Ecological Monographs

Climate change is expected to alter forest community composition and functioning, with consequences for the ecosystem services forests provide. However, most macroecological projections focus on individual species distributions and offer limited insight into whether entire communities will remain functionally compatible with future climatic conditions. Here we quantify the risk that present-day forest communities will become functionally misaligned with projected climates using a trait-based approach. We analysed forest inventory data from more than 42,000 mature plots across the United States and Canada. For each plot we estimated community-weighted means for 24 functional traits describing leaf economics, hydraulic function, wood structure, abiotic tolerances and symbiotic strategies. We modelled relationships between community functional composition and environmental conditions, and used these relationships to estimate the trait profiles most compatible with projected late-century climates (2080-2100). Trait-environment misalignment (TEM) risk was quantified as the multivariate distance between current community trait composition and the trait profile associated with the projected future climate at each location, accounting for covariance among traits and intraspecific trait variation. Projected climatic conditions favour trait combinations associated with greater hydraulic capacity and reduced cold and shade tolerance. However, the magnitude of functional misalignment varies strongly across space. The highest TEM risk occurs in high-latitude and montane conifer forests across western and central North America, whereas many mid-latitude broadleaf and mixed forests show lower risk because projected climatic changes reinforce existing drought-adapted functional strategies. Critically, high species richness was the strongest predictor of reduced risk, reinforcing the importance of biodiversity in buffering against adverse outcomes. Our results suggest that many forests are projected to experience climatic conditions associated with functional strategies that differ from those characterising the current community. By identifying where the largest functional adjustments are implied, this trait-based framework provides a scalable way to pinpoint forests most likely to experience suboptimal climate conditions and to prioritise monitoring and climate-adapted management.

Temperature fluctuations across space and time create a multidimensional thermal landscape within which organisms are exposed to local climates while conducting their daily activities. Tropical species are considered to be particularly sensitive to climate change, with narrow thermal safety margins - the buffer between operative and lethal temperatures. In tropical rainforests, however, species can hypothetically mediate thermal exposure via activity over two local thermal dimensions: vertical (ground-canopy) and temporal (day-night). Such spatiotemporal flexibility could protect species from elevated temperatures and improve thermal safety margins, but this mechanism has not been previously investigated. We test this hypothesis using rainforest ants at a warm lowland and cool upland site (100, 1200 m a.s.l.) in the Australian Wet Tropics. At lowland and upland sites, we quantified microclimate, foraging activity, community composition, and thermal ecology of ants across vertical and temporal dimensions. To assess spatiotemporal flexibility as a climate change mitigation strategy, we calculated thermal safety margins (TSM) as the difference between a species upper thermal limit (CTmax) and mean activity temperature (Te). For each species in each of their spatiotemporal niches (ground-arboreal-day-night) we test whether shifting activity to cooler niches increases TSM using the hottest niches (arboreal and/or daytime) as a baseline. At both lowland and upland sites, ant species were highly stratified vertically, but the large majority (77 - 87.5%) were active both day and night, indicating widespread temporal generalisation. Shifting activity to cooler parts of the thermal landscape substantially improved TSMs: in the lowlands, species with arboreal diurnal foraging increased their TSM by an average of 4.4 {degrees}C ({+/-} 1.7 SE) by shifting to the ground and 6.7 {degrees}C ({+/-} 1.63 SE) by shifting to nocturnal foraging. Improvements were more modest in the uplands: arboreal diurnal foragers increased TSM by 2.1 {degrees}C ({+/-} 2.07 SE) and 2 {degrees}C ({+/-} 0.28 SE) for ground and nocturnal shifts respectively. We therefore demonstrate that foraging niche flexibility is an important climate-change mitigation trait and is most beneficial in the lowlands. Lowland diurnal canopy specialists, however, are most at risk. This represents a large proportion of tropical rainforest biodiversity, supporting previous hypotheses of lowland biotic attrition under climate change.

