In 2023, more than half of olive harvests ( Olea europaea ) across Spain, Greece, and Türkiye were lost to drought. The same year late freeze destroyed 90% of the peach crop ( Prunus persica ) on the Georgia Piedmont and the apple crop ( Malus domestica ) in central New York, Vermont, and southern Quebec. Climate extremes now rank with the costliest threats to agriculture, but their role in forest recovery from diebacks that are happening globally is unknown for lack of tree fecundity estimates in forests. Tolerance of climate extremes could depend on past exposure but constrained by phylogenetic conservatism. We report a continental scale analysis of climate extremes and forest fecundity across North America and Europe showing that responses to late freeze and drought are happening now. Species differences are not explained by the traits typically included in ecological studies and they are weakly associated with phylogeny. Late freeze, that is, freezing temperatures that follow the onset of flower development in spring, is shown to be “normal” in North America, but not Europe, potentially explaining failed seed production due to delayed onset and the resultant shorter growing period by North American transplants dating back at least to the 18th century. Drought has thus far had the greatest impacts in dry forested regions, but here too, species differences are not explained by traditional trait values. If responses have been buffered from drought and late freeze by past exposure, acclimation and local adaptation prove inadequate as extremes intensify.

The powdery mildew fungus Erysiphe quercicola (Erysiphaceae) has a complex taxonomic history that has long complicated assessments of its geographic distribution and host associations. Although knowledge of the global host range of this species has expanded substantially over the past two decades, sequencing-confirmed records from North America remain scarce, and despite its recognition as an introduced pathogen, the timing of introduction and the geographic extent and host range of E. quercicola in the United States are poorly understood. In this study, herbarium specimens of E. quercicola from North America, spanning both historical and contemporary collections, were examined using molecular phylogenetic approaches. Specimens collected from multiple Quercus species across several regions of the United States, as well as from related hosts within the Fagaceae, were evaluated. Sequence data confirm the presence of E. quercicola in North America on Quercus species based on herbarium specimens collected as early as 1944, as well as on mango (Mangifera indica; Anacardiaceae) in Florida from material collected in 1935. These records raise the possibility of historical introduction pathways associated with cultivated hosts, potentially from the horticulturally important mango tree (M. indica); however, additional multilocus phylogenetic analyses and host range inoculation experiments will be required to determine whether powdery mildew populations infecting mango and Quercus in North America represent the same lineage. Additional sequencing-confirmed records document the species on multiple native oak species representing different sections of Quercus including Q. bicolor, Q. gambelii, Q. garryana, Q. geminata, Q. kelloggii, Quercus & times; jolonensis and Q. macrocarpa as well as on Notholithocarpus densiflorus. Together, these findings clarify the long-term presence of E. quercicola in the United States, expand knowledge of its North American host range, and demonstrate the value of herbaria for reconstructing the invasion history of forest pathogens.

The global decrease in species diversity from low to high latitudes is among the most robust biogeographic patterns1,2. There is continuing debate on the contribution of conspecific negative density dependence (CNDD) to the latitudinal diversity gradient evident for trees3,4. Theory suggests that CNDD based on pairwise interactions alone is not sufficient to explain the intricacies of diverse communities, because higher-order interactions (HOIs) may greatly modify these interactions5,6. However, there has been a lack of empirical studies investigating how HOIs intertwine with pairwise interactions and how they may contribute to the latitudinal tree diversity gradient. Here we examined both pairwise interactions and HOIs across 32 large permanent forest plots, most in the northern hemisphere. We detected evidence of HOIs in 40% of the 1,543 species-plot combinations for tree growth, and 23% of the 1,340 such combinations for tree survival, with the strength of these interactions declining with latitude. HOIs were found to benefit rare species but disadvantage common species, suggesting a potential mechanism promoting species diversity. This stabilizing effect weakened towards higher latitudes, consistent with the latitudinal tree diversity gradient. Our findings reveal an important interplay between pairwise interactions and HOIs in promoting the latitudinal tree diversity gradient and help to clarify the contribution of CNDD to this biogeographic pattern.

This study presents the development and application of models to estimate leaf wetness duration and their integration with drone-based imagery to analyze plant disease patterns across a coastal gradient. By comparing machine learning algorithms with empirical models, we identified that both approaches effectively predict leaf wetness, particularly in a temperate maritime ecosystem. The models were applied to study two manzanita species (Arctostaphylos tomentosa and A. pumila), revealing a strong correlation between leaf wetness and disease prevalence. This work highlights the role of microclimate conditions in shaping plant health and disease distribution in coastal shrublands. We compared nine popular machine learning algorithms and four empirical threshold models to characterize leaf wetness patterns in a spatially diverse temperate maritime wildland ecosystem. We suggest that simple empirical leaf wetness models based on dew point depression or relative humidity thresholds perform as well as machine learning techniques and should not be overlooked. The relationship between leaf wetness duration and the spatial distribution of plant disease along a coastal-to-inland climate gradient offers valuable insights into disease dynamics.

