Effects of plant diversity on productivity strengthen over time due to trait-dependent shifts in species overyielding.

Plant diversity effects on community productivity often increase over time. Whether the strengthening of diversity effects is caused by temporal shifts in species-level overyielding (i.e., higher species-level productivity in diverse communities compared with monocultures) remains unclear. Here, using data from 65 grassland and forest biodiversity experiments, we show that the temporal strength of diversity effects at the community scale is underpinned by temporal changes in the species that yield. These temporal trends of species-level overyielding are shaped by plant ecological strategies, which can be quantitatively delimited by functional traits. In grasslands, the temporal strengthening of biodiversity effects on community productivity was associated with increasing biomass overyielding of resource-conservative species increasing over time, and with overyielding of species characterized by fast resource acquisition either decreasing or increasing. In forests, temporal trends in species overyielding differ when considering above- versus belowground resource acquisition strategies. Overyielding in stem growth decreased for species with high light capture capacity but increased for those with high soil resource acquisition capacity. Our results imply that a diversity of species with different, and potentially complementary, ecological strategies is beneficial for maintaining community productivity over time in both grassland and forest ecosystems.

Drivers of plant diversity, community composition, functional traits, and soil processes along an alpine gradient in the central Chilean Andes.

High alpine regions are threatened but understudied ecosystems that harbor diverse endemic species, making them an important biome for testing the role of environmental factors in driving functional trait-mediated community assembly processes. We tested the hypothesis that plant community assembly along a climatic and elevation gradient is influenced by shifts in habitat suitability, which drive plant functional, phylogenetic, and spectral diversity. In a high mountain system (2400-3500 m) Región Metropolitana in the central Chilean Andes (33°S, 70°W). We surveyed vegetation and spectroscopic reflectance (400-2400 nm) to quantify taxonomic, phylogenetic, functional, and spectral diversity at five sites from 2400 to 3500 m elevation. We characterized soil attributes and processes by measuring water content, carbon and nitrogen, and net nitrogen mineralization rates. At high elevation, colder temperatures reduced available soil nitrogen, while at warmer, lower elevations, soil moisture was lower. Metrics of taxonomic, functional, and spectral alpha diversity peaked at mid-elevations, while phylogenetic species richness was highest at low elevation. Leaf nitrogen increased with elevation at the community level and within individual species, consistent with global patterns of increasing leaf nitrogen with colder temperatures. The increase in leaf nitrogen, coupled with shifts in taxonomic and functional diversity associated with turnover in lineages, indicate that the ability to acquire and retain nitrogen in colder temperatures may be important in plant community assembly in this range. Such environmental filters have important implications for forecasting shifts in alpine plant communities under a warming climate.

Mechanistic links between physiology and spectral reflectance enable previsual detection of oak wilt and drought stress.

Tree mortality due to global change-including range expansion of invasive pests and pathogens-is a paramount threat to forest ecosystems. Oak forests are among the most prevalent and valuable ecosystems both ecologically and economically in the United States. There is increasing interest in monitoring oak decline and death due to both drought and the oak wilt pathogen (Bretziella fagacearum). We combined anatomical and ecophysiological measurements with spectroscopy at leaf, canopy, and airborne levels to enable differentiation of oak wilt and drought, and detection prior to visible symptom appearance. We performed an outdoor potted experiment with Quercus rubra saplings subjected to drought stress and/or artificially inoculated with the pathogen. Models developed from spectral reflectance accurately predicted ecophysiological indicators of oak wilt and drought decline in both potted and field experiments with naturally grown saplings. Both oak wilt and drought resulted in blocked water transport through xylem conduits. However, oak wilt impaired conduits in localized regions of the xylem due to formation of tyloses instead of emboli. The localized tylose formation resulted in more variable canopy photosynthesis and water content in diseased trees than drought-stressed ones. Reflectance signatures of plant photosynthesis, water content, and cellular damage detected oak wilt and drought 12 d before visual symptoms appeared. Our results show that leaf spectral reflectance models predict ecophysiological processes relevant to detection and differentiation of disease and drought. Coupling spectral models that detect physiological change with spatial information enhances capacity to differentiate plant stress types such as oak wilt and drought.

Drought response strategies are coupled with leaf habit in 35 evergreen and deciduous oak (Quercus) species across a climatic gradient in the Americas.

