Using Landlab, a Fine Scale Biogeography Model, to Measure the Sustainability of Semi-arid Vegetation in a Changing Climate PDF Download
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Author: Lucy Gelb
Publisher:
ISBN:
Category : Biogeography
Languages : en
Pages : 93
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Book Description
"The distribution of vegetation in water-limited ecosystems is a product of complex and nonlinear interactions between climatic forcings (e.g., precipitation, temperature, solar radiation) and the underlying geomorphic template, which includes topography, geology, and soils. Changes in climate, particularly in precipitation and temperature, can dramatically alter the organization of vegetation. This is especially true in ecotones such as our area of study: the semi-arid transition between Great Basin shrub-steppe ecosystems and the coniferous forests of the Northern Rockies. Understanding and predicting how the spatial composition of terrestrial vegetation communities will change in these ecosystems is critical to predicting important future landscape changes such as landslides, erosion, fires, and water storage capacity. This study promotes understanding of the relative sensitivity of vegetation types to changes in weather and climate in water-limited environments using a land modeling framework. Specifically, we use the Landlab framework to develop and conduct a suite of numerical experiments that use ensemble methods to diagnose how changes in precipitation and temperature regimes affect the organization of plant functional types across varying hillslope aspects. This methodology yielded a broader perspective than previous studies that rely on analysis of deterministic runs, including detailed information about the variation within the results of each climate scenario we modeled. The impact of topographic variation such as changes in elevation or aspect are not not the same for temperature and precipitation, and understanding the relative importance of each is useful when extending the implications of results from this study to varying real-world locations. We synthesized a watershed using Landlab́09s landscape evolution capabilities to produce a topographic setting with contrasting hillslope aspects and randomly seeded vegetation (trees, shrubs, grasses, and bare soil). We then allowed that initial vegetation distribution to equilibrate to climatic conditions broadly consistent with contemporary climate. We then subjected the output distribution of vegetation to a perturbed climate, created by interpolating a group of Coupled Model Inter-Comparison Project 5 (CMIP5) climate projections that were downscaled using the Multivariate Adaptive Constructed Analogs (MACA) method to the approximate elevation of the site. We designed a suite of numerical experiments that investigated the sensitivity of the distribution of vegetation to changes in precipitation and temperature independently, as well as the combined effects of changes in both. To examine the sensitivity of vegetation composition to individual realizations of precipitation and temperature time series, and therefore the robustness of any conclusions about changes in vegetation composition to climate, we took an ensemble approach with all simulations in which five-hundred realizations of precipitation and temperature forcings consistent with the altered climate were used to drive the climate change scenarios. We then investigated the probability density functions of the distribution of tree, shrub, grass, and bare soil coverage across aspects and simulations. Regardless of scenario, we find that vegetation patterns on north-facing slopes were constant regardless of changes to precipitation or temperature alone. By contrast, vegetation patterns on south-facing slopes were sensitive to changes in both precipitation and temperature. In climate scenarios with reduced precipitation, the percentage of area covered by trees declined on south-facing slopes, while shrub coverage increased to fill areas vacated by trees. Temperature exacerbated this trend. A climate scenario with low precipitation and high temperatures had the lowest recorded tree cover on south-facing slopes, though high precipitation negated the effects of temperature. Using the Landlab framework allowed us to rapidly develop an effective model of the relative sensitives of vegetation types and conclude that precipitation is the most important variable with regard to forest replacement by grasses and shrubs in response to climate change. It is important to underscore, however, that the modeling framework used does not currently include key biogeochemical processes known to influence semi-arid ecosystems. As such, this study cannot examine nutrient limitations in these semi-arid ecosystems. This suggests a potential avenue for future study that leverages the modeling framework and approach taken here."--Boise State University ScholarWorks.
