scholarly journals Root foraging alters global patterns of ecosystem legacy from climate perturbations

2021 ◽  
Author(s):  
Max Berkelhammer ◽  
Beth Drewniak ◽  
Benjamin Ahlswede ◽  
Miquel Gonzalez-Meler
Keyword(s):  
Land Surface ◽  
Climate Extremes ◽  
Terrestrial Ecosystems ◽  
Arid Ecosystems ◽  
Earth System ◽  
Area Index ◽  
Ecosystem Sensitivity ◽  
Initial Event ◽  
Global Patterns ◽  
Rain Events

The response of terrestrial ecosystems to climate perturbations typically persist longer than the timescale of the forcing, a phenomenon that is broadly referred to as ecosystem legacy. Understanding the strength of legacy is critical for predicting ecosystem sensitivity to climate extremes and the extent to which persistent changes in land surface-atmosphere exchange might feedback onto the climate, for example, extending drought. The cause of ecosystem legacy has been tied to numerous factors such as changes in leaf area index, however, few studies have tested how changes in root profiles in response to stress might alter an ecosystem's recovery time. We utilize an Earth System Model that includes a dynamic root module where vegetation can forage for water and nutrients by altering their root profiles. As expected, the simulations show that in response to water stress events most ecosystems deepen their root profiles. In semi-arid ecosystems, this response expedites recovery (i.e. less legacy) relative to simulations without dynamics roots because access to deeper water pools after the initial event remains favorable. In wetter ecosystems, the development of deeper root profiles slows down the recovery timescale (i.e. more legacy) because the deeper root profile reduces access to nutrients. The recovery of hyperarid systems is also delayed presumably to the loss of shallow roots and ability to access water from smaller rain events. The results show that the response of root profiles to external forcing is a critical component of global patterns of legacy that is not typically represented in Earth System Models.

scholarly journals Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature)

2006 ◽  
Vol 6 (1) ◽  
pp. 107-173 ◽  
Author(s):  
A. Guenther ◽  
T. Karl ◽  
P. Harley ◽  
C. Wiedinmyer ◽  
P. I. Palmer ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Model Development ◽  
Terrestrial Ecosystems ◽  
Global Climate Models ◽  
Earth System ◽  
Area Index ◽  
Isoprene Emission ◽  
Global Emission ◽  
High Emission

Abstract. Reactive gases and aerosols are produced by terrestrial ecosystems, processed within plant canopies, and can then be emitted into the above-canopy atmosphere. Estimates of the above-canopy fluxes are needed for quantitative earth system studies and assessments of past, present and future air quality and climate. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) is described and used to quantify net terrestrial biosphere emission of isoprene into the atmosphere. MEGAN is designed for both global and regional emission modeling and has global coverage with ~1 km2 spatial resolution. Field and laboratory investigations of the processes controlling isoprene emission are described and data available for model development and evaluation are summarized. The factors controlling isoprene emissions include biological, physical and chemical driving variables. MEGAN driving variables are derived from models and satellite and ground observations. Broadleaf trees, mostly in the tropics, contribute about half of the estimated global annual isoprene emission due to their relatively high emission factors and because they are often exposed to conditions that are conducive for isoprene emission. The remaining flux is primarily from shrubs which are widespread and dominate at higher latitudes. MEGAN estimates global annual isoprene emissions of ~600 Tg isoprene but the results are very sensitive to the driving variables, including temperature, solar radiation, Leaf Area Index, and plant functional type. The annual global emission estimated with MEGAN ranges from about 500 to 750 Tg isoprene depending on the driving variables that are used. Differences in estimated emissions are more than a factor of 3 for specific times and locations. It is difficult to evaluate isoprene emission estimates using the concentration distributions simulated using chemistry and transport models due to the substantial uncertainties in other model components. However, comparison with isoprene emissions estimated from satellite formaldehyde observations indicates reasonable agreement. The sensitivity of isoprene emissions to earth system changes (e.g., climate and landcover) suggests potentially large changes in future emissions. Using temperature distributions simulated by global climate models for year 2100, MEGAN estimates that isoprene emissions increase by more than a factor of two. This is considerably greater than previous estimates and additional observations are needed to evaluate and improve the methods used to predict future isoprene emissions.

