Search

Lianas (woody climbers) are crucial components of tropical forests and they have been increasingly recognized to have profound effects on tropical forest carbon dynamics. Despite their importance, lianas' representation in vegetation models remains limited, partly due to the complexity of liana-tree dynamics and the diversity in liana life history strategies. This paper provides a comprehensive review of advances and challenges for mechanistically representing lianas in forest ecosystem models and a proposed path towards effectively representing lianas in these models. Defining a liana plant functional type is a significant challenge because of the high morphological and physiological diversity amongst liana species, and because of their structural association with trees. Here, we identify critical liana traits that likely should contribute to establishing a liana plant functional type, along with key processes to properly represent lianas in ecosystem models. Subsequently, we discuss a variety of possible liana implementation strategies with their associated strengths, limitations, computational costs and data requirements. A fundamental redesign of the tree-centric demographic vegetation models seems appropriate to accommodate the unique growth and competition strategies of lianas. We illustrate the potential of such models with a single-site case study where we disentangle putative mechanisms of liana increasing abundance. Furthermore, we underscore the critical need for comprehensive liana demographic and functional data (including long-term, physiological, and pantropical observations) for the qualitative implementation and evaluation in the proposed modeling efforts. Currently, there is a scarcity of liana data and the data that do exist have a neotropical bias. We finally introduce a new liana functional trait database that can centralize existing liana trait data, incentivize improved data gathering and thus facilitate model development and scientific analyses.

Wood density (WD) is an important quality and functional trait of wood. However, despite the relationships between WD and abiotic factors being important to model or predict spatial distributions of functional traits, as well as responses of vegetation to climate changes, in current Earth system models or dynamic global vegetation models (ESMs/DGVMs), WD is often oversimplified, being defined as a globally uniform constant either for all plant functional types (PFTs) or for each individual PFT. Such oversimplifications may lead to simulation biases in the morphology of woody PFTs, as well as ecosystem transition and vegetation–atmosphere interactions. Moreover, existing conclusions about the relationships between WD and abiotic factors drawn from field observations remain mixed, making model parameterization improvements difficult. This study systematically investigated the influences of climate and soil factors on WD across various PFTs. Optimal fitting models for predicting WD within each PFT were then constructed by utilizing our collated global database of 138 604 observations. For WDs of tree PFTs, climate emerges as a more influential factor than soil characteristics, whereas for shrub PFTs the effects of climate and soil are of equivalent significance. Across all six PFTs, correlation coefficients between predictions by fitting models and observed WD range from 0.49 to 0.93. The predicted and observed WD exhibit good agreement across climate space. It is expected that the incorporation of our research findings into DGVMs will improve the simulation of tree height and forest fractional coverage, particularly in the central forest areas and forest transition zones. [ABSTRACT FROM AUTHOR]

A well-constructed tsunami evacuation facility can be crucial in a disaster. Understanding a tsunami's force and the flow structure variation across various building configurations are essential to engineering designs. Hence, this study assessed the steady-state flow structure at building models (BM) incorporating outer frame openings, including piloti-type designs with a different width-to-spacing ratio of piloti-type columns following an embankment model (EM) with a vegetation model (VM). The experiments also demonstrated the outer frame opening percentage's impact and orientation toward the overtopping tsunami flow at the BM. The results show that the arrangement of an opening on the outer frame and the piloti-type columns are critical in reducing the tsunami force concerning the experimental setup. Moreover, allowing a free surface flow beneath the BM implies that the correct piloti-pillar arrangement is crucial for resilient structure design. In addition, the three-dimensional numerical simulation was utilized to explain the turbulence intensity of the overtopping flow around the critical BM type. The derived resistance coefficient ( C R ) defined the drag and the hydrostatic characteristics at the BM due to the overtopping tsunami flow. Furthermore, for the impervious BM, the value C R was consistent with the previous studies, while the C R value for the BMs with an outer frame opening was directly coincident with the percentage of porosity. [ABSTRACT FROM AUTHOR]

The rapid acceleration of urbanization has a serious impact on the urban ecological environment. It is of great importance to carry out numerical simulation research on urban spatial thermal environment for improving urban ecological environment. At present, there are few studies on the influence and accuracy evaluation of different vegetation settings in computational fluid dynamics (CFD) on the simulation results. Aiming to quantify impacts of vegetation changes and vegetation model settings on the numerical simulation of urban three-dimensional thermal environment, this study 1) based on Gaofen-2 remote sensing data and CFD model, the wind and heat environment at the block scale was simulated and analysed; 2) The vegetation model is assumed to be three models including cold source, constant temperature wall, and porous medium. Based on the heat transfer and cooling mechanism of vegetation, these three different vegetation models and their related CFD parameter settings are used to simulate the 3D spatial thermal environment. The research results show that the distribution of temperature has a great correlation with the direction of wind. The temperature distribution at different heights at night did not show significant differences. Due to the obvious convective heat transfer between the building surface and the atmosphere, the temperature in the upwind direction is significantly lower than that in the downwind direction. At a height of 2 m and below, setting the vegetation as the wall model has the best performance, and at a height above 5 m, the results of the wind and heat environment of the three setting methods are basically similar. The wind environment results of the same vegetation setting are different at different heights. [ABSTRACT FROM AUTHOR]