Fuel availability and fuel dryness are consistently shown to be the primary drivers of wildfire intensity and burnt area. Here we hypothesise that differences in the timing of fuel build up and drying determine the optimal time for wildfire occurrence. We use gross primary production (GPP) as a measure of biomass production and hence fuel availability, and vapour pressure deficit (VPD) as a measure of fuel drying. We use the phase difference in the seasonal time course and magnitude of GPP and VPD to cluster regions that should therefore have distinct wildfire behaviour. We then show that each of the resultant clusters is distinctive in terms of one or more fire properties, specifically number of ignitions, burnt area, size, speed, duration, intensity, and length of the wildfire season. The emergence of distinct regimes as a function of two biophysical drivers reflects the fact that both vegetation and wildfire properties are a consequence of eco-evolutionary adaptions to environmental conditions. We then examine the degree to which human activities or vegetation properties modify these fire regimes within each of these clusters. Variability in GPP and VPD largely explains the within-cluster variation in fire properties. The type of vegetation cover has an influence on burnt area and carbon emissions in particular, while human activities are more important for fire properties such as size, rate of spread and duration largely through their influence of landscape fragmentation. Although both human activities and vegetation properties modify wildfire regimes, the ability to distinguish wildfire regimes using GPP and VPD alone emphasizes that land management, fire use and fire suppression are constrained by environmental conditions. This eco-evolutionary optimality approach to characterising wildfire regimes provides a basis for designing a simple fire model for Earth System modelling.

Biologists aim to predict where species will survive and thrive as the planet warms. To do so, we often rely on data-hungry species distribution models (SDMs) that use associations between species occurrences and environmental predictors to capture the realised niche. An alternative basis for predictions is to experimentally quantify the effect of environmental drivers on performance, which captures the fundamental niche. We presently do not know which of these approaches represents a better path towards accurate forecasts. SDMs may depend too strongly on present-day environmental covariation, which will change in the future. In contrast, a major shortcoming of experiments is that they ignore most environmental drivers to focus on one or two. Quantifying how well fundamental and realised niches agree today would help establish how useful both SDMs and experiments are likely to be. We therefore compared both niches in 39 relatively common marine phytoplankton species. The temperature-dependence of population growth rate was characterised with a thermal performance curve model applied to lab experimental data, and the temperature-dependence of species occurrence probability estimated with SDMs applied to a global compilation of marine presence records. We found a fairly strong, near 1:1 relationship between measures of thermal niche centre: the median growth temperature in the lab and the median occurrence temperature in the field (R2 = 0.49). We also found a modest positive relationship between measures of thermal niche width, the growth niche width and the occurrence niche width (R2 = 0.24). This agreement should increase our confidence in environmental preferences inferred with SDMs. It also suggests that simple experiments can reliably constrain species ranges and help forecast range shifts. This has important implications for forecasting community composition and ecosystem processes, as we ought to be able to predict range shifts in biogeochemically-important taxa such as diatoms and nitrogen-fixing cyanobacteria.

Mediterranean forests are becoming increasingly vulnerable under climate change, as the growing frequency and intensity of droughts and heatwaves amplify physiological stress, reduce productivity, and heighten the risk of large-scale disturbances. Yet vegetation activity trends, as revealed by remote sensing, may obscure divergent responses between photosynthetic activity and growth, a critical early warning of forest vulnerability. Therefore, the long-term relationship between photosynthesis and tree growth remains poorly understood at regional scales, especially in Mediterranean areas. To address this challenge, we applied a mechanistic, process-based forest ecosystem model across approximately 2,400 km{superscript 2} of Mediterranean forests in southern Italy, encompassing a heterogeneous landscape characterized by diverse stand structures and species dominance. This framework enabled us to explicitly trace carbon fluxes from gross primary productivity (GPP) through allocation processes to average tree growth. By mean of a factorial approach, we identify over extended areas an emergent spatial pattern of divergence of summer GPP and radial tree growth amplified in space and time by the climate variability of the last two decades and shaped by forest legacy. Our findings reveal also that canopy-level greening can mask structural vulnerability and previsual decline across Mediterranean forests. Data show as an apparent long-term trend in photosynthesis decline during summer, not necessarily translates to tree growth decline. Improving our ability to determine if, where and when a key change in forest behaviour will occurs, remains essential for designing effective restoration measure and anticipating tipping points in forest resilience under accelerating climate change.

