An improved method for searching plant functional types by numerical analysis

Abstract. The use of plant functional types (PFTs) to describe patterns and processes in plant communities has become essential to study and predict consequences of global change on vegetation and ecosystem processes. A PFT is a group of plants that, irrespective of phylogeny, are similar in a given set of traits and similar in their association to certain variables, which may be factors to which the plants are responding or effects of the plants in the ecosystem. To define PFTs relevant traits must be selected and an appropriate method must be used to classify plants into types. We critically review methods used for the analysis of PFT‐based data and describe a new recursive algorithm to numerically search for traits and find optimal PFTs. The algorithm uses three data matrices: describing populations by traits, communities by these populations and community sites by environmental factors or effects. It defines PFTs polythetically by cluster analysis, revealing plant types whose performance in communities is maximally associated to the specified environmental variables. We test the method with data from natural grassland communities of southern Brazil, which were experimentally subjected to combinations of grazing levels and N‐fertilizer. The new method is found to be better than similar analytical procedures previously described. Redundancy among traits is discussed and a procedure for comparing alternative solutions is presented based on the similarity in terms of PFT responses between different trait subsets. The concept of PFT response group is illustrated by example.     

用于全球变化研究的中国植物功能型划分

 植物功能型(Plant functional types, PFTs)作为沟通植物的结构和功能与生态系统属性的桥梁,随着全球变化与植被的关系研究的深入而受到广泛重视。植物功能型的划分依赖于研究的背景、尺度和要解决的问题。为了区域尺度全球变化研究的需要,该文提出了一个基于植物关键特征的植物功能型划分方法。该方法首先选择了6项植物特征,包括3项冠层特征：木本-草本、常绿-落叶和针叶-阔叶,以及3项生理特征：光合途径(C3 / C4)、植物的水分需求和热量需求,作为划分植物功能型的关键特征;然后,先根据植物冠层特征划分得到5个基本类型,再根据水分和热量条件进行详细划分,得到29种备选类型;需要时,再根据研究目的从这29种备选类型中选择所需类型。根据这个方法,在充分考虑了我国季风气候条件下特有的水热配置和高海拔环境对植物的形态和功能特征影响的基础上,从备选类型中选择了一套适合中国气候和植被特征的植物功能型体系。这套体系包括18类植物功能型,其中含7类‘树’功能型、6类‘灌木’功能型和5类‘草’功能型,另根据需要设置2类‘裸地’功能型。并且根据植物的生理生态特征和中国植被的地理分布确定了用于限制植物功能型分布的气候因子,这些气候因子包括绝对最低温度、最暖月平均温度、有效积温、年最热月平均温和最冷月平均温之差、湿润指数、年均降水量。应用表明,这套植物功能型可用于模拟我国植被在当前气候条件下的分布。该研究为发展适于我国的植被模型和区域气候模型、评估全球变化对我国植被的影响及植被变化对气候的反馈作用提供依据与参数。     

Differences in xylem and leaf hydraulic traits explain differences in drought tolerance among mature Amazon rainforest trees