The tree height–diameter at breast height (H–DBH) and crown radius–DBH (CR–DBH) relationships are key for forest carbon/biomass estimation, parameterization in vegetation models and vegetation–atmosphere interactions. Although the H–DBH relationship has been widely investigated on site or regional scales, and a few of studies have involved CR–DBH relationships based on plot-level data, few studies have quantitatively verified the universality of these two relationships on a global scale. This study evaluated the ability of 29 functions to fit the H–DBH and CR–DBH relationships for six different plant functional types (PFTs) on a global scale, based on a global plant trait database. Results showed that most functions were able to capture the H–DBH relationship for tropical PFTs and boreal needleleaf trees relatively accurately, but slightly less for temperate PFTs and boreal broadleaf trees (BB). For boreal PFTs, the S-shaped Logistic function fitted the H–DBH relationship best, while for temperate PFTs the Chapman–Richards function performed well. For tropical needleleaf trees, the fractional function of DBH satisfactorily captured the H–DBH relationship, while for tropical broadleaf trees, the Weibull function and a composite function of fractions were the best choices. For CR–DBH, the fitting capabilities of all the functions were comparable for all PFTs except BB. The Logistic function performed best for two boreal PFTs and temperate broadleaf trees, but for temperate needleleaf trees and two tropical PFTs, some exponential functions demonstrated higher skill. This work provides valuable information for parameterization improvements in vegetation models and forest field investigations. [ABSTRACT FROM AUTHOR]

A well-constructed tsunami evacuation facility can be crucial in a disaster. Understanding a tsunami’s force and the flow structure variation across various building configurations are essential to engineering designs. Hence, this study assessed the steady-state flow structure at building models (BM) incorporating outer frame openings, including piloti-type designs with a different width-to-spacing ratio of piloti-type columns following an embankment model (EM) with a vegetation model (VM). The experiments also demonstrated the outer frame opening percentage’s impact and orientation toward the overtopping tsunami flow at the BM. The results show that the arrangement of an opening on the outer frame and the piloti-type columns are critical in reducing the tsunami force concerning the experimental setup. Moreover, allowing a free surface flow beneath the BM implies that the correct piloti-pillar arrangement is crucial for resilient structure design. In addition, the three-dimensional numerical simulation was utilized to explain the turbulence intensity of the overtopping flow around the critical BM type. The derived resistance coefficient (CR) defined the drag and the hydrostatic characteristics at the BM due to the overtopping tsunami flow. Furthermore, for the impervious BM, the value CR was consistent with the previous studies, while the CR value for the BMs with an outer frame opening was directly coincident with the percentage of porosity.

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901-2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

Drought-induced tree mortality is projected to increase due to climate change, which will have manifold ecological and societal impacts including the potential to weaken or reverse the terrestrial carbon sink. Predictions of tree mortality remain limited, in large part because within-species variations in ecophysiology due to plasticity or adaptation and ecosystem adjustments could buffer mortality in dry locations. Here, we conduct a meta-analysis of 50 studies spanning >100 woody plant species globally to quantify how populations within species vary in vulnerability to drought mortality and whether functional traits or climate mediate mortality patterns. We find that mortality predominantly occurs in drier populations and this pattern is more pronounced in species with xylem that can tolerate highly negative water potentials, typically considered to be an adaptive trait for dry regions, and species that experience higher variability in water stress. Our results indicate that climate stress has exceeded physiological and ecosystem-level tolerance or compensating mechanisms by triggering extensive mortality at dry range edges and provides a foundation for future mortality projections in empirical distribution and mechanistic vegetation models.

Forest leaf area has enormous leverage on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Despite widespread evidence that trees are capable of adjusting to changes in environment across both space and time through modifying carbon allocation to leaves, many vegetation models use fixed carbon allocation schemes independent of environment, which introduces large uncertainties into predictions of future forest responses to atmospheric CO2 fertilization and anthropogenic climate change. Here, we develop an optimization-based model, whereby tree carbon allocation to leaves is an emergent property of environment and plant hydraulic traits. Using a combination of meta-analysis, observational datasets, and model predictions, we find strong evidence that optimal hydraulic-carbon coupling explains observed patterns in leaf allocation across large environmental and CO2 concentration gradients. Furthermore, testing the sensitivity of leaf allocation strategy to a diversity in hydraulic and economic spectrum physiological traits, we show that plant hydraulic traits in particular have an enormous impact on the global change response of forest leaf area. Our results provide a rigorous theoretical underpinning for improving carbon cycle predictions through advancing model predictions of leaf area, and underscore that tree-level carbon allocation to leaves should be derived from first principles using mechanistic plant hydraulic processes in the next generation of vegetation models.

The fluxes of energy, water, and carbon from terrestrial ecosystems influence the atmosphere. Land-atmosphere feedbacks can intensify extreme climate events like severe droughts and heatwaves because low soil moisture decreases both evaporation and plant transpiration and increases local temperature. Here, we combine data from a network of temperate and boreal eddy covariance towers, satellite data, plant trait datasets, and a mechanistic vegetation model to diagnose the controls of soil moisture feedbacks to drought. We find that climate and plant functional traits, particularly those related to maximum leaf gas exchange rate and water transport through the plant hydraulic continuum, jointly affect drought intensification. Our results reveal that plant physiological traits directly affect drought intensification and indicate that inclusion of plant hydraulic transport mechanisms in models may be critical for accurately simulating land-atmosphere feedbacks and climate extremes under climate change.