An organisms life history strategy is an attempt to optimize fitness, given environmental constraints and inherent demographic tradeoffs. As such, life history helps to shape an organisms ecological and evolutionary responses to environmental change. However, life history can also be shaped by the environment, as the organisms demographic rates respond--directly or through tradeoffs--to the new conditions. This feedback between life history and environment remains poorly understood, limiting our ability to predict the outcomes of environmental change. Here, we studied the effects of environmental change - specifically altered pollination services - on four perennial plant species. We conducted a field-based demography experiment that subjected naturally occurring populations of Delphinium nuttallianum, Hydrophyllum fendleri, Potentilla pulcherrima and Erigeron speciosus to three pollination treatments: ambient (control), reduced, or increased pollination. We estimated population growth rate ({lambda}) and 11 metrics describing life history strategy and demographic resilience from an Integral Projection Model we constructed for each species and parameterized with 4-5 years of census data. Although most life history metrics responded idiosyncratically to pollination treatment, we found consistent effects of pollination on generation time, longevity and, in three of four species, recovery time. Specifically, reduced pollination led to increased longevity, generation time, and recovery time, and increased pollination led to the opposite. These changes in life history resemble shifts along the slow-fast continuum; reduced pollination led to slower lives and increased pollination led to faster lives. This is consequential because generation time and longevity influence short- and long-term population dynamics - for example, by affecting demographic stochasticity and sensitivity to environmental stochasticity, or rates of adaptation to novel conditions. Notably, these changes occurred largely independent from changes in population growth. Altogether, our results highlight changes in life history as an important but underappreciated consequence of environmental change.

Understanding and predicting future plant biodiversity and productivity is critical for prioritizing global change mitigation, conservation, and restoration efforts. One major challenge is that we know remarkably little of how interspecific interactions may modulate the effects of global change factors on diversity and productivity. Here, we develop and test a synthetic conceptual framework about how different biotic modulators (herbivory, plant-plant interactions, pathogens, mycorrhiza) can either amplify or mitigate the effects of global change drivers (nutrient and CO2 enrichment, changes in rainfall and temperature) on plant community biomass and diversity. We report that herbivores mitigated both biomass increment and diversity decline caused by different global change drivers, while plant competition did not significantly alter global change impacts due to mixed effects (both amplification and mitigation). Pathogens tended to function similarly to herbivores, while mycorrhiza both amplified and mitigated community responses. Our conceptual framework further identifies mechanisms by which species interactions can modify global change effects, provides new testable hypotheses, and identifies research gaps and future research directions. We conclude that plant consumers can be important agents stabilizing plant productivity and safeguarding plant biodiversity in the Anthropocene, while more research is urgently needed to understand the role of other biotic modulators.

Understanding plant functional diversity across scales requires integrating field-based ecology and remote sensing, yet these disciplines differ in how traits are studied. We evaluated the conceptual and methodological convergence between these disciplines. Our results reveal that field-based ecology has undergone longer conceptual development and covers a broader range of traits, while remote sensing has experienced rapid growth driven by technological advances. Both disciplines are increasingly converging on similar concepts. However, major gaps in empirical coverage persist across biomes in both disciplines. Although plant-dominated ecosystems have been extensively studied, extreme ecosystems remain undersampled. While there is considerable diversity in the definition "functional traits", both disciplines converge on using a similar set of traits, reflecting their central role in plant strategies and spectral detectability. Our synthesis underscores the potential for methodological synergy. Harmonizing trait definitions, scaling assumptions, and computational steps involved in estimating plant functional diversity are crucial for building a unified, multiscale framework for biodiversity monitoring in ecosystems undergoing biodiversity loss and climate change. TeaserA synthesis of how field ecology and remote sensing can be aligned to monitor plant functional diversity across scales.

