Mapping the global distribution of C4 vegetation using observations and optimality theory.

Plants with the C4 photosynthesis pathway typically respond to climate change differently from more common C3-type plants, due to their distinct anatomical and biochemical characteristics. These different responses are expected to drive changes in global C4 and C3 vegetation distributions. However, current C4 vegetation distribution models may not predict this response as they do not capture multiple interacting factors and often lack observational constraints. Here, we used global observations of plant photosynthetic pathways, satellite remote sensing, and photosynthetic optimality theory to produce an observation-constrained global map of C4 vegetation. We find that global C4 vegetation coverage decreased from 17.7% to 17.1% of the land surface during 2001 to 2019. This was the net result of a reduction in C4 natural grass cover due to elevated CO2 favoring C3-type photosynthesis, and an increase in C4 crop cover, mainly from corn (maize) expansion. Using an emergent constraint approach, we estimated that C4 vegetation contributed 19.5% of global photosynthetic carbon assimilation, a value within the range of previous estimates (18-23%) but higher than the ensemble mean of dynamic global vegetation models (14 ± 13%; mean ± one standard deviation). Our study sheds insight on the critical and underappreciated role of C4 plants in the contemporary global carbon cycle.

Climate change increases threat to plant diversity in tropical forests of Central America and southern Mexico.

Global biodiversity is negatively affected by anthropogenic climate change. As species distributions shift due to increasing temperatures and precipitation fluctuations, many species face the risk of extinction. In this study, we explore the expected trend for plant species distributions in Central America and southern Mexico under two alternative Representative Concentration Pathways (RCPs) portraying moderate (RCP4.5) and severe (RCP8.5) increases in greenhouse gas emissions, combined with two species dispersal assumptions (limited and unlimited), for the 2061-2080 climate forecast. Using an ensemble approach employing three techniques to generate species distribution models, we classified 1924 plant species from the region's (sub)tropical forests according to IUCN Red List categories. To infer the spatial and taxonomic distribution of species' vulnerability under each scenario, we calculated the proportion of species in a threat category (Vulnerable, Endangered, Critically Endangered) at a pixel resolution of 30 arc seconds and by family. Our results show a high proportion (58-67%) of threatened species among the four experimental scenarios, with the highest proportion under RCP8.5 and limited dispersal. Threatened species were concentrated in montane areas and avoided lowland areas where conditions are likely to be increasingly inhospitable. Annual precipitation and diurnal temperature range were the main drivers of species' relative vulnerability. Our approach identifies strategic montane areas and taxa of conservation concern that merit urgent inclusion in management plans to improve climatic resilience in the Mesoamerican biodiversity hotspot. Such information is necessary to develop policies that prioritize vulnerable elements and mitigate threats to biodiversity under climate change.

Capturing patterns of evolutionary relatedness with reflectance spectra to model and monitor biodiversity.

Biogeographic history can set initial conditions for vegetation community assemblages that determine their climate responses at broad extents that land surface models attempt to forecast. Numerous studies have indicated that evolutionarily conserved biochemical, structural, and other functional attributes of plant species are captured in visible-to-short wavelength infrared, 400 to 2,500 nm, reflectance properties of vegetation. Here, we present a remotely sensed phylogenetic clustering and an evolutionary framework to accommodate spectra, distributions, and traits. Spectral properties evolutionarily conserved in plants provide the opportunity to spatially aggregate species into lineages (interpreted as "lineage functional types" or LFT) with improved classification accuracy. In this study, we use Airborne Visible/Infrared Imaging Spectrometer data from the 2013 Hyperspectral Infrared Imager campaign over the southern Sierra Nevada, California flight box, to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from 1372 surveys and a phylogeny representing 1,572 species. Despite temporal and spatial differences in our training data, we classified plant lineages with moderate reliability (Kappa = 0.76) and overall classification accuracy of 80.9%. We present an assessment of classification error and detail study limitations to facilitate future LFT development. This work demonstrates that lineage-based methods may be a promising way to leverage the new-generation high-resolution and high return-interval hyperspectral data planned for the forthcoming satellite missions with sparsely sampled existing ground-based ecological data.

Evolutionary lineage explains trait variation among 75 coexisting grass species.

