Intensive leaf cooling promotes tree survival during a record heatwave.

Increasing heatwaves are threatening forest ecosystems globally. Leaf thermal regulation and tolerance are important for plant survival during heatwaves, though the interaction between these processes and water availability is unclear. Genotypes of the widely distributed foundation tree species Populus fremontii were studied in a controlled common garden during a record summer heatwave-where air temperature exceeded 48 °C. When water was not limiting, all genotypes cooled leaves 2 to 5 °C below air temperatures. Homeothermic cooling was disrupted for weeks following a 72-h reduction in soil water, resulting in leaf temperatures rising 3 °C above air temperature and 1.3 °C above leaf thresholds for physiological damage, despite the water stress having little effect on leaf water potentials. Tradeoffs between leaf thermal safety and hydraulic safety emerged but, regardless of water use strategy, all genotypes experienced significant leaf mortality following water stress. Genotypes from warmer climates showed greater leaf cooling and less leaf mortality after water stress in comparison with genotypes from cooler climates. These results illustrate how brief soil water limitation disrupts leaf thermal regulation and potentially compromises plant survival during extreme heatwaves, thus providing insight into future scenarios in which ecosystems will be challenged with extreme heat and unreliable soil water access.

Predicting and Prioritising Community Assembly: Learning Outcomes via Experiments.

Community assembly provides the foundation for applications in biodiversity conservation, climate change, invasion, restoration and synthetic ecology. However, predicting and prioritising assembly outcomes remains difficult. We address this challenge via a mechanism-free approach useful when little data or knowledge exist (LOVE; Learning Outcomes Via Experiments). We carry out assembly experiments ('actions', here, random combinations of species additions) potentially in multiple environments, wait, and measure abundance outcomes. We then train a model to predict outcomes of novel actions or prioritise actions that would yield the most desirable outcomes. Across 10 single- and multi-environment datasets, when trained on 89 randomly selected actions, LOVE predicts outcomes with 0.5%-3.4% mean error, and prioritises actions for maximising richness, maximising abundance, or removing unwanted species, with 94%-99% mean true positive rate and 10%-84% mean true negative rate across tasks. LOVE complements existing mechanism-first approaches for community ecology and may help address numerous applied challenges.

Negative allometry of leaf xylem conduit diameter and double-wall thickness: implications for implosion safety.

Xylem conduits have lignified walls to resist crushing pressures. The thicker the double-wall (T) relative to its diameter (D), the greater the implosion safety. Having safer conduits may incur higher costs and reduced flow, while having less resistant xylem may lead to catastrophic collapse under drought. Although recent studies have shown that conduit implosion commonly occurs in leaves, little is known about how leaf xylem scales T vs D to trade off safety, flow efficiency, mechanical support, and cost. We measured T and D in > 7000 conduits of 122 species to investigate how T vs D scaling varies across clades, habitats, growth forms, leaf, and vein sizes. As conduits become wider, their double-cell walls become proportionally thinner, resulting in a negative allometry between T and D. That is, narrower conduits, which are usually subjected to more negative pressures, are proportionally safer than wider ones. Higher implosion safety (i.e. higher T/D ratios) was found in asterids, arid habitats, shrubs, small leaves, and minor veins. Despite the strong allometry, implosion safety does not clearly trade off with other measured leaf functions, suggesting that implosion safety at whole-leaf level cannot be easily predicted solely by individual conduits' anatomy.

Leaf venation network architecture coordinates functional trade-offs across vein spatial scales: evidence for multiple alternative designs.