The existence of a causal link between biodiversity and forest productivity remains largely unexplored in natural systems, especially in hyper-diverse tropical forests. Canopy packing-- greater crown complementarity, resulting in more densely packed canopies--has recently emerged as a key structural pathway through which diversity influences forest functioning, though evidence remains limited and sometimes contradictory.In this study, we used repeated airborne LiDAR acquisitions and long-term field monitoring from a tropical logging experiment in French Guiana to quantify canopy packing using the Shannon evenness of plant area density (PAD) and assess its role in mediating the relationship between trait diversity and biomass gains in old-growth and disturbed Amazonian forest stands.Our results show that, in undisturbed forests, functionally diverse communities promote greater canopy packing, which in turn enhances biomass gains. However, this effect was absent in previously logged stands, where forest structural diversity did not fully recover even after 40 years. Our findings indicate that logging reduces canopy structural complexity and disrupts the link between species composition, canopy packing, and productivity in these hyper-diverse, hyper-productive ecosystems. Significance StatementIn this study, measurements from repeated airborne LiDAR acquisitions and long-term field monitoring from a tropical logging experiment in the Amazon forest are used to understand the causal link between biodiversity and forest productivity. The study shows that greater crown complementarity mediates diversity-productivity relationships, with functionally diverse communities promoting greater canopy packing, which in turn enhances biomass gains. However, this effect is lost in disturbed forests. These findings are relevant for understand the ecological mechanisms driving forest productivity and tropical forests response to disturbance and for forest carbon management strategies.

Plant communities within a metacommunity can vary widely in their degree of invasion by introduced species. Disturbance, propagule pressure, and biotic resistance are common explanations for this variation, but empirical evidence for these hypotheses is mixed. Alternatively, the community assembly framework predicts that local assembly filters determine both native and exotic composition, but lower trait variation in the introduced species pool may exclude them from certain sites. We examined evidence for this framework using observational data from forests and woodlands of Long Island, NY, USA. These forests vary in vegetation composition and invasion along a soil gradient. They are also highly disturbed and fragmented, yet some stands have almost no introduced plants. Using data collected in 1998 and 2021-22, we quantified relationships between community composition, soil characteristics, and functional traits for native and exotic assemblages, as indicators of environmental filtering. We found similar trait-environment relationships in native and introduced species, suggesting that both groups follow the same local assembly rules. Introduced species were predominantly found in sites with more nutrient-rich soils and were absent from sites with nutrient-poor soils. At the regional scale, the exotic species pool was biased toward trait values favored in more nutrient-rich environments, particularly high growth rates and low leaf C:N ratios, which explains their absence from nutrient-poor environments. These patterns were consistent over time, and stands that were uninvaded in 1998 remained so in 2021-22, supporting the robustness and reliability of short-term studies. This study shows that invasion patterns in plant communities can be explained by the assembly rules that govern native species. By linking local environmental filtering with regional species pool characteristics, this work advances our understanding of how some communities remain uninvaded despite high disturbance and propagule pressure. Overall, these results highlight the utility of the community assembly framework, and emphasize the importance of regional processes in constraining the local distribution of introduced species.

