Leveraging plant hydraulics to yield predictive and dynamic plant leaf allocation in vegetation models with climate change

Abstract. Atmospheric CO2 drives most of the greenhouse effect increase. One major uncertainty on the future rate of increase of CO2 in the atmosphere is the impact of the anticipated climate change on the vegetation. Dynamic Global Vegetation Models (DGVM) are used to address this question. ORCHIDEE is such a DGVM that has proven useful for climate change studies. However, there is no objective and methodological way to accurately assess each new available version on the global scale. In this paper, we submit a methodological evaluation of ORCHIDEE by correlating satellite-derived Vegetation Index time series against those of the modeled Fraction of absorbed Photosynthetically Active Radiation (FPAR). A perfect correlation between the two is not expected, however an improvement of the model should lead to an increase of the overall performance. We detail two case studies in which model improvements are demonstrated, using our methodology. In the first one, a new phenology version in ORCHIDEE is shown to bring a significant impact on the simulated annual cycles, in particular for C3 Grasses and C3 Crops. In the second case study, we compare the simulations when using two different weather fields to drive ORCHIDEE. The ERA-Interim forcing leads to a better description of the FPAR interannual anomalies than the simulation forced by a mixed CRU-NCEP dataset. This work shows that long time series of satellite observations, despite their uncertainties, can identify weaknesses in global vegetation models, a necessary first step to improving them.

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Plant hydraulic traits reveal islands as refugia from worsening drought

Conservation Physiology ◽

10.1093/conphys/coz115 ◽

2020 ◽

Vol 8 (1) ◽

Cited By ~ 2

Author(s):

Aaron R Ramirez ◽

Mark E De Guzman ◽

Todd E Dawson ◽

David D Ackerly

Keyword(s):

Climate Change ◽

Water Relations ◽

Plant Traits ◽

Regional Climate ◽

Channel Islands ◽

Local Conditions ◽

Early 21St Century ◽

Plant Hydraulics ◽

Drought Conditions ◽

Potential Climate Change

Abstract Relatively mesic environments within arid regions may be important conservation targets as ‘climate change refugia’ for species persistence in the face of worsening drought conditions. Semi-arid southern California and the relatively mesic environments of California’s Channel Islands provide a model system for examining drought responses of plants in potential climate change refugia. Most methods for detecting refugia are focused on ‘exposure’ of organisms to certain abiotic conditions, which fail to assess how local adaptation or acclimation of plant traits (i.e. ‘sensitivity’) contribute to or offset the benefits of reduced exposure. Here, we use a comparative plant hydraulics approach to characterize the vulnerability of plants to drought, providing a framework for identifying the locations and trait patterns that underlie functioning climate change refugia. Seasonal water relations, xylem hydraulic traits and remotely sensed vegetation indices of matched island and mainland field sites were used to compare the response of native plants from contrasting island and mainland sites to hotter droughts in the early 21st century. Island plants experienced more favorable water relations and resilience to recent drought. However, island plants displayed low plasticity/adaptation of hydraulic traits to local conditions, which indicates that relatively conserved traits of island plants underlie greater hydraulic safety and localized buffering from regional drought conditions. Our results provide an explanation for how California’s Channel Islands function as a regional climate refugia during past and current climate change and demonstrate a physiology-based approach for detecting potential climate change refugia in other systems.

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Forest carbon allocation modelling under climate change

Tree Physiology ◽

10.1093/treephys/tpz105 ◽

2019 ◽

Vol 39 (12) ◽

pp. 1937-1960 ◽

Cited By ~ 19

Author(s):

Katarína Merganičová ◽

Ján Merganič ◽

Aleksi Lehtonen ◽

Giorgio Vacchiano ◽

Maša Zorana Ostrogović Sever ◽

...

Keyword(s):

Climate Change ◽

Environmental Conditions ◽

Carbon Allocation ◽

Hybrid Approach ◽

Ecosystem Dynamics ◽

Nonstructural Carbohydrates ◽

The Past ◽

Process Understanding ◽

Vegetation Models ◽

The Impact

Abstract Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31 contrasting models to identify the main gaps compared with our theoretical and empirical understanding of carbon allocation. A hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in the examined models, while physiologically more sophisticated approaches were used less often than empirical ones. The analysis revealed that, although the number of carbon allocation studies over the past 10 years has substantially increased, some background processes are still insufficiently understood and some issues in models are frequently poorly represented, oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilization of nonstructural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge of carbon allocation into defence, regeneration and improved resource uptake in order to better account for changing environmental conditions.

