We assessed whether diversity in plant hydraulic traits can explain the observed diversity in plant responses to water stress in seasonally dry tropical forests (SDTFs).
The Ecosystem Demography ...model 2 (ED2) was updated with a trait-driven mechanistic plant hydraulic module, as well as novel drought-phenology and plant water stress schemes. Four plant functional types were parameterized on the basis of meta-analysis of plant hydraulic traits. Simulations from both the original and the updated ED2 were evaluated against 5 yr of field data from a Costa Rican SDTF site and remote-sensing data over Central America.
The updated model generated realistic plant hydraulic dynamics, such as leaf water potential and stem sap flow. Compared with the original ED2, predictions from our novel traitdriven model matched better with observed growth, phenology and their variations among functional groups. Most notably, the original ED2 produced unrealistically small leaf area index (LAI) and underestimated cumulative leaf litter. Both of these biases were corrected by the updated model. The updated model was also better able to simulate spatial patterns of LAI dynamics in Central America.
Plant hydraulic traits are intercorrelated in SDTFs. Mechanistic incorporation of plant hydraulic traits is necessary for the simulation of spatiotemporal patterns of vegetation dynamics in SDTFs in vegetation models.
AIM: Previous studies have shown that warming temperatures can affect the phenology of cold deciduous forests, delaying the timing of leaf coloration. However, these works have principally been based ...on observations from a small number of sites. Consequently it has been challenging to infer continental‐scale variations in the phenology of individual deciduous forest species and the extent to which there may be underlying climate drivers for these variations. To address that problem, this study evaluated and predicted the large‐scale variations of leaf colouring by using macroscale observations and models. LOCATION: North America. METHODS: We developed leaf colouring models using select observations (1) from Harvard Forest only and (2) from both Harvard Forest and a new, ground‐based, Alaskan dataset from the USA National Phenology Network (USA‐NPN). Both model types were evaluated using reserved observations from the continental‐scale USA‐NPN that were not used in model calibration. Validated models were then used to assess the spatial scaling and interspecies variation in the timing of leaf coloration. The sensitivity of the models to projected climate change was also evaluated. RESULTS: Using a model calibrated only with data from Harvard Forest, significant biases were found in predictions of leaf colouring date for species with broad habitat ranges in the temperate to boreal regions. When calibration data from both Harvard Forest and Alaska were used, model performance improved throughout the whole continent. It was also found that species with similar shade tolerance could be described by similar models. Finally, the models indicated that climate change over the next century will affect leaf coloration in Alaska less than in the Harvard Forest region. MAIN CONCLUSIONS: For a given species, continental‐scale variations in the timing of autumn leaf coloration can be predicted using a model driven by photoperiod and daily temperature. The temperature sensitivity of the leaf colouring date is nonlinear, such that warmer regions have a larger temperature sensitivity than cooler regions. Species‐specific measurements from multiple environments are essential for model parameterization.
Tree abundance in tropical savannas exhibits large and unexplained spatial variability. Here, we propose that differentiated tree and grass water use strategies can explain the observed negative ...relation between maximum tree abundance and rainfall intensity (defined as the characteristic rainfall depth on rainy days), and we present a biophysical tree–grass competition model to test this idea. The model is founded on a premise that has been well established in empirical studies, namely, that the relative growth rate of grasses is much higher compared with trees in wet conditions but that grasses are more susceptible to water stress and lose biomass more quickly in dry conditions. The model is coupled with a stochastic rainfall generator and then calibrated and tested using field observations from several African savanna sites. We show that the observed negative relation between maximum tree abundance and rainfall intensity can be explained only when differentiated water use strategies are accounted for. Numerical experiments reveal that this effect is more significant than the effect of root niche separation. Our results emphasize the importance of vegetation physiology in determining the responses of tree abundance to climate variations in tropical savannas and suggest that projected increases in rainfall intensity may lead to an increase in grass in this biome.
Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an ...important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real‐world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first‐generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter‐disciplinary communication.
In this review, we summarize in detail the development of vegetation demographics models as components of Earth System Models. We particularly highlight the ecological uncertainties around the strength of growth‐resource acquisition feedbacks that are common across model developments, and illustrate the myriad new opportunities for ecological‐scale data streams to inform and validate these new model structures.
Drought‐related tree mortality is now a widespread phenomenon predicted to increase in magnitude with climate change. However, the patterns of which species and trees are most vulnerable to drought, ...and the underlying mechanisms have remained elusive, in part due to the lack of relevant data and difficulty of predicting the location of catastrophic drought years in advance. We used long‐term demographic records and extensive databases of functional traits and distribution patterns to understand the responses of 20–53 species to an extreme drought in a seasonally dry tropical forest in Costa Rica, which occurred during the 2015 El Niño Southern Oscillation event. Overall, species‐specific mortality rates during the drought ranged from 0% to 34%, and varied little as a function of tree size. By contrast, hydraulic safety margins correlated well with probability of mortality among species, while morphological or leaf economics spectrum traits did not. This firmly suggests hydraulic traits as targets for future research.
