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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 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.

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).)

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]

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]

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.

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.

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: 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]

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]

• 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.

Forest ecosystems play an important role in the interaction between the land surface and the atmosphere. Measurements and modelling efforts have revealed significant uncertainties in state-of-the-art flux assessments due to spatial inhomogeneities in the airflow and land surface. Here, a field experiment is used to describe the turbulent flow across a typical Central European forest clearing. A three-dimensional model of the inhomogeneous forest stand was developed using an innovative approach based on terrestrial laser-scanner technology. The comparison of the wind statistics of two measurement campaigns (5 and 12 months long) showed the spatial and temporal representativeness of the ultrasonic anemometer measurements within the canopy. An improved method for the correction of the vertical velocity enables the distinction between the instrumental offsets and the vertical winds due to the inclination of the instrument. Despite a 13 % fraction of deciduous plants within the otherwise evergreen canopy, the effects of phenological seasons on the velocity profiles were small. The data classified according to the wind speed revealed the intermittent nature of recirculating air in the clearing. Furthermore, the development of sub-canopy wind-speed maxima is explained by considering the velocity moments and the momentum equation (including measurements of the local pressure gradient). Clearings deflect the flow downward and feed the sub-canopy flow, i.e., advective fluxes, according to wind speed and, likely, clearing size, whereas local pressure gradients play an important role in the development of sub-canopy flow. The presented dataset is freely available at the project homepage. [ABSTRACT FROM AUTHOR]

Plant hydraulics mediate terrestrial woody plant productivity, influencing global water, carbon, and biogeochemical cycles, as well as ecosystem vulnerability to drought and climate change. While inter-specific differences in hydraulic traits are widely documented, intra-specific hydraulic variability is less well known and is important for predicting climate change impacts. Here, I present a conceptual framework for this intra-specific hydraulic trait variability, reviewing the mechanisms that drive variability and the consequences for vegetation response to climate change. I performed a meta-analysis on published studies ( n = 33) of intra-specific variation in a prominent hydraulic trait - water potential at which 50% stem conductivity is lost (P50) - and compared this variation to inter-specific variability within genera and plant functional types used by a dynamic global vegetation model. I found that intra-specific variability is of ecologically relevant magnitudes, equivalent to c. 33% of the inter-specific variability within a genus, and is larger in angiosperms than gymnosperms, although the limited number of studies highlights that more research is greatly needed. Furthermore, plant functional types were poorly situated to capture key differences in hydraulic traits across species, indicating a need to approach prediction of drought impacts from a trait-based, rather than functional type-based perspective. [ABSTRACT FROM AUTHOR]

Climate change has significant effects on critical ecosystem functions such as carbon and water cycling. Vegetation and especially forest ecosystems play an important role in the carbon and hydrological cycles. Vegetation models that include detailed belowground processes require accurate soil data to decrease uncertainty and increase realism in their simulations. The MC2 DGVM uses three modules to simulate biogeography, biogeochemistry and fire effects, all three of which use soil data either directly or indirectly. This study includes a correlation analysis of the MC2 model to soil depth by comparing a subset of the model’s carbon and hydrological outputs using soil depth data of different scales and qualities. The results show that the model is very sensitive to soil depth in simulations of carbon and hydrological variables, but competing algorithms make the fire module less sensitive to changes in soil depth. Simulated historic evapotranspiration and net primary productivity show the strongest positive correlations (both have correlation coefficients of 0.82). The strongest negative correlation is streamflow (−0.82). Ecosystem carbon, vegetation carbon and forest carbon show the next strongest correlations (0.78, 0.74 and 0.74, respectively). Carbon consumed by forest fires and the part of each grid cell burned show only weak negative correlations (−0.24 and −0.0013 respectively). In the model, when the water demand is met (deep soil with good water availability), production increases and fuels build up as more litter gets generated, thus increasing the overall fire risk during upcoming dry periods. However, when soil moisture is low, fuels dry and fire risk increases. In conclusion, it is clear climate change impact models need accurate soil depth data to simulate the resilience or vulnerability of ecosystems to future conditions. [ABSTRACT FROM AUTHOR]