Distinct survival strategies can result from trade-offs in plant function under contrasting environments. Investment in drought resistance mechanisms can enhance survivorship but result in conservative growth. We tested the hypothesis that the widespread oaks (Quercus spp.) of the Americas exhibit an interspecific trade-off between drought resistance and growth capacity. Using experimental water treatments, we isolated adaptive trait associations among species in relation to their broad climates of origin and tested for correlated evolution between plant functional responses to water availability and habitat. Across all lineages, oaks displayed plastic drought responses - typically acclimating through osmolyte accumulation in leaves and/or employing conservative growth. Oaks from xeric climates had higher osmolytes and reduced stomatal pore area index, which allows for moderated gas exchange and limits tissue loss. Patterns suggest drought resistance strategies are convergent and under strong adaptive pressure. Leaf habit, however, mediates the growth and drought resistance strategies of oaks. Deciduous species, and evergreen species from xeric climates, have increased drought tolerance through osmoregulation, which allows for continuous, conservative growth. Evergreen mesic species show limited drought resistance but could enhance growth under well-watered conditions. Consequently, evergreen species from mesic environments are especially vulnerable to chronic drought and climate change.

Disentangling leaf structural and material properties in relationship to their anatomical and chemical compositional traits in oaks (Quercus L.).

BACKGROUND AND AIMS: The existence of sclerophyllous plants has been considered an adaptive strategy against different environmental stresses. Given that it literally means 'hard-leaved', it is essential to quantify the leaf mechanical properties to understand sclerophylly. However, the relative importance of each leaf trait for mechanical properties is not yet well established. METHODS: Genus Quercus is an excellent system to shed light on this because it minimizes phylogenetic variation while having a wide variation in sclerophylly. We measured leaf anatomical traits and cell wall composition, analysing their relationship with leaf mass per area and leaf mechanical properties in a set of 25 oak species. KEY RESULTS: The upper epidermis outer wall makes a strong and direct contribution to the leaf mechanical strength. Moreover, cellulose plays a crucial role in increasing leaf strength and toughness. The principal component analysis plot based on leaf trait values clearly separates Quercus species into two groups corresponding to evergreen and deciduous species. CONCLUSIONS: Sclerophyllous Quercus species are tougher and stronger owing to their thicker epidermis outer wall and/or higher cellulose concentration. Furthermore, section Ilex species share common traits, although they occupy different climates. In addition, evergreen species living in mediterranean-type climates share common leaf traits irrespective of their different phylogenetic origin.

Consistent physiological, ecological and evolutionary effects of fire regime on conservative leaf economics strategies in plant communities.

The functional response of plant communities to disturbance is hypothesised to be controlled by changes in environmental conditions and evolutionary history of species within the community. However, separating these influences using direct manipulations of repeated disturbances within ecosystems is rare. We evaluated how 41 years of manipulated fire affected plant leaf economics by sampling 89 plant species across a savanna-forest ecotone. Greater fire frequencies created a high-light and low-nitrogen environment, with more diverse communities that contained denser leaves and lower foliar nitrogen content. Strong trait-fire coupling resulted from the combination of significant intraspecific trait-fire correlations being in the same direction as interspecific trait differences arising through the turnover in functional composition along the fire-frequency gradient. Turnover among specific clades helped explain trait-fire trends, but traits were relatively labile. Overall, repeated burning led to reinforcing selective pressures that produced diverse plant communities dominated by conservative resource-use strategies and slow soil nitrogen cycling.

The global spectrum of plant form and function: enhanced species-level trait dataset.

Here we provide the 'Global Spectrum of Plant Form and Function Dataset', containing species mean values for six vascular plant traits. Together, these traits -plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass - define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.

Tree species and genetic diversity increase productivity via functional diversity and trophic feedbacks.

Addressing global biodiversity loss requires an expanded focus on multiple dimensions of biodiversity. While most studies have focused on the consequences of plant interspecific diversity, our mechanistic understanding of how genetic diversity within plant species affects plant productivity remains limited. Here, we use a tree species × genetic diversity experiment to disentangle the effects of species diversity and genetic diversity on tree productivity, and how they are related to tree functional diversity and trophic feedbacks. We found that tree species diversity increased tree productivity via increased tree functional diversity, reduced soil fungal diversity, and marginally reduced herbivory. The effects of tree genetic diversity on productivity via functional diversity and soil fungal diversity were negative in monocultures but positive in the mixture of the four tree species tested. Given the complexity of interactions between species and genetic diversity, tree functional diversity and trophic feedbacks on productivity, we suggest that both tree species and genetic diversity should be considered in afforestation.