Climate change is increasing the frequency of wildfires in ecosystems that historically rarely burn, such as wet heaths and peatlands, thereby threatening carbon storage, biodiversity, and ecosystem functioning. We conducted a three-year, multi-level study to assess early post-fire recovery trajectories of soil physicochemical properties, vegetation, and soil microbial communities in a wet peatland-heathland mosaic affected by a flaming wildfire. Using a paired-plot design of burned and adjacent intact plots, we observed immediate spikes in bioavailable nitrogen (NH, NO-) and phosphorus (POlsen) and a reduction in soil moisture in burned plots, yet two years later these parameters had normalized, indicating rapid abiotic recovery. Vegetation was also strongly altered in the year of the fire, quantifiable by a distinct destruction of herb, moss, tree and litter cover. Although initial regrowth was dominated by a relatively fast resprouting of the graminoid Molinia caerulea, its absolute cover in burned plots never exceeded its cover in intact plots, suggesting this species did not expand post-fire. More typical peatland and wet heath species, including ericoid shrubs and Sphagnum mosses, recovered more gradually but largely returned to pre-fire levels within the timespan of our study, highlighting high vegetation resilience. Soil microbial communities showed contrasting responses. Prokaryotic communities shifted immediately after burning but largely recovered within one year. Fungal communities, however, exhibited stronger and more persistent changes and followed a distinct recovery trajectory shaped by succession of immediate and delayed fungal responders. Overall, pyrophilous and fire-tolerant fungi, such as Coniochaeta spp., increased, as did many presumably generalist or opportunistic saprotrophs. Litter and wood-associated saprotrophs as well as many mycorrhizal taxa, however, declined. Ongoing fungal shifts occurred even after soil chemistry and vegetation had largely returned to baseline, reflecting a temporary decoupling between above- and belowground communities that may have cascading effects on ecosystem functioning. In conclusion, our results reveal differential recovery trajectories across the soil-microbiome-vegetation interface and highlight that seemingly rapid abiotic and aboveground biotic recovery can mask prolonged microbial disruptions. We emphasize the importance of multi-level assessments for understanding ecosystem resilience. HighlightsO_LISoil physicochemistry, vegetation and prokaryotes recovered rapidly after a peatland wildfire C_LIO_LIFungal communities lagged behind and followed a slower recovery trajectory C_LIO_LIThe timing and duration of fungal responses to fire varied across taxa and included immediate or delayed as well as short-lived or persistent responders C_LIO_LIThere was a mismatch between vegetation and fungal recovery trajectories, evidenced by a transient post-disturbance decoupling between above- and belowground biotic communities C_LIO_LIPresumed aboveground recovery can mask prolonged belowground disruptions, with potential implications for decomposition, nutrient cycling, and plant-microbe interactions C_LI

The seasonal forms of the temperate butterfly Araschnia levana (Nymphalidae: Nymphalinae) differ in morphology (weight, wing area, and wing loading) and colouration. Spring individuals are predominantly orange with higher weight per wing area, (i.e. wing loading) while summer individuals are black with a white stripe and have lower wing loading. However, it remains unclear if and how these seasonal differences affect heating and cooling dynamics. We compared thermal responses of seasonal forms, focusing on the roles of morphology and colouration. Further, we assessed whether live butterflies heat and cool differently from dead individuals to detect the presence of active thermoregulation. Morphology and colouration influenced the thermal dynamics of the thorax and wings as expected from heat-transfer principles, but we found no evidence of active thermoregulation on the thorax. Based on aligned temperature curves, seasonal forms showed similar thermal dynamics. This similarity was driven by morphology and colouration, with larger wing area accelerating thermal change and higher body weight (or wing loading) reducing it, thereby masking underlying form-specific patterns. After accounting for significant morphological differences between forms, the thorax of spring individuals heated and cooled faster than that of summer ones. This trend suggests form-specific optimisation of thermal performance, likely as a response to temperate climates. Thermal responses differ between forms in ways not directly explained by the polyphenism itself, potentially reflecting a broader trait of multivoltine ectotherms to cope with seasonal temperature changes.