Considerable uncertainty surrounds the impacts of anthropogenic climate change on the composition and structure of Amazon forests. Building upon results from two large‐scale ecosystem drought experiments in the eastern Brazilian Amazon that observed increases in mortality rates among some tree species but not others, in this study we investigate the physiological traits underpinning these differential demographic responses. Xylem pressure at 50% conductivity (xylem‐P₅₀), leaf turgor loss point (TLP), cellular osmotic potential (π_o), and cellular bulk modulus of elasticity (ε), all traits mechanistically linked to drought tolerance, were measured on upper canopy branches and leaves of mature trees from selected species growing at the two drought experiment sites. Each species was placed a priori into one of four plant functional type (PFT) categories: drought‐tolerant versus drought‐intolerant based on observed mortality rates, and subdivided into early‐ versus late‐successional based on wood density. We tested the hypotheses that the measured traits would be significantly different between the four PFTs and that they would be spatially conserved across the two experimental sites. Xylem‐P₅₀, TLP, and π_o, but not ε, occurred at significantly higher water potentials for the drought‐intolerant PFT compared to the drought‐tolerant PFT; however, there were no significant differences between the early‐ and late‐successional PFTs. These results suggest that these three traits are important for determining drought tolerance, and are largely independent of wood density—a trait commonly associated with successional status. Differences in these physiological traits that occurred between the drought‐tolerant and drought‐intolerant PFTs were conserved between the two research sites, even though they had different soil types and dry‐season lengths. This more detailed understanding of how xylem and leaf hydraulic traits vary between co‐occuring drought‐tolerant and drought‐intolerant tropical tree species promises to facilitate a much‐needed improvement in the representation of plant hydraulics within terrestrial ecosystem and biosphere models, which will enhance our ability to make robust predictions of how future changes in climate will affect tropical forests.     

Responses of plant functional types to an environmental gradient on the Northeast China Transect

The hypothesis that some plant traits such as life form are robust surrogates for plant functional type (PFT) has provoked an ongoing debate. Based on a dataset from the Northeast China Transect (NECT), we attempted to test the hypothesis by comparing an objective PFT identification framework in which large datasets of plant traits were considered with two subjective PFT frameworks in which only a few plant traits were involved. Additionally, we addressed the relations between the relative abundance of PFTs and the environmental gradient represented by actual evapotranspiration (AET) along the NECT. We also discuss the changes in ecosystem functioning associated with the PFT turnover along the environmental gradient. Based on an objective PFT classification, eight PFTs were identified: deciduous trees, shrubs, perennial forbs with lower net photosynthesis, perennial forbs with higher net photosynthesis, perennial bulb-grasses, perennial tiller-grasses, annual C₄ herbs and evergreen trees. Our results indicated that some plant traits, such as life form and photosynthesis pathway, are robust surrogates for PFTs, implying that subjective approaches to PFT classification are useful. Nonetheless, caution should be used during the classification of PFTs. The framework adopted for PFT classification should depend on the specific scientific issues being dealt with. It is therefore meaningless to pursue a general framework for the identification of PFTs even within given plant communities. On the other hand, our quantitative classification of PFTs confirmed recurrent patterns with respect to PFT turnover along an environmental gradient. Furthermore, with the turnover in PFT along the NECT from the west to the east, ecosystem properties such as productivity and carbon storage are predicted to decrease, while photosynthesis is predicted to increase, suggesting that PFT turnover would inevitably lead to changes in ecosystem functioning.     

黄土丘陵区植物叶片与细根功能性状关系及其变化

通过植物叶片功能性状(比叶面积、叶组织密度、叶氮含量)和细根功能性状(比根长、根组织密度、根氮含量)间的相互关系,分析植物对环境的适应途径;然后根据性状间的差异进行了层次聚类,将物种划分为3大功能型,并分析了不同功能型对环境的适应策略.结果表明:黄土丘陵区延河流域149种植物的叶氮含量与比叶面积和根氮含量正相关、与叶组织密度负相关,比根长与根组织密度负相关,除了根氮含量,其余根性状与叶性状不相关.此外,功能性状间关系变化和适应策略在不同功能型之间也存在差异.功能型1的植物具有最强的耐旱力和防御力;功能型3的植物具有最强的养分维持能力用以对抗营养贫瘠的环境;功能型2的植物居中,生长速率最高,具有较强的竞争力、分布最广;根据C-S-R理论,功能型1和3属于“胁迫忍耐型”策略(S策略),功能型2则属于“竞争型”(C)和“干扰型”(R)策略的综合.研究结果为黄土丘陵区植被恢复规划及物种配置等提供依据.     