We took advantage of an exceptionally strong El Niño‐related drought in 2015 to understand the effects on tree mortality in a diverse, seasonally dry tropical forest. Tree mortality rates differed widely among species, ranging from 0% to 34%, and varied little as a function of tree size. We correlated the mean mortality rates by species with a large number of potential explanatory variables and found that hydraulic safety margins correlated well with probability of mortality among species, while soft traits such as wood density did not. This firmly suggests hydraulic traits as targets for future research.
Earth system models (ESMs) have been developed to represent the role of terrestrial ecosystems on the energy, water, and carbon cycles. However, many ESMs still lack representation of ...within-ecosystem heterogeneity and diversity. In this paper, we present the Ecosystem Demography model version 2.2 (ED-2.2). In ED-2.2, the biophysical and physiological processes account for the horizontal and vertical heterogeneity of the ecosystem: the energy, water, and carbon cycles are solved separately for a series of vegetation cohorts (groups of individual plants of similar size and plant functional type) distributed across a series of spatially implicit patches (representing collections of micro-environments that have a similar disturbance history). We define the equations that describe the energy, water, and carbon cycles in terms of total energy, water, and carbon, which simplifies the differential equations and guarantees excellent conservation of these quantities in long-term simulation (< 0.1 % error over 50 years). We also show examples of ED-2.2 simulation results at single sites and across tropical South America. These results demonstrate the model's ability to characterize the variability of ecosystem structure, composition, and functioning both at stand and continental scales. A detailed model evaluation was conducted and is presented in a companion paper (Longo et al., 2019a). Finally, we highlight some of the ongoing model developments designed to improve the model's accuracy and performance and to include processes hitherto not represented in the model.
Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models ...predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are already limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.
In temperate regions, the budburst date of deciduous trees is mainly regulated by temperature variation, but the exact nature of the temperature dependence has been a matter of debate. One hypothesis ...is that budburst date depends purely on the accumulation of warm temperature; a competing hypothesis states that exposure to cold temperatures is also important for budburst. In this study, variability in budburst is evaluated using 15 years of budburst data for 17 tree species at Harvard Forest. We compare two budburst hypotheses through reversible jump Markov chain Monte Carlo. We then investigate how uncertainties in budburst date mapped onto uncertainties in ecosystem carbon using the Geophysical Fluid Dynamics Laboratory's LM3 land model. For 15 of 17 species, we find that more complicated budburst models that account for a chilling period are favored over simpler models that do not include such dependence. LM3 simulations show that the choice of budburst model induces differences in the timing of carbon uptake commencement of ∼11 days, in the magnitude of April–May carbon uptake of ∼1.03 g C m−2 day−1, and in total ecosystem carbon stocks of ∼2 kg C m−2. While the choice of whether to include a chilling period in the budburst model strongly contributes to this variability, another important factor is how the species‐dependent field data gets mapped onto LM3's single deciduous plant functional type (PFT). We conclude budburst timing has a strong impact on simulated CO2 fluxes, and uncertainty in the fluxes can be substantially reduced by improving the model's representation of PFT diversity.
Key Points
Importance of phenology in terrestrial carbon cycle
Evaluations of budburst hypothesis
Implications of phenology for earth system model
A major uncertainty in the land carbon cycle is whether symbiotic nitrogen fixation acts to enhance the tropical forest carbon sink. Nitrogen-fixing trees can supply vital quantities of the ...growth-limiting nutrient nitrogen, but the extent to which the resulting carbon-nitrogen feedback safeguards ecosystem carbon sequestration remains unclear. We combine (i) field observations from 112 plots spanning 300 years of succession in Panamanian tropical forests, and (ii) a new model that resolves nitrogen and light competition at the scale of individual trees. Fixation doubled carbon accumulation in early succession and enhanced total carbon in mature forests by ~10% (~12MgC ha
) through two mechanisms: (i) a direct fixation effect on tree growth, and (ii) an indirect effect on the successional sequence of non-fixing trees. We estimate that including nitrogen-fixing trees in Neotropical reforestation projects could safeguard the sequestration of 6.7 Gt CO
over the next 20 years. Our results highlight the connection between functional diversity of plant communities and the critical ecosystem service of carbon sequestration for mitigating climate change.
This study investigates how future deforestation in the Amazon may alter precipitation statistics in South America using a variable-resolution GCM. The model's grid mesh is set up to cover South ...America and nearby oceans at mesoscale (25 km) resolution, and then to gradually coarsen and cover the rest of the world at 200-km resolution. Because of the computational efficiency of this approach, it was possible to carry out the first decadal-scale simulations of Amazon deforestation at mesoscale resolution. Unlike traditional mesoscale models, this approach does not require lateral boundary conditions. The results indicate that deforestation reduces simulated precipitation in the Amazon, but this reduction is much smaller than that seen in most previous GCM studies. Furthermore, a subcontinental redistribution of precipitation is found whereby the northwest Amazon becomes drier and the southeast Amazon becomes wetter. During most of the year, these changes are driven by changes in the mean intensity of precipitation events; however, in September–November, changes in precipitation frequency are also important. Large changes in June–August hydroclimate were also found, with extreme cold events becoming more common. These changes have consequences for agriculture, natural ecosystems, and surface hydrology.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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