Aim Projections of future climate change suggest that regional climates may evolve to states that are unlike any climate regime found on Earth today. These climates will impose novel constraints on plant species, and are likely to give rise to plant associations that are compositionally unlike any found on Earth today. Here, we explore whether the geographical distribution of previously mapped no-analogue climates corresponds to the geographical distribution of simulated no-analogue vegetation under scenarios of global warming. Location Global landmasses. Methods We used J e D i, a process-based vegetation model that accounts for ecophysiological trade-offs in plant growth and survival, to identify the assembly of plant functional types into no-analogue associations under scenarios of global warming. We compared the geographical distribution of these no-analogue vegetation types with those of no-analogue climates derived from seasonal temperature and precipitation. To better understand the climatic causes that lead to no-analogue vegetation, we performed a set of J e D i simulation experiments and compared them, as well as selected climate indices, with the geographical distribution of no-analogue vegetation. Finally, we explored the changes in plant characteristics leading to no-analogue vegetation composition. Results In our model simulations, a no-analogue vegetation type emerged in Northern Eurasia due to the interacting effects of rising temperatures and the prolongation of the growing season, combined with stable patterns in the seasonal insolation cycle. Future tropical biomes experiencing novel temperature and precipitation regimes however, resemble contemporary vegetation despite significant losses of plant diversity. Main conclusions Our modelling study shows how no-analogue vegetation can emerge in response to novel climates produced by rising temperatures and stable insolation, while also suggesting that no-analogue climates do not necessarily lead to no-analogue vegetation types. This result underlines the importance of considering plant diversity and the need to integrate ecophysiological knowledge through process-orientated models when projecting future vegetation. [ABSTRACT FROM AUTHOR]

Global patterns of drought-induced forest die-off indicate that many forests may be sensitive to climate-driven mortality, but the lack of understanding of how trees and saplings die during drought hinders the projections of die-off, demographic bottlenecks and ecosystem trajectories. In this study, we performed a severe controlled drought experiment on saplings of Pinus edulis Engelm. and Juniperus osteosperma (Torr.) Little, two species that both experienced die-off in a recent ‘climate change-type’ drought. We examined the roles of carbohydrate and hydraulic changes in multiple tissues as the saplings died. We found that saplings of both species exhibited large degrees of loss of hydraulic conductivity prior to death. Neither species exhibited significant changes in carbohydrate concentrations in any tissue during the relatively short and severe imposed drought. Native hydraulic conductivity successfully predicted the degree of canopy mortality in both species, highlighting the importance of drought characteristics and tree attributes in influencing physiological pathways to mortality. The relationships elucidated here, as well as the differences between our results and previous findings in adult trees, can help inform mortality mechanisms in climate–vegetation models, especially for young trees, and to understand species response to severe drought across ontogeny. [ABSTRACT FROM AUTHOR]

Abstract: Hydrological alteration caused by dam operation and river modification has changed the dynamics of riparian vegetation in most river floodplain systems. In this study, a dynamic vegetation model was used to analyze the change in floodplain area occupied by individual vegetation types and vegetation succession dynamics as consequences of river modification and dam operation. The vegetation model simulates spatially distributed vegetation types based on simulated river floodplain physical processes. Study periods were classified into historic, pre-dam and post-dam conditions. The statistical t-test was used to analyze changes in the normalized mean area occupied by different vegetation types between different time periods. Furthermore, the Mann–Kendall test was used to evaluate the succession trend of vegetation with respect to spatial area and age. The area occupied by colonization and cottonwood young transition vegetation was similar in historic and pre-dam conditions, but decreased gradually from pre-dam to post-dam conditions. In contrast, the reed and grassland vegetation gradually increased from historic to post-dam conditions. The cottonwood old transition vegetation increased from pre-dam to post dam condition. The average age of the vegetation did not significantly increase or decrease in historic and pre-dam conditions; however, it increased in the post-dam condition. There were no significant differences in the succession trends of vegetation area between historic and pre-dam conditions for most of the vegetation types, except for reed and grassland and cottonwood old transition vegetation. The succession trends of vegetation area were significantly different between pre- and post-dam conditions for all vegetation types except for the wetland vegetation. Our vegetation model illustrated the impact of altered physical processes on riparian ecosystems. Such spatial and quantitative measurements of vegetation distributions can be used to quantify the riparian habitat losses from dam operation, which can help to manage and restore riparian vegetation in human disturbed systems. [Copyright &y& Elsevier]