Evolutionary history plays a key role driving patterns of trait variation across plant species. For scaling and modeling purposes, grass species are typically organized into C3 vs C4 plant functional types (PFTs). Plant functional type groupings may obscure important functional differences among species. Rather, grouping grasses by evolutionary lineage may better represent grass functional diversity. We measured 11 structural and physiological traits in situ from 75 grass species within the North American tallgrass prairie. We tested whether traits differed significantly among photosynthetic pathways or lineages (tribe) in annual and perennial grass species. Critically, we found evidence that grass traits varied among lineages, including independent origins of C4 photosynthesis. Using a rigorous model selection approach, tribe was included in the top models for five of nine traits for perennial species. Tribes were separable in a multivariate and phylogenetically controlled analysis of traits, owing to coordination of important structural and ecophysiological characteristics. Our findings suggest grouping grass species by photosynthetic pathway overlooks variation in several functional traits, particularly for C4 species. These results indicate that further assessment of lineage-based differences at other sites and across other grass species distributions may improve representation of C4 species in trait comparison analyses and modeling investigations.

Towards a circular economy in virgin olive oil production: Valorization of the olive mill waste (OMW) "alpeorujo" through polyphenol recovery with natural deep eutectic solvents (NADESs) and vermicomposting.

Virgin olive oil (VOO) production generates large amounts of a harmful by-product, olive mill waste (OMW) or alpeorujo, which has a strong environmental impact and that must be recycled to adapt VOO production to a circular economy model. Here, the valorization of OMW was studied by considering three consecutive stages: Stage 1 involves the generation of OMW; Stage 2 the recovery of bioactive phenolic compounds from the fresh OMW using natural deep eutectic solvents (NADESs), generating a valuable phenolic extract and a new by-product, a dephenolized OMW named "alpeoNADES"; and Stage 3 involves vermicomposting alpeoNADES with Eisenia fetida earthworms. Six NADES were formulated and tested, selecting a NADES composed of citric acid and fructose (CF) derived from food grade and biodegradable substances. CF was the most effective solvent to obtain phenolic extracts for nutraceutical and agronomical purposes, extracting 3988.74 mg/kg of polyphenols from fresh OMW. This alpeoNADES is a non-palatable substrate for E. fetida earthworms, as the residual CF gives it an acidic pH (pH 2). Its palatability was improved by mixing it with horse manure and straw for vermicomposting, in a 1:1 and 3:1 dry weight ratio. When these substrates were precomposted for 3 weeks they reached pH 5.5-6 and they could then be vermicomposted for 23 weeks (using OMW as a control). The best substrate for vermicomposting was determined by the worm biomass, growth rate, carbon to nitrogen (C:N) ratio, and N and P content. AlpeoNADES and manure 3:1 produced the highest quality vermicompost in the shortest time, generating a product that complied with European standards for organic fertilizers. Hence, alpeoNADES was recycled to a low-cost, organic balanced fertilizer in Stage 3, enabling the olive oil industry to transition to sustainable production through this integrated circular economy design.

Landscape-scale forest cover drives the predictability of forest regeneration across the Neotropics.

Abandonment of agricultural lands promotes the global expansion of secondary forests, which are critical for preserving biodiversity and ecosystem functions and services. Such roles largely depend, however, on two essential successional attributes, trajectory and recovery rate, which are expected to depend on landscape-scale forest cover in nonlinear ways. Using a multi-scale approach and a large vegetation dataset (843 plots, 3511 tree species) from 22 secondary forest chronosequences distributed across the Neotropics, we show that successional trajectories of woody plant species richness, stem density and basal area are less predictable in landscapes (4 km radius) with intermediate (40-60%) forest cover than in landscapes with high (greater than 60%) forest cover. This supports theory suggesting that high spatial and environmental heterogeneity in intermediately deforested landscapes can increase the variation of key ecological factors for forest recovery (e.g. seed dispersal and seedling recruitment), increasing the uncertainty of successional trajectories. Regarding the recovery rate, only species richness is positively related to forest cover in relatively small (1 km radius) landscapes. These findings highlight the importance of using a spatially explicit landscape approach in restoration initiatives and suggest that these initiatives can be more effective in more forested landscapes, especially if implemented across spatial extents of 1-4 km radius.

No evidence of canopy-scale leaf thermoregulation to cool leaves below air temperature across a range of forest ecosystems.