Biodiversity, the richness of species in a given ecosystem, is essential for maintaining ecological functions. This is supported by many long-term biodiversity experiments where researchers manipulated the numbers of tree species they planted in a forest and then evaluated both its productivity (how much biological material the forest produced in a given timeframe) and the health of its trees. This work contributed to our understanding of forest ecology and paved the way for better reforestation approaches. The most important observation was that diverse forests, which contain several tree species, are more productive and healthier than monocultures where a single tree species dominates. However, it remained unclear what the role of genetic diversity within individual tree species is in determining productivity and health of forests. Tang, Zhang et al. set out to improve on previous studies on tree genetic diversity and community productivity by looking at two possible mechanisms that might affect the productivity of a forest ecosystem using publicly available data. First, they looked at the diversity of traits found within a tree population, which determines what resources in the ecosystem the trees can exploit; for example, trees with varied specific leaf areas (that is the ratio between a leaf's area and its dry mass) have more access to different intensities of sunlight for photosynthesis, allowing the whole forest to gain more biomass. Second, they considered interactions with other organisms such as herbivore animals and soil fungi that affect tree growth by either consuming their leaves or competing for the same resources. Tang, Zhang et al. used a mathematical model to interpret a complex dataset that includes multiple parameters for each of four types of forest: a forest with a single tree species seeded from a single parent tree (which will have low species and genetic diversity), a forest with a single tree species seeded from several parent trees (low species diversity and high genetic diversity, due to the diversity of parents), a forest with four tree species each seeded from a single parent tree (high species diversity and low genetic diversity), and a forest with four tree species each seeded from several parent trees (high species and genetic diversity). Using their model, Tang, Zhang et al. determined that species diversity promotes productivity because the increased diversity of traits allows trees to exploit more of the surrounding resources. Genetic diversity, on the other hand, did not seem to have a direct effect on overall productivity. However, greater genetic diversity did coincide with an increase in the diversity of traits in forests with a single tree species, which led to a decrease in damage to tree leaves by herbivores. This suggests that high genetic diversity in species-rich forests is likely also beneficial as herbivores are less able to damage tree foliage. As expected, in single-species forests with both low and high genetic diversity, higher soil fungi diversity was associated with a loss in productivity. Interestingly, in forests that had high species and genetic diversity, this effect was reversed, and higher genetic diversity reduced the loss of productivity caused by soil fungi, resulting in higher productivity overall. These results should be considered in reforestation projects to promote genetic diversity of trees on top of species diversity when replanting. How genetic diversity leads to downstream mechanisms that benefit community productivity is not fully understood and future research could look at what specific genetic features matter most to help select the ideal mixture of trees to maximize productivity and increase the land's ecological and economic value.

Remotely detected aboveground plant function predicts belowground processes in two prairie diversity experiments.

Imaging spectroscopy provides the opportunity to incorporate leaf and canopy optical data into ecological studies, but the extent to which remote sensing of vegetation can enhance the study of belowground processes is not well understood. In terrestrial systems, aboveground and belowground vegetation quantity and quality are coupled, and both influence belowground microbial processes and nutrient cycling. We hypothesized that ecosystem productivity, and the chemical, structural and phylogenetic-functional composition of plant communities would be detectable with remote sensing and could be used to predict belowground plant and soil processes in two grassland biodiversity experiments: the BioDIV experiment at Cedar Creek Ecosystem Science Reserve in Minnesota and the Wood River Nature Conservancy experiment in Nebraska. We tested whether aboveground vegetation chemistry and productivity, as detected from airborne sensors, predict soil properties, microbial processes and community composition. Imaging spectroscopy data were used to map aboveground biomass, green vegetation cover, functional traits and phylogenetic-functional community composition of vegetation. We examined the relationships between the image-derived variables and soil carbon and nitrogen concentration, microbial community composition, biomass and extracellular enzyme activity, and soil processes, including net nitrogen mineralization. In the BioDIV experiment-which has low overall diversity and productivity despite high variation in each-belowground processes were driven mainly by variation in the amount of organic matter inputs to soils. As a consequence, soil respiration, microbial biomass and enzyme activity, and fungal and bacterial composition and diversity were significantly predicted by remotely sensed vegetation cover and biomass. In contrast, at Wood River-where plant diversity and productivity were consistently higher-belowground processes were driven mainly by variation in the quality of aboveground inputs to soils. Consequently, remotely sensed functional, chemical and phylogenetic composition of vegetation predicted belowground extracellular enzyme activity, microbial biomass, and net nitrogen mineralization rates but aboveground biomass (or cover) did not. The contrasting associations between the quantity (productivity) and quality (composition) of aboveground inputs with belowground soil attributes provide a basis for using imaging spectroscopy to understand belowground processes across productivity gradients in grassland systems. However, a mechanistic understanding of how above and belowground components interact among different ecosystems remains critical to extending these results broadly.