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Dynamic forest vegetation models for predicting impacts of climate change on forests: An Indian perspective

Indian Journal of Forestry ◽

10.54207/bsmps1000-2018-f7l9y5 ◽

2018 ◽

Vol 41 (1) ◽

pp. 1-12

Author(s):

Manoj Kumar ◽

◽

S.P.S. Rawat ◽

Hukum Singh ◽

N.H. Ravindranath ◽

...

Keyword(s):

Climate Change ◽

Environmental Variables ◽

Net Primary Productivity ◽

Climate Change Impacts ◽

Forest Vegetation ◽

Elevated Concentration ◽

Impact Prediction ◽

Vegetation Models ◽

Ibis Model ◽

The Impact

Understanding climate change vulnerability of Indian forests has received wider attention in recent years and a number of assessments with different approaches have emerged over time. These assessments have mostly used climate-sensitive vegetation models to explain the climate change impacts. In these studies, trees constituting a particular forest are often clubbed together into small number of groups having similar functional traits referred as Plant Functional Types (PFTs). Most of the Forest Vegetation Models (FVMs) are still in their developmental stage and there have been attempts at various levels to develop more versatile and precise models. Several developing countries, including India, still lag behind in developing dynamic vegetation models (DVMs), which could be appropriate for the local applications to predict the impact on forests at regional level. This is restrained mainly because of the lack of long-term observations with respect to various interacting biotic, abiotic and climatic (or environmental) variables in a forest ecosystem, like water and nitrogen use efficiency, response to elevated concentration of CO2, nutrient cycling, net primary productivity, etc. The observations on influence of the environmental variables on forest ecosystems are available in discrete form. Existing FVMs integrate observations more appropriately for their place of origin for which they have been developed. Different types of forests in different climatic zones are supposed to respond differently to climatic changes. Hence, it is imperative that models are developed for the specific biogeographic regions in order to predict the influences more accurately. It may not be wise to use existing FVMs in their pristine form for all of the region without considering the regional influences. Various challenges associated with the usage of the generic models of external origin with special reference to Integrated Biosphere Simulator (IBIS) model - being widely used and accepted in Indian policy documents- is presented in this paper. We also discuss on the need for developing a regional FVM for climate change impact studies, so that the impact prediction is more precise and reliable.

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Local-scale and spatially explicit response of tropical forests to climate change

10.5194/egusphere-egu2020-10396 ◽

2020 ◽

Author(s):

Florian Hofhansl ◽

Werner Huber ◽

Anton Weissenhofer ◽

Wolfgang Wanek ◽

Oskar Franklin

Keyword(s):

Climate Change ◽

Forest Ecosystem ◽

Ecosystem Processes ◽

Ecosystem Responses ◽

Climate Anomalies ◽

Local Site ◽

Aboveground Productivity ◽

Site Characteristics ◽

Vegetation Models

Currently applied dynamic vegetation models do not realistically represent forest ecosystem processes and thus are not able to reproduce in-situ observations of forest ecosystem responses to drought. This is due to the fact that models typically rely on plant functional types to forecast the functional response of vegetation to climate change and to anthropogenic disturbance. However, recent observations of divergent ecosystem responses between topographic forest sites, differing in the availability of water and nutrients, indicate that we should no longer rely on this outdated concept but rather should explore new avenues of representing vegetation dynamics and associated climate change response in next-generation approaches.Global climate change scenarios forecast increasing severity of climate extremes in association with El Ni&#241;o&#8211;Southern Oscillation (ENSO). Such climate anomalies have been shown to affect forest ecosystem processes such as net primary productivity, which is determined by climate (precipitation, temperature, and light) and soil fertility (geology and topography). However, more recently it has been suggested that the impact of such climate fluctuations on forest productivity was strongly related to local site characteristics, which determined the sensitivity of forest ecosystem processes to climate anomalies.We propose a novel approach integrating in-situ observations with remotely sensed estimates of forest aboveground productivity for parameterization of next-generation vegetation models capable of forecasting realistic forest ecosystem responses under future scenarios. Our approach considers local site characteristics associated with topography and disturbance history, both of which determine the sensitivity of forest aboveground productivity to projected climate anomalies. Our results therefore should have crucial implications for management and restoration of forest ecosystems and could be used to refine estimates of forest C sink-strength under future scenarios.