Understanding and predicting the relationship between leaf temperature (Tleaf) and air temperature (Tair) is essential for projecting responses to a warming climate, as studies suggest that many forests are near thermal thresholds for carbon uptake. Based on leaf measurements, the limited leaf homeothermy hypothesis argues that daytime Tleaf is maintained near photosynthetic temperature optima and below damaging temperature thresholds. Specifically, leaves should cool below Tair at higher temperatures (i.e., > ∼25-30°C) leading to slopes <1 in Tleaf/Tair relationships and substantial carbon uptake when leaves are cooler than air. This hypothesis implies that climate warming will be mitigated by a compensatory leaf cooling response. A key uncertainty is understanding whether such thermoregulatory behavior occurs in natural forest canopies. We present an unprecedented set of growing season canopy-level leaf temperature (Tcan) data measured with thermal imaging at multiple well-instrumented forest sites in North and Central America. Our data do not support the limited homeothermy hypothesis: canopy leaves are warmer than air during most of the day and only cool below air in mid to late afternoon, leading to Tcan/Tair slopes >1 and hysteretic behavior. We find that the majority of ecosystem photosynthesis occurs when canopy leaves are warmer than air. Using energy balance and physiological modeling, we show that key leaf traits influence leaf-air coupling and ultimately the Tcan/Tair relationship. Canopy structure also plays an important role in Tcan dynamics. Future climate warming is likely to lead to even greater Tcan, with attendant impacts on forest carbon cycling and mortality risk.

Native Hyperaccumulator Plants with Differential Phytoremediation Potential in an Artisanal Gold Mine of the Ecuadorian Amazon.

In tropical forests of southern Ecuador, artisanal gold mining releases heavy metals that become xenobiotic with indefinite circulation and eventual bioaccumulation. Restoration and rehabilitation of degraded mining sites represent a major ecological, technological and economic issue. In this study, we estimate the capacity of two native woody plants to accumulate cadmium (Cd), lead (Pb), zinc (Zn) and mercury (Hg), with the goal of developing effective strategies for phytoremediation of mining sites. Individuals of Erato polymnioides and Miconia sp., as well as their rhizospheric soils, were sampled from a natural zone (NZ) of montane cloud forest, used as a control, and a polluted zone (PZ) subjected to active gold mining. Concentrations of the four heavy metals were analyzed using atomic absorption spectrophotometry. Cd, Zn and Hg concentrations were higher in soils of PZ than NZ. Bioaccumulation (BCF) and translocation factors (TF) showed that Miconia sp. has potential for Cd and Zn phytostabilization, E. polymnioides has potential for Cd and Zn phytoextraction, and both species have potential for Hg phytoextraction. Despite the low productivity of these species, their adaptability to the edaphoclimatic conditions of the region and the possibility of using amendments to increase their biomass could compensate for the effectiveness of these species in reclaiming soils contaminated by mining.

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.

A multifaceted approach to understanding bat community response to disturbance in a seasonally dry tropical forest.

Given widespread habitat degradation and loss, reliable indicators are needed that provide a comprehensive assessment of community response to anthropogenic disturbance. The family Phyllostomidae (Order Chiroptera) has frequently been the focus of research evaluating bats' response to habitat disturbance in seasonally dry tropical forests (SDTFs). However, few studies compare this family to the larger bat assemblage to assess its efficacy as a bioindicator. We compared community and species-specific attributes of understory phyllostomid and all understory bat species: (1) along a gradient of habitat disturbance within a human-modified SDTF landscape; and (2) between forest and riparian habitats within each disturbance level. We captured 290 individuals belonging to 13 species and 4 families. Phyllostomid species exhibited greater sensitivity to disturbance than the understory bat community as a whole based on richness and beta diversity. Both groups were more sensitive to disturbance in forest than riparian habitat, but phyllostomid species were more likely to be lost from highly disturbed forest habitat. The two dominant species declined in abundance with disturbance but variation in body condition was species-specific. These results suggest that Phyllostomidae are more effective indicators of human disturbance in SDTF than the understory bat community as a whole and evaluation of bats' response to disturbance is best accomplished with a multifaceted approach.

Soil nutrients and precipitation are major drivers of global patterns of grass leaf silicification.