Forest mapping provides critical observational data needed to understand the dynamics of forest environments. Notably, tree diameter at breast height (DBH) is a metric used to estimate forest biomass and carbon dioxide (CO2) sequestration. Manual methods of forest mapping are labor intensive and time consuming, a bottleneck for large-scale mapping efforts. Automated mapping relies on acquiring dense forest reconstructions, typically in the form of point clouds. Terrestrial laser scanning (TLS) and mobile laser scanning (MLS) generate point clouds using expensive LiDAR sensing and have been used successfully to estimate tree diameter. Neural radiance fields (NeRFs) are an emergent technology enabling photorealistic, vision-based reconstruction by training a neural network on a sparse set of input views. In this paper, we present a comparison of MLS and NeRF forest reconstructions for the purpose of trunk diameter estimation in a mixed-evergreen Redwood forest. In addition, we propose an improved DBH-estimation method using convex-hull modeling. Using this approach, we achieved 1.68 cm RMSE (2.81%), which consistently outperformed standard cylinder modeling approaches.

The microbiomes of plants can modulate the impacts of pests, including through interactions with the microbiomes of pathogen vectors, such as ambrosia beetles. Although physical and chemical traits of plant hosts are known to affect beetle-carried microbes, how beetle and host microbiomes interact is seldom explored. We aimed to determine whether wood-inhabiting endophytes mediate host susceptibility to Fusarium dieback, an emergent tree disease complex that includes ambrosia beetle vectors. We studied three competent host tree species (Persea americana, Salix spp., and Platanus racemosa) common in disease hot spots in agricultural and wildland habitats. Using culturing methods, we compared the wood microbiomes of 319 attacked and 133 nonattacked trees across a network of 47 beetle-infested and 41 noninfested plots in Southern California, United States. We conducted 1,148 in vitro assays to evaluate antagonism by wood-inhabiting endophytic fungi (60 species) and bacteria (40 species) to the Fusarium pathogens and found 15 fungal and 11 bacterial species with clear antagonism to the pathogen. Such wood endophytes may have potential to protect tree hosts as biological control agents. However, antagonistic microbes were more common in attacked trees than in nonattacked trees, suggesting that either the abundance of antagonistic fungi and bacteria in the wood microbiome is insufficient to determine the host susceptibility to attack or antagonistic strains could be enriched in attacked trees in response to the pathogen invasion. Wood-inhabiting microbial communities were consistently different between cultivated Persea americana and wildland tree species, as there were some differences based on host attack status. Differences between attacked and nonattacked trees were reflected in different microbial consortia rather than the abundance of individual, antagonistic microbial species.Copyright (c) 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Forecasting emergent pest spread is paramount to mitigating their impacts. For host-specialized pests, epidemiological models of spread through a single host population are well developed. However, most pests attack multiple host species; the challenge is predicting which communities are most vulnerable to infestation. Here, we develop a phylogenetically-informed approach to predict establishment of emergent multi-host pests across heterogeneous landscapes. We model a beetle-pathogen symbiotic complex on trees, introduced from Southeast Asia to California. The phyloEpi model for likelihood of establishment was predicted from the phylogenetic composition of woody species in the invaded community and the influence of temperature on beetle reproduction. Plant communities dominated by close relatives of known epidemiologically critical hosts were four times more likely to become infested than communities with more distantly related species. Where microclimate favored beetle reproduction, pest establishment was greater than expected based only on species composition. We applied this phyloEpi model to predict infestation risk in California using weather data and complete tree inventories from 9262 1-km2 grids in 170 cities. Regions in the state predicted with low likelihood of infestation were confirmed by independent monitoring. Analysts can adapt these phylogenetic ecology tools to predict spread of any multi-host pest in novel habitats.