Variation in leaf venation network architecture may reflect trade-offs among multiple functions including efficiency, resilience, support, cost, and resistance to drought and herbivory. However, our knowledge about architecture-function trade-offs is mostly based on studies examining a small number of functional axes, so we still lack a more integrative picture of multidimensional trade-offs. Here, we measured architecture and functional traits on 122 ferns and angiosperms species to describe how trade-offs vary across phylogenetic groups and vein spatial scales (small, medium, and large vein width) and determine whether architecture traits at each scale have independent or integrated effects on each function. We found that generalized architecture-function trade-offs are weak. Architecture strongly predicts leaf support and damage resistance axes but weakly predicts efficiency and resilience axes. Architecture traits at different spatial scales contribute to different functional axes, allowing plants to independently modulate different functions by varying network properties at each scale. This independence of vein architecture traits within and across spatial scales may enable evolution of multiple alternative leaf network designs with similar functioning.

Why are triploid quaking aspen (Populus tremuloides) common?

PREMISE: Quaking aspen is a clonal tree species that has mixed ploidy, often with high relative abundance of both diploids and triploids but no haploids or tetraploids. Triploids typically have low fertility, leaving their occurrence apparently unlikely from an evolutionary perspective, unless they provide a "triploid bridge" to generating higher-fitness tetraploids-which are not observed in this species. This study focused on how triploidy can be maintained in quaking aspen. METHODS: A computational model was used to simulate gamete production, sexual reproduction, asexual reproduction, parent survival, and offspring survival in a population. All parameters were assumed to be cytotype-dependent and environment-independent. Sampling methods were used to identify parameter combinations consistent with observed cytotype frequencies. RESULTS: Many processes and parameter values were sufficient to yield a moderate frequency of triploids, and very few were necessary. The most plausible route involved higher triploid survival at the parent or offspring stage and limited unreduced gamete production by either diploid or triploid parents. Triploid fertility was helpful but not necessary. CONCLUSIONS: The coexistence of diploids and triploids in quaking aspen is statistically likely and promoted by the existence of commonly observed, long-lived triploid clones. However, other mechanisms not captured by the model related to environmental variation could also occur. Further empirical data or more complex but difficult-to-parameterize models are needed to gain further insight.

Navigation between initial and desired community states using shortcuts.

Ecological management problems often involve navigating from an initial to a desired community state. We ask whether navigation without brute-force additions and deletions of species is possible via: adding/deleting a small number of individuals of a species, changing the environment, and waiting. Navigation can yield direct paths (single sequence of actions) or shortcut paths (multiple sequences of actions with lower cost than a direct path). We ask (1) when is non-brute-force navigation possible?; (2) do shortcuts exist and what are their properties?; and (3) what heuristics predict shortcut existence? Using a state diagram framework applied to several empirical datasets, we show that (1) non-brute-force navigation is only possible between some state pairs, (2) shortcuts exist between many state pairs; and (3) changes in abundance and richness are the strongest predictors of shortcut existence, independent of dataset and algorithm choices. State diagrams thus unveil hidden strategies for manipulating species coexistence and efficiently navigating between states.

Plant water use theory should incorporate hypotheses about extreme environments, population ecology, and community ecology.

Plant water use theory has largely been developed within a plant-performance paradigm that conceptualizes water use in terms of value for carbon gain and that sits within a neoclassical economic framework. This theory works very well in many contexts but does not consider other values of water to plants that could impact their fitness. Here, we survey a range of alternative hypotheses for drivers of water use and stomatal regulation. These hypotheses are organized around relevance to extreme environments, population ecology, and community ecology. Most of these hypotheses are not yet empirically tested and some are controversial (e.g. requiring more agency and behavior than is commonly believed possible for plants). Some hypotheses, especially those focused around using water to avoid thermal stress, using water to promote reproduction instead of growth, and using water to hoard it, may be useful to incorporate into theory or to implement in Earth System Models.

Does plant ecosystem thermoregulation occur? An extratropical assessment at different spatial and temporal scales.