Author: Lucy Gelb
Publisher:
ISBN:
Category : Biogeography
Languages : en
Pages : 93
Get Book Here
Book Description
"The distribution of vegetation in water-limited ecosystems is a product of complex and nonlinear interactions between climatic forcings (e.g., precipitation, temperature, solar radiation) and the underlying geomorphic template, which includes topography, geology, and soils. Changes in climate, particularly in precipitation and temperature, can dramatically alter the organization of vegetation. This is especially true in ecotones such as our area of study: the semi-arid transition between Great Basin shrub-steppe ecosystems and the coniferous forests of the Northern Rockies. Understanding and predicting how the spatial composition of terrestrial vegetation communities will change in these ecosystems is critical to predicting important future landscape changes such as landslides, erosion, fires, and water storage capacity. This study promotes understanding of the relative sensitivity of vegetation types to changes in weather and climate in water-limited environments using a land modeling framework. Specifically, we use the Landlab framework to develop and conduct a suite of numerical experiments that use ensemble methods to diagnose how changes in precipitation and temperature regimes affect the organization of plant functional types across varying hillslope aspects. This methodology yielded a broader perspective than previous studies that rely on analysis of deterministic runs, including detailed information about the variation within the results of each climate scenario we modeled. The impact of topographic variation such as changes in elevation or aspect are not not the same for temperature and precipitation, and understanding the relative importance of each is useful when extending the implications of results from this study to varying real-world locations. We synthesized a watershed using Landlab́09s landscape evolution capabilities to produce a topographic setting with contrasting hillslope aspects and randomly seeded vegetation (trees, shrubs, grasses, and bare soil). We then allowed that initial vegetation distribution to equilibrate to climatic conditions broadly consistent with contemporary climate. We then subjected the output distribution of vegetation to a perturbed climate, created by interpolating a group of Coupled Model Inter-Comparison Project 5 (CMIP5) climate projections that were downscaled using the Multivariate Adaptive Constructed Analogs (MACA) method to the approximate elevation of the site. We designed a suite of numerical experiments that investigated the sensitivity of the distribution of vegetation to changes in precipitation and temperature independently, as well as the combined effects of changes in both. To examine the sensitivity of vegetation composition to individual realizations of precipitation and temperature time series, and therefore the robustness of any conclusions about changes in vegetation composition to climate, we took an ensemble approach with all simulations in which five-hundred realizations of precipitation and temperature forcings consistent with the altered climate were used to drive the climate change scenarios. We then investigated the probability density functions of the distribution of tree, shrub, grass, and bare soil coverage across aspects and simulations. Regardless of scenario, we find that vegetation patterns on north-facing slopes were constant regardless of changes to precipitation or temperature alone. By contrast, vegetation patterns on south-facing slopes were sensitive to changes in both precipitation and temperature. In climate scenarios with reduced precipitation, the percentage of area covered by trees declined on south-facing slopes, while shrub coverage increased to fill areas vacated by trees. Temperature exacerbated this trend. A climate scenario with low precipitation and high temperatures had the lowest recorded tree cover on south-facing slopes, though high precipitation negated the effects of temperature. Using the Landlab framework allowed us to rapidly develop an effective model of the relative sensitives of vegetation types and conclude that precipitation is the most important variable with regard to forest replacement by grasses and shrubs in response to climate change. It is important to underscore, however, that the modeling framework used does not currently include key biogeochemical processes known to influence semi-arid ecosystems. As such, this study cannot examine nutrient limitations in these semi-arid ecosystems. This suggests a potential avenue for future study that leverages the modeling framework and approach taken here."--Boise State University ScholarWorks.
Author: Sai Siddhartha Nudurupati
Publisher:
ISBN:
Category : Climatic changes
Languages : en
Pages : 127
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Book Description
Ecosystems are in transition globally with critical societal consequences. Global warming, growing climatic extremes, land degradation, human-introduced herbivores, and climate-related disturbances (wildfires, diseases, insect outbreaks) drive rapid changes in ecosystem productivity and structure, with complex feedbacks in watershed hydrology, geomorphology and biogeochemistry. There is need to develop models that can represent ecosystem changes by incorporating the role of individual plant patches. In my research I developed ecohydrologic components in Landlab, an open source toolkit written in Python (http://landlab.github.io/#/), to study global change drivers in watersheds with emphasis on woody plant encroachment (WPE). I will first discuss the development of Landlab, its design, architecture, and illustrate examples of building models with Landlab. I will then present the development of ecohydrologic components and illustrate examples of coupling these components for simulating local soil moisture and plant dynamics with spatially explicit cellular automaton (CA)-based plant establishment, mortality, fire, and grazing processes. Several key features of arid and semiarid ecosystems will be discussed. Coexistence of tree-grass cover on north facing slopes (NFS) and shrub cover on south facing slopes (SFS) in central New Mexico is attributed to the competitive advantage of trees due to their longer seed dispersal range against shrubs in cooler and moist NFS. Incorporating a rule to represent inhibitory effects of shrubs on grasses enhance modeled shrub cover, while both trees and grasses are favored when runon is included in the local soil moisture model. Feedbacks among livestock grazing, grassland fire frequency and size, resource redistribution on woody plant encroachment are investigated using different ecohydrologic model configurations. These feedbacks have led to a three-phase woody plant expansion processes in the model, with rates of encroachment controlled by the state transition probabilities of vegetation types in relation to plant susceptibility to fires, grazing, and age-related mortality. A critical area of woody plant emerges in the model with which a negative feedback between fire size and woody plant expansion begins, providing a spatially-explict modelling evidence to the alternative stable states hypothesis. Finally, I investigate the transient ecosystem response to climate variability since the Late Pleistocene using paleoclimatic reconstructions of precipitation and temperature in central New Mexico, USA. The interplay between ecosystem state, change in climate, resultant grass connectivity, and hence fire frequency, and topography are explored with an ecohydrologic model discussed earlier. A transition from cool-wet climate to a warm-dry climate leads to shrub expansion due to drought-induced loss of grass connectivity. Shrubs dominate the ecosystem if dry conditions persist longer. Transition back to a tree or grass dominated ecosystem from shrub dominated ecosystem can only happen when climate shifts from dry to wet. The importance of length of dry or wet spells on ecosystem structure is highlighted. Aspect plays a critical role in providing topographical refugia for trees during dry periods and influences the rate of ecosystem transitions during climate change.