Sensitivity of plant functional types to climate change: classification tree analysis of a simulation model

Question: The majority of studies investigating the impact of climate change on local plant communities ignores changes in regional processes, such as immigration from the regional seed pool. Here we explore: (i) the potential impact of climate change on composition of the regional seed pool, (ii) the influence of changes in climate and in the regional seed pool on local community structure, and (iii) the combinations of life history traits, i.e. plant functional types (PFTs), that are most affected by environmental changes. Location: Fire‐prone, Mediterranean‐type shrublands in southwestern Australia. Methods: Spatially explicit simulation experiments were conducted at the population level under different rainfall and fire regime scenarios to determine the effect of environmental change on the regional seed pool for 38 PFTs. The effects of environmental and seed immigration changes on local community dynamics were then derived from community‐level experiments. Classification tree analyses were used to investigate PFT‐specific vulnerabilities to climate change. Results: The classification tree analyses revealed that responses of PFTs to climate change are determined by specific trait characteristics. PFT‐specific seed production and community patterns responded in a complex manner to climate change. For example, an increase in annual rainfall caused an increase in numbers of dispersed seeds for some PFTs, but decreased PFT diversity in the community. Conversely, a simulated decrease in rainfall reduced the number of dispersed seeds and diversity of PFTs. Conclusions: PFT interactions and regional processes must be considered when assessing how local community structure will be affected by environmental change.     

Global trends in senesced-leaf nitrogen and phosphorus

Aim Senesced‐leaf litter plays an important role in the functioning of terrestrial ecosystems. While green‐leaf nutrients have been reported to be affected by climatic factors at the global scale, the global patterns of senesced‐leaf nutrients are not well understood. Location Global. Methods Here, bringing together a global dataset of senesced‐leaf N and P spanning 1253 observations and 638 plant species at 365 sites and of associated mean climatic indices, we describe the world‐wide trends in senesced‐leaf N and P and their stoichiometric ratios. Results Concentration of senesced‐leaf N was highest in tropical forests, intermediate in boreal, temperate, and mediterranean forests and grasslands, and lowest in tundra, whereas P concentration was highest in grasslands, lowest in tropical forests and intermediate in other ecosystems. Tropical forests had the highest N : P and C : P ratios in senesced leaves. When all data were pooled, N concentration significantly increased, but senesced‐leaf P concentration decreased with increasing mean annual temperature (MAT) and mean annual precipitation (MAP). The N : P and C : P ratios also increased with MAT and MAP, but C : N ratios decreased. Plant functional type (PFT), i.e. life‐form (grass, herb, shrub or tree), phylogeny (angiosperm versus gymnosperm) and leaf habit (deciduous versus evergreen), affected senesced‐leaf N, P, N : P, C : N and C : P with a ranking of senesced‐leaf N from high to low: forbs ≈ shrubs ≈ trees > grasses, while the ranking of P was forbs ≈ shrubs ≈ trees < grasses. The climatic trends of senesced‐leaf N and P and their stoichiometric ratios were similar between PFTs. Main conclusions Globally, senesced‐leaf N and P concentrations differed among ecosystem types, from tropical forest to tundra. Differences were significantly related to global climate variables such as MAT and MAP and also related to plant functional types. These results at the global scale suggest that nutrient feedback to soil through leaf senescence depends on both the climatic conditions and the plant composition of an ecosystem.     

A biome classification of China based on plant functional types and the BIOME3 model