Numerous plant traits are known to influence aspects of individual performance, including rates of carbon uptake, tissue turnover, mortality and fecundity. These traits are bound to influence emergent properties of vegetation because quantities such as leaf-area cover, average height, primary productivity and density of standing biomass result from the collective behaviour of individuals. Yet, little is known about the influence of individual traits on these emergent properties, despite the widespread use in current vegetation models of plant functional types, each of which is defined by a constellation of traits. We examine the influence of four key traits (leaf economic strategy, height at maturation, wood density, and seed size) on four emergent vegetation properties (average height of leaf area, leaf-area index, net primary productivity and biomass density). We employ a trait-, size- and patch-structured model of vegetation dynamics that allows scaling up from individual-level growth processes and probabilistic disturbances to landscape-level predictions. A physiological growth model incorporating relevant trade-offs was designed and calibrated based on known empirical patterns. The resulting vegetation model naturally exhibits a range of phenomena commonly observed in vegetation dynamics. We modelled single-species stands, varying each trait over its known empirical range. Seed size had only a small effect on vegetation properties, primarily because our metapopulations were not seed-limited. The remaining traits all had larger effects on vegetation properties, especially on biomass density. Leaf economic strategy influenced minimum light requirement, and thus total leaf area and basal area. Wood density and height at maturation influenced vegetation mainly by modifying individual stem mass. These effects of traits were maintained, and sometimes amplified, across stands differing in productivity and mean disturbance interval. Synthesis: Natural trait variation can cause large differences in emergent properties of vegetation, the magnitudes of which approach those arising through changes to site productivity and disturbance frequency. Our results therefore underscore the need for next-generation vegetation models that incorporate functional traits together with their effects on the patch and size structure of vegetation. [ABSTRACT FROM AUTHOR]

Aim The northern limits of temperate broadleaved species in Fennoscanndia are controlled by their requirements for summer warmth for successful regeneration and growth as well as by the detrimental effects of winter cold on plant tissue. However, occurrences of meteorological conditions with detrimental effects on individual species are rare events rather than a reflection of average conditions. We explore the effect of changes in inter-annual temperature variability on the abundances of the tree species Tilia cordata, Quercus robur and Ulmus glabra near their distribution limits using a process-based model of ecosystem dynamics. Location A site in central Sweden and a site in southern Finland were used as examples for the ecotone between boreal and temperate forests in Fennoscandia. The Finnish site was selected because of the availability of varve-thickness data. Methods The dynamic vegetation model LPJ-GUESS was run with four scenarios of inter-annual temperature forcing for the last 10,000 years. In one scenario the variability in the thickness of summer and winter varves from the annually laminated lake in Finland was used as a proxy for past inter-annual temperature variability. Two scenarios were devised to explore systematically the effect of stepwise changes in the variance and shape parameter of a probability distribution. All variability scenarios were run both with and without the long-term trend in Holocene temperature change predicted by an atmospheric general circulation model. Results Directional changes in inter-annual temperature variability have significant effects on simulated tree distribution limits through time. Variations in inter-annual temperature variability alone are shown to alter vegetation composition by magnitudes similar to the magnitude of changes driven by variation in mean temperatures. Main conclusions The varve data indicate that inter-annual climate variability has changed in the past. The model results show that past changes in species abundance can be explained by changes in the inter-annual variability of climate parameters as well as by mean climate. Because inter-annual climatic variability is predicted to change in the future, this component of climate change should be taken into account both when making projections of future plant distributions and when interpreting vegetation history. [ABSTRACT FROM AUTHOR]

Abstract: The LPJ dynamic global vegetation and hydrology model with river routing is implemented on a compute cluster in order to reduce the overall computation time. In order to achieve this, a parallel algorithm had to be developed for the river routing part of the LPJ code. It can be shown that the run time of the parallel LPJ model scales well with the number of parallel tasks, even getting a super-linear speedup for 8–128 tasks. The sequential part of the model code can be estimated to be only 0.16%. This offers the opportunity, for example, to apply the model to find optimal climate change mitigation/adaptation paths requiring a multitude of subsequent simulation runs. The algorithm can also be used for networks with a different topology than river routing networks. [Copyright &y& Elsevier]