Author: Sam Cushman
Publisher:
ISBN:
Category : Climatic changes
Languages : en
Pages : 56
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Book Description
Reliable predictions of how changing climate and disturbance regimes will affect forest ecosystems are crucial for effective forest management. Current fire and climate research in forest ecosystem and community ecology offers data and methods that can inform such predictions. However, research in these fields occurs at different scales, with disparate goals, methods, and context. Often results are not readily comparable among studies and defy integration. We discuss the strengths and weaknesses of three modeling paradigms: empirical gradient models, mechanistic ecosystem models, and stochastic landscape disturbance models. We then propose a synthetic approach to multi-scale analysis of the effects of climatic change and disturbance on forest ecosystems. Empirical gradient models provide an anchor and spatial template for stand-level forest ecosystem models by quantifying key parameters for individual species and accounting for broad-scale geographic variation among them. Gradient imputation transfers predictions of fine-scale forest composition and structure across geographic space. Mechanistic ecosystem dynamic models predict the responses of biological variables to specific environmental drivers and facilitate understanding of temporal dynamics and disequilibrium. Stochastic landscape dynamics models predict frequency, extent, and severity of broad-scale disturbance. A robust linkage of these three modeling paradigms will facilitate prediction of the effects of altered fire and other disturbance regimes on forest ecosystems at multiple scales and in the context of climatic variability and change.
Author: Mannava VK Sivakumar
Publisher: Springer Science & Business Media
ISBN: 3540724389
Category : Science
Languages : en
Pages : 629
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Book Description
Based on an International Workshop held in Arusha, Tanzania, this book presents state-of-the-art papers, real world applications, and innovative techniques for combating land degradation. It offers recommendations for effectively using weather and climate information for sustainable land management practices.
Author: Andrew C. Millington
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 480
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Book Description
Encompasses a wide-ranging selection of peer-reviewed papers covering geomorphology and biogeography including research which has sought to integrate the two disciplines. The main division of articles has been made in terms of timescales of the studies in which the majority of evidence presented relates to environments before the last 1000 years.
Author: C. Ashton Drew
Publisher: Springer Science & Business Media
ISBN: 1441973907
Category : Science
Languages : en
Pages : 319
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Book Description
Most projects in Landscape Ecology, at some point, define a species-habitat association. These models are inherently spatial, dealing with landscapes and their configurations. Whether coding behavioral rules for dispersal of simulated organisms through simulated landscapes, or designing the sampling extent of field surveys and experiments in real landscapes, landscape ecologists must make assumptions about how organisms experience and utilize the landscape. These convenient working postulates allow modelers to project the model in time and space, yet rarely are they explicitly considered. The early years of landscape ecology necessarily focused on the evolution of effective data sources, metrics, and statistical approaches that could truly capture the spatial and temporal patterns and processes of interest. Now that these tools are well established, we reflect on the ecological theories that underpin the assumptions commonly made during species distribution modeling and mapping. This is crucial for applying models to questions of global sustainability. Due to the inherent use of GIS for much of this kind of research, and as several authors’ research involves the production of multicolored map figures, there would be an 8-page color insert. Additional color figures could be made available through a digital archive, or by cost contributions of the chapter authors. Where applicable, would be relevant chapters’ GIS data and model code available through a digital archive. The practice of data and code sharing is becoming standard in GIS studies, is an inherent method of this book, and will serve to add additional research value to the book for both academic and practitioner audiences.