A biome classification for China was established based on plant functional types (PFTs) using the BIOME3 model to include 16 biomes. In the eastern part of China, the PFTs of trees determine mostly the physiognomy of landscape. Biomes range from boreal deciduous coniferous forest/woodland, boreal mixed forest/woodland, temperate mixed forest, temperate broad-leaved deciduous forest, warm-temperate broad-leaved evergreen/mixed forest, warm-temperate/cool-temperate evergreen coniferous forest, xeric woodland/scrub, to tropical seasonal and rain forest, and tropical deciduous forest from north to south. In the northern and western part of China, grass is the dominant PFT. From northeast to west and southwest the biomes range from moist savannas, tall grassland, short grassland, dry savannas, arid shrubland/steppe, desert, to alpine tundra/ice/polar desert. Comparisons between the classification introduced here and the four classifications which were established over the past two decades, i.e. the vegetation classification, the vegetation division, the physical ecoregion, and the initial biome classification have showed that the different aims of biome classifications have resulted in different biome schemes each with its own unique characteristics and disadvantages for global change study. The new biome classification relies not only on climatic variables, but also on soil factor, vegetation functional variables, ecophysiological parameters and competition among the PFTs. It is a comprehensive classification that using multivariables better expresses the vegetation distribution and can be compared with world biome classifications. It can be easily used in the response study of Chinese biomes to global change, regionally and globally.     

BioMove – an integrated platform simulating the dynamic response of species to environmental change

BioMove simulates plant species' geographic range shifts in response to climate, habitat structure and disturbance, at annual time steps. This spatially explicit approach integrates species' bioclimatic suitability and population‐level demographic rates with simulation of landscape‐level processes (dispersal, disturbance, species' response to dynamic dominant vegetation structure). Species population dynamics are simulated through matrix modelling that includes scaling demographic rates by climatic suitability. Dispersal functions simulate population spread. User‐specified plant functional types (PFTs) provide vegetation structure that determines resource competition and disturbance. PFTs respond annually through dispersal, inter‐PFT competition and demographic shifts. BioMove provides a rich framework for dynamic range simulations.     

Dynamic global vegetation modelling for prediction of plant functional types and biogenic trace gas fluxes

1. A Dynamic Global Vegetation Model (DGVM) has been developed as a new feature of the NASA-CASA (Carnegie Ames Stanford Approach) ecosystem production and trace gas model. This DGVM includes seasonal phenology algorithms calibrated using historical interannual data sets derived from the Advanced Very High Resolution (AVHRR) satellite ‘greenness’ index. 2. The coupled CASA-DGVM design is based conceptually on two main elements of Tilman's resource-ratio hypothesis of vegetation change, namely: 1) plant competition for resources (water and light) over relatively short time periods of months and seasons; and 2) the long-term pattern in the supply of growth-limiting resources such as water and nutrients, i.e. the resource-supply trajectory. This simulation model generates global gridded estimates of primary production, above and below ground biomass, leaf area index (LAI), and trace gas fluxes from soil. 3. Eight distributed test locations for the DGVM were evaluated initially to represent a variety of climate conditions ranging from Arctic (64°N Alaska) to tropical and subtropical (24°S southern Africa) latitude zones. At all test locations, the predicted plant functional type (PFT) matched closely with the actual reported PFT. 4. In the process of running the model to steady state PFTs, most forest locations showed a rapid progression of transient states, from bare ground to grassland, to grasses with shrub cover, and finally to the forest PFT. From this first global application, the DGVM correctly predicts the presence of forest classes in approximately 75–95% of all cases worldwide, and grasslands in approximately 58% of all cases. 5. The effects of two hypothetical climate change scenarios were evaluated. Scenario I was set by warming air surface temperatures linearly to 4 °C above average over a 25-year simulation period. Scenario II was set by decreasing annual rainfall amounts linearly to 50% below average over a 25-year simulation period. 6. The warming scenario I resulted in PFT at high-latitude forest and boreal forest sites changing to mixed coniferous forest, accompanied by increase in canopy LAI. The drought scenario II resulted in PFT at the boreal forest and savanna sites changing to grasslands. At locations where PFT did not change with climate, however, soil water and canopy LAI were predicted to decline progressively under the warming scenario, beginning from steady-state temperate and tropical zone PFTs. They also declined under the drought scenario beginning from practically any steady state PFT.     