Aim To project the distribution of three major forest types in the northeastern USA in response to expected climate change. Location The New England region of the United States. Methods We modelled the potential distribution of boreal conifer, northern deciduous hardwood and mixed oak–hickory forests using the process-based BIOME4 vegetation model parameterized for regional forests under historic and projected future climate conditions. Projections of future climate were derived from three general circulation models forced by three global warming scenarios that span the range of likely anthropogenic greenhouse gas emissions. Results Annual temperature in New England is projected to increase by 2.2–3.3 °C by 2041–70 and by 3.0–5.2 °C by 2071–99 with corresponding increases in precipitation of 4.7–9.5% and 6.4–11.4%, respectively. We project that regional warming will result in the loss of 71–100% of boreal conifer forest in New England by the late 21st century. The range of mixed oak–hickory forests will shift northward by 1.0–2.1 latitudinal degrees ( c. 100–200 km) and will increase in area by 149–431% by the end of the 21st century. Northern deciduous hardwoods are expected to decrease in area by 26% and move upslope by 76 m on average. The upslope movement of the northern deciduous hardwoods and the increase in oak–hickory forests coincide with an approximate 556 m upslope retreat of the boreal conifer forest by 2071–99. In our simulations, rising atmospheric CO2 concentrations reduce the losses of boreal conifer forest in New England from expected losses based on climatic change alone. Main conclusion Projected climate warming in the 21st century is likely to cause the extensive loss of boreal conifer forests, reduce the extent of northern hardwood deciduous forests, and result in large increases of mixed oak–hickory forest in New England. [ABSTRACT FROM AUTHOR]

Aim To investigate the impact of past environmental changes on Cedrus atlantica and its current genetic diversity, and to predict its future distribution. Location Morocco, Algeria and Tunisia. Methods Eleven fossil pollen records from these three countries were used to locate putative glacial refugia and to reconstruct past climate changes. A mechanistic vegetation distribution model was used to simulate the distribution of C. atlantica in the year 2100. In addition, a genetic survey was carried out on modern Moroccan C. atlantica. Results Pollen records indicate that Cedrus was present during the last glacial period, probably in scattered refugia, in Tunisia, Algeria and Morocco. In the Tunisian and Algerian sites, cedar expanded during the late glacial and the early Holocene, then disappeared after c. 8000 yr bp. Reconstructed mean annual precipitation and January temperature show that the last glacial period in Morocco was cooler by 10–15°C and drier by c. 300–400 mm year−1 than the climate today. Modern chloroplast microsatellites of 15 C. atlantica populations in Morocco confirm the presence of multiple refugia and indicate that cedar recolonized the Moroccan mountains fairly recently. Model simulation indicates that by the year 2100 the potential distribution of C. atlantica will be much restricted with a potential survival area located in the High Atlas. Main conclusions Environmental changes in northern Africa since the last glacial period have had an impact on the geographical distribution of C. atlantica and on its modern genetic diversity. It is possible that by the end of this century C. atlantica may be unable to survive in its present-day locations. To preserve the species, we suggest that seedlings from modern C. atlantica populations located in the High Atlas mountains, where a high genetic diversity is found, be transplanted into the western High Atlas. [ABSTRACT FROM AUTHOR]

Research in the area of 3-D city modeling from remote sensed data greatly developed in recent years with an emphasis on systems dealing with the detection and representation of man-made objects, such as buildings and streets. While these systems produce accurate representations of urban environments, they ignore information about the vegetation component of a city. This paper presents a complete image analysis system which, from high-resolution color infrared (CIR) digital images, and a Digital Surface Model (DSM), extracts, segments, and classifies vegetation in high density urban areas, with very high reliability. The process starts with the extraction of all vegetation areas using a supervised classification system based on a Support Vector Machines (SVM) classifier. The result of this first step is further on used to separate trees from lawns using texture criteria computed on the DSM. Tree crown borders are identified through a robust region growing algorithm based on tree-shape criteria. A SVM classifier gives the species class for each tree-region previously identified. This classification is used to enhance the appearance of 3-D city models by a realistic representation of vegetation according to the vegetation land use, shape and tree species. [ABSTRACT FROM PUBLISHER]