RESUMO
Tropical forests are important to the regulation of climate and the maintenance of biodiversity on Earth. However, these ecosystems are threatened by climate change, as temperatures rise and droughts' frequency and duration increase. Xylem anatomical traits are an essential component in understanding and predicting forest responses to changes in water availability. We calculated the community-weighted means and variances of xylem anatomical traits of hydraulic and structural importance (plot-level trait values weighted by species abundance) to assess their linkages to local adaptation and community assembly in response to varying soil water conditions in an environmentally diverse Brazilian Atlantic Forest habitat. Scaling approaches revealed community-level tradeoffs in xylem traits not observed at the species level. Towards drier sites, xylem structural reinforcement and integration balanced against hydraulic efficiency and capacitance xylem traits, leading to changes in plant community diversity. We show how general community assembly rules are reflected in persistent fiber-parenchyma and xylem hydraulic tradeoffs. Trait variation across a moisture gradient is larger between species than within species and is realized mainly through changes in species composition and abundance, suggesting habitat specialization. Modeling efforts to predict tropical forest diversity and drought sensitivity may benefit from adding hydraulic architecture traits into the analysis.
Assuntos
Secas , Árvores , Ecossistema , Florestas , Folhas de Planta , Árvores/fisiologia , Clima Tropical , Água , Xilema/fisiologiaRESUMO
Biodiversity contributes to the ecological and climatic stability of the Amazon Basin1,2, but is increasingly threatened by deforestation and fire3,4. Here we quantify these impacts over the past two decades using remote-sensing estimates of fire and deforestation and comprehensive range estimates of 11,514 plant species and 3,079 vertebrate species in the Amazon. Deforestation has led to large amounts of habitat loss, and fires further exacerbate this already substantial impact on Amazonian biodiversity. Since 2001, 103,079-189,755 km2 of Amazon rainforest has been impacted by fires, potentially impacting the ranges of 77.3-85.2% of species that are listed as threatened in this region5. The impacts of fire on the ranges of species in Amazonia could be as high as 64%, and greater impacts are typically associated with species that have restricted ranges. We find close associations between forest policy, fire-impacted forest area and their potential impacts on biodiversity. In Brazil, forest policies that were initiated in the mid-2000s corresponded to reduced rates of burning. However, relaxed enforcement of these policies in 2019 has seemingly begun to reverse this trend: approximately 4,253-10,343 km2 of forest has been impacted by fire, leading to some of the most severe potential impacts on biodiversity since 2009. These results highlight the critical role of policy enforcement in the preservation of biodiversity in the Amazon.
Assuntos
Biodiversidade , Conservação dos Recursos Naturais/legislação & jurisprudência , Secas , Agricultura Florestal/legislação & jurisprudência , Floresta Úmida , Incêndios Florestais/estatística & dados numéricos , Animais , Brasil , Mudança Climática/estatística & dados numéricos , Florestas , Mapeamento Geográfico , Plantas , Árvores/fisiologia , VertebradosRESUMO
Recent work has shown that leaf traits and spectral properties change through time and/or seasonally as leaves age. Current field and hyperspectral methods used to estimate canopy leaf traits could, therefore, be significantly biased by variation in leaf age. To explore the magnitude of this effect, we used a phenological dataset comprised of leaves of different leaf age groups -developmental, mature, senescent and mixed-age- from canopy and emergent tropical trees in southern Peru. We tested the performance of partial least squares regression models developed from these different age groups when predicting traits for leaves of different ages on both a mass and area basis. Overall, area-based models outperformed mass-based models with a striking improvement in prediction observed for area-based leaf carbon (Carea) estimates. We observed trait-specific age effects in all mass-based models while area-based models displayed age effects in mixed-age leaf groups for Parea and Narea. Spectral coefficients and variable importance in projection (VIPs) also reflected age effects. Both mass- and area-based models for all five leaf traits displayed age/temporal sensitivity when we tested their ability to predict the traits of leaves of other age groups. Importantly, mass-based mature models displayed the worst overall performance when predicting the traits of leaves from other age groups. These results indicate that the widely adopted approach of using fully expanded mature leaves to calibrate models that estimate remotely-sensed tree canopy traits introduces error that can bias results depending on the phenological stage of canopy leaves. To achieve temporally stable models, spectroscopic studies should consider producing area-based estimates as well as calibrating models with leaves of different age groups as they present themselves through the growing season. We discuss the implications of this for surveys of canopies with synchronised and unsynchronised leaf phenology.