The trunks of forest trees store massive amounts of carbon, but fungi actively and invisibly decay wood inside even seemingly healthy trees. Wood-decay fungi are responsible for the loss of stored carbon in living trees, and they make trees susceptible to snapping and uprooting in storms. We used sonic tomography to measure the prevalence and severity of decay in 1744 live trees (≥20 cm diameter) of 171 species on the 50-ha Forest Dynamics Plot on Barro Colorado Island, Panama. A median of <2% of the cross-sectional trunk area showed decay, but 15% of trees had >20% decay. Twenty percent of the combined basal area showed decay, representing a loss of approximately 1% of aboveground biomass. Larger trees more often showed internal decay, with one quarter of trees showing decay before reaching canopy height. Decay severity varied by species; 23% of species showed <2% decay while 9% of species lost over half their basal area. Rare species were more affected than locally abundant species, and species with traits associated with a fast life history were more susceptible to decay. These results suggest that hidden wood decay affects a large proportion of living tropical forest trees.

The future trajectory of global forests is closely intertwined with tree demography, and a major fundamental goal in ecology is to understand the key mechanisms governing spatio‐temporal patterns in tree population dynamics. While previous research has made substantial progress in identifying the mechanisms individually, their relative importance among forests remains unclear mainly due to practical limitations. One approach to overcome these limitations is to group mechanisms according to their shared effects on the variability of tree vital rates and quantify patterns therein. We developed a conceptual and statistical framework (variance partitioning of Bayesian multilevel models) that attributes the variability in tree growth, mortality, and recruitment to variation in species, space, and time, and their interactions – categories we refer to as organising principles (OPs). We applied the framework to data from 21 forest plots covering more than 2.9 million trees of approximately 6500 species. We found that differences among species, the species OP, proved a major source of variability in tree vital rates, explaining 28–33% of demographic variance alone, and 14–17% in interaction with space, totalling 40–43%. Our results support the hypothesis that the range of vital rates is similar across global forests. However, the average variability among species declined with species richness, indicating that diverse forests featured smaller interspecific differences in vital rates. Moreover, decomposing the variance in vital rates into the proposed OPs showed the importance of unexplained variability, which includes individual variation, in tree demography. A focus on how demographic variance is organized in forests can facilitate the construction of more targeted models with clearer expectations of which covariates might drive a vital rate. This study therefore highlights the most promising avenues for future research, both in terms of understanding the relative contributions of groups of mechanisms to forest demography and diversity, and for improving projections of forest ecosystems.

Fungi are among the most diverse and ecologically important kingdoms in life. However, the distributional ranges of fungi remain largely unknown as do the ecological mechanisms that shape their distributions(1,2). To provide an integrated view of the spatial and seasonal dynamics of fungi, we implemented a globally distributed standardized aerial sampling of fungal spores(3). The vast majority of operational taxonomic units were detected within only one climatic zone, and the spatiotemporal patterns of species richness and community composition were mostly explained by annual mean air temperature. Tropical regions hosted the highest fungal diversity except for lichenized, ericoid mycorrhizal and ectomycorrhizal fungi, which reached their peak diversity in temperate regions. The sensitivity in climatic responses was associated with phylogenetic relatedness, suggesting that large-scale distributions of some fungal groups are partially constrained by their ancestral niche. There was a strong phylogenetic signal in seasonal sensitivity, suggesting that some groups of fungi have retained their ancestral trait of sporulating for only a short period. Overall, our results show that the hyperdiverse kingdom of fungi follows globally highly predictable spatial and temporal dynamics, with seasonality in both species richness and community composition increasing with latitude. Our study reports patterns resembling those described for other major groups of organisms, thus making a major contribution to the long-standing debate on whether organisms with a microbial lifestyle follow the global biodiversity paradigms known for macroorganisms(4,5).

Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m3 of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition.

The fundamental trade-off between current and future reproduction has long been considered to result in a tendency for species that can grow large to begin reproduction at a larger size. Due to the prolonged time required to reach maturity, estimates of tree maturation size remain very rare and we lack a global view on the generality and the shape of this trade-off. Using seed production from five continents, we estimate tree maturation sizes for 486 tree species spanning tropical to boreal climates. Results show that a species' maturation size increases with maximum size, but in a non-proportional way: the largest species begin reproduction at smaller sizes than would be expected if maturation were simply proportional to maximum size. Furthermore, the decrease in relative maturation size is steepest in cold climates. These findings on maturation size drivers are key to accurately represent forests' responses to disturbance and climate change.