scholarly journals Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications

2019 ◽  
Vol 11 (18) ◽  
pp. 2103 ◽  
Author(s):  
Francisco Javier García-Haro ◽  
Fernando Camacho ◽  
Beatriz Martínez ◽  
Manuel Campos-Taberner ◽  
Beatriz Fuster ◽  
...  
Keyword(s):  
Land Surface ◽  
Expert Knowledge ◽  
Terrestrial Ecosystems ◽  
Environmental Applications ◽  
Climate Data ◽  
Area Index ◽  
Infrared Imager ◽  
Statistical Relationships ◽  
Spectral Mixture

The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed by vegetation (FAPAR) and the fractional vegetation cover (FVC), for the whole Meteosat disk at two temporal frequencies, daily and 10-days. The FVC algorithm relies on a novel stochastic spectral mixture model which addresses the variability of soils and vegetation types using statistical distributions whereas the LAI and FAPAR algorithms use statistical relationships general enough for global applications. An overview of the LSA SAF SEVIRI/MSG vegetation products, including expert knowledge and quality assessment of its internal consistency is provided. The climate data record (CDR) is freely available in the LSA SAF, offering more than fifteen years (2004-present) of homogeneous time series required for climate and environmental applications. The high frequency and good temporal continuity of SEVIRI products addresses the needs of near-real-time users and are also suitable for long-term monitoring of land surface variables. The study also evaluates the potential of the SEVIRI/MSG vegetation products for environmental applications, spanning from accurate monitoring of vegetation cycles to resolving long-term changes of vegetation.

A review of the application of BRDF models to infer land cover parameters at regional and global scales

2001 ◽  
Vol 25 (4) ◽  
pp. 483-511 ◽  
Author(s):  
Gareth Roberts
Keyword(s):  
Land Surface ◽  
Lower Boundary ◽  
Terrestrial Ecosystems ◽  
Remotely Sensed Data ◽  
Area Index ◽  
Lower Boundary Condition ◽  
Surface Parameters ◽  
Case Examples ◽  
Global Circulation Models ◽  
Land Surface Parameters

This paper presents a review of the application of Bi-directional Reflectance Distribution Function (BRDF) models in the inference of land surface parameters at regional and global scales using remotely sensed data. Information on land surface parameters, such as Leaf Area Index (LAI), fraction of Absorbed Photosynthetically Active Radiation (fAPAR), aerodynamic surface roughness and albedo, are valuable for understanding the transfer of energy and mass between terrestrial ecosystems and the atmosphere (e.g., carbon, nitrogen and methane cycling) and for ingestion into the lower boundary condition of global circulation models (GCM)s. Conventional techniques for acquiring information on land surface parameters do not account for or utilize the directional nature of surface reflectance. This paper reviews empirical, semi-empirical and, to a lesser extent, physical BRDF models that describe the surface BRDF. In each case examples are given of their application in inferring land surface parameters. The review concludes by discussing the future prospects of BRDF modelling using spaceborne sensors.

Ecosystem sensitivity to land-surface models and leaf area index

1996 ◽  
Vol 13 (1-4) ◽  
pp. 89-98 ◽  
Author(s):  
W.J. Parton ◽  
A. Haxeltine ◽  
P. Thornton ◽  
R. Anne ◽  
Melannie Hartman
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Land Surface Models ◽  
Area Index ◽  
Ecosystem Sensitivity ◽  
Surface Models

scholarly journals Implementation and validation of a new irrigation scheme in the ISBA land surface model

2021 ◽  
Author(s):  
Arsène Druel ◽  
Simon Munier ◽  
Anthony Mucia ◽  
Clément Albergel ◽  
Jean-Christophe Calvet
Keyword(s):  
Land Surface ◽  
Vegetation Type ◽  
Spatial Scales ◽  
Terrestrial Ecosystems ◽  
Moisture Stress ◽  
Surface Model ◽  
Irrigation Scheme ◽  
Area Index ◽  
Natural Processes ◽  
The Impact