Climate change will alter the site conditions for European vegetation. This is likely to shift the potential distribution of species and habitats outside its current boundaries. To enable future projections on shifts in vegetation potentials, we fitted a multiclass model to the current potential natural vegetation (PNV) of Europe using climatic predictors. The model was then applied to climate data of the time slice 2061–2080 with the Representative Concentration Pathways (RCPs) 4.5 and RCP 8.5. With an accuracy of 0.78, simulations well represented the site-equivalent vegetation types of the current PNV across Europe. Projections show drastic shifts in vegetation potentials in all parts of Europe. Boreal forests could lose up to 75% of their current potential, while Mediterranean Quercus forests and steppes would double their potential area. Deserts are projected to be on the rice, and the potential of currently widespread vegetation such as Fagus forests would be translocated. These estimated alterations of European vegetation potentials could have great effects on the stability of current forests, affecting nature conservation strategies and forest management. [ABSTRACT FROM AUTHOR]

We introduce a new method to compute plant distribution in Ethiopia under paleoclimatic conditions using fuzzy logic. Using a published map of the potential vegetation for Ethiopia we decipher the boundary conditions for the main vegetation units shown, reflecting modern climatic conditions for temperature and precipitation in this region. Fuzzy logic using these climatic values on a GIS platform then derived the computational map of the potential vegetation. Comparing it with the original map shows a general correspondence of about 90%. By changing the underlying climate parameters, we then used this model for hypothetical paleoclimatic conditions to simulate the vegetational response on these changed climate settings. Finally, vegetational response maps for Ethiopia are presented for two scenarios: (i) a colder and drier condition (such as the Last Glacial Maximum) and (ii) a warmer and wetter condition (such as the last interglacial) than today.

The mechanisms governing tree drought mortality and recovery remain a subject of inquiry and active debate given their role in the terrestrial carbon cycle and their concomitant impact on climate change. Counter-intuitively, many trees do not die during the drought itself. Indeed, observations globally have documented that trees often grow for several years after drought before mortality. A combination of meta-analysis and tree physiological models demonstrate that optimal carbon allocation after drought explains observed patterns of delayed tree mortality and provides a predictive recovery framework. Specifically, post-drought, trees attempt to repair water transport tissue and achieve positive carbon balance through regrowing drought-damaged xylem. Furthermore, the number of years of xylem regrowth required to recover function increases with tree size, explaining why drought mortality increases with size. These results indicate that tree resilience to drought-kill may increase in the future, provided that CO2 fertilisation facilitates more rapid xylem regrowth.

Vegetation patterns with a variety of structures is amazing phenomena in arid or semi-arid areas, which can identify the evolution law of vegetation and are typical signals of ecosystem functions. Many achievements have been made in this respect, yet the mechanisms of uptake–diffusion feedback on the pattern structures of vegetation is not fully understood. To well reveal the influences of parameters perturbation on the pattern formation of vegetation, we give a comprehensive analysis on a vegetation–water model in the forms of reaction–diffusion equation which is posed by Zelnik et al. (Proc Natl Acad Sci 112:12,327–12,331, 2015). We obtain the exact parameters range for stationary patterns and show the dynamical behaviors near the bifurcation point based on nonlinear analysis. It is found that the model has the properties of spot, labyrinth and gap patterns. Moreover, water diffusion rate prohibits the growth of vegetation while shading parameter promotes the increase of vegetation biomass. Our results show that gradual transitions from uniform state to gap pattern can occur for suitable value of parameters which may induce the emergence of desertification. [ABSTRACT FROM AUTHOR]

Lianas (woody climbers) are crucial components of tropical forests and they have been increasingly recognized to have profound effects on tropical forest carbon dynamics. Despite their importance, lianas' representation in vegetation models remains limited, partly due to the complexity of liana-tree dynamics and the diversity in liana life history strategies. This paper provides a comprehensive review of advances and challenges for mechanistically representing lianas in forest ecosystem models and a proposed path towards effectively representing lianas in these models. Defining a liana plant functional type is a significant challenge because of the high morphological and physiological diversity amongst liana species, and because of their structural association with trees. Here, we identify critical liana traits that likely should contribute to establishing a liana plant functional type, along with key processes to properly represent lianas in ecosystem models. Subsequently, we discuss a variety of possible liana implementation strategies with their associated strengths, limitations, computational costs and data requirements. A fundamental redesign of the tree-centric demographic vegetation models seems appropriate to accommodate the unique growth and competition strategies of lianas. We illustrate the potential of such models with a single-site case study where we disentangle putative mechanisms of liana increasing abundance. Furthermore, we underscore the critical need for comprehensive liana demographic and functional data (including long-term, physiological, and pantropical observations) for the qualitative implementation and evaluation in the proposed modeling efforts. Currently, there is a scarcity of liana data and the data that do exist have a neotropical bias. We finally introduce a new liana functional trait database that can centralize existing liana trait data, incentivize improved data gathering and thus facilitate model development and scientific analyses., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

• Coupled modeling of porous medium and solar radiation for vegetation transpiration • The impacts of environmental factors on vegetation transpiration are quantified • Adjustment distance of Momentum to fully-developed region is less than Energy/Mass Vegetation cooling effects can effectively improve the outdoor microclimate. To explore the potential of vegetation transpiration cooling, we validated the feasibility of a new coupled porous medium and solar radiation model to simulate the interactions between vegetation transpiration and other physical processes in CFD. To emphasize the spatial extent of vegetation's influence, we compared and quantified the flow-adjustment distances(L FA) for wind speed, the temperature difference between simulated temperature and background temperature(ΔT (°C)), and water vapor mass fraction(ΔM w (g/kg)) between shrub(100m) and tree(200m) canopies: 1)For both vegetations, the L FA required for ΔT and ΔM w exceeds that of wind speed achieve fully-developed, indicating the momentum adjustment occurs more rapidly than energy and mass transport processes. 2)Vegetation drag effect depends on both leaf area density and vegetation canopy's height and width.3)Vegetation exhibits a significantly higher transpiration cooling effect under ambient relative humidity(RH) = 0% than RH =60%(the mean value of ΔT, ΔT fd), for the tree(z =1.5m): ΔT fd is -5.4°C (-1.4∼-1.5°C) at RH =0%/60%. 4)At RH =60%, both shrubs and trees exhibit a notable warming phenomenon near the vegetation canopies tops(ΔT Max =1.3°C/0.9°C for shrubs/trees). This study provides and confirms a reliable numerical method for simulating the interactions of vegetation transpiration and other physical processes in urban or rural areas. [Display omitted] [ABSTRACT FROM AUTHOR]