Grasses accumulate high concentrations of silicon (Si) in their tissues, with potential benefits including herbivore defense, improved water balance, and reduced leaf construction costs. Although Si is one of the most widely varying leaf constituents among individuals, species, and ecosystems, the environmental forces driving this variation remain elusive and understudied. To understand relationships between environmental factors and grass Si accumulation better, we analyzed foliar chemistry of grasses from 17 globally distributed sites where nutrient inputs and grazing were manipulated. These sites span natural gradients in temperature, precipitation, and underlying soil properties, which allowed us to assess the relative importance of soil moisture and nutrients across variation in climate. Foliar Si concentration did not respond to large mammalian grazer exclusion, but significant variation in herbivore abundance among sites may have precluded the observation of defoliation effects at these sites. However, nutrient addition consistently reduced leaf Si, especially at sites with low soil nitrogen prior to nutrient addition. Additionally, a leaf-level trade-off between Si and carbon (C) existed that was stronger at arid sites than mesic sites. Our results suggest soil nutrient limitation favors investment in Si over C-based leaf construction, and that fixing C is especially costly relative to assimilating Si when water is limiting. Our results demonstrate the importance of soil nutrients and precipitation as key drivers of global grass silicification patterns.

Lineage-based functional types: characterising functional diversity to enhance the representation of ecological behaviour in Land Surface Models.

Process-based vegetation models attempt to represent the wide range of trait variation in biomes by grouping ecologically similar species into plant functional types (PFTs). This approach has been successful in representing many aspects of plant physiology and biophysics but struggles to capture biogeographic history and ecological dynamics that determine biome boundaries and plant distributions. Grass-dominated ecosystems are broadly distributed across all vegetated continents and harbour large functional diversity, yet most Land Surface Models (LSMs) summarise grasses into two generic PFTs based primarily on differences between temperate C3 grasses and (sub)tropical C4 grasses. Incorporation of species-level trait variation is an active area of research to enhance the ecological realism of PFTs, which form the basis for vegetation processes and dynamics in LSMs. Using reported measurements, we developed grass functional trait values (physiological, structural, biochemical, anatomical, phenological, and disturbance-related) of dominant lineages to improve LSM representations. Our method is fundamentally different from previous efforts, as it uses phylogenetic relatedness to create lineage-based functional types (LFTs), situated between species-level trait data and PFT-level abstractions, thus providing a realistic representation of functional diversity and opening the door to the development of new vegetation models.

Comment on "The global tree restoration potential".

Bastin et al's estimate (Reports, 5 July 2019, p. 76) that tree planting for climate change mitigation could sequester 205 gigatonnes of carbon is approximately five times too large. Their analysis inflated soil organic carbon gains, failed to safeguard against warming from trees at high latitudes and elevations, and considered afforestation of savannas, grasslands, and shrublands to be restoration.

A novel approach to assessing environmental disturbance based on habitat selection by zebra fish as a model organism.

Aquatic ecotoxicity assays used to assess ecological risk assume that organisms living in a contaminated habitat are forcedly exposed to the contamination. This assumption neglects the ability of organisms to detect and avoid contamination by moving towards less disturbed habitats, as long as connectivity exists. In fluvial systems, many environmental parameters vary spatially and thus condition organisms' habitat selection. We assessed the preference of zebra fish (Danio rerio) when exposed to water samples from two western Ecuadorian rivers with apparently distinct disturbance levels: Pescadillo River (highly disturbed) and Oro River (moderately disturbed). Using a non-forced exposure system in which water samples from each river were arranged according to their spatial sequence in the field and connected to allow individuals to move freely among samples, we assayed habitat selection by D. rerio to assess environmental disturbance in the two rivers. Fish exposed to Pescadillo River samples preferred downstream samples near the confluence zone with the Oro River. Fish exposed to Oro River samples preferred upstream waters. When exposed to samples from both rivers simultaneously, fish exhibited the same pattern of habitat selection by preferring the Oro River samples. Given that the rivers are connected, preference for the Oro River enabled us to predict a depression in fish populations in the Pescadillo River. Although these findings indicate higher disturbance levels in the Pescadillo River, none of the physical-chemical variables measured was significantly correlated with the preference pattern towards the Oro River. Non-linear spatial patterns of habitat preference suggest that other environmental parameters like urban or agricultural contaminants play an important role in the model organism's habitat selection in these rivers. The non-forced exposure system represents a habitat selection-based approach that can serve as a valuable tool to unravel the factors that dictate organisms' spatial distribution in connected ecosystems.

Herbivory and eutrophication mediate grassland plant nutrient responses across a global climatic gradient.

