scholarly journals Developing and optimizing shrub parameters representing sagebrush (<i>Artemisia</i> spp.) ecosystems in the northern Great Basin using the Ecosystem Demography (EDv2.2) model

2019 ◽  
Vol 12 (11) ◽  
pp. 4585-4601
Author(s):  
Karun Pandit ◽  
Hamid Dashti ◽  
Nancy F. Glenn ◽  
Alejandro N. Flores ◽  
Kaitlin C. Maguire ◽  
...  
Keyword(s):  
Climate Change ◽  
Great Basin ◽  
Dynamic Models ◽  
Gross Primary Production ◽  
Model Performance ◽  
Field Measurements ◽  
Fire Regimes ◽  
Ecosystem Model ◽  
Sagebrush Steppe ◽  
Steppe Ecosystem

Abstract. Ecosystem dynamic models are useful for understanding ecosystem characteristics over time and space because of their efficiency over direct field measurements and applicability to broad spatial extents. Their application, however, is challenging due to internal model uncertainties and complexities arising from distinct qualities of the ecosystems being analyzed. The sagebrush-steppe ecosystem in western North America, for example, has substantial spatial and temporal heterogeneity as well as variability due to anthropogenic disturbance, invasive species, climate change, and altered fire regimes, which collectively make modeling dynamic ecosystem processes difficult. Ecosystem Demography (EDv2.2) is a robust ecosystem dynamic model, initially developed for tropical forests, that simulates energy, water, and carbon fluxes at fine scales. Although EDv2.2 has since been tested on different ecosystems via development of different plant functional types (PFT), it still lacks a shrub PFT. In this study, we developed and parameterized a shrub PFT representative of sagebrush (Artemisia spp.) ecosystems in order to initialize and test it within EDv2.2, and to promote future broad-scale analysis of restoration activities, climate change, and fire regimes in the sagebrush-steppe ecosystem. Specifically, we parameterized the sagebrush PFT within EDv2.2 to estimate gross primary production (GPP) using data from two sagebrush study sites in the northern Great Basin. To accomplish this, we employed a three-tier approach. (1) To initially parameterize the sagebrush PFT, we fitted allometric relationships for sagebrush using field-collected data, information from existing sagebrush literature, and parameters from other land models. (2) To determine influential parameters in GPP prediction, we used a sensitivity analysis to identify the five most sensitive parameters. (3) To improve model performance and validate results, we optimized these five parameters using an exhaustive search method to estimate GPP, and compared results with observations from two eddy covariance (EC) sites in the study area. Our modeled results were encouraging, with reasonable fidelity to observed values, although some negative biases (i.e., seasonal underestimates of GPP) were apparent. Our finding on preliminary parameterization of the sagebrush shrub PFT is an important step towards subsequent studies on shrubland ecosystems using EDv2.2 or any other process-based ecosystem model.

scholarly journals Optimizing shrub parameters to estimate gross primary production of the sagebrush ecosystem using the Ecosystem Demography (EDv2.2) model

2018 ◽  
Author(s):  
Karun Pandit ◽  
Hamid Dashti ◽  
Nancy F. Glenn ◽  
Alejandro N. Flores ◽  
Kaitlin C. Maguire ◽  
...  
Keyword(s):  
Climate Change ◽  
Invasive Species ◽  
Primary Production ◽  
Dynamic Models ◽  
Gross Primary Production ◽  
Ecosystem Dynamics ◽  
Spatiotemporal Variability ◽  
Sagebrush Steppe ◽  
Steppe Ecosystems ◽  
Global Carbon

Abstract. Gross primary production (GPP) is one of the most critical processes in the global carbon cycle, but is difficult to quantify in part because of its high spatiotemporal variability. Direct techniques to quantify GPP are lacking, thus, researchers rely on data inferred from eddy covariance (EC) towers and/or ecosystem dynamic models. The latter are useful to quantify GPP over time and space because of their efficiency over direct field measurements and applicability to broad spatial extents. However, such models have also been associated with internal uncertainties and complexities arising from distinct qualities of the ecosystem being analyzed. Widely distributed sagebrush-steppe ecosystems in western North America are threatened by anthropogenic disturbance, invasive species, climate change, and altered fire regimes. Although land managers have focused on different restoration techniques, the effects of these activities and their interactions with fire, climate change, and invasive species on ecosystem dynamics are poorly understood. In this study, we applied an ecosystem dynamic model, Ecosystem Demography (EDv2.2), to parameterize and predict GPP for sagebrush-steppe ecosystems in the Reynolds Creek Experimental Watershed (RCEW), located in the northern Great Basin. Our primary objective was to develop and parameterize a sagebrush (Artemisia spp.) shrubland Plant Functional Type (PFT) for use in the EDv2.2 model, which will support future studies to model estimates of GPP under different climate and management scenarios. To accomplish this, we employed a three-tiered approach. First, to parameterize the sagebrush PFT, we fitted allometric relationships for sagebrush using field-collected data, gathered information from existing sagebrush literature, and borrowed values from other PFTs in EDv2.2. Second, we identified the five most sensitive parameters out of thirteen that were found to be influential in GPP prediction based on previous studies. Third, we optimized the five parameters using an exhaustive search method to predict GPP, and performed validation using observations from two EC sites in the study area. Our modeled results were encouraging, with reasonable fidelity to observed values, although some negative biases (i.e., seasonal underestimates of GPP) were apparent. We expect that, with further refinement, the resulting sagebrush PFT will permit explicit scenario testing of potential anthropogenic modifications of GPP in sagebrush ecosystems, and will contribute to a better understanding of the role of sagebrush ecosystems in shaping global carbon cycles.