Summary: Forests are a critical carbon sink and widespread tree mortality resulting from climate‐induced drought stress has the potential to alter forests from a carbon sink to a source, causing a positive feedback on climate change. Process‐based vegetation models aim to represent the current understanding of the underlying mechanisms governing plant physiological and ecological responses to climate. Yet model accuracy varies across scales, and regional‐scale model predictive skill is frequently poor when compared with observations of drought‐driven mortality. I propose a framework that leverages differences in model predictive skill across spatial scales, mismatches between model predictions and observations, and differences in the mechanisms included and absent across models to advance the understanding of the physiological and ecological processes driving observed patterns drought‐driven mortality. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China Agricultural University is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Carbon use efficiency (CUE) represents how efficient a plant is at translating carbon gains through gross primary productivity (GPP) into net primary productivity (NPP) after respiratory costs (Ra). CUE varies across space with climate and species composition, but how CUE will respond to climate change is largely unknown due to uncertainty in Ra at novel high temperatures. We use a plant physiological model validated against global CUE observations and LIDAR vegetation canopy height data and find that model‐predicted decreases in CUE are diagnostic of transitions from forests to shrubland at dry range edges. Under future climate scenarios, we show mean growing season CUE increases in core forested areas, but forest extent decreases at dry range edges, with substantial uncertainty in absolute CUE due to uncertainty in Ra. Our results highlight that future forest resilience is nuanced and controlled by multiple competing mechanisms. [ABSTRACT FROM AUTHOR]

We introduce a new method to compute plant distribution in Ethiopia under paleoclimatic conditions using fuzzy logic. Using a published map of the potential vegetation for Ethiopia we decipher the boundary conditions for the main vegetation units shown, reflecting modern climatic conditions for temperature and precipitation in this region. Fuzzy logic using these climatic values on a GIS platform then derived the computational map of the potential vegetation. Comparing it with the original map shows a general correspondence of about 90%. By changing the underlying climate parameters, we then used this model for hypothetical paleoclimatic conditions to simulate the vegetational response on these changed climate settings. Finally, vegetational response maps for Ethiopia are presented for two scenarios: (i) a colder and drier condition (such as the Last Glacial Maximum) and (ii) a warmer and wetter condition (such as the last interglacial) than today. [ABSTRACT FROM AUTHOR]

The effect of nutrient availability on plant growth and the terrestrial carbon sink under climate change and elevated CO2 remains one of the main uncertainties of the terrestrial carbon cycle. This is partially due to the difficulty of assessing nutrient limitation at large scales over long periods of time. Consistent declines in leaf nitrogen (N) content and leaf δ15N have been used to suggest that nitrogen limitation has increased in recent decades, most likely due to the concurrent increase in atmospheric CO2. However, such data sets are often not straightforward to interpret due to the complex factors that contribute to the spatial and temporal variation in leaf N and isotope concentration. We use the land surface model (LSM) QUINCY, which has the unique capacity to represent N isotopic processes, in conjunction with two large data sets of foliar N and N isotope content. We run the model with different scenarios to test whether foliar δ15N isotopic data can be used to infer large‐scale N limitation and if the observed trends are caused by increasing atmospheric CO2, changes in climate or changes in sources and magnitude of anthropogenic N deposition. We show that while the model can capture the observed change in leaf N content and predict widespread increases in N limitation, it does not capture the pronounced, but very spatially heterogeneous, decrease in foliar δ15N observed in the data across the globe. The addition of an observation‐based temporal trend in isotopic composition of N deposition leads to a more pronounced decrease in simulated leaf δ15N. Our results show that leaf δ15N observations cannot, on their own, be used to assess global‐scale N limitation and that using such a data set in conjunction with an LSM can reveal the drivers behind the observed patterns. [ABSTRACT FROM AUTHOR]

Abstract Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ‐GUESS, ORCHIDEE, SiB‐3, and SiB‐CASA. All models were wrapped in a software framework driven with common forcing data, spin‐up, and run protocols specified by the Multi‐scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901–2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open‐source, cloud‐based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

The boreal biome plays an important role in the global carbon cycle. However, current estimates of its sink‐source strength and responses to changes in climate are primarily derived from models and thus remain uncertain. A major challenge is the validation of these models at a regional scale since empirical flux estimates are typically confined to ecosystem or continental scales. The Integrated Carbon Observation System (ICOS)‐Svartberget atmospheric station (SVB) provides observations including tall tower eddy covariance (EC) and atmospheric concentration measurements that can contribute to such validation in Northern Sweden. Thus, the overall aim of this study was to quantify the carbon balance in Northern Sweden region by integrating land‐atmosphere fluxes and atmospheric carbon dioxide (CO2) concentrations. There were three specific objectives. First, to compare flux estimates from four models (VPRM, LPJ‐GUESS, ORCHIDEE, and SiBCASA) to tall tower EC measurements at SVB during the years 2016–2018. Second to assess the fluxes' impact on atmospheric CO2 concentrations using a regional transport model. Third, to assess the impact of the drought in 2018. The comparison of estimated concentrations with ICOS observations helped the evaluation of the models' regional scale performance. Both the simulations and observations indicate there were similar reductions in the net CO2 uptake during drought. All the models (except for SiBCASA) and observations indicated the region was a net carbon sink during the 3‐year study period. Our study highlights a need to improve vegetation models through comparisons with empirical data and demonstrate the ICOS network's potential utility for constraining CO2 fluxes in the region. Plain Language Summary: As the largest global carbon sink, the boreal region can play an important role in climate mitigation strategies. Thus, it is important to estimate the region's sink strength properly. However, due to limitations in measurement techniques at the regional scale, the sink strength estimates are often obtained from models, which require robust validation. Therefore, we combined flux and atmospheric concentration data from one of the stations in Northern Europe to validate estimates generated using four vegetation models. We also used a transport model to connect the fluxes to atmospheric concentration dynamics, then compared the modeled CO2 concentration patterns with observations to provide a regional scale validation of the vegetation models. These observed and modeled fluxes and concentrations are also used to investigate the impact of the 2018 drought over Nordic vegetation. We find that the 2018 European drought had only limited impact on the carbon fluxes over Northern Sweden. Both the modeling and measurements show that the study region was a carbon sink during the study period (2016–2018), with some variation in estimates from the four models. Key Points: Northern Sweden region was a carbon sink in the years 2016–2018 according to vegetation model estimates and observationsBoth concentration and flux measurements suggest 2018 drought had limited impact on the Nordic carbon balanceEmpirical measurements can improve vegetation models by integrating them into model simulations at site and regional scaleHowever, annual net ecosystem exchange values generated by the models varied between −275 and −25 gC m−2 year−1 [ABSTRACT FROM AUTHOR]