Abstract. With an increase in the number of natural processes represented, global land surface models (LSMs) have become more and more accurate in representing natural terrestrial ecosystems. However, they are still limited, especially in the representation of the impact of agriculture on land surface variables. This is particularly true for agro-hydrological processes related to a strong human control on freshwater. While most LSMs consider natural processes only, the development of human-related processes, e.g. crop phenology and irrigation in LSMs, is key. In this study we present the implementation of a new irrigation scheme in the ISBA (Interaction between Soil, Biosphere, and Atmosphere) LSM. This highly flexible scheme is designed to account for various configurations and can be applied at different spatial scales. For each vegetation type within a model grid cell, three irrigation systems can be used at the same time. A limited number of parameters are used to control (1) the amount of water used for irrigation, (2) irrigation triggering (based on the soil moisture stress) and (3) crop seasonality (emergence, harvesting). After a presentation of the simulations of the new scheme at a plot scale, an evaluation is proposed over Nebraska (USA). This region is chosen for its high irrigation density and because independent observations of irrigation practices can be used to verify the simulated irrigation amounts. The ISBA simulations with and without the irrigation scheme are compared to different satellite-based observations. The comparison shows that the irrigation scheme improves the simulated vegetation variables such as leaf area index and gross primary productivity and other variables largely impacted by irrigation such as evapotranspiration and land surface temperature. In addition to a better representation of land surface processes, the results point to potential applications of this new version of the ISBA model for water resource monitoring and climate change impact studies.

scholarly journals Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature)

2006 ◽  
Vol 6 (11) ◽  
pp. 3181-3210 ◽  
Author(s):  
A. Guenther ◽  
T. Karl ◽  
P. Harley ◽  
C. Wiedinmyer ◽  
P. I. Palmer ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Model Development ◽  
Terrestrial Ecosystems ◽  
Global Climate Models ◽  
Earth System ◽  
Area Index ◽  
Isoprene Emission ◽  
High Emission ◽  
Reactive Gases

Abstract. Reactive gases and aerosols are produced by terrestrial ecosystems, processed within plant canopies, and can then be emitted into the above-canopy atmosphere. Estimates of the above-canopy fluxes are needed for quantitative earth system studies and assessments of past, present and future air quality and climate. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) is described and used to quantify net terrestrial biosphere emission of isoprene into the atmosphere. MEGAN is designed for both global and regional emission modeling and has global coverage with ~1 km2 spatial resolution. Field and laboratory investigations of the processes controlling isoprene emission are described and data available for model development and evaluation are summarized. The factors controlling isoprene emissions include biological, physical and chemical driving variables. MEGAN driving variables are derived from models and satellite and ground observations. Tropical broadleaf trees contribute almost half of the estimated global annual isoprene emission due to their relatively high emission factors and because they are often exposed to conditions that are conducive for isoprene emission. The remaining flux is primarily from shrubs which have a widespread distribution. The annual global isoprene emission estimated with MEGAN ranges from about 500 to 750 Tg isoprene (440 to 660 Tg carbon) depending on the driving variables which include temperature, solar radiation, Leaf Area Index, and plant functional type. The global annual isoprene emission estimated using the standard driving variables is ~600 Tg isoprene. Differences in driving variables result in emission estimates that differ by more than a factor of three for specific times and locations. It is difficult to evaluate isoprene emission estimates using the concentration distributions simulated using chemistry and transport models, due to the substantial uncertainties in other model components, but at least some global models produce reasonable results when using isoprene emission distributions similar to MEGAN estimates. In addition, comparison with isoprene emissions estimated from satellite formaldehyde observations indicates reasonable agreement. The sensitivity of isoprene emissions to earth system changes (e.g., climate and land-use) demonstrates the potential for large future changes in emissions. Using temperature distributions simulated by global climate models for year 2100, MEGAN estimates that isoprene emissions increase by more than a factor of two. This is considerably greater than previous estimates and additional observations are needed to evaluate and improve the methods used to predict future isoprene emissions.

scholarly journals A model using marginal efficiency of investment to analyze carbon and nitrogen interactions in terrestrial ecosystems (ACONITE Version 1)

2014 ◽  
Vol 7 (5) ◽  
pp. 2015-2037 ◽  
Author(s):  
R. Q. Thomas ◽  
M. Williams
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Primary Productivity ◽  
N Uptake ◽  
Terrestrial Ecosystems ◽  
N Fixation ◽  
Earth System ◽  
Area Index ◽  
Temperate Deciduous ◽  
C And N