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IPR 1.0: an efficient method for calculating solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities

Geoscientific Model Development ◽

10.5194/gmd-7-1357-2014 ◽

2014 ◽

Vol 7 (4) ◽

pp. 1357-1376

Author(s):

Y. Zhang ◽

W. Chen ◽

J. Li

Keyword(s):

Climate Change ◽

Solar Radiation ◽

Plant Communities ◽

Woody Plant ◽

Diffuse Radiation ◽

Individual Plant ◽

Vegetation Models ◽

Composition Structure ◽

Distribution Composition

Abstract. Climate change may alter the spatial distribution, composition, structure and functions of plant communities. Transitional zones between biomes, or ecotones, are particularly sensitive to climate change. Ecotones are usually heterogeneous with sparse trees. The dynamics of ecotones are mainly determined by the growth and competition of individual plants in the communities. Therefore it is necessary to calculate the solar radiation absorbed by individual plants in order to understand and predict their responses to climate change. In this study, we developed an individual plant radiation model, IPR (version 1.0), to calculate solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities. The model is developed based on geometrical optical relationships assuming that crowns of woody plants are rectangular boxes with uniform leaf area density. The model calculates the fractions of sunlit and shaded leaf classes and the solar radiation absorbed by each class, including direct radiation from the sun, diffuse radiation from the sky, and scattered radiation from the plant community. The solar radiation received on the ground is also calculated. We tested the model by comparing with the results of random distribution of plants. The tests show that the model results are very close to the averages of the random distributions. This model is efficient in computation, and can be included in vegetation models to simulate long-term transient responses of plant communities to climate change. The code and a user's manual are provided as Supplement of the paper.

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Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses

Geoscientific Model Development ◽

10.5194/gmd-8-1097-2015 ◽

2015 ◽

Vol 8 (4) ◽

pp. 1097-1110 ◽

Cited By ~ 26

Author(s):

L. Rowland ◽

A. Harper ◽

B. O. Christoffersen ◽

D. R. Galbraith ◽

H. M. A. Imbuzeiro ◽

...

Keyword(s):

Climate Change ◽

Tropical Forests ◽

Extreme Temperature ◽

Dynamic Global Vegetation Model ◽

Area Index ◽

Community Land Model ◽

Model Version ◽

Climate Change Responses ◽

Intrinsic Water Use Efficiency ◽

Vegetation Models

Abstract. Accurately predicting the response of Amazonia to climate change is important for predicting climate change across the globe. Changes in multiple climatic factors simultaneously result in complex non-linear ecosystem responses, which are difficult to predict using vegetation models. Using leaf- and canopy-scale observations, this study evaluated the capability of five vegetation models (Community Land Model version 3.5 coupled to the Dynamic Global Vegetation model – CLM3.5–DGVM; Ecosystem Demography model version 2 – ED2; the Joint UK Land Environment Simulator version 2.1 – JULES; Simple Biosphere model version 3 – SiB3; and the soil–plant–atmosphere model – SPA) to simulate the responses of leaf- and canopy-scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation, but all the models were consistent with the prediction that GPP would be higher if tropical forests were 5 °C cooler than current ambient temperatures. There was greater model–data consistency in the response of net ecosystem exchange (NEE) to changes in temperature than in the response to temperature by net photosynthesis (An), stomatal conductance (gs) and leaf area index (LAI). Modelled canopy-scale fluxes are calculated by scaling leaf-scale fluxes using LAI. At the leaf-scale, the models did not agree on the temperature or magnitude of the optimum points of An, Vcmax or gs, and model variation in these parameters was compensated for by variations in the absolute magnitude of simulated LAI and how it altered with temperature. Across the models, there was, however, consistency in two leaf-scale responses: (1) change in An with temperature was more closely linked to stomatal behaviour than biochemical processes; and (2) intrinsic water use efficiency (IWUE) increased with temperature, especially when combined with drought. These results suggest that even up to fairly extreme temperature increases from ambient levels (+6 °C), simulated photosynthesis becomes increasingly sensitive to gs and remains less sensitive to biochemical changes. To improve the reliability of simulations of the response of Amazonian rainforest to climate change, the mechanistic underpinnings of vegetation models need to be validated at both leaf- and canopy-scales to improve accuracy and consistency in the quantification of processes within and across an ecosystem.