Genomic offsets are increasingly used to quantify the mismatch between a populations current genetic composition and the composition predicted under changed environmental conditions. While genomic offset is a promising tool for assessing climate maladaptation, the sensitivity of predictions to different methodological choices is not well understood. In this study, we compared two fundamentally different approaches to detect outliers before predicting genomic offsets: Gradient Forest (GF, non-linear, non-parametric) and Canonical Correlation Analysis (CANCOR, linear, parametric). To do so, we used 457 natural populations of perennial ryegrass (Lolium perenne L.), an important agricultural forage species throughout Europe. Using a data set of 189,968 SNPs and 75 climatic variables, we experimentally validated genomic offsets against 105 phenotypic traits measured across three common gardens during multiple years. We also assessed the sensitivity of outlier detection and genomic offset predictions to the number and spatial distribution of sampled populations. Both GF and CANCOR detected a substantial number of outlier loci associated with environmental gradients (2,113 and 653, respectively), with 429 loci identified by both approaches. When used to model spatial variation in genetic adaptation and estimate genomic offsets, the different outlier sets produce spatially congruent projections. We also found significant correlations between experienced genomic offset in the common garden predicted by both outlier sets and phenotypic traits, identifying traits that could serve as good fitness proxies for assessing climate risk. Analyses based on different population subsamples revealed that GF was less sensitive to sample size and geographic biases than CANCOR. Our findings provide practical guidance for designing genomic offset studies in both agricultural and natural systems and suggest that non-linear, non-paramateric methods like GF may be less sensitive to sampling design and therefore potentially more robust for predicting climate maladaptation.

Long-term field observations typically are the "gold-standard" for inferences of phenological sensitivities in montane systems but are spatially limited. Herbarium specimens provide broader spatial coverage, but their utility to accurately capture montane phenology remains poorly known. We compared flowering phenology of 45 species inferred from herbarium specimens with comparable data from nearly 50 years of direct observations at the Rocky Mountain Biological Laboratory. Estimates of flowering time and phenological sensitivity to snow density were consistent between herbarium specimens and observations, but observations revealed secondary flowering peaks. Herbarium specimens additionally yielded shallower estimates of phenological sensitivity to spring temperature than did field observations. Across co-occurring species, "early" flowering individuals inferred from herbarium specimens, rather than the mean response across all individuals, may better approximate community-level phenological responses to temperature changes. We conclude that herbarium specimens are reliable resources for closing gaps in understanding phenological variation along elevational gradients of montane systems.

Timing of flowering is shifting with climate change. Although climate-driven shifts in phenology sometimes affect seed production, whether changing phenology will scale up to affect population dynamics of long-lived plants remains largely unknown, particularly under changing precipitation. Understanding how phenology affects persistence and extinction risk is a pressing need given contemporary biodiversity loss. We combined nearly a decade of demographic censuses and a four-year phenological survey in a rainfall manipulation experiment to examine the effects of experimental drought and irrigation on flowering phenology, vital rates (e.g., survival and individual growth), and population growth in the perennial herb Lomatium utriculatum. We found that drought advanced flowering by 3.3 days on average, and that earlier-flowering plants produced more seeds regardless of treatment. However, both rainfall treatments reduced seed production compared to controls. We quantified the phenology-mediated and direct, non-phenological effects of rainfall manipulation on population growth rates using integral projection models and a life table response experiment. Drought and irrigation increased {lambda} through increased individual growth, but these effects were partially negated by treatment-driven declines in seed output. In contrast, changes to seed production resulting from shifting flowering times had negligible effects on population growth. Our results suggest that climate-driven phenological shifts may only marginally impact population dynamics in perennial plants and highlight that assessing phenologys consequences for persistence under climate change must also account for direct demographic effects of the climate driver(s) themselves. SignificanceWill changing flowering times under climate change increase extinction risk in plant populations? Despite well-documented earlier flowering and its influence on the number of offspring produced, how changing flowering times will affect population growth or decline is still mostly unknown. We study this in a perennial wildflower subject to changes in rainfall. While we found that drought meant earlier flowering and that, all else equal, early flowering meant more seeds, these effects only marginally affected population growth. Instead, population growth was influenced mostly by rainfall-driven changes to individual plant growth. While shifting flowering times remain an important indicator of climate change, assessing extirpation in plants requires considering flowering times as only one of many life cycle processes changing with climate.