Large, mapped forest research plots are important sources of data to understand spatial and temporal changes in forest communities in the context of global change. Here, we describe the data from the first three censuses of the 16-ha UC Santa Cruz Forest Ecology Research Plot, located in the Mediterranean-climate forest on the central coast of California, USA. The forest includes both mixed-evergreen forest and redwood-dominated forest and is recovering from significant logging disturbances in the early 20th century. Each woody stem with a diameter ≥ 1 cm at 1.3 m was mapped, tagged, identified, and measured, with censuses performed at ~5-year intervals. The first census included just 6 ha (previously described), and the area was then expanded to 16 ha in the second census. We describe the temporal dynamics of the forest in the original 6 ha, as well as the structure and temporal dynamics of the full 16 ha. The community includes 34 woody species, including 4 gymnosperm and 9 angiosperm tree species, 18 species of shrubs, and 3 species of lianas. The community includes eight non-native species, representing less than 0.5% of the stems. More than half the species show greater rates of mortality than recruitments, reflective of a dynamic forest community. Over a decade, the number of living woody stems has declined, but the basal area has increased, reflecting a self-thinning process.

Coast redwoods (Sequoia sempervirens) are long-lived trees that create deep shade and litter layers, and have limited recruitment from seedlings. Botrytis cinerea is an airborne fungal pathogen that attacks redwood seedlings. B. cinerea lives as a saprotroph in dead plant matter or as a necrotroph in live tissue. In the coast redwood forest, accumulated leaf litter may provide inoculum for subsequent infections, limiting redwood seedling recruitment. Here, we examine the response of B. cinerea to fire in the coast redwood forest. We measured the abundance of airborne B. cinerea spores in paired burned and unburned plots using a selective and diagnostic medium. In a greenhouse experiment, we grew seedlings in four different treatments: (1) burned soil with no leaf litter, (2) unburned soil with no leaf litter, (3) burned soil with leaf litter collected from the burn plot, (4) unburned soil with leaf litter collected from the unburned plot. Spore trapping showed no difference in the abundance of airborne spores in the paired plots. The seedling experiment showed that disease was greatest and survival lowest when grown in burned soil; leaf litter collected from burned plots reduced survival while leaf litter from not-burned plots increased survival. These results indicate that fire did not affect airborne B. cinerea and post-fire conditions did not provide favorable growth conditions for coast redwood seedlings.

Numerous studies have shown reduced performance in plants that are surrounded by neighbours of the same species 1 , 2 , a phenomenon known as conspecific negative density dependence (CNDD) 3 . A long-held ecological hypothesis posits that CNDD is more pronounced in tropical than in temperate forests 4 , 5 , which increases community stabilization, species coexistence and the diversity of local tree species 6 , 7 . Previous analyses supporting such a latitudinal gradient in CNDD 8 , 9 have suffered from methodological limitations related to the use of static data 10 – 12 . Here we present a comprehensive assessment of latitudinal CNDD patterns using dynamic mortality data to estimate species-site-specific CNDD across 23 sites. Averaged across species, we found that stabilizing CNDD was present at all except one site, but that average stabilizing CNDD was not stronger toward the tropics. However, in tropical tree communities, rare and intermediate abundant species experienced stronger stabilizing CNDD than did common species. This pattern was absent in temperate forests, which suggests that CNDD influences species abundances more strongly in tropical forests than it does in temperate ones 13 . We also found that interspecific variation in CNDD, which might attenuate its stabilizing effect on species diversity 14 , 15 , was high but not significantly different across latitudes. Although the consequences of these patterns for latitudinal diversity gradients are difficult to evaluate, we speculate that a more effective regulation of population abundances could translate into greater stabilization of tropical tree communities and thus contribute to the high local diversity of tropical forests.

Abstract Accelerating patterns of land-use change, air pollution, global trade, and climate change all contribute to changes in plant-pathogen interactions and the emergence of novel infectious plant diseases. Land conversion to agriculture has led to new encounters between crops and local pathogens, leading to the emergence of novel diseases through spillover. Habitat fragmentation may change patterns of pathogen spread through plant populations. Air pollution and resulting acid precipitation and nitrogen deposition are associated with changes in the types, prevalence, and severity of plant diseases. Globalization, trade, and travel drive the accelerating introduction of new plant and pathogen species into all regions of the globe, creating scenarios for the emergence of novel plant–pathogen interactions. Some destructive epidemics of novel pathogens have had transformative effects on wild plant communities and critical agricultural crops. Chestnut blight, Sudden oak death, and Phytophthora (Jarrah) dieback are iconic examples of these transformative epidemics. Plant pathogens can also play roles in the emergence of invasive plant species, if introduced plants leave important pathogens behind in their native range (enemy release), or if local pathogens attack naïve introduce plants and prevent them from invading (biotic resistance). In biological control, plant pathogens are used intentionally to limit the spread of invasive plant species. Climate change is affecting temperature and precipitation, along with elevated CO2 levels. In turn, these changes affect plant and microbe physiology, phenology, and geographic ranges. Species distribution models and process-based models can help inform predictions about how plant–pathogen interactions will respond to climate change.