scholarly journals Uncertainty sources in simulated ecosystem indicators of the 21st century climate change

2019 ◽  
Author(s):  
Jarmo Mäkelä ◽  
Francesco Minunno ◽  
Tuula Aalto ◽  
Annikki Mäkelä ◽  
Tiina Markkanen ◽  
...  
Keyword(s):  
Climate Change ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Ecosystem Model ◽  
Forest Growth ◽  
Model Parameters ◽  
Management Actions ◽  
Uncertainty Sources ◽  
Ecosystem Indicators ◽  
Rcp Scenario

Abstract. The forest ecosystems are already responding to increased CO2 concentrations and changing environmental conditions. These ongoing developments affect how societies can utilise and benefit from the woodland areas in the future, be it e.g. climate change mitigation as carbon sinks, lumber for wood industry or preserved for nature tourism and recreational activities. We assess the effect and the relative magnitude of different uncertainty sources in ecosystem model simulations from the year 1980 to 2100 for two Finnish boreal forest sites. The models used in this study are the land ecosystem model JSBACH and the forest growth model PREBAS. The considered uncertainty sources for both models are model parameters, four prescribed climates and two RCP (Representative Concentration Pathway) scenarios. PREBAS simulations also include an additional RCP scenario and two forest management actions. We assess the effect of these sources at four different stages of the simulations on several ecosystem indicators of climate change, e.g. gross primary production (GPP), ecosystem respiration, soil moisture, recurrence of drought, length of the vegetation active period (VAP), length of the snow melting period and the stand volume. The climate model uncertainty remains roughly the same throughout the simulations and is overtaken by the RCP scenario impact halfway through the experiment. The management actions are the most dominant uncertainty factors for Hyytiälä and as important as RCP scenarios at the end of the simulations, but contribute only half as much for Sodankylä. The parameter uncertainty is the most elusive to estimate due to non-linear and adverse effects on the simulated ecosystem indicators.

Nutrient constraints on the Amazon carbon sink: from field measurements to model projections

2020 ◽  
Author(s):  
Katrin Fleischer ◽  
Carlos Alberto Quesada ◽  
David Lapola ◽  
Lucia Fuchslueger ◽  
Laynara Lugli ◽  
...  
Keyword(s):  
Climate Change ◽  
Atmospheric Carbon Dioxide ◽  
Amazon Basin ◽  
Carbon Sink ◽  
Soil Phosphorus ◽  
Field Measurements ◽  
Ecosystem Model ◽  
Future Research ◽  
The Future ◽  
Increasing Demand

&lt;p&gt;The Amazon rainforest faces immense pressures from human-induced deforestation and climate change and its future existence is largely indeterminate. Accurately projecting the forest&amp;#8217;s response to future conditions, and thus preparing for the best possible outcome, requires a sound process-based understanding of its ecological and biogeochemical functioning. The intact forest acts as a sink of atmospheric carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), however, this invaluable function is slowing down for unclear reasons, according to long-term plot measurements of tree growth. Earth system models, on the other hand, assume a continuous sink of carbon into the 21&lt;sup&gt;st&lt;/sup&gt; century, predominantly driven by CO&lt;sub&gt;2&lt;/sub&gt; fertilization, concurrently buffering against adverse effects by climate change. Advancing empirical and experimental evidence points to strong nutrient constraints on the Amazon carbon sink, foremostly by phosphorus and other cations, so that the projected strength of the future carbon sink is certainly unrealistic. It is highly uncertain, however, to which degree nutrients are and will diminish elevated CO&lt;sub&gt;2&lt;/sub&gt;-induced productivity, and to which extent plant-based mechanisms may upregulate phosphorus supply or optimize phosphorus use to facilitate the increasing demand by elevated CO&lt;sub&gt;2&lt;/sub&gt;. Site-scale ecosystem model ensemble analysis underscores the diverging hypotheses on phosphorus feedbacks we are currently facing. In addition, heterogeneous soil phosphorus availability across the Amazon basin, in combination with a hyperdiverse plant community, challenges current efforts to project phosphorus constraints on the future of the Amazon carbon sink. We here give an outlook of current progress and future research needs of model-experiment integration to tackle this pressing question.&lt;/p&gt;