Abstract. Carbon (C) and nitrogen (N) cycles are coupled in terrestrial ecosystems through multiple processes including photosynthesis, tissue allocation, respiration, N fixation, N uptake, and decomposition of litter and soil organic matter. Capturing the constraint of N on terrestrial C uptake and storage has been a focus of the Earth System Modeling community. However, there is little understanding of the trade-offs and sensitivities of allocating C and N to different tissues in order to optimize the productivity of plants. Here we describe a new, simple model of ecosystem C–N cycling and interactions (ACONITE), that builds on theory related to plant economics in order to predict key ecosystem properties (leaf area index, leaf C : N, N fixation, and plant C use efficiency) based on the outcome of assessments of the marginal change in net C or N uptake associated with a change in allocation of C or N to plant tissues. We simulated and evaluated steady-state ecosystem stocks and fluxes in three different forest ecosystems types (tropical evergreen, temperate deciduous, and temperate evergreen). Leaf C : N differed among the three ecosystem types (temperate deciduous < tropical evergreen < temperature evergreen), a result that compared well to observations from a global database describing plant traits. Gross primary productivity (GPP) and net primary productivity (NPP) estimates compared well to observed fluxes at the simulation sites. Simulated N fixation at steady-state, calculated based on relative demand for N and the marginal return on C investment to acquire N, was an order of magnitude higher in the tropical forest than in the temperate forest, consistent with observations. A sensitivity analysis revealed that parameterization of the relationship between leaf N and leaf respiration had the largest influence on leaf area index and leaf C : N. A parameter governing how photosynthesis scales with day length had the largest influence on total vegetation C, GPP, and NPP. Multiple parameters associated with photosynthesis, respiration, and N uptake influenced the rate of N fixation. Overall, our ability to constrain leaf area index and allow spatially and temporally variable leaf C : N can help address challenges simulating these properties in ecosystem and Earth System models. Furthermore, the simple approach with emergent properties based on coupled C–N dynamics has potential for use in research that uses data-assimilation methods to integrate data on both the C and N cycles to improve C flux forecasts.

scholarly journals Testing stomatal models at stand level in deciduous angiosperm and evergreen gymnosperm forests using CliMA Land (v0.1)

2021 ◽  
Author(s):  
Yujie Wang ◽  
Philipp Köhler ◽  
Liyin He ◽  
Russell Doughty ◽  
Renato K. Braghiere ◽  
...  
Keyword(s):  
Optical Properties ◽  
Land Surface ◽  
System Modeling ◽  
Optimization Models ◽  
Climate Modelling ◽  
Earth System ◽  
Water Fluxes ◽  
Area Index ◽  
Single Leaf ◽  
The Impact

Abstract. At the leaf level, stomata control the exchange of water and carbon across the air-leaf interface. Stomatal conductance is typically modeled empirically, based on environmental conditions at the leaf surface. Recently developed stomatal optimization models show great skills at predicting carbon and water fluxes at both the leaf and tree levels. However, it has not been evaluated how well the optimization models perform at larger scales. Furthermore, stomatal models are often used with simple single-leaf representations of canopy radiative transfer (RT), such as big-leaf models. Nevertheless, the single-leaf canopy RT schemes do not have the capability to model optical properties of the leaves or the entire canopy. As a result, they are unable to evaluate the impact of vertical gradients within the canopy, or directly link canopy optical properties with light distribution within the canopy to remote sensing data observed from afar. Here we incorporated one optimization-based and two empirical stomatal models with a comprehensive RT model in the land component of a new Earth System model within CliMA, the Climate Modelling Alliance. The model allowed us to simultaneously simulate carbon and water fluxes as well as leaf and canopy reflectance and fluorescence spectra. We tested our model by comparing our modeled carbon and water fluxes and solar-induced chlorophyll fluorescence (SIF) to two flux tower observations (a gymnosperm forest and an angiosperm forest) and satellite SIF retrievals, respectively. All three stomatal models quantitatively predicted the carbon and water fluxes for both forests. The optimization model, in particular, showed increased skill in predicting the water flux given the lower error (c. 14.2 % and 21.8 % improvement for the gymnosperm and angiosperm forests, respectively) and better 1 : 1 comparison (slope increases from c. 0.34 to 0.91 for the gymnosperm forest, and from c. 0.38 to 0.62 for the angiosperm forest). Our model also predicted the SIF yield, quantitatively reproducing seasonal cycles for both forests. We found that using stomatal optimization with a comprehensive RT model showed high accuracy in simulating land surface processes. The ever-increasing number of regional and global datasets of terrestrial plants, such as leaf area index and chlorophyll contents, will help parameterize the land model and improve future Earth System modeling in general.

scholarly journals Biogeophysical feedbacks enhance Arctic terrestrial carbon sink in regional Earth system dynamics