Key Points Forests may help climate mitigation if they can store carbon for centuries Climate‐driven disturbances may greatly undermine these aims in California Multi‐disciplinary and open research is urgently needed to inform policy

The impacts of extreme heat events are amplified in cities due to unique urban thermal properties. Urban greenspace mitigates high temperatures through evapotranspiration and shading; however, quantification of vegetative cooling potential in cities is often limited to simple remote sensing greenness indices or sparse, in situ measurements. Here, we develop a spatially explicit, high-resolution model of urban latent heat flux from vegetation. The model iterates through three core equations that consider urban climatological and physiological characteristics, producing estimates of latent heat flux at 30-m spatial resolution and hourly temporal resolution. We find strong agreement between field observations and model estimates of latent heat flux across a range of ecosystem types, including cities. This model introduces a valuable tool to quantify the spatial heterogeneity of vegetation cooling benefits across the complex landscape of cities at an adequate resolution to inform policies addressing the effects of extreme heat events.

• Calibration and validation of a process-based ecosystem model at an Indian forest. • Modelled and observed annual GPP are 2433 gC m−2 y−1 and 2399 gC m−2 y−1. • Mismatch exists between empirically derived and modelled photosynthetic parameters. • Model simulated sensible and latent heat fluxes concur with direct observations. The ecosystem-atmosphere exchanges of terrestrial ecosystems are key drivers of global carbon, water, and energy cycles which are crucial to be measured accurately and represented in bottom-up biogeochemically and biogeophysically coupled ecosystem, Earth system, and climate models for improving the model predictions and impact assessment of climate change on these ecosystems. The diverse natural ecosystems in India are poorly represented in these models due to the absence any of integrated data-model framework and intercomparison study so far. To partially address this, we have used flux-tower measurements in this study to simulate the gross primary productivity (GPP), sensible (H), and latent heat fluxes (LE) of a moist semi-evergreen deciduous forest in the Kaziranga National Park in subtropical Northeast India using a process-based model ISAM. The model is calibrated using two years of measurement which improves its performance when subsequently run to simulate these fluxes for a year. The model produced annual GPP, mean maximum H, and LE are 2432.26 gC m−2 y−1, 29 and 82 W m−2 respectively as compared to their measured values i.e. 2398.47 gC m−2 y−1, 26 and 73 W m−2 correspondingly. Additionally, we report the calibrated model biogeochemical and biogeophysical parameters which will be useful to simulate the fluxes in this forest using the aforementioned models. [Display omitted] [ABSTRACT FROM AUTHOR]

Epiphytic lichens are a characteristic feature of many forests around the world, where they often cover large areas on stems and branches. Recently, it has been found that lichens may contribute substantially to carbon and nutrient uptake in forests. Moreover, they have a large influence on interception of rainfall at the global scale, which leads to a shift of the water balance toward evaporation and a cooling of near-surface air temperature. It is thus crucial to understand which environmental factors are relevant for their growth and survival, and which potential risks may result from climate change. Water supply is a key factor which controls active time and, consequently, the carbon balance of the epiphytes. However, it is largely unclear, to what extent different modes of water uptake, which include bark water, may affect active time and growth under varying environmental conditions. Quantitative estimates on the relevance of bark water storage and its interspecific variation are, however, missing. Here, we apply the process-based, dynamic non-vascular vegetation model LiBry to assess the relevance of bark water for epiphytic lichens. LiBry not only accounts for the main physiological processes of mosses and lichens, it also represents explicitly the diversity of the organisms, by simulating a large number of possible physiological strategies. We run the model for a site in Sardinia, where epiphytic lichens are abundant. Moreover, the Mediterranean region is of interest due to likely substantial effects of global warming on local epiphytes. For current climatic conditions, the LiBry model predicts net primary production (NPP) of 32 g C m−2a−1 per stem area and biomass of 48 g C m−2 for the study region. In a second run, where uptake of bark water is switched off in the model, estimated NPP is reduced by 21%. Moreover, the simulated number of surviving strategies, representing physiological diversity, decreases by 23%. This is accompanied by changes in the simulated community composition, where strategies which have a more compact thallus increase their share on the total cover. Hence, our model simulation suggests a substantial role of bark water for growth and morphology of epiphytic lichens in Sardinia.