Integrating remote sensing with ecology and evolution to advance biodiversity conservation.

Remote sensing has transformed the monitoring of life on Earth by revealing spatial and temporal dimensions of biological diversity through structural, compositional and functional measurements of ecosystems. Yet, many aspects of Earth's biodiversity are not directly quantified by reflected or emitted photons. Inclusive integration of remote sensing with field-based ecology and evolution is needed to fully understand and preserve Earth's biodiversity. In this Perspective, we argue that multiple data types are necessary for almost all draft targets set by the Convention on Biological Diversity. We examine five key topics in biodiversity science that can be advanced by integrating remote sensing with in situ data collection from field sampling, experiments and laboratory studies to benefit conservation. Lowering the barriers for bringing these approaches together will require global-scale collaboration.

Representing plant diversity in land models: An evolutionary approach to make "Functional Types" more functional.

Plants are critical mediators of terrestrial mass and energy fluxes, and their structural and functional traits have profound impacts on local and global climate, biogeochemistry, biodiversity, and hydrology. Yet, Earth System Models (ESMs), our most powerful tools for predicting the effects of humans on the coupled biosphere-atmosphere system, simplify the incredible diversity of land plants into a handful of coarse categories of "Plant Functional Types" (PFTs) that often fail to capture ecological dynamics such as biome distributions. The inclusion of more realistic functional diversity is a recognized goal for ESMs, yet there is currently no consistent, widely accepted way to add diversity to models, that is, to determine what new PFTs to add and with what data to constrain their parameters. We review approaches to representing plant diversity in ESMs and draw on recent ecological and evolutionary findings to present an evolution-based functional type approach for further disaggregating functional diversity. Specifically, the prevalence of niche conservatism, or the tendency of closely related taxa to retain similar ecological and functional attributes through evolutionary time, reveals that evolutionary relatedness is a powerful framework for summarizing functional similarities and differences among plant types. We advocate that Plant Functional Types based on dominant evolutionary lineages ("Lineage Functional Types") will provide an ecologically defensible, tractable, and scalable framework for representing plant diversity in next-generation ESMs, with the potential to improve parameterization, process representation, and model benchmarking. We highlight how the importance of evolutionary history for plant function can unify the work of disparate fields to improve predictive modeling of the Earth system.

Coupling spectral and resource-use complementarity in experimental grassland and forest communities.

Reflectance spectra provide integrative measures of plant phenotypes by capturing chemical, morphological, anatomical and architectural trait information. Here, we investigate the linkages between plant spectral variation, and spectral and resource-use complementarity that contribute to ecosystem productivity. In both a forest and prairie grassland diversity experiment, we delineated n-dimensional hypervolumes using wavelength bands of reflectance spectra to test the association between the spectral space occupied by individual plants and their growth, as well as between the spectral space occupied by plant communities and ecosystem productivity. We show that the spectral space occupied by individuals increased with their growth, and the spectral space occupied by plant communities increased with ecosystem productivity. Furthermore, ecosystem productivity was better explained by inter-individual spectral complementarity than by the large spectral space occupied by productive individuals. Our results indicate that spectral hypervolumes of plants can reflect ecological strategies that shape community composition and ecosystem function, and that spectral complementarity can reveal resource-use complementarity.

Predicting species distributions and community composition using satellite remote sensing predictors.