Author: David J. Tongway
Publisher: Springer Science & Business Media
ISBN: 1461302072
Category : Science
Languages : en
Pages : 266
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Book Description
Aerial photography has revealed the striking, widespread phenomenon of repeating patterns of vegetation in more arid areas of the world. Two interdependent phases, bands of dense and sparse vegetation, alternate in the landscape. This volume synthesizes half a century's accumulated knowledge of both theoretical and applied landscape function from a variety of these regions. It covers structure, dynamics, and methods of study, as well as disturbances to these landscapes and relevant management issues. Various chapters discuss the role of modeling in answering questions about the origins and complex processes of banded landscapes.
Author: Allen M. Solomon
Publisher: Springer
ISBN: 9781461362173
Category : Science
Languages : en
Pages : 338
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Book Description
During the summer of 1987, a series of discussions I was held at the International Institute for Applied Systems Analysis (nASA) in Laxenburg, Austria, to plan a study of global vegetation change. The work was aimed at promoting the Interna tional Geosphere-Biosphere Programme (IGBP), sponsored by the International Council of Scientific Unions (lCSU), of which nASA is a member. Our study was designed to provide initial guidance in the choice of approaches, data sets and objectives for constructing global models of the terrestrial biosphere. We hoped to provide substantive and concrete assistance in formulating the working plans of IGBP by involving program planners in the development and application of models which were assembled from available data sets and modeling ap proaches. Recent acceptance of the "nASA model" as the starting point for endeavors of the Global Change and Terrestrial Ecosystems Core Project of the IGBP suggests we were successful in that aim. The objective was implemented by our initiation of a mathematical model of global vegetation, including agriculture, as defined by the forces which control and change vegetation. The model was to illustrate the geographical consequences to vegetation structure and functioning of changing climate and land use, based on plant responses to environmental variables. The completed model was also expected to be useful for examining international environmental policy responses to global change, as well as for studying the validity of IIASA's experimental approaches to environmental policy development.
Author: United States Department of Agriculture
Publisher: CreateSpace
ISBN: 9781511614191
Category :
Languages : en
Pages : 56
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Book Description
Reliable predictions of how changing climate and disturbance regimes will affect forest ecosystems are crucial for effective forest management. Current fire and climate research in forest ecosystem and community ecology offers data and methods that can inform such predictions. However, research in these fields occurs at different scales, with disparate goals, methods, and context. Often results are not readily comparable among studies and defy integration. We discuss the strengths and weaknesses of three modeling paradigms: empirical gradient models, mechanistic ecosystem models, and stochastic landscape disturbance models. We then propose a synthetic approach to multi-scale analysis of the effects of climatic change and disturbance on forest ecosystems. Empirical gradient models provide an anchor and spatial template for stand-level forest ecosystem models by quantifying key parameters for individual species and accounting for broad-scale geographic variation among them. Gradient imputation transfers predictions of fine-scale forest composition and structure across geographic space. Mechanistic ecosystem dynamic models predict the responses of biological variables to specific environmental drivers and facilitate understanding of temporal dynamics and disequilibrium. Stochastic landscape dynamics models predict frequency, extent, and severity of broad-scale disturbance. A robust linkage of these three modeling paradigms will facilitate prediction of the effects of altered fire and other disturbance regimes on forest ecosystems at multiple scales and in the context of climatic variability and change.
Author: Mahesh K. Gaur
Publisher: Springer
ISBN: 9783319859729
Category : Science
Languages : en
Pages : 348
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Book Description
This edited volume is devoted to the examination of the implications of the inevitable changes wrought by global change on the welfare and livelihoods of tens of millions of people who live in dryland regions. Global change is more than just climate change and the ramifications of changing trade patterns (geopolitical and economic aspects), the shift to the market economy, demographic factors (population growth, urbanization and re-settlement), receive attention here. Land use change specialists, policy makers and natural resource management agencies will find the book very useful. Chapters focus on examples that are drawn from a number of sources including previously unpublished studies on the impact of climate change, markets and economics on pastoralist and dryland farming households. The key focus is to provide readers with insights into the real world implications of change (including an analysis of the drivers of change) on these vulnerable groups within dryland societies. The role of humans as agents of these changes is canvassed. A regional analysis of the world's drylands is also performed including those in Australia, Argentina, India, North America, China, North Africa, Central Asia and Southern Africa.