2014 ◽  
Vol 11 (5) ◽  
pp. 6715-6754 ◽  
Author(s):  
W. Zhang ◽  
C. Jansson ◽  
P. A. Miller ◽  
B. Smith ◽  
P. Samuelsson
Keyword(s):  
Land Surface ◽  
General Circulation ◽  
Terrestrial Ecosystems ◽  
General Circulation Models ◽  
The Arctic ◽  
Earth System ◽  
Terrestrial Carbon ◽  
Near Surface ◽  
C Cycle ◽  
Biogeophysical Feedbacks

Abstract. Continued warming of the Arctic will likely accelerate terrestrial carbon (C) cycling by increasing both uptake and release of C. There are still large uncertainties in modelling Arctic terrestrial ecosystems as a source or sink of C. Most modelling studies assessing or projecting the future fate of C exchange with the atmosphere are based an either stand-alone process-based models or coupled climate–C cycle general circulation models, in either case disregarding biogeophysical feedbacks of land surface changes to the atmosphere. To understand how biogeophysical feedbacks will impact on both climate and C budget over Arctic terrestrial ecosystems, we apply the regional Earth system model RCA-GUESS over the CORDEX-Arctic domain. The model is forced with lateral boundary conditions from an GCMs CMIP5 climate projection under the RCP 8.5 scenario. We perform two simulations with or without interactive vegetation dynamics respectively to assess the impacts of biogeophysical feedbacks. Both simulations indicate that Arctic terrestrial ecosystems will continue to sequester C with an increased uptake rate until 2060s–2070s, after which the C budget will return to a weak C sink as increased soil respiration and biomass burning outpaces increased net primary productivity. The additional C sinks arising from biogeophysical feedbacks are considerable, around 8.5 Gt C, accounting for 22% of the total C sinks, of which 83.5% are located in areas of Arctic tundra. Two opposing feedback mechanisms, mediated by albedo and evapotranspiration changes respectively, contribute to this response. Albedo feedback dominates over winter and spring season, amplifying the near-surface warming by up to 1.35 K in spring, while evapotranspiration feedback dominates over summer exerting the evaporative cooling by up to 0.81 K. Such feedbacks stimulate vegetation growth with an earlier onset of growing-season, leading to compositional changes in woody plants and vegetation redistribution.

scholarly journals Accounting for forest age in the tile-based dynamic global vegetation model JSBACH4 (4.20p7; git feature/forests) – a land surface model for the ICON-ESM

2020 ◽  
Vol 13 (1) ◽  
pp. 185-200 ◽  
Author(s):  
Julia E. M. S. Nabel ◽  
Kim Naudts ◽  
Julia Pongratz
Keyword(s):  
Forest Management ◽  
Land Surface ◽  
Surface Model ◽  
Earth System ◽  
Forest Age ◽  
Age Classes ◽  
Dynamic Global Vegetation Model ◽  
Area Index ◽  
Global Vegetation ◽  
Age Structures

Abstract. Natural and anthropogenic disturbances, in particular forest management, affect forest age structures all around the globe. Forest age structures in turn influence key land surface processes, such as photosynthesis and thus the carbon cycle. Yet, many dynamic global vegetation models (DGVMs), including those used as land surface models (LSMs) in Earth system models (ESMs), do not account for subgrid forest age structures, despite being used to investigate land-use effects on the global carbon budget or simulating biogeochemical responses to climate change. In this paper we present a new scheme to introduce forest age classes in hierarchical tile-based DGVMs combining benefits of recently applied approaches the first being a computationally efficient age-dependent simulation of all relevant processes, such as photosynthesis and respiration, using a restricted number of age classes and the second being the tracking of the exact forest age, which is a prerequisite for any implementation of age-based forest management. This combination is achieved by using the tile hierarchy to track the area fraction for each age on an aggregated plant functional type level, whilst simulating the relevant processes for a set of age classes. We describe how we implemented this scheme in JSBACH4, the LSM of the ICOsahedral Non-hydrostatic Earth system model (ICON-ESM). Subsequently, we compare simulation output to global observation-based products for gross primary production, leaf area index, and above-ground biomass to assess the ability of simulations with and without age classes to reproduce the annual cycle and large-scale spatial patterns of these variables. The comparisons show decreasing differences and increasing computation costs with an increasing number of distinguished age classes. The results demonstrate the benefit of the introduction of age classes, with the optimal number of age classes being a compromise between computation costs and error reduction.

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