There have been vociferous calls for 'tree-centered' vegetation models to refine predictions of forest carbon (C) cycling. Unfortunately, our global survey at flux-tower sites indicates insufficient empirical data support for this much-needed model development. We urge for a new generation of studies across large environmental gradients that strategically pair long-term ecosystem monitoring with manipulative experiments on mature trees. For this, we outline a versatile experimental framework to build cross-scale data archives of C uptake and allocation to structural, non-structural, and respiratory sinks. Community-wide efforts and discussions are needed to implement this framework, especially in hitherto underrepresented tropical forests. Global coordination and realistic priorities for data collection will thereby be key to achieve and maintain adequate empirical support for tree-centered vegetation modeling. Vegetation models are converging on an intermediate complexity with the tree level as the target for simulation. Field and laboratory observations of forest ecosystem processes are indispensable to parameterize, evaluate, or be assimilated into tree-centered vegetation models. Observations of C allocation in trees are not being developed at the same pace as tree-centered vegetation models, lack scalability, and are scarce in tropical and boreal forests. Flux towers measure the net C gain or loss of ecosystems at very high temporal resolution and provide an advanced setup for monitoring meteorological, biogeochemical, and ecological variables. Experimental manipulations of mature trees are methodologically challenging, but recent advances have provided unprecedented insight in C uptake, respiration, and allocation to structural and non-structural sinks in trees under climate change. [ABSTRACT FROM AUTHOR]

In this article, we present a multipolarimetric estimation approach for two model-based vegetation structure parameters (shape ${A}_{P}$ and orientation distribution ${\psi }$ of the main canopy elements). The approach is based on a reduced observation set of three incoherent (no phase information) polarimetric backscatter intensities ($| {S}_{\mathrm{ HH}} |^{2}$ , $| {S}_{\mathrm{ HV}} |^{2}$ , and $| {S}_{\mathrm{ VV}} |^{2}$) combined with a two-parameter (${A}_{P}$ and ${\psi }$) discrete scatterer model of vegetation. The objective is to understand whether this confined set of observations contains enough information to estimate the two vegetation structure parameters from the L-band radar signals. In order to disentangle soil and vegetation scattering influences on these signals and ultimately perform a vegetation-only retrieval of vegetation shape ${A}_{P}$ and orientation distribution ${\psi }$ , we use the subpixel spatial heterogeneity expressed by the covariation of co- and cross-polarized backscatter ${\Gamma }_{{{\mathrm{PP-PQ}}}}$ of the neighboring cells and assume it is indicative for the amount of a vegetation-only co-to-cross-polarized backscatter ratio ${\mu }_{{{\mathrm{PP-PQ}}}}$. The ratio-based retrieval approach enables a relative (no absolute backscatter) estimation of the vegetation structure parameters which is more robust compared to retrievals with absolute terms. The application of the developed algorithm on global L-band Soil Moisture Active Passive (SMAP) radar data acquired from April to July 2015 indicates the potential and limitations of estimating these two parameters when no fully polarimetric data are available. A focus study on six different regions of interest, spanning land cover from barren land to tropical rainforest, shows a steady increase in orientation distribution toward randomly oriented volumes and a continuous decrease in shape arriving at dipoles for tropical vegetation. A comparison with independent data sets of vegetation height and above-ground biomass confirms this consistent and meaningful retrieval of ${A}_{P}$ and ${\psi }$. The retrieved shapes and orientation distributions represent the main vegetation elements matching the literature results from model-based decompositions of fully polarimetric L-band data at the SMAP spatial resolution. Based on our findings, ${A}_{P}$ and ${\psi }$ can be directly applied for parameterizing the vegetation scattering component of model-based polarimetric decompositions. This should facilitate decomposition into ground and vegetation scattering components and improve the retrieval of soil parameters (moisture and roughness) under vegetation. [ABSTRACT FROM AUTHOR]

This article is a Commentary on Eller et al., 226: 1622–1637, and Sabot et al., 226: 1638–1655. [ABSTRACT FROM AUTHOR]

Summary: Drought‐induced tree mortality has major impacts on ecosystem carbon and water cycles, and is expected to increase in forests across the globe with climate change. A large body of research in the past decade has advanced our understanding of plant water and carbon relations under drought. However, despite intense research, we still lack generalizable, cross‐scale indicators of mortality risk. In this Viewpoint, we propose that a more explicit consideration of water pools could improve our ability to monitor and anticipate mortality risk. Specifically, we focus on the relative water content (RWC), a classic metric in plant water relations, as a potential indicator of mortality risk that is physiologically relevant and integrates different aspects related to hydraulics, stomatal responses and carbon economy under drought. Measures of plant water content are likely to have a strong mechanistic link with mortality and to be integrative, threshold‐prone and relatively easy to measure and monitor at large spatial scales, and may complement current mortality metrics based on water potential, loss of hydraulic conductivity and nonstructural carbohydrates. We discuss some of the potential advantages and limitations of these metrics to improve our capacity to monitor and predict drought‐induced tree mortality. [ABSTRACT FROM AUTHOR]

Abstract: The response of forest growth to climate variability varies along environmental gradients. A growth increase and decrease with warming is usually observed in cold‐humid and warm‐dry regions, respectively. However, it remains poorly known where the sign of these temperature effects switches. Here we introduce a newly developed European tree ring network that has been specifically collected to reconstruct forest aboveground biomass increment (ABI). We quantify, how the long‐term (1910–2009) interannual variability of ABI depends on local mean May–August temperature and test, if a dynamic global vegetation model ensemble reflects the resulting patterns. We find that sites at 8 °C mean May–August temperature increase ABI on average by 5.7 ± 1.3%, whereas sites at 20 °C decrease ABI by 3.0 ± 1.8% m−2 year−1 Δ°C−1. A threshold temperature between beneficial and detrimental effects of warming and the associated increase in water demand on tree growth emerged at 15.9 ± 1.4 °C mean May–August temperature. Because interannual variability increases proportionally with mean growth rate—that is, the coefficient of variation stays constant—we were able to validate these findings with a much larger tree ring data set that had been established following classic dendrochronological sampling schemes. While the observed climate sensitivity pattern is well reflected in the dynamic global vegetation model ensemble, there is a large spread of threshold temperatures between the individual models. Also, individual models disagree strongly on the magnitude of climate impact at the coldest and warmest locations, suggesting where model improvement is most needed to more accurately predict forest growth and effectively guide silvicultural practices. [ABSTRACT FROM AUTHOR]