A global assessment of forest surface albedo and its relationships with climate and atmospheric nitrogen deposition

We present a global assessment of the relationships between the short‐wave surface albedo of forests, derived from the MODIS satellite instrument product at 0.5° spatial resolution, with simulated atmospheric nitrogen deposition rates (N_dep), and climatic variables (mean annual temperature T_m and total annual precipitation P), compiled at the same spatial resolution. The analysis was performed on the following five forest plant functional types (PFTs): evergreen needle‐leaf forests (ENF); evergreen broad‐leaf forests (EBF); deciduous needle‐leaf forests (DNF); deciduous broad‐leaf forests (DBF); and mixed‐forests (MF). Generalized additive models (GAMs) were applied in the exploratory analysis to assess the functional nature of short‐wave surface albedo relations to environmental variables. The analysis showed evident correlations of albedo with environmental predictors when data were pooled across PFTs: T_m and N_dep displayed a positive relationship with forest albedo, while a negative relationship was detected with P. These correlations are primarily due to surface albedo differences between conifer and broad‐leaf species, and different species geographical distributions. However, the analysis performed within individual PFTs, strengthened by attempts to select ‘pure’ pixels in terms of species composition, showed significant correlations with annual precipitation and nitrogen deposition, pointing toward the potential effect of environmental variables on forest surface albedo at the ecosystem level. Overall, our global assessment emphasizes the importance of elucidating the ecological mechanisms that link environmental conditions and forest canopy properties for an improved parameterization of surface albedo in climate models.     

Functional traits as indicators of fodder provision over a short time scale in species-rich grasslands

Background and Aims: Fodder provision in species-rich grasslands, i.e. herbage growth,proportion of leaf, and leaf and stem digestibility, is difficultto predict for short periods of time, such as between two defoliationsor less. The value of two methods based on plant traits forevaluating these agronomic properties was examined. Methods: One method is based on plant trait measurements on the plantcommunity (leaf dry matter content, plant height, floweringdate); the other is on vegetation composition expressed as plantfunctional types (acquisitive versus conservative PFTs) establishedby measuring leaf dry matter content on pure grass stands. Theexperiment consisted of 18 fields with three different defoliationregimes (combinations of cutting and grazing) and two levelsof fertilization. To establish a growth curve over the firstgrowth cycle, herbage was sampled about 10 times in spring. Key Results: Coefficients of correlation between agronomic properties ofthe vegetation and its functional composition were higher whenthe latter was assessed through PFT and an indicator of theplant nutrient status (Ni) instead of measured plant traits.The date at which the ceiling yield occurred for the standingherbage mass or only the leaf component, which varied by upto 500 degree-days between treatments, and the leaf proportion,depended entirely on the PFT, and largely so for the leaf digestibility.The standing herbage mass at the time of ceiling yield dependedonly on Ni, or mainly so in the case of the daily herbage growthrate. Similar plant digestibility between plant communitieswas found at flowering time, although there were big differencesin PFT composition. The shape of the growth curve was flatterwhen there was great functional diversity in the plant community. Conclusions: The PFT composition and the Ni were more reliable than the plantfunctional traits measured in the field for evaluating herbagegrowth pattern and digestibility in spring.     

Regeneration of different plant functional types in a Masson pine forest following pine wilt disease

Pine wilt disease is a severe threat to the native pine forests in East Asia. Understanding the natural regeneration of the forests disturbed by pine wilt disease is thus critical for the conservation of biodiversity in this realm. We studied the dynamics of composition and structure within different plant functional types (PFTs) in Masson pine forests affected by pine wilt disease (PWD). Based on plant traits, all species were assigned to four PFTs: evergreen woody species (PFT1), deciduous woody species (PFT2), herbs (PFT3), and ferns (PFT4). We analyzed the changes in these PFTs during the initial disturbance period and during post-disturbance regeneration. The species richness, abundance and basal area, as well as life-stage structure of the PFTs changed differently after pine wilt disease. The direction of plant community regeneration depended on the differential response of the PFTs. PFT1, which has a higher tolerance to disturbances, became dominant during the post-disturbance regeneration, and a young evergreen-broad-leaved forest developed quickly after PWD. Results also indicated that the impacts of PWD were dampened by the feedbacks between PFTs and the microclimate, in which PFT4 played an important ecological role. In conclusion, we propose management at the functional type level instead of at the population level as a promising approach in ecological restoration and biodiversity conservation.     

Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model

Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual‐ and trait‐based version of the DGVM LPJmL (Lund‐Potsdam‐Jena managed Land) called LPJmL‐ flexible individual traits (LPJmL‐FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL‐FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N_area), the maximum carboxylation rate of Rubisco per leaf area (), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade‐offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade‐offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species‐rich center of the region with relatively low climatic variability. LPJmL‐FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects.     

Divergence of functional traits at early stages of development in Stipa tenacissima populations distributed along an environmental gradient of the Mediterranean

Assessing differences in plant functional traits (PFTs) along climatic gradients is potentially useful for understanding variation within and across populations, and for predicting their responses to climate change. This study investigates the intraspecific variability of several PFTs in Stipa tenacissima (Alpha grass) seedlings from different populations distributed across a climatic gradient. Seven populations from Tunisia to Spain within a 100–600 mm/year rainfall range were selected. Seedlings from each population were grown in a common garden. We expected the functional characteristics to differ among seedling populations according to their climatic gradient. The response patterns were helpful to predict acclimation and fitness under future climatic conditions in these populations. The seedling development analysis showed differences in PFTs among S. tenacissima populations. The biomass traits analysis revealed that higher above-ground biomass was related to higher below-ground development. The leaf traits proved that seedlings with longer leaf length would have less sclerophyllous leaves, a trade-off between productivity and drought resistance. The root traits analysis reflects seedling strategies to maximize resource uptake efficiency. PFTs showed several significant relationships with climatic conditions. The less rainfall, the higher plant allocation to root systems exploring soil. Higher mean temperatures were related to reduced root/plant development. The PFT analysis proves that species followed the ‘optimal partitioning theory’, in that plants preferentially allocate biomass to acquire the resource that most limits their development. However, both the environmental conditions and genetic diversity in S. tenacissima populations influenced seedling growth and behaviour to face ongoing climate change.

     

Elevational trends of biodiversity and plant traits do not converge—a test in the Helan Range, NW China

When elevational gradients include combinations of different climatic gradients, such as a decline in temperature combined with an increase in moisture, vegetation and plant trait responses are difficult to explain. Here, we used plant species richness and morphometric traits data across steep elevational gradients in the Helan Range of Northwestern China in an attempt to separate general trends (temperature related) from regional peculiarity (moisture related). Based on the floristic data of the Helan Range as well as plot-based data, both drought (at low elevation) and low temperature (high elevation) are associated with low species richness presumably also explaining the peak in diversity at mid-elevation, where climatic conditions are moderate. However, this mid-elevation peak in diversity is not mirrored in trends of plant traits such as leaf size and inflorescence size, which show either unidirectional trends or no change with elevation (with impacts of drought and low temperature perhaps gradually replacing each other). Our analysis illustrated the taxonomic and plant functional type (PFT)-related biases in functional trait studies and showed that consistent patterns only emerge after careful data stratification, with taxonomy (family level) holding more promises than PFTs. Inflorescence size increased with elevation in major insect-pollinated families, a trend not seen in wind-pollinated (graminoid) families. However, the reproductive effort expressed as inflorescence/leaf length ratio increases with elevation in the majority of plant families, irrespective of their pollination system. The fact that these biometric responses to elevation do not correlate with responses in species richness (which peaks at mid-elevation) may reflect contrasting drivers of trait selection and biodiversity. Based on our plot-based data, this analysis also confirmed the usefulness of floristic archive data for testing ecological theory related to elevational gradients.     