To what degree plant ecosystems thermoregulate their canopy temperature (Tc ) is critical to assess ecosystems' metabolisms and resilience with climate change, but remains controversial, with opinions from no to moderate thermoregulation capability. With global datasets of Tc , air temperature (Ta ), and other environmental and biotic variables from FLUXNET and satellites, we tested the 'limited homeothermy' hypothesis (indicated by Tc & Ta regression slope < 1 or Tc < Ta around midday) across global extratropics, including temporal and spatial dimensions. Across daily to weekly and monthly timescales, over 80% of sites/ecosystems have slopes ≥1 or Tc > Ta around midday, rejecting the above hypothesis. For those sites unsupporting the hypothesis, their Tc -Ta difference (ΔT) exhibits considerable seasonality that shows negative, partial correlations with leaf area index, implying a certain degree of thermoregulation capability. Spatially, site-mean ΔT exhibits larger variations than the slope indicator, suggesting ΔT is a more sensitive indicator for detecting thermoregulatory differences across biomes. Furthermore, this large spatial-wide ΔT variation (0-6°C) is primarily explained by environmental variables (38%) and secondarily by biotic factors (15%). These results demonstrate diverse thermoregulation patterns across global extratropics, with most ecosystems negating the 'limited homeothermy' hypothesis, but their thermoregulation still occurs, implying that slope < 1 or Tc < Ta are not necessary conditions for plant thermoregulation.

Climate lags and genetics determine phenology in quaking aspen (Populus tremuloides).

Spatiotemporal patterns of phenology may be affected by mosaics of environmental and genetic variation. Environmental drivers may have temporally lagged impacts, but patterns and mechanisms remain poorly known. We combine multiple genomic, remotely sensed, and physically modeled datasets to determine the spatiotemporal patterns and drivers of canopy phenology in quaking aspen, a widespread clonal dioecious tree species with diploid and triploid cytotypes. We show that over 391 km2 of southwestern Colorado: greenup date, greendown date, and growing season length vary by weeks and differ across sexes, cytotypes, and genotypes; phenology has high phenotypic plasticity and heritabilities of 31-61% (interquartile range); and snowmelt date, soil moisture, and air temperature predict phenology, at temporal lags of up to 3 yr. Our study shows that lagged environmental effects are needed to explain phenological variation and that the effect of cytotype on phenology is obscured by its correlation with topography. Phenological patterns are consistent with responses to multiyear accumulation of carbon deficit or hydraulic damage.

Process-explicit models reveal pathway to extinction for woolly mammoth using pattern-oriented validation.

Pathways to extinction start long before the death of the last individual. However, causes of early stage population declines and the susceptibility of small residual populations to extirpation are typically studied in isolation. Using validated process-explicit models, we disentangle the ecological mechanisms and threats that were integral in the initial decline and later extinction of the woolly mammoth. We show that reconciling ancient DNA data on woolly mammoth population decline with fossil evidence of location and timing of extinction requires process-explicit models with specific demographic and niche constraints, and a constrained synergy of climatic change and human impacts. Validated models needed humans to hasten climate-driven population declines by many millennia, and to allow woolly mammoths to persist in mainland Arctic refugia until the mid-Holocene. Our results show that the role of humans in the extinction dynamics of woolly mammoth began well before the Holocene, exerting lasting effects on the spatial pattern and timing of its range-wide extinction.

Gas exchange analysers exhibit large measurement error driven by internal thermal gradients.

Portable gas exchange analysers provide critical data for understanding plant-atmosphere carbon and water fluxes, and for parameterising Earth system models that forecast climate change effects and feedbacks. We characterised temperature measurement errors in the Li-Cor LI-6400XT and LI-6800, and estimated downstream errors in derived quantities, including stomatal conductance (gsw ) and leaf intercellular CO2 concentration (Ci ). The LI-6400XT exhibited air temperature errors (differences between reported air temperature and air temperature measured near the leaf) up to 7.2°C, leaf temperature errors up to 5.3°C, and relative errors in gsw and Ci that increased as temperatures departed from ambient. This caused errors in leaf-to-air temperature relationships, assimilation-temperature curves and CO2 response curves. Temperature dependencies of maximum Rubisco carboxylation rate (Vcmax ) and maximum RuBP regeneration rate (Jmax ) showed errors of 12% and 35%, respectively. These errors are likely to be idiosyncratic and may differ among machines and environmental conditions. The LI-6800 exhibited much smaller errors. Earth system model predictions may be erroneous, as much of their parametrisation data were measured on the LI-6400XT system, depending on the methods used. We make recommendations for minimising errors and correcting data in the LI-6400XT. We also recommend transitioning to the LI-6800 for future data collection.