Abstract: Stomatal response to environmental conditions forms the backbone of all ecosystem and carbon cycle models, but is largely based on empirical relationships. Evolutionary theories of stomatal behaviour are critical for guarding against prediction errors of empirical models under future climates. Longstanding theory holds that stomata maximise fitness by acting to maintain constant marginal water use efficiency over a given time horizon, but a recent evolutionary theory proposes that stomata instead maximise carbon gain minus carbon costs/risk of hydraulic damage. Using data from 34 species that span global forest biomes, we find that the recent carbon‐maximisation optimisation theory is widely supported, revealing that the evolution of stomatal regulation has not been primarily driven by attainment of constant marginal water use efficiency. Optimal control of stomata to manage hydraulic risk is likely to have significant consequences for ecosystem fluxes during drought, which is critical given projected intensification of the global hydrological cycle. [ABSTRACT FROM AUTHOR]

This study presents an efficient model for the calculation of 3-dimensional time-resolved solar potentials, based on the Perez solar model. The new model features a novel interpolation scheme for the generation of annual hourly time-series, diffuse and specular inter-reflection, a multi-layer approach to model the attenuation of solar radiation through vegetation, and snow-coverage. It is fully integrated in a 3D CAD environment to facilitate its application. Extensive validation case studies prove the high match of the new model to three other well-established programs: Radiance, Daysim and EnergyPlus. A thorough analysis of the effect of various model parameter settings highlights the importance of assessing site specific characteristics and modelling uncertainty caused by parameter selection. Our results show a significant reduction in computing times compared to Daysim and EnergyPlus, while generating less mismatches in geometric obstruction calculations when assuming Radiance as a reference. Furthermore, the considered case studies suggest that modelling the shading effect of vegetation is indispensable in solar potential analyses and should not be neglected. [ABSTRACT FROM AUTHOR]

Arctic and alpine treelines worldwide differ in their reactions to climate change. A northward advance of or densification within the treeline ecotone will likely influence climate-vegetation feedback mechanisms. In our study, which was conducted in the Taimyr Depression in the North Siberian Lowlands, w present a combined field- and model-based approach helping us to better understand the population processes involved in the responses of the whole treeline ecotone, spanning from closed forest to single-tree tundra, to climate warming. Using information on stand structure, tree age, and seed quality and quantity from seven sites, we investigate effects of intra-specific competition and seed availability on the specific impact of recent climate warming on larch stands. Field data show that tree density is highest in the forest-tundra, and average tree size decreases from closed forest to single-tree tundra. Age-structure analyses indicate that the trees in the closed forest and forest-tundra have been present for at least ~240 yr. At all sites except the most southerly ones, past establishment is positively correlated with regional temperature increase. In the single-tree tundra, however, a change in growth form from krummholz to erect trees, beginning ~130 yr ago, rather than establishment date has been recorded. Seed mass decreases from south to north, while seed quantity increases. Simulations with LAVESI (Larix Vegetation Simulator) further suggest that relative density changes strongly in response to a warming signal in the forest-tundra while intra-specific competition limits densification in the closed forest and seed limitation hinders densification in the single-tree tundra. We find striking differences in strength and timing of responses to recent climate warming. While forest-tundra stands recently densified, recruitment is almost non-existent at the southern and northern end of the ecotone due to autecological processes. Palaeo-treelines may therefore be inappropriate to infer past temperature changes at a fine scale. Moreover, a lagged treeline response to past warming will, via feedback mechanisms, influence climate change in the future. [ABSTRACT FROM AUTHOR]

We have developed a computer model of plant community dynamics for Louisiana’s coastal wetland ecosystems. The model was improved as a part of the Louisiana Coastal Master Plan of 2017 and is one of several linked models used to evaluate the potential effects of climate change and sea levels rise as well as the potential effects of alternative approaches to managing the region’s natural resources to mitigate the effects of sea level rise. The model we describe here incorporates a number of improvements over the previous version of the model developed for the 2012 Master Plan, including an expansion of the number of species and habitat types represented, the inclusion of bottomland forests and barrier islands, and the incorporation of additional ecological processes such as dispersal. Here, we present results from the model used to evaluate large scale ecosystem restoration projects, as well as three alternative management scenarios to illustrate the utility of the model and the ability of current management plans to address the threats that sea level rise pose to Louisiana’s coastal wetland ecosystems. [ABSTRACT FROM AUTHOR]

Forests are subjected to stress from climatic and non-climatic sources. In this study, we have reported the results of inherent, as well as climate change driven vulnerability assessments for Indian forests. To assess inherent vulnerability of forests under current climate, we have used four indicators, namely biological richness, disturbance index, canopy cover, and slope. The assessment is presented as spatial profile of inherent vulnerability in low, medium, high and very high vulnerability classes. Fourty percent forest grid points in India show high or very high inherent vulnerability. Plantation forests show higher inherent vulnerability than natural forests. We assess the climate change driven vulnerability by combining the results of inherent vulnerability assessment with the climate change impact projections simulated by the Integrated Biosphere Simulator dynamic global vegetation model. While 46% forest grid points show high, very high, or extremely high vulnerability under future climate in the short term (2030s) under both representative concentration pathways 4.5 and 8.5, such grid points are 49 and 54%, respectively, in the long term (2080s). Generally, forests in the higher rainfall zones show lower vulnerability as compared to drier forests under future climate. Minimizing anthropogenic disturbance and conserving biodiversity can potentially reduce forest vulnerability under climate change. For disturbed forests and plantations, adaptive management aimed at forest restoration is necessary to build long-term resilience. [ABSTRACT FROM AUTHOR]