Biodiversity is rapidly changing due to changes in the climate and human related activities; thus, the accurate predictions of species composition and diversity are critical to developing conservation actions and management strategies. In this paper, using satellite remote sensing products as covariates, we constructed stacked species distribution models (S-SDMs) under a Bayesian framework to build next-generation biodiversity models. Model performance of these models was assessed using oak assemblages distributed across the continental United States obtained from the National Ecological Observatory Network (NEON). This study represents an attempt to evaluate the integrated predictions of biodiversity models-including assemblage diversity and composition-obtained by stacking next-generation SDMs. We found that applying constraints to assemblage predictions, such as using the probability ranking rule, does not improve biodiversity prediction models. Furthermore, we found that independent of the stacking procedure (bS-SDM versus pS-SDM versus cS-SDM), these kinds of next-generation biodiversity models do not accurately recover the observed species composition at the plot level or ecological-community scales (NEON plots are 400 m2). However, these models do return reasonable predictions at macroecological scales, i.e., moderately to highly correct assignments of species identities at the scale of NEON sites (mean area ~ 27 km2). Our results provide insights for advancing the accuracy of prediction of assemblage diversity and composition at different spatial scales globally. An important task for future studies is to evaluate the reliability of combining S-SDMs with direct detection of species using image spectroscopy to build a new generation of biodiversity models that accurately predict and monitor ecological assemblages through time and space.

Disease and fire interact to influence transitions between savanna-forest ecosystems over a multi-decadal experiment.

Global change is shifting disturbance regimes that may rapidly change ecosystems, sometimes causing ecosystems to shift between states. Interactions between disturbances such as fire and disease could have especially severe effects, but experimental tests of multi-decadal changes in disturbance regimes are rare. Here, we surveyed vegetation for 35 years in a 54-year fire frequency experiment in a temperate oak savanna-forest ecotone that experienced a recent outbreak of oak wilt. Different fire regimes determined whether plots were savanna or forest by regulating tree abundance (r2  = 0.70), but disease rapidly reversed the effect of fire exclusion, increasing mortality by 765% in unburned forests, but causing relatively minor changes in frequently burned savannas. Model simulations demonstrated that disease caused unburned forests to transition towards a unique woodland that was prone to transition to savanna if fire was reintroduced. Consequently, disease-fire interactions could shift ecosystem resilience and biome boundaries as pathogen distributions change.

Enhanced light interception and light use efficiency explain overyielding in young tree communities.

Diverse plant communities are often more productive than mono-specific ones. Several possible mechanisms underlie this phenomenon but their relative importance remains unknown. Here we investigated whether light interception alone or in combination with light use efficiency (LUE) of dominant and subordinate species explained greater productivity of mixtures relative to monocultures (i.e. overyielding) in 108 young experimental tree communities. We found mixed-species communities that intercepted more light than their corresponding monocultures had 84% probability of overyielding. Enhanced LUE, which arose via several pathways, also mattered: the probability of overyielding was 71% when, in a mixture, species with higher 'inherent' LUE (i.e. LUE in monoculture) intercepted more light than species with lower LUE; 94% when dominant species increased their LUE in mixture; and 79% when subordinate species increased their LUE. Our results suggest that greater light interception and greater LUE, generated by inter and intraspecific variation, together drive overyielding in mixed-species forests.

Deciduous and evergreen oaks show contrasting adaptive responses in leaf mass per area across environments.

Increases in leaf mass per area (LMA) are commonly observed in response to environmental stresses and are achieved through increases in leaf thickness and/or leaf density. Here, we investigated how the two underlying components of LMA differ in relation to species native climates and phylogeny, across deciduous and evergreen species. Using a phylogenetic approach, we quantified anatomical, compositional and climatic variables from 40 deciduous and 45 evergreen Quercus species from across the Northern Hemisphere growing in a common garden. Deciduous species from shorter growing seasons tended to have leaves with lower LMA and leaf thickness than those from longer growing seasons, while the opposite pattern was found for evergreens. For both habits, LMA and thickness increased in arid environments. However, this shift was associated with increased leaf density in evergreens but reduced density in deciduous species. Deciduous and evergreen oaks showed fundamental leaf morphological differences that revealed a diverse adaptive response. While LMA in deciduous species may have diversified in tight coordination with thickness mainly modulated by aridity, diversification of LMA within evergreens appears to be dependent on the infrageneric group, with diversification in leaf thickness modulated by both aridity and cold, while diversification in leaf density is only modulated by aridity.