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Past, present, and future distribution of Afromontane rodents (Muridae: Otomys) reflect climate-change predicted biome changes

Mammalia ◽

10.1515/mammalia-2015-0033 ◽

2016 ◽

Vol 80 (4) ◽

Cited By ~ 5

Author(s):

Peter John Taylor ◽

Aluwani Nengovhela ◽

Jabulani Linden ◽

Roderick M. Baxter

Keyword(s):

Climate Change ◽

Potential Threat ◽

Central Plateau ◽

Tropical Mountains ◽

Montane Biodiversity ◽

Similar Range ◽

Low Altitude ◽

Vegetation Models ◽

Few Data ◽

Great Escarpment

AbstractClimate change constitutes a potential threat to montane biodiversity, particularly in low-altitude, tropical mountains; however, few data exist for the Afromontane taxa. In South Africa, the temperate grassland and fynbos biomes are mostly associated with the Great Escarpment and the high-lying central plateau. Varying contractions of the grassland and fynbos biomes are predicted under different climate scenarios by 2050. Animal taxa adapted to these biomes should suffer similar range declines and can be used to independently test the vegetation models. We constructed MaxEnt models from 271 unique locality records for three species of montane and submontane vlei rats that are closely associated with grassland (

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The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests

10.5194/essd-2019-220 ◽

2019 ◽

Cited By ~ 2

Author(s):

Christopher P. O. Reyer ◽

Ramiro Silveyra Gonzalez ◽

Klara Dolos ◽

Florian Hartig ◽

Ylva Hauf ◽

...

Keyword(s):

Climate Change ◽

Nitrogen Deposition ◽

Forest Stand ◽

Climate Impacts ◽

Ecosystem Dynamics ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Flat File ◽

Wide Range ◽

Vegetation Models

Abstract. Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand-level, as well as remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction, and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a SQLite relational database or ASCII flat file version (at https://doi.org/10.5880/PIK.2019.008). The data policies of the individual, contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R-package (https://github.com/COST-FP1304-PROFOUND/ProfoundData), which provides basic functions to explore, plot, and extract the data for model set-up, calibration and evaluation.

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Impact of droughts on the C-cycle in European vegetation: a probabilistic risk analysis using six vegetation models

Biogeosciences Discussions ◽

10.5194/bgd-11-8325-2014 ◽

2014 ◽

Vol 11 (6) ◽

pp. 8325-8371 ◽

Cited By ~ 4

Author(s):

M. Van Oijen ◽

J. Balkovič ◽

C. Beer ◽

D. Cameron ◽

P. Ciais ◽

...

Keyword(s):

Climate Change ◽

Risk Analysis ◽

Net Primary Productivity ◽

Climate Model ◽

Grid Cell ◽

Climate Data ◽

Drought Vulnerability ◽

Ecosystem Vulnerability ◽

C Cycle ◽

Vegetation Models

Abstract. We analyse how climate change may alter risks posed by droughts to carbon fluxes in European ecosystems. The approach follows a recently proposed framework for risk analysis based on probability theory. In this approach, risk is quantified as the product of hazard probability and ecosystem vulnerability. The probability of a drought hazard is calculated here from the Standardised Precipitation Evapotranspiration Index. Vulnerability is calculated from the response to drought simulated by process-based vegetation models. Here we use six different models: three for generic vegetation (JSBACH, LPJmL, ORCHIDEE) and three for specific ecosystems (Scots pine forests: BASFOR; winter wheat fields: EPIC; grasslands: PASIM). The periods 1971–2000 and 2071–2100 are compared. Climate data are based on observations and on output from the regional climate model REMO using the SRES A1B scenario. The risk analysis is carried out for ∼22 000 grid cells of 0.25° × 0.25° across Europe. For each grid cell, drought vulnerability and risk are quantified for five seasonal variables: net primary and ecosystem productivity (NPP, NEP), heterotrophic respiration (RH), soil water content and evapotranspiration. Climate change is expected to lead to increased drought risks to net primary productivity in the Mediterranean area: five of the models estimate that risk will exceed 15%. The risks will increase mainly because of greater drought probability; ecosystem vulnerability will increase to lesser extent. Because NPP will be affected more than RH, future C-sequestration (NEP) will also be at risk predominantly in southern Europe, with risks exceeding 0.25 g C m−2 d−1 according to most models, amounting to reductions in carbon sequestration of 20 to 80%.

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