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Abstract Nonlocal models have demonstrated their indispensability in numerical simulations across a spectrum of critical domains, ranging from analyzing crack and fracture behavior in structural engineering to modeling anomalous diffusion phenomena in materials science and simulating convection processes in heterogeneous environments. In this study, we present a novel framework for constructing nonlocal convection–diffusion models using Gaussian‐type kernels. Our framework uniquely formulates the diffusion term by correlating the constant diffusion coefficient with the variance of the Gaussian kernel. Simultaneously, the convection term is defined by integrating the variable velocity field into the kernel as the expectation of a multivariate Gaussian distribution, facilitating a comprehensive representation of convective transport phenomena. We rigorously establish the well‐posedness of the proposed nonlocal model and derive a maximum principle to ensure its stability and reliability in numerical simulations. Furthermore, we develop a meshfree discretization scheme tailored for numerically simulating our model, designed to uphold both the discrete maximum principle and asymptotic compatibility. Through extensive numerical experiments, we validate the efficacy and versatility of our framework, demonstrating its superior performance compared to existing approaches. 

Summary Leaf dark respiration (R_dark), an important yet rarely quantified component of carbon cycling in forest ecosystems, is often simulated from leaf traits such as the maximum carboxylation capacity (V_cmax), leaf mass per area (LMA), nitrogen (N) and phosphorus (P) concentrations, in terrestrial biosphere models. However, the validity of these relationships across forest types remains to be thoroughly assessed.Here, we analyzedR_darkvariability and its associations withV_cmaxand other leaf traits across three temperate, subtropical and tropical forests in China, evaluating the effectiveness of leaf spectroscopy as a superior monitoring alternative.We found that leaf magnesium and calcium concentrations were more significant in explaining cross‐siteR_darkthan commonly used traits like LMA, N and P concentrations, but univariate trait–R_darkrelationships were always weak (r² ≤ 0.15) and forest‐specific. Although multivariate relationships of leaf traits improved the model performance, leaf spectroscopy outperformed trait–R_darkrelationships, accurately predicted cross‐siteR_dark(r² = 0.65) and pinpointed the factors contributing toR_darkvariability.Our findings reveal a few novel traits with greater cross‐site scalability regardingR_dark, challenging the use of empirical trait–R_darkrelationships in process models and emphasize the potential of leaf spectroscopy as a promising alternative for estimatingR_dark, which could ultimately improve process modeling of terrestrial plant respiration. 

Summary Decades of studies have demonstrated links between biodiversity and ecosystem functioning, yet the generality of the relationships and the underlying mechanisms remain unclear, especially for forest ecosystems.Using 11 tree‐diversity experiments, we tested tree species richness–community productivity relationships and the role of arbuscular (AM) or ectomycorrhizal (ECM) fungal‐associated tree species in these relationships.Tree species richness had a positive effect on community productivity across experiments, modified by the diversity of tree mycorrhizal associations. In communities with both AM and ECM trees, species richness showed positive effects on community productivity, which could have resulted from complementarity between AM and ECM trees. Moreover, both AM and ECM trees were more productive in mixed communities with both AM and ECM trees than in communities assembled by their own mycorrhizal type of trees. In communities containing only ECM trees, species richness had a significant positive effect on productivity, whereas species richness did not show any significant effects on productivity in communities containing only AM trees.Our study provides novel explanations for variations in diversity–productivity relationships by suggesting that tree–mycorrhiza interactions can shape productivity in mixed‐species forest ecosystems. 

Abstract We evaluate the longitudinal variation in meridional shifts of the tropical rainbelt in response to natural and anthropogenic forcings using a large suite of coupled climate model simulations. We find that the energetic framework of the zonal mean Hadley cell is generally not useful for characterizing shifts of the rainbelt at regional scales, regardless of the characteristics of the forcing. Forcings with large hemispheric asymmetry such as extratropical volcanic forcing, meltwater forcing, and the Last Glacial Maximum give rise to robust zonal mean shifts of the rainbelt; however, the direction and magnitude of the shift vary strongly as a function of longitude. Even the Pacific rainband does not shift uniformly under any forcing considered. Forcings with weak hemispheric asymmetry such as CO₂and mid‐Holocene forcing give rise to zonal mean shifts that are small or absent, but the rainbelt does shift regionally in coherent ways across models that may have important dynamical consequences. 

Abstract Enhancing tree diversity may be important to fostering resilience to drought‐related climate extremes. So far, little attention has been given to whether tree diversity can increase the survival of trees and reduce its variability in young forest plantations.We conducted an analysis of seedling and sapling survival from 34 globally distributed tree diversity experiments (363,167 trees, 168 species, 3744 plots, 7 biomes) to answer two questions: (1) Do drought and tree diversity alter the mean and variability in plot‐level tree survival, with higher and less variable survival as diversity increases? and (2) Do species that survive poorly in monocultures survive better in mixtures and do specific functional traits explain monoculture survival?Tree species richness reduced variability in plot‐level survival, while functional diversity (Rao's Q entropy) increased survival and also reduced its variability. Importantly, the reduction in survival variability became stronger as drought severity increased. We found that species with low survival in monocultures survived comparatively better in mixtures when under drought. Species survival in monoculture was positively associated with drought resistance (indicated by hydraulic traits such as turgor loss point), plant height and conservative resource‐acquisition traits (e.g. low leaf nitrogen concentration and small leaf size).Synthesis.The findings highlight: (1) The effectiveness of tree diversity for decreasing the variability in seedling and sapling survival under drought; and (2) the importance of drought resistance and associated traits to explain altered tree species survival in response to tree diversity and drought. From an ecological perspective, we recommend mixing be considered to stabilize tree survival, particularly when functionally diverse forests with drought‐resistant species also promote high survival of drought‐sensitive species.