of energy, water, and carbon exchange, regulated by a feedback loop involving leaf physiology and atmospheric dynamics. Studies using or the relationship-whether from remote sensing or field data-as a proxy for forest stress or function, must account for this coupling.

ABSTRACTBoreal peatlands provide an important carbon store, which is highly susceptible to future changes in the global climate. Predictions of climate feedbacks on the peatland carbon balance require an in‐depth understanding of how vegetation dynamics and environmental conditions jointly govern the production and decomposition of organic matter. However, detailed knowledge on the separate roles of plant functional groups (PFGs) in regulating peatland production and respiration fluxes in response to various abiotic factors at sub‐seasonal scales is currently lacking. In this study, we used high‐temporal resolution CO2 flux data from an automated chamber system established across experimental vegetation removal plots to separate the production and respiration fluxes of vascular plants and Sphagnum mosses over three growing seasons (2021–2023) in a boreal peatland. We found that gross primary production (GPP) of Sphagnum mosses exceeded that of vascular plants during green‐up (average ratio: 1.18) and senescence (1.11), whereas vascular plants were the main contributor during the peak season (0.88). Vascular plants dominated autotrophic respiration (RA; 78%–93%) in all phenophases and contributed 38%–40% to growing season ecosystem respiration. For both PFGs, plant phenology was the primary driver for variations in GPP during green‐up, whereas photosynthetic photon flux density was most important in regulating GPP during the peak season and senescence. Vascular plants reached greater maximum GPP throughout all phenophases, whereas Sphagnum mosses had a higher initial light use efficiency during green‐up and senescence. Moss RA exhibited greater daytime temperature sensitivity than vascular plants during the peak season and senescence, but not during nighttime. These findings highlight that climate change effects on vegetation phenology and composition may strongly alter the peatland carbon cycle. Thus, understanding the separate roles of vascular plants and Sphagnum mosses in regulating production and respiration fluxes in different environmental conditions is crucial to improve predictions of northern peatland carbon cycle‐climate feedbacks.

While spring phenology has been widely studied, the magnitude and drivers of its decoupling from thermal cues across extratropical biomes remain poorly understood. Using satellite data from 1982 to 2021, we show that the onset of vegetation green-up (GSOS) generally lags the onset of the thermal growing season (TSOS). This mismatch (ΔSOS) has increased by 1.51 days per decade (p < 0.001) since 1996, largely driven by shrublands and grasslands. GSOS in these biomes exhibits lower sensitivity to spring temperature but stronger responses to shotwave radiation and precipitation, with higher ratios of heat accumulation to winter chilling associated with delayed green-up under reduced chilling. Phenological decoupling is strongly biome dependent: in warm-dry grasslands and shrublands (ΔSOS > 15 days), warming-driven advances in TSOS are increasingly decoupled from GSOS, as declining precipitation and enhanced evaporative demand intensify moisture limitation and delay green-up; in temperate forests (both coniferous and broadleaf), warming together with enhanced shortwave radiation promotes faster GSOS advancement relative to TSOS, thereby dampening the mismatch. These contrasting pathways reveal an accelerating yet heterogeneous phenology-temperature decoupling, with far-reaching consequences for ecosystem synchrony, seasonal carbon uptake, and land-climate feedbacks. Our results underscore the need to incorporate non-thermal drivers and biome-specific controls into phenological and Earth system models to better constrain future climate-biosphere interactions.