Assuntos
Fenótipo , Folhas de Planta/fisiologia , Carbono/análise , Análise dos Mínimos Quadrados , Modelos Biológicos , Peru , Folhas de Planta/crescimento & desenvolvimento , Estações do Ano , Análise EspectralRESUMO
Tropical forest leaf albedo (reflectance) greatly impacts how much energy the planet absorbs; however; little is known about how it might be impacted by climate change. Here, we measure leaf traits and leaf albedo at ten 1-ha plots along a 3,200-m elevation gradient in Peru. Leaf mass per area (LMA) decreased with warmer temperatures along the elevation gradient; the distribution of LMA was positively skewed at all sites indicating a shift in LMA towards a warmer climate and future reduced tropical LMA. Reduced LMA was significantly (P < 0.0001) correlated with reduced leaf near-infrared (NIR) albedo; community-weighted mean NIR albedo significantly (P < 0.01) decreased as temperature increased. A potential future 2 °C increase in tropical temperatures could reduce lowland tropical leaf LMA by 6-7 g m-2 (5-6%) and reduce leaf NIR albedo by 0.0015-0.002 units. Reduced NIR albedo means that leaves are darker and absorb more of the Sun's energy. Climate simulations indicate this increased absorbed energy will warm tropical forests more at high CO2 conditions with proportionately more energy going towards heating and less towards evapotranspiration and cloud formation.
Assuntos
Mudança Climática , Folhas de Planta/fisiologia , Árvores/fisiologia , Clima Tropical , Altitude , Dióxido de Carbono/análise , Florestas , Temperatura Alta , Modelos Teóricos , Peru , Folhas de Planta/química , Árvores/químicaRESUMO
The functional composition of plant communities is commonly thought to be determined by contemporary climate. However, if rates of climate-driven immigration and/or exclusion of species are slow, then contemporary functional composition may be explained by paleoclimate as well as by contemporary climate. We tested this idea by coupling contemporary maps of plant functional trait composition across North and South America to paleoclimate means and temporal variation in temperature and precipitation from the Last Interglacial (120 ka) to the present. Paleoclimate predictors strongly improved prediction of contemporary functional composition compared to contemporary climate predictors, with a stronger influence of temperature in North America (especially during periods of ice melting) and of precipitation in South America (across all times). Thus, climate from tens of thousands of years ago influences contemporary functional composition via slow assemblage dynamics.
Assuntos
Clima , Fenômenos Fisiológicos Vegetais , Mudança Climática , História Antiga , América do Norte , América do Sul , TemperaturaRESUMO
Tropical montane cloud forests (TMCFs) harbour high levels of biodiversity and large carbon stocks. Their location at high elevations make them especially sensitive to climate change, because a warming climate is enhancing upslope species migration, but human disturbance (especially fire) may in many cases be pushing the treeline downslope. TMCFs are increasingly being affected by fire, and the long-term effects of fire are still unknown. Here, we present a 28-year chronosequence to assess the effects of fire and recovery pathways of burned TMCFs, with a detailed analysis of carbon stocks, forest structure and diversity. We assessed rates of change of carbon (C) stock pools, forest structure and tree-size distribution pathways and tested several hypotheses regarding metabolic scaling theory (MST), C recovery and biodiversity. We found four different C stock recovery pathways depending on the selected C pool and time since last fire, with a recovery of total C stocks but not of aboveground C stocks. In terms of forest structure, there was an increase in the number of small stems in the burned forests up to 5-9 years after fire because of regeneration patterns, but no differences on larger trees between burned and unburned plots in the long term. In support of MST, after fire, forest structure appears to approximate steady-state size distribution in less than 30 years. However, our results also provide new evidence that the species recovery of TMCF after fire is idiosyncratic and follows multiple pathways. While fire increased species richness, it also enhanced species dissimilarity with geographical distance. This is the first study to report a long-term chronosequence of recovery pathways to fire suggesting faster recovery rates than previously reported, but at the expense of biodiversity and aboveground C stocks.