Remote sensing of cytotype and its consequences for canopy damage in quaking aspen.

Mapping geographic mosaics of genetic variation and their consequences via genotype x environment interactions at large extents and high resolution has been limited by the scalability of DNA sequencing. Here, we address this challenge for cytotype (chromosome copy number) variation in quaking aspen, a drought-impacted foundation tree species. We integrate airborne imaging spectroscopy data with ground-based DNA sequencing data and canopy damage data in 391 km2 of southwestern Colorado. We show that (1) aspen cover and cytotype can be remotely sensed at 1 m spatial resolution, (2) the geographic mosaic of cytotypes is heterogeneous and interdigitated, (3) triploids have higher leaf nitrogen, canopy water content, and carbon isotope shifts (δ13 C) than diploids, and (4) canopy damage varies among cytotypes and depends on interactions with topography, canopy height, and trait variables. Triploids are at higher risk in hotter and drier conditions.

Automated and accurate segmentation of leaf venation networks via deep learning.

Leaf vein network geometry can predict levels of resource transport, defence and mechanical support that operate at different spatial scales. However, it is challenging to quantify network architecture across scales due to the difficulties both in segmenting networks from images and in extracting multiscale statistics from subsequent network graph representations. Here we developed deep learning algorithms using convolutional neural networks (CNNs) to automatically segment leaf vein networks. Thirty-eight CNNs were trained on subsets of manually defined ground-truth regions from >700 leaves representing 50 southeast Asian plant families. Ensembles of six independently trained CNNs were used to segment networks from larger leaf regions (c. 100 mm2 ). Segmented networks were analysed using hierarchical loop decomposition to extract a range of statistics describing scale transitions in vein and areole geometry. The CNN approach gave a precision-recall harmonic mean of 94.5% ± 6%, outperforming other current network extraction methods, and accurately described the widths, angles and connectivity of veins. Multiscale statistics then enabled the identification of previously undescribed variation in network architecture across species. We provide a LeafVeinCNN software package to enable multiscale quantification of leaf vein networks, facilitating the comparison across species and the exploration of the functional significance of different leaf vein architectures.

Cytotype and genotype predict mortality and recruitment in Colorado quaking aspen (Populus tremuloides).

Species responses to climate change depend on environment, genetics, and interactions among these factors. Intraspecific cytotype (ploidy level) variation is a common type of genetic variation in many species. However, the importance of intraspecific cytotype variation in determining demography across environments is poorly known. We studied quaking aspen (Populus tremuloides), which occurs in diploid and triploid cytotypes. This widespread tree species is experiencing contractions in its western range, which could potentially be linked to cytotype-dependent drought tolerance. We found that interactions between cytotype and environment drive mortality and recruitment across 503 plots in Colorado. Triploids were more vulnerable to mortality relative to diploids and had reduced recruitment on more drought-prone and disturbed plots relative to diploids. Furthermore, there was substantial genotype-dependent variation in demography. Thus, cytotype and genotype variation are associated with decline in this foundation species. Future assessment of demographic responses to climate change will benefit from knowledge of how genetic and environmental mosaics interact to determine species' ecophysiology and demography.

Human diets drive range expansion of megafauna-dispersed fruit species.