O_LISpecies diversity potentially has a dual effect on communities: a generally positive effect on overall community biomass, reflecting the expression of species response and interaction traits, and a poorly characterised effect on mass-specific species contribution to ecosystem functions, reflecting the expression of their effect traits. Disentangling the effects of biodiversity on total biomass from those on effect trait expression would help settle a long-standing debate by clarifying how biodiversity relates to both facets of species effects on ecosystem functioning. C_LIO_LIFollowing the classical BEF approach, we calculate expected ecosystem function based on observed functioning in monoculture. We then derive a net biodiversity effect (NBE) and decompose it into four components: the classical complementarity and selection effects on total community biomass, and complementarity and selection effects on effect trait expression. The latter two reflect, respectively, a complementarity or facilitation in how effect traits influence the function, and how species with the highest potential for increasing the function become dominant in the community. C_LIO_LIWe illustrate this NBE decomposition with three ecosystem functions (nitrogen retention capacity, soil hydraulic conductivity improvement, and forage digestibility) measured in assembled communities under controlled experimental conditions of perennial grassland plants. Regarding nitrogen retention, we find a positive complementary effect via total biomass, but a negative biodiversity effect via effect trait expression. For hydraulic conductivity improvement, biodiversity effects are mostly mediated by total biomass. As for forage digestibility, we found a positive complementarity effect on trait expression, outweighed however by a negative selection effect. This analysis reveals how biodiversity may have contrasting effects on ecosystem functions via its impact on biomass and effect trait expression. C_LI SynthesisSeparating between the effect of biodiversity on plant community biomass and on effect trait expression at the community level is one important step towards understanding the pathways by which diverse plant communities drive ecosystem functioning.

The mid-domain effect (MDE) predicts that geometric constraints drive unimodal species richness patterns within bounded gradients. However, the role of this effect in ecological networks is currently unexplored. Here we evaluate the role of the MDE in structuring interaction networks. We combine null-model simulations and empirical analyses of plant-pollinator and ant-plant networks along elevational gradients to assess whether the MDE can drive systematic variation in network structure. Our simulations demonstrated that the MDE alone can generate unimodal/U-shaped patterns in network metrics such as connectance, generality, and vulnerability. However, empirical networks only partially conformed to MDE predictions, with deviations indicating the likely influence of other ecological processes. MDE-based models best explained patterns in network-level specialization and nestedness, while only partially explaining patterns in connectance and generality. Because MDEs can shape interaction networks, MDE null models should be used when quantifying the influence of other ecological processes on network structure.

Biomass and surface area allocation affect resource uptake and carbon (C) residence time in forests, but the influence of tree diversity on allocation remains poorly understood. Moreover, mycorrhizal associations can alter this relationship, which has been rarely tested in mature forests. We investigated the role of both the proportion of ectomycorrhizal (ECM) trees and tree diversity on tree biomass and surface area allocation across a dual gradient of tree diversity (0 - 1.68 Shannon diversity) and ECM dominance (0 - 100 %) in a mixed deciduous forest area in Central Germany. We found that the two gradients affected tree biomass and surface area differently and mostly independently. Tree diversity had no significant effect on biomass or surface area in the investigated forest area, but increased the spatial variability of the leaf area index (LAI) from 21 % to 40 %. In contrast, a higher proportion of ECM trees was associated with an increase in fruit biomass (from 10 to 141 g m-2) and LAI (from 4 to 7 m2 m-2). Although tree diversity and the portion of ECM produced similar parsimonious models for explaining belowground biomass and surface area, neither showed a significant direct effect. Notably, their interaction enhanced the spatial variability of fine root biomass and root surface area; that is, forests with high diversity and a greater proportion of ECM trees exhibited a more heterogeneous distribution of fine roots. Allocation to fine root biomass appeared independent of tree diversity and the proportion of ECM trees, being influenced primarily by stand structure, with higher allocations observed in stands with lower stem basal area. We conclude that biomass allocation in this Central European Forest, where resource availability is relatively uniform, is primarily productivity-driven. A comparison of the biotic influences shows that ECM trees have a stronger control on aboveground surface area and fruit biomass than tree diversity, which may contribute to the ability of dominant ECM trees, such as European beech, to outcompete light competitors, but also puts temperate ECM forests at risk of physiological failures in increasingly drier future conditions.

