Increasing impacts of extreme droughts on vegetation productivity under climate change

Terrestrial gross primary production (GPP) is the basis of vegetation growth and food production globally1 and plays a critical role in regulating atmospheric CO2 through its impact on ecosystem carbon balance. Even though higher CO2 concentrations in future decades can increase GPP2, low soil water availability, heat stress and disturbances associated with droughts could reduce the benefits of such CO2 fertilization. Here we analysed outputs of 13 Earth system models to show an increasingly stronger impact on GPP by extreme droughts than by mild and moderate droughts over the twenty-first century. Due to a dramatic increase in the frequency of extreme droughts, the magnitude of globally averaged reductions in GPP associated with extreme droughts was projected to be nearly tripled by the last quarter of this century (2075–2099) relative to that of the historical period (1850–1999) under both high and intermediate GHG emission scenarios. By contrast, the magnitude of GPP reductions associated with mild and moderate droughts was not projected to increase substantially. Our analysis indicates a high risk of extreme droughts to the global carbon cycle with atmospheric warming; however, this risk can be potentially mitigated by positive anomalies of GPP associated with favourable environmental conditions

Toward a Mechanistic Modeling of Nitrogen Limitation on Vegetation Dynamics

Nitrogen is a dominant regulator of vegetation dynamics, net primary production, and terrestrial carbon cycles; however, most ecosystem models use a rather simplistic relationship between leaf nitrogen content and photosynthetic capacity. Such an approach does not consider how patterns of nitrogen allocation may change with differences in light intensity, growing-season temperature and CO2 concentration. To account for this known variability in nitrogen-photosynthesis relationships, we develop a mechanistic nitrogen allocation model based on a trade-off of nitrogen allocated between growth and storage, and an optimization of nitrogen allocated among light capture, electron transport, carboxylation, and respiration. The developed model is able to predict the acclimation of photosynthetic capacity to changes in CO2 concentration, temperature, and radiation when evaluated against published data of Vc,max (maximum carboxylation rate) and Jmax (maximum electron transport rate). A sensitivity analysis of the model for herbaceous plants, deciduous and evergreen trees implies that elevated CO2 concentrations lead to lower allocation of nitrogen to carboxylation but higher allocation to storage. Higher growing-season temperatures cause lower allocation of nitrogen to carboxylation, due to higher nitrogen requirements for light capture pigments and for storage. Lower levels of radiation have a much stronger effect on allocation of nitrogen to carboxylation for herbaceous plants than for trees, resulting from higher nitrogen requirements for light capture for herbaceous plants. As far as we know, this is the first model of complete nitrogen allocation that simultaneously considers nitrogen allocation to light capture, electron transport, carboxylation, respiration and storage, and the responses of each to altered environmental conditions. We expect this model could potentially improve our confidence in simulations of carbon-nitrogen interactions and the vegetation feedbacks to climate in Earth system models

Modeling stomatal conductance in the earth system: linking leaf water-use efficiency and water transport along the soil–plant–atmosphere continuum

The Ball–Berry stomatal conductance model is commonly used in earth system models to simulate biotic regulation of evapotranspiration. However, the dependence of stomatal conductance (<i>g</i>_s) on vapor pressure deficit (<i>D</i>_s) and soil moisture must be empirically parameterized. We evaluated the Ball–Berry model used in the Community Land Model version 4.5 (CLM4.5) and an alternative stomatal conductance model that links leaf gas exchange, plant hydraulic constraints, and the soil–plant–atmosphere continuum (SPA). The SPA model simulates stomatal conductance numerically by (1) optimizing photosynthetic carbon gain per unit water loss while (2) constraining stomatal opening to prevent leaf water potential from dropping below a critical minimum. We evaluated two optimization algorithms: intrinsic water-use efficiency (&Delta;<i>A</i>_n /&Delta;<i>g</i>_s, the marginal carbon gain of stomatal opening) and water-use efficiency (&Delta;<i>A</i>_n /&Delta;<i>E</i>_l, the marginal carbon gain of transpiration water loss). We implemented the stomatal models in a multi-layer plant canopy model to resolve profiles of gas exchange, leaf water potential, and plant hydraulics within the canopy, and evaluated the simulations using leaf analyses, eddy covariance fluxes at six forest sites, and parameter sensitivity analyses. The primary differences among stomatal models relate to soil moisture stress and vapor pressure deficit responses. Without soil moisture stress, the performance of the SPA stomatal model was comparable to or slightly better than the CLM Ball–Berry model in flux tower simulations, but was significantly better than the CLM Ball–Berry model when there was soil moisture stress. Functional dependence of <i>g</i>_s on soil moisture emerged from water flow along the soil-to-leaf pathway rather than being imposed a priori, as in the CLM Ball–Berry model. Similar functional dependence of <i>g</i>_s on <i>D</i>_s emerged from the &Delta;<i>A</i>_n/&Delta;<i>E</i>_l optimization, but not the &Delta;<i>A</i>_n /<i>g</i>_s optimization. Two parameters (stomatal efficiency and root hydraulic conductivity) minimized errors with the SPA stomatal model. The critical stomatal efficiency for optimization (&iota;) gave results consistent with relationships between maximum <i>A</i>_n and <i>g</i>_s seen in leaf trait data sets and is related to the slope (<i>g</i>₁) of the Ball–Berry model. Root hydraulic conductivity (<i>R</i>_r^*) was consistent with estimates from literature surveys. The two central concepts embodied in the SPA stomatal model, that plants account for both water-use efficiency and for hydraulic safety in regulating stomatal conductance, imply a notion of optimal plant strategies and provide testable model hypotheses, rather than empirical descriptions of plant behavior

Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs

Integration of a Frost Mortality Scheme Into the Demographic Vegetation Model FATES

Frost is damaging to plants when air temperature drops below their tolerance threshold. The set of mechanisms used by cold-tolerant plants to withstand freezing is called “hardening” and typically take place in autumn to protect against winter damage. The recent incorporation of a hardening scheme in the demographic vegetation model FATES opens up the possibility to investigate frost mortality to vegetation. Previously, the hardening scheme was used to improve hydraulic processes in cold-tolerant plants. In this study, we expand upon the existing hardening scheme by implementing hardiness-dependent frost mortality into CLM5.0-FATES to study the impacts of frost on vegetation in temperate and boreal sites from 1950 to 2015. Our results show that the original freezing mortality approach of FATES, where each plant type had a fixed freezing tolerance threshold—an approach common to many other dynamic vegetation models, was restricted to predicting plant type distribution. The main results emerging from the new scheme are a high autumn and spring frost mortality, especially at colder sites, and increasing mid-winter frost mortality due to global warming, especially at warmer sites. We demonstrate that the new frost scheme is a major step forward in dynamically representing vegetation in ESMs by for the first time including a level of frost tolerance that is responding to the environment and includes some level of cost (implicitly) and benefit. By linking hardening and frost mortality in a land surface model, we open new ways to explore the impact of frost events in the context of global warming.publishedVersio

Increasing impacts of extreme droughts on vegetation productivity under climate change

Terrestrial gross primary production (GPP) is the basis of vegetation growth and food production globally1 and plays a critical role in regulating atmospheric CO2 through its impact on ecosystem carbon balance. Even though higher CO2 concentrations in future decades can increase GPP2, low soil water availability, heat stress and disturbances associated with droughts could reduce the benefits of such CO2 fertilization. Here we analysed outputs of 13 Earth system models to show an increasingly stronger impact on GPP by extreme droughts than by mild and moderate droughts over the twenty-first century. Due to a dramatic increase in the frequency of extreme droughts, the magnitude of globally averaged reductions in GPP associated with extreme droughts was projected to be nearly tripled by the last quarter of this century (2075–2099) relative to that of the historical period (1850–1999) under both high and intermediate GHG emission scenarios. By contrast, the magnitude of GPP reductions associated with mild and moderate droughts was not projected to increase substantially. Our analysis indicates a high risk of extreme droughts to the global carbon cycle with atmospheric warming; however, this risk can be potentially mitigated by positive anomalies of GPP associated with favourable environmental conditions

Are northern hemisphere boreal forest fires more sensitive to future aerosol mitigation than to greenhouse gas–driven warming?

Considerable interest exists in understanding how climate change affects wildfire activity. Here, we use the Community Earth System Model version 2 to show that future anthropogenic aerosol mitigation yields larger increases in fire activity in the Northern Hemisphere boreal forests, relative to a base simulation that lacks climate policy and has large increases in greenhouse gases. The enhanced fire response is related to a deeper layer of summertime soil drying, consistent with increased downwelling surface shortwave radiation and enhanced surface evapotranspiration. In contrast, soil column drying is muted under increasing greenhouse gases due to plant physiological responses to increased carbon dioxide and by enhanced melting of soil ice at a depth that increases soil liquid water. Although considerable uncertainty remains in the representation of fire processes in models, our results suggest that boreal forest fires may be more sensitive to future aerosol mitigation than to greenhouse gas–driven warming

Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA r7236) and evaluation at the Caxiuanã drought experiment

Extreme drought events in Amazon forests are expected to become more frequent and more intense with climate change, threatening ecosystem function and carbon balance. Yet large uncertainties exist on the resilience of this ecosystem to drought. A better quantification of tree hydraulics and mortality processes is needed to anticipate future drought effects on Amazon forests. Most state-of-the-art dynamic global vegetation models are relatively poor in their mechanistic description of these complex processes. Here, we implement a mechanistic plant hydraulic module within the ORCHIDEE-CAN-NHA r7236 land surface model to simulate the percentage loss of conductance (PLC) and changes in water storage among organs via a representation of the water potentials and vertical water flows along the continuum from soil to roots, stems and leaves. The model was evaluated against observed seasonal variability in stand-scale sap flow, soil moisture and productivity under both control and drought setups at the Caxiuanã throughfall exclusion field experiment in eastern Amazonia between 2001 and 2008. A relationship between PLC and tree mortality is built in the model from two empirical parameters, the cumulated duration of drought exposure that triggers mortality, and the mortality fraction in each day exceeding the exposure. Our model captures the large biomass drop in the year 2005 observed 4 years after throughfall reduction, and produces comparable annual tree mortality rates with observation over the study period. Our hydraulic architecture module provides promising avenues for future research in assimilating experimental data to parameterize mortality due to drought-induced xylem dysfunction. We also highlight that species-based (isohydric or anisohydric) hydraulic traits should be further tested to generalize the model performance in predicting the drought risks.</p