Inclusion of ecologically based trait variation in plant functional types reduces the projected land carbon sink in an earth system model

Earth system models demonstrate large uncertainty in projected changes in terrestrial carbon budgets. The lack of inclusion of adaptive responses of vegetation communities to the environment has been suggested to hamper the ability of modeled vegetation to adequately respond to environmental change. In this study, variation in functional responses of vegetation has been added to an earth system model (ESM) based on ecological principles. The restriction of viable mean trait values of vegetation communities by the environment, called ‘habitat filtering’, is an important ecological assembly rule and allows for determination of global scale trait–environment relationships. These relationships were applied to model trait variation for different plant functional types (PFTs). For three leaf traits (specific leaf area, maximum carboxylation rate at 25 °C, and maximum electron transport rate at 25 °C), relationships with multiple environmental drivers, such as precipitation, temperature, radiation, and CO₂, were determined for the PFTs within the Max Planck Institute ESM. With these relationships, spatiotemporal variation in these formerly fixed traits in PFTs was modeled in global change projections (IPCC RCP8.5 scenario). Inclusion of this environment‐driven trait variation resulted in a strong reduction of the global carbon sink by at least 33% (2.1 Pg C yr^?1) from the 2nd quarter of the 21st century onward compared to the default model with fixed traits. In addition, the mid‐ and high latitudes became a stronger carbon sink and the tropics a stronger carbon source, caused by trait‐induced differences in productivity and relative respirational costs. These results point toward a reduction of the global carbon sink when including a more realistic representation of functional vegetation responses, implying more carbon will stay airborne, which could fuel further climate change.     

A biogeochemistry‐based dynamic vegetation model and its application along a moisture gradient in the continental United States

Abstract. We develop and evaluate a large‐scale dynamic vegetation model, TEM‐LPJ, which considers interactions among water, light and nitrogen in simulating ecosystem function and structure. We parameterized the model for three plant functional types (PFTs): a temperate deciduous forest, a temperate coniferous forest, and a temperate C₃ grassland. Model parameters were determined using data from forest stands at the Harvard Forest in Massachusetts. Applications of the model reasonably simulated stand development over 120 yr for Populus tremuloides in Wisconsin and for Pinus elliottii in Florida. Our evaluation of tree‐grass interactions simulated by the model indicated that competition for light led to dominance by the deciduous forest PFT in moist regions of eastern United States and that water competition led to dominance by the grass PFT in dry regions of the central United States. Along a moisture transect at 41.5° N in the eastern United States, simulations by TEM‐LPJ reproduced the composition of potential temperate deciduous forest, temperate savanna, and C3 grassland located along the transect.     

Differentiating drought legacy effects on vegetation growth over the temperate Northern Hemisphere

In view of future changes in climate, it is important to better understand how different plant functional groups (PFGs) respond to warmer and drier conditions, particularly in temperate regions where an increase in both the frequency and severity of drought is expected. The patterns and mechanisms of immediate and delayed impacts of extreme drought on vegetation growth remain poorly quantified. Using satellite measurements of vegetation greenness, in‐situ tree‐ring records, eddy‐covariance CO₂ and water flux measurements, and meta‐analyses of source water of plant use among PFGs, we show that drought legacy effects on vegetation growth differ markedly between forests, shrubs and grass across diverse bioclimatic conditions over the temperate Northern Hemisphere. Deep?rooted forests exhibit a drought legacy response with reduced growth during up to 4 years after an extreme drought, whereas shrubs and grass have drought legacy effects of approximately 2 years and 1 year, respectively. Statistical analyses partly attribute the differences in drought legacy effects among PFGs to plant eco‐hydrological properties (related to traits), including plant water use and hydraulic responses. These results can be used to improve the representation of drought response of different PFGs in land surface models, and assess their biogeochemical and biophysical feedbacks in response to a warmer and drier climate.