Plant stoichiometry, the relative concentration of elements, is a key regulator of ecosystem functioning and is also being altered by human activities. In this paper we sought to understand the global drivers of plant stoichiometry and compare the relative contribution of climatic vs. anthropogenic effects. We addressed this goal by measuring plant elemental (C, N, P and K) responses to eutrophication and vertebrate herbivore exclusion at eighteen sites on six continents. Across sites, climate and atmospheric N deposition emerged as strong predictors of plot-level tissue nutrients, mediated by biomass and plant chemistry. Within sites, fertilization increased total plant nutrient pools, but results were contingent on soil fertility and the proportion of grass biomass relative to other functional types. Total plant nutrient pools diverged strongly in response to herbivore exclusion when fertilized; responses were largest in ungrazed plots at low rainfall, whereas herbivore grazing dampened the plant community nutrient responses to fertilization. Our study highlights (1) the importance of climate in determining plant nutrient concentrations mediated through effects on plant biomass, (2) that eutrophication affects grassland nutrient pools via both soil and atmospheric pathways and (3) that interactions among soils, herbivores and eutrophication drive plant nutrient responses at small scales, especially at water-limited sites.

Comment on "The extent of forest in dryland biomes".

Bastin et al (Reports, 12 May 2017, p. 635) infer forest as more globally extensive than previously estimated using tree cover data. However, their forest definition does not reflect ecosystem function or biotic composition. These structural and climatic definitions inflate forest estimates across the tropics and undermine conservation goals, leading to inappropriate management policies and practices in tropical grassy ecosystems.

Leaf thickness controls variation in leaf mass per area (LMA) among grazing-adapted grasses in Serengeti.

Leaf mass per area (LMA) is a primary plant functional trait that represents the cost of constructing a leaf. Ultimately, plants modify LMA by altering leaf thickness (LT), leaf dry matter content (LDMC), or both. While LMA can be modified through both of these constituents, studies of LMA have found that there is variation in whether LT or LDMC changes are responsible for LMA-and the relationships change depending on the species or functional groups being compared. In this study, we used a phylogenetic framework to determine that evolutionary shifts in LMA are driven by LT, and not LDMC, among 45 Serengeti grass species. We considered two alternative hypotheses that could result in evolutionary correlation of LMA on LT but not LDMC: either (1) LT is more labile than LDMC-and is therefore a less costly means to change LMA or (2) LDMC is tightly coupled to a different dimension of leaf variation (e.g., leaf hydraulics), leaving LT as the source of variation in LMA. LT was not more labile than LDMC, leading us to conclude that the evolution of LMA has been shaped by LT because LDMC is responding to other demands on leaf physiology. We speculate that leaf hydraulics provide this constraint on LDMC. The decoupling of LDMC from LT may allow plants to better optimize resource allocation in ecosystems where gradients in light competition, herbivory, and aridity place competing demands on leaf economics.

Responses of African Grasses in the Genus Sporobolus to Defoliation and Sodium Stress: Tradeoffs, Cross-Tolerance, or Independent Responses?

In the Serengeti ecosystem of East Africa, grazing ungulates prefer areas with elevated grass Na, suggesting that some grasses tolerate both high soil Na and defoliation. We performed a factorial Na-by-defoliation greenhouse study with five abundant Sporobolus congeners to explore whether Serengeti grasses possess traits which: (i) confer tolerance to both Na and defoliation (cross-tolerance); (ii) display a tradeoff; or (iii) act independently in their tolerances. Our expectation was that related grasses would exhibit cross-tolerance when simultaneously subjected to Na and defoliation. Instead, we found that physiological tolerances and growth responses to Na and defoliation did not correlate but instead acted independently: species characterized by intense grazing in the field showed no growth or photosynthetic compensation for combined Na and defoliation. Additionally, in all but the highest Na dosage, mortality was higher when species were exposed to both Na and defoliation together. Across species, mortality rates were greater in short-statured species which occur on sodic soils in heavily grazed areas. Mortality among species was positively correlated with specific leaf area, specific root length, and relative growth rate, suggesting that rapidly growing species which invest in low cost tissues have higher rates of mortality when exposed to multiple stressors. We speculate that the prevalence of these species in areas of high Na and disturbance is explained by alternative strategies, such as high fecundity, a wide range of germination conditions, or further dispersal, to compensate for the lack of additional tolerance mechanisms.