• A vegetation model is coupled with a hydrological model of bioretention system. • The model can simulate seasonal and interannual variation of vegetation. • Evapotranspiration is sensitive to most parameters in the vegetation model. • Vegetation variation mainly affects evapotranspiration and soil moisture. • Vegetation affects exfiltration and outflow in the season with long dry period. Bioretention systems are widely used to mitigate the adverse effects of urbanization on the hydrological cycle. Vegetation plays a key role in the hydrological performance of bioretention systems; however, few model studies have focused on the effects of vegetation dynamics on performance. In this study, we propose an eco-hydrological model of bioretention systems by coupling a vegetation growth model with a hydrological model. The eco-hydrological model was verified using 2-year observed data on vegetation coverage, soil moisture, water depths in the gravel layer, and outflow rates of a bioretention system in Shenzhen, China. Based on the validated model, scenarios were designed to simulate seasonal or interannual changes in vegetation coverage and evaluate their influence on the hydrological performance of the bioretention system. The results indicate that (i) the model is able to explicitly describe vegetation dynamics and hydrological processes of the system, and the Nash Sutcliffe Efficiency of vegetation coverage, soil moisture, water depth in the gravel layer, and outflow rates range from 0.6 to 0.9; (ii) vegetation coverage and evapotranspiration volume are moderately or highly sensitive to most parameters of the vegetation module; the volume of exfiltration into the surrounding soil and outflow are sensitive to three parameters (potential maximum vegetation coverage (f cmax), potential heat units required for maturation (PHU), and accumulated heat units at the beginning of vegetation coverage decline (HU point)) in the months with a long antecedent dry period; and (iii) the seasonal and interannual variation in vegetation mainly affects soil moisture and evapotranspiration; in addition, the variations affect exfiltration and outflow for rainfall events with a long antecedent dry period (>9 d). Therefore, an eco-hydrological model that considers the influence of vegetation dynamics can be used to evaluate the long-term hydrological performance of bioretention systems. This study investigated the performance of one species (Canna indica L.). Further studies are necessary to prove the adaptability of the model to bioretention systems with other vegetation types in different climatic zones. [ABSTRACT FROM AUTHOR]

• The implementation of variation and adaptation of traits in a vegetation model changes the results. • The northern treeline of Siberia could be advancing faster than previously predicted. • The larches of central Siberia cannot withstand future drought even if they adapted. With changing climate, the boreal forest could potentially migrate north and become threatened by droughts in the south. However, whether larches, the dominant tree species in eastern Siberia, can adapt to novel situations is largely unknown but is crucial for predicting future population dynamics. Exploring variable traits and trait adaptation through inheritance in an individual-based model can improve our understanding and help future projections. We updated the individual-based spatially explicit vegetation model LAVESI (Larix Vegetation Simulator), used for forest predictions in Eastern Siberia, with trait value variation and incorporated inheritance of parental values to their offspring. Forcing the model with both past and future climate projections, we simulated two areas – the expanding northern treeline and a southerly area experiencing drought. While the specific trait of 'seed weight' regulates migration, the abstract 'drought resistance' protects stands. We show that trait variation with inheritance leads to an increase in migration rate (∼ 3% area increase until 2100). The drought resistance simulations show that, under increasing stress, including adaptive traits leads to larger surviving populations (17% of threatened under RCP 4.5 (Representative Concentration Pathway)). We show that with the increase expected under the RCP 8.5 scenario vast areas (80% of the extrapolated area) of larch forest are threatened and could disappear due to drought as adaptation plays only a minor role under strong warming. We conclude that variable traits facilitate the availability of variants under environmental changes. Inheritance allows populations to adapt to environments and promote successful traits, which leads to populations that can spread faster and be more resilient, provided the changes are not too drastic in both time and magnitude. We show that trait variation and inheritance contribute to more accurate models that can improve our understanding of responses of boreal forests to global change. [ABSTRACT FROM AUTHOR]

Urban trees can significantly improve the outdoor thermal environment, especially in subtropical zones. However, due to the lack of fundamental evaluations of numerical simulation models, design and modification strategies for optimizing the thermal environment in subtropical hot-humid climate zones cannot be proposed accurately. To resolve this issue, this study investigated the physiological parameters (leaf surface temperature and vapor flux) and thermal effects (solar radiation, air temperature, and humidity) of four common tree species (Michelia alba, Mangifera indica, Ficus microcarpa, and Bauhinia blakeana) in both spring and summer in Guangzhou, China. A comprehensive comparison of the observed and modeled data from ENVI-met (v4.2 Science, a three-dimensional microclimate model) was performed. The results show that the most fundamental weakness of ENVI-met is the limitation of input solar radiation, which cannot be input hourly in the current version and may impact the thermal environment in simulation. For the tree model, the discrepancy between modeled and observed microclimate parameters was acceptable. However, for the physiological parameters, ENVI-met tended to overestimate the leaf surface temperature and underestimate the vapor flux, especially at midday in summer. The simplified calculation of the tree model may be one of the main reasons. Furthermore, the thermal effect of trees, meaning the differences between nearby treeless sites and shaded areas, were all underestimated in ENVI-met for each microclimate variable. This study shows that the tree model is suitable in subtropical hot-humid climates, but also needs some improvement.