Assuntos
Incêndios , Florestas , Árvores , Biodiversidade , Carbono , Mudança Climática , Peru , Fatores de Tempo , Clima TropicalRESUMO
Humans are both fertilizing the world and depleting its soils, decreasing the diversity of aquatic ecosystems and terrestrial plants in the process. We know less about how nutrients shape the abundance and diversity of the prokaryotes, fungi, and invertebrates of Earth's soils. Here we explore this question in the soils of a Panama forest subject to a 13-yr fertilization with factorial combinations of nitrogen (N), phosphorus (P), and potassium (K) and a separate micronutrient cocktail. We contrast three hypotheses linking biogeochemistry to abundance and diversity. Consistent with the Stress Hypothesis, adding N suppressed the abundance of invertebrates and the richness of all three groups of organisms by ca. 1 SD or more below controls. Nitrogen addition plots were 0.8 pH units more acidic with 18% more exchangeable aluminum, which is toxic to both prokaryotes and eukaryotes. These stress effects were frequently reversed, however, when N was added with P (for prokaryotes and invertebrates) and with added K (for fungi). Consistent with the Abundance Hypothesis, adding P generally increased prokaryote and invertebrate diversity, and adding K enhanced invertebrate diversity. Also consistent with the Abundance Hypothesis, increases in invertebrate abundance generated increases in richness. We found little evidence for the Competition Hypothesis: that single nutrients suppressed diversity by favoring a subset of high nutrient specialists, and that nutrient combinations suppressed diversity even more. Instead, combinations of nutrients, and especially the cation/micronutrient treatment, yielded the largest increases in richness in the two eukaryote groups. In sum, changes in soil biogeochemistry revealed a diversity of responses among the three dominant soil groups, positive synergies among nutrients, and-in contrast with terrestrial plants-the frequent enhancement of soil biodiversity.
Assuntos
Biodiversidade , Florestas , Fungos/classificação , Invertebrados/classificação , Microbiologia do Solo , Animais , Ecossistema , Panamá , SoloRESUMO
Understanding functional trait-environment relationships (TERs) may improve predictions of community assembly. However, many empirical TERs have been weak or lacking conceptual foundation. TERs based on leaf venation networks may better link individuals and communities via hydraulic constraints. We report measurements of vein density, vein radius, and leaf thickness for more than 100 dominant species occurring in ten forest communities spanning a 3,300 m Andes-Amazon elevation gradient in Peru. We use these data to measure the strength of TERs at community scale and to determine whether observed TERs are similar to those predicted by physiological theory. We found strong support for TERs between all traits and temperature, as well weaker support for a predicted TER between maximum abundance-weighted leaf transpiration rate and maximum potential evapotranspiration. These results provide one approach for developing a more mechanistic trait-based community assembly theory.
Assuntos
Florestas , Fenótipo , Plantas/anatomia & histologia , Peru , Folhas de Planta , Plantas/classificaçãoRESUMO
Leaf aging is a fundamental driver of changes in leaf traits, thereby regulating ecosystem processes and remotely sensed canopy dynamics. We explore leaf reflectance as a tool to monitor leaf age and develop a spectra-based partial least squares regression (PLSR) model to predict age using data from a phenological study of 1099 leaves from 12 lowland Amazonian canopy trees in southern Peru. Results demonstrated monotonic decreases in leaf water (LWC) and phosphorus (Pmass ) contents and an increase in leaf mass per unit area (LMA) with age across trees; leaf nitrogen (Nmass ) and carbon (Cmass ) contents showed monotonic but tree-specific age responses. We observed large age-related variation in leaf spectra across trees. A spectra-based model was more accurate in predicting leaf age (R2 = 0.86; percent root mean square error (%RMSE) = 33) compared with trait-based models using single (R2 = 0.07-0.73; %RMSE = 7-38) and multiple (R2 = 0.76; %RMSE = 28) predictors. Spectra- and trait-based models established a physiochemical basis for the spectral age model. Vegetation indices (VIs) including the normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), normalized difference water index (NDWI) and photosynthetic reflectance index (PRI) were all age-dependent. This study highlights the importance of leaf age as a mediator of leaf traits, provides evidence of age-related leaf reflectance changes that have important impacts on VIs used to monitor canopy dynamics and productivity and proposes a new approach to predicting and monitoring leaf age with important implications for remote sensing.
Assuntos
Fenômenos Químicos , Luz , Folhas de Planta/crescimento & desenvolvimento , Folhas de Planta/fisiologia , Árvores/fisiologia , Ecossistema , Análise dos Mínimos Quadrados , Modelos Teóricos , Peru , Folhas de Planta/anatomia & histologia , Folhas de Planta/química , Tecnologia de Sensoriamento Remoto , Comunicações Via Satélite , Especificidade da EspécieRESUMO
Climate warming is increasingly leading to marked changes in plant and animal biodiversity, but it remains unclear how temperatures affect microbial biodiversity, particularly in terrestrial soils. Here we show that, in accordance with metabolic theory of ecology, taxonomic and phylogenetic diversity of soil bacteria, fungi and nitrogen fixers are all better predicted by variation in environmental temperature than pH. However, the rates of diversity turnover across the global temperature gradients are substantially lower than those recorded for trees and animals, suggesting that the diversity of plant, animal and soil microbial communities show differential responses to climate change. To the best of our knowledge, this is the first study demonstrating that the diversity of different microbial groups has significantly lower rates of turnover across temperature gradients than other major taxa, which has important implications for assessing the effects of human-caused changes in climate, land use and other factors.