Concern over microbial contamination limits the adoption of home production of sprouts as a nutritious and sustainable food. Simple, accessible approaches to seed disinfection could support safe home seed sprouting. Here, we quantify bacterial and fungal contamination of seeds of 14 plant cultivars sold for home sprout production and test a range of chemical and physical methods for seed disinfestation appropriate for home use. Most seeds are contaminated with a variety of bacteria and fungi, and those microbes are usually limited to the seed surface. Heat treatments are not effective for seed disinfection because the high temperatures needed to effectively reduce microbial contamination also reduce seed germination. Two chlorine-based chemical disinfectants-dilute household bleach (0.6% sodium hypochlorite) and freshly generated hypochlorous acid (800 ppm chlorine)-were the most effective disinfection agents tested (up to a 5-log reduction in bacteria) that also did not harm seed germination.

Plant diseases cause hundreds of billions of dollars in global crop production each year. Many plant diseases develop when pathogens germinate and proliferate in the fertile environment of excess water on the leaf surfaces. Accurate measurement of how long a leaf stays wet is important to assess the risk of pathogen infestation and decide on appropriate management tactics. Commercial leaf wetness sensors estimate the duration of leaf wetness by monitoring the water accumulated on the sensor surface. However, this one-size-fits-all sensor surface does not replicate the wetting behavior of specific leaves resulting in an imprecise measurement of leaf wetness. Here it is developed a leaf wetness sensor with replica molded surfaces that closely mimic the leaf of interest and provide a more accurate measurement of leaf wetness duration compared to commercial sensors. This simple approach allows for better prediction of leaf wetness duration for each plant species, affording individualized and more effective disease forecasting for the management of plant diseases. Accurate measurement of leaf wetness duration is essential for predicting the risk of plant disease. Here, a novel leaf wetness sensor with a biomimetic leaf replica surface that more accurately predicts leaf wetness across plant species is developed. image

Wildland conservation efforts require accurate maps of plant species distribution across large spatial scales. High-resolution species mapping is difficult in diverse, dense plant communities, where extensive ground-based surveys are labor-intensive and risk damaging sensitive flora. High-resolution satellite imagery is available at scales needed for plant community conservation across large areas, but can be cost prohibitive and lack resolution to identify species. Deep learning analysis of drone-based imagery can aid in accurate classification of plant species in these communities across large regions. This study assessed whether drone-based imagery and deep learning modeling approaches could be used to map species in complex chaparral, coastal sage scrub, and oak woodland communities. We tested the effectiveness of random forest, support vector machine, and convolutional neural network (CNN) coupled with object-based image analysis (OBIA) for mapping in diverse shrublands. Our CNN + OBIA approach outperformed random forest and support vector machine methods to accurately identify tree and shrub species, vegetation gaps, and communities, even distinguishing two congeneric shrub species with similar morphological characteristics. Similar accuracies were attained when applied to neighboring sites. This work is key to the accurate species identification and large scale mapping needed for conservation research and monitoring in chaparral and other wildland plant communities. Uncertainty in model application is associated with less common species and intermixed canopies.

Abstract The assemblage of microbes that inhabit the plant as symbionts comprises the plant microbiome. The activities of plant roots have a great effect on the density and composition of bacteria and fungi growing around them, known as the rhizosphere effect. Plant–microbe and microbe–microbe interactions in the rhizosphere have large impacts on plant health. Rhizobia are symbiotic bacteria that fix nitrogen in association with legumes, relying on a complex signaling process that results in the production of root nodules. Mycorrhizae are plant–fungal symbioses that extend the capacity of roots to absorb nutrients and water; the four major groups are ectomycorrhizae, arbuscular mycorrhizae, ericoid mycorrhizae, and orchid mycorrhizae. Common mycorrhizal networks connect plants and result in the transfer of signals, carbon, and nutrients among individuals and even among species. Endophytic fungi and bacteria colonize all parts of plants including the phylloplane; endophytes may be commensals, parasites, or mutualists, with a variety of impacts on the hosts. Endophytes may be horizontally transmitted or vertically transmitted, colonizing seeds and then growing in the next generation of plants. Microbes in the plant microbiome interact with each other through parasitism, predation, competition, antibiosis, and sometimes syntrophy. Such microbe–microbe interactions shape access to the plant by plant pathogens.