Honeybee breeding plans are relatively recent in most countries. In France, diverse small-scale breeding groups are emerging. Beekeepers are highly diverse in their motivations, farm productions and services, practices and management techniques. Yet, little is known about what beekeepers would consider as relevant breeding goals in the design of breeding plans. We therefore conducted an online survey answered by about 250 French beekeepers, mostly professionals, to assess their perceived importance of including 20 pre-defined traits in breeding goals and to identify how beekeeping profiles might influence these priorities. Respondents rated each trait as essential, useful, or useless, and indicated if they wished useful or essential traits to be genetically improved or merely maintained at their current level. Results indicated a strong preference for multi-trait selection, with a median of 13 traits considered useful or essential. Honey yield, disease resistance, swarming tendency, gentleness, and summer feed autonomy, emerged as the main traits of interest with about 90% of beekeepers finding them at least useful. About 40% or more only wished to maintain these traits at their current level rather than to directionally improve them. A major exception to this was disease resistance, that 75% wanted to improve. Bees genetic background influenced the most the importance attributed to breeding goal traits, while other beekeeping profile characteristics only had a marginal effect on breeding goal trait priorities. Some poorly studied traits, such as summer and winter feed autonomy, winter diapause, and longevity, were considered at least useful in a breeding goal by over 70% of beekeepers. Future research is needed to explore possible selection criteria for these traits and estimate the potential for their genetic improvement. ImplicationsOur survey shows that French beekeepers wish to improve or maintain through selective breeding usual colony production and behavioral traits, but also colony resilience, especially disease resistance and feed autonomy. However, trait priorities differ depending on the genetic background of the bees used. This knowledge is essential for designing breeding programs that truly match beekeeper needs and for identifying which traits deserve research attention. In France, beekeepers are increasingly starting breeding efforts to adapt their bees to current conditions, facing growing pressures from climate change, diseases, invasive species, and pesticides. Well-designed breeding programs can support sustainable beekeeping and essential pollination services.

Mediterranean mountain grasslands are ecosystems of high ecological and economic value. They are shaped by the dry and warm climate and land use, such as grazing, although the combined effects of both drivers remain poorly understood. In this study, we analyzed shifts in functional composition in thirty-two plant communities in Mediterranean mountain grasslands of the Pindos Range (Greece) by measuring five plant functional traits related to resource acquisition in dominant plant species. We examined the adaptive value of each trait as well as community-level responses along a well-defined two-dimensional gradient of grazing intensity and aridity, using mixed models and functional diversity analyses, and tested whether individual species trait shifts are related to aridity and grazing intensity. At the community level, aridity decreased plant height and leaf area whereas grazing only affected traits associated with tissue recovery such as high specific leaf area (SLA) and low community-weighted mean leaf dry matter content (LDMC). As aridity increased, plant height functional dispersion decreased. This convergence pattern indicates a shift towards more similar growth forms under arid conditions. Species-specific analysis indicated various responses of traits to the interaction of aridity and grazing that could not be detected using only community-level patterns. Overall, our findings demonstrate that aridity and grazing act through separate functional axes at the community level, while their combined effects emerge through species-specific trait plasticity.