scholarly journals Modeling and Monitoring Terrestrial Primary Production in a Changing Global Environment: Toward a Multiscale Synthesis of Observation and Simulation

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Shufen Pan ◽  
Hanqin Tian ◽  
Shree R. S. Dangal ◽  
Zhiyun Ouyang ◽  
Bo Tao ◽  
...  
Keyword(s):  
Primary Production ◽  
Model Simulation ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Terrestrial Ecosystem ◽  
Field Measurements ◽  
Ecosystem Model ◽  
Global Environment ◽  
Ecosystem Models ◽  
Key Indicator

There is a critical need to monitor and predict terrestrial primary production, the key indicator of ecosystem functioning, in a changing global environment. Here we provide a brief review of three major approaches to monitoring and predicting terrestrial primary production: (1) ground-based field measurements, (2) satellite-based observations, and (3) process-based ecosystem modelling. Much uncertainty exists in the multi-approach estimations of terrestrial gross primary production (GPP) and net primary production (NPP). To improve the capacity of model simulation and prediction, it is essential to evaluate ecosystem models against ground and satellite-based measurements and observations. As a case, we have shown the performance of the dynamic land ecosystem model (DLEM) at various scales from site to region to global. We also discuss how terrestrial primary production might respond to climate change and increasing atmospheric CO2and uncertainties associated with model and data. Further progress in monitoring and predicting terrestrial primary production requires a multiscale synthesis of observations and model simulations. In the Anthropocene era in which human activity has indeed changed the Earth’s biosphere, therefore, it is essential to incorporate the socioeconomic component into terrestrial ecosystem models for accurately estimating and predicting terrestrial primary production in a changing global environment.

VEMAP 2: MONTHLY ECOSYSTEM MODEL RESPONSES TO U.S. CLIMATE CHANGE, 1994-2100

2005 ◽  
Author(s):  
S. AULENBACH ◽  
C. DALY ◽  
H. H. FISHER ◽  
W. P. GIBSON ◽  
C. KAUFMAN ◽  
...  
Keyword(s):  
Climate Change ◽  
Ecosystem Model

VEMAP 2: ANNUAL ECOSYSTEM MODEL RESPONSES TO U.S. CLIMATE CHANGE, 1994-2100

2005 ◽  
Author(s):  
S. AULENBACH ◽  
C. DALY ◽  
H. H. FISHER ◽  
W. P. GIBSON ◽  
C. KAUFMAN ◽  
...  
Keyword(s):  
Climate Change ◽  
Ecosystem Model

Shrub Size Modulates Resource Heterogeneity in a Sagebrush-Steppe Ecosystem

2020 ◽  
Vol 80 (1) ◽  
pp. 28
Author(s):  
Lin Liu ◽  
Kari E. Veblen ◽  
Thomas A. Monaco
Keyword(s):  
Sagebrush Steppe ◽  
Resource Heterogeneity ◽  
Steppe Ecosystem

Transformation

2018 ◽  
Author(s):  
Karen J. Esler ◽  
Anna L. Jacobsen ◽  
R. Brandon Pratt
Keyword(s):  
Climate Change ◽  
Fire Regimes ◽  
Human Populations ◽  
Land Use Land Cover ◽  
Mountainous Areas ◽  
Drivers Of Change ◽  
Natural Systems ◽  
Natural Landscapes ◽  
Habitat Conversion ◽  
Residential Use

Extensive habitat loss and habitat conversion has occurred across all mediterranean-type climate (MTC) regions, driven by increasing human populations who have converted large tracts of land to production, transport, and residential use (land-use, land-cover change) while simultaneously introducing novel forms of disturbance to natural landscapes. Remaining habitat, often fragmented and in isolated or remote (mountainous) areas, is threatened and degraded by altered fire regimes, introduction of invasive species, nutrient enrichment, and climate change. The types and impacts of these threats vary across MTC regions, but overall these drivers of change show little signs of abatement and many have the potential to interact with MTC region natural systems in complex ways.

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