Neotropical fruit species once dispersed by Pleistocene megafauna have regained relevance in diversifying human diets to address malnutrition. Little is known about the historic interactions between humans and these fruit species. We quantified the human role in modifying geographic and environmental ranges of Neotropical fruit species by comparing the distribution of megafauna-dispersed fruit species that have been part of both human and megafauna diets with fruit species that were exclusively part of megafauna diets. Three quarters of the fruit species that were once dispersed by megafauna later became part of human diets. Our results suggest that, because of extensive dispersal and management, humans have expanded the geographic and environmental ranges of species that would otherwise have suffered range contraction after extinction of megafauna. Our results suggest that humans have been the principal dispersal agent for a large proportion of Neotropical fruit species between Central and South America. Our analyses help to identify range segments that may hold key genetic diversity resulting from historic interactions between humans and these fruit species. These genetic resources are a fundamental source to improve and diversify contemporary food systems and to maintain critical ecosystem functions. Public, private, and societal initiatives that stimulate dietary diversity could expand the food usage of these megafauna-dispersed fruit species to enhance human nutrition in combination with biodiversity conservation.

High water use in desert plants exposed to extreme heat.

Many plant water use models predict leaves maximize carbon assimilation while minimizing water loss via transpiration. Alternate scenarios may occur at high temperature, including heat avoidance, where leaves increase water loss to evaporatively cool regardless of carbon uptake; or heat failure, where leaves non-adaptively lose water also regardless of carbon uptake. We hypothesized that these alternative scenarios are common in species exposed to hot environments, with heat avoidance more common in species with high construction cost leaves. Diurnal measurements of leaf temperature and gas exchange for 11 Sonoran Desert species revealed that 37% of these species increased transpiration in the absence of increased carbon uptake. High leaf mass per area partially predicted this behaviour (r2  = 0.39). These data are consistent with heat avoidance and heat failure, but failure is less likely given the ecological dominance of the focal species. These behaviours are not yet captured in any extant plant water use model.

Community Assembly and Climate Mismatch in Late Quaternary Eastern North American Pollen Assemblages.

Plant community response to climate change ranges from synchronous tracking to strong mismatch. Explaining this variation in climate change response is critical for accurate global change modeling. Here we quantify how closely assemblages track changes in climate (match/mismatch) and how broadly climate niches are spread within assemblages (narrow/broad ecological tolerance, or "filtering") using data for the past 21,000 years for 531 eastern North American fossil pollen assemblages. Although climate matching has been strong over the last 21 millennia, mismatch increased in 30% of assemblages during the rapid climate shifts between 14.5 and 10 ka. Assemblage matching rebounded toward the present day in 10%-20% of assemblages. Climate-assemblage mismatch was greater in tree-dominated and high-latitude assemblages, consistent with persisting populations, slower dispersal rates, and glacial retreat. In contrast, climate matching was greater for assemblages comprising taxa with higher median seed mass. More than half of the assemblages were climatically filtered at any given time, with peak filtering occurring at 8.5 ka for nearly 80% of assemblages. Thus, vegetation assemblages have highly variable rates of climate mismatch and filtering over millennial scales. These climate responses can be partially predicted by species' traits and life histories. These findings help constrain predictions for plant community response to contemporary climate change.

Linking functional traits to multiscale statistics of leaf venation networks.

Leaf venation networks evolved along several functional axes, including resource transport, damage resistance, mechanical strength, and construction cost. Because functions may depend on architectural features at different scales, network architecture may vary across spatial scales to satisfy functional tradeoffs. We develop a framework for quantifying network architecture with multiscale statistics describing elongation ratios, circularity ratios, vein density, and minimum spanning tree ratios. We quantify vein networks for leaves of 260 southeast Asian tree species in samples of up to 2 cm2 , pairing multiscale statistics with traits representing axes of resource transport, damage resistance, mechanical strength, and cost. We show that these multiscale statistics clearly differentiate species' architecture and delineate a phenotype space that shifts at larger scales; functional linkages vary with scale and are weak, with vein density, minimum spanning tree ratio, and circularity ratio linked to mechanical strength (measured by force to punch) and elongation ratio and circularity ratio linked to damage resistance (measured by tannins); and phylogenetic conservatism of network architecture is low but scale-dependent. This work provides tools to quantify the function and evolution of venation networks. Future studies including primary and secondary veins may uncover additional insights.

Mapping local and global variability in plant trait distributions.

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.