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About this Report | Global Climate Change Impacts in …
Understanding changes in ecosystem services at regional scales is increasingly important for environmental scientists, managers, planners, and decision makers as climate and land-use change continue (de Groot et al. 2010). Management decisions require an improved understanding of the drivers and processes that influence ecosystem services. Change in major environmental drivers, such as climate and land cover, typically result in large changes in ecosystem service supply (Schroeter et al. 2005). These changes are interactive and complex across space and time (Chen et al. 2013), requiring the development of appropriate methods to elucidate functional tradeoffs between management strategies. In order for stakeholders and citizens to be able to assess the value of the ecosystem services being provided, they need them to be expressed in terms of indicators that clearly relate to environmental condition (Nelson et al. 2009, Carpenter et al. 2015, Qiu and Turner 2015). Indicators of ecosystem services should be quantifiable, scalable (Bagstad et al. 2013a, Carpenter et al. 2015), explicit in time and space, and sensitive to land-cover or management change (Burkhard et al. 2012, van Oudenhoven et al. 2012). Moreover, the appropriate indicator is dependent on the method by which the ecosystem service is being valued (de Groot et al. 2010). Commonly used indicators that are easily monetizable may be incomplete for more comprehensive sociocultural preference valuations (Mavrommati et al. 2017).
A variety of spatially explicit models or tools have been used for watershed-scale studies of environmental indicators and ecosystem services. Examples include Artificial Intelligence for Ecosystem Services (ARIES) (Villa et al. 2009), Multiscale Integrated Models of Ecosystem Services (MIMES) (Boumans et al. 2015), and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) (Tallis and Polasky 2009, Bagstad et al. 2013b, Tallis et al. 2013). These models do not capture seasonal or subseasonal climate variability, which is projected to change regionally (Wood et al. 2002, Hayhoe et al. 2007, Horton et al. 2014) and is important for capturing watershed functions related to flood attenuation, water provisioning, river temperature regulation, and other ecosystem services (Vigerstol and Aukema 2011). To fully account for changes in ecosystem function associated with altered precipitation, temperature, and land-use and land-cover patterns, process-based models that incorporate key space- and time-varying hydrological and ecological processes are critical (Bagstad et al. 2013b).
Global Climate Change Impacts in the United States 2009 Report ..
The Intergovernmental Panel on Climate Change (IPCC) estimates that in 2010, urban areas accounted for 67–76% of global energy use and 71–76% of global CO2 emissions from final energy use. See: Seto andDhakal, 2014. Chapter 12: Human Settlements, Infrastructure, and Spatial Planning.
Seto, K.C. and Dhakal, S., 2014. Chapter 12: Human Settlements, Infrastructure, and Spatial Planning. In Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. O. Edenhofer, R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, et al. (eds.). Cambridge University Press, Cambridge, UK, and New York.
Intergovernmental Panel on Climate Change - Official …
This chapter presents a framework designed to achieve “better growth” that increases quality of life across key dimensions – including incomes, better health, more liveable cities, resilience, poverty reduction and faster innovation – while also achieving a “better climate” (reducing GHGs). The framework starts from the recognition that economies are not static, but rather are dynamic and constantly changing. It has four main building blocks:
There is a perception that there is a trade-off in the short- to medium term between economic growth and climate action, but this is due largely to a misconception (built into many model-based assessments) that economies are static, unchanging and perfectly efficient. Any reform or policy which forces an economy to deviate from this counterfactual incurs a trade-off or cost, so any climate policy is often found to impose large short- and medium-term costs.
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IPCC - Intergovernmental Panel on Climate Change
Our study contributes to the evolution of ecosystem service models by emphasizing shorter-term temporal dynamics in a spatially distributed and process-based framework that links terrestrial and aquatic function. This framework provides a new perspective for understanding the impacts that climate and land-cover and land-use change have on terrestrial and aquatic resources.
IPCC 2013 report on climate change
Then there are the unprecedented risks posed by climate change. The strong growth of the global economy before the financial crisis was accompanied by a marked surge in greenhouse gas (GHG) emissions. Most of this came from the growing use of fossil fuels, along with other sources including agriculture, deforestation and industry. If current emission trends continue unchecked, the resultant increase in average global temperature could exceed 4°C above pre-industrial levels by the end of the century. This would be more than double the 2°C rise that world leaders have set as a limit to avoid the most dangerous climate impacts.
Economics of adaptation to climate change - Synthesis report
We present an approach that links time-varying (daily time-step) terrestrial and aquatic ecosystem models at regional scales and apply this model into the future using scenarios of climate and land cover to project changes in ecosystem services. First, we describe an indicator framework that succinctly represents a comprehensive suite of environmental conditions relevant to important ecosystem services. Second, we describe the linkage and validation of the terrestrial and aquatic ecosystem models to simulate aquatic indicators through the 21st century. We integrated the Photosynthetic Evapotranspiration-Carbon and Nitrogen (PnET-CN) forest ecosystem model (Ollinger et al. 2002, 2008, Aber et al. 2005) and the Framework for the Aquatic Modeling of the Earth System (FrAMES) aquatic ecosystem model (Wollheim et al. 2008a, b, Wisser et al. 2010, Stewart et al. 2011, 2013, Mineau et al. 2015; Zuidema, Wollheim, Mineau, et al., unpublished manuscript). These models integrate the dynamics of terrestrial and aquatic processes and linkages at daily time-steps, making them ideal for studying aquatic ecosystem responses in forest-dominated watersheds. In coordination with a separate effort described elsewhere in this special issue (Mavrommati et al. 2017) to assess the value of ecosystem services provided by the Upper Merrimack River watershed (UMRW) of New Hampshire, we contrast two extremes of projected futures in climate and land-cover change. The outcome suggests that climate change influences most indicators of environmental condition in the UMRW more than changes in land cover, although land cover has important interactive capacity to dampen or exacerbate the effects of the changing supply of ecosystem services in the future.
Climate Change 2007: Synthesis Report ..
Several processed-based terrestrial and/or aquatic biogeophysical models have recently been used for ecosystem service valuation (Logsdon and Chaubey 2012a, Bagstad et al. 2013a, Carpenter et al. 2015). The Variable Infiltration Capacity (VIC) model is a large-scale, semidistributed hydrological model (Liang et al. 1994) that simulated provisioning hydrological ecosystem services (Vigerstol and Aukema 2011) and flood regulation (Lee et al. 2015). The Soil Water Assessment Tool (SWAT), a process-based, spatially distributed hydrological and water quality model (Notter et al. 2012) was used to evaluate aquatic environmental variables, including water yield (Karabulut et al. 2015) and water quality (Logsdon and Chaubey 2012b). To compute dynamic ecosystem services in the agricultural Yahara watershed, a linked terrestrial–aquatic model used a process-based agroecosystem model (Agro-IBIS) (Soylu et al. 2014, Carpenter et al. 2015), a terrestrial hydrology model (THMB) (Coe 2000), a three-dimensional groundwater flow model (MODFLOW) (Harbaugh 2005), and a hydrological routing model (HYDRA), which lacked instream biogeochemistry (Coe 2000). There are a few robust examples of coupled human and biogeophysical models that have quantified ecosystem services at global (Boumans et al. 2002) and watershed (Costanza et al. 2002) scales. The Global Unified Metamodel of the Biosphere (GUMBO) simplifies several existing dynamic global models of both natural and social systems at an intermediate level of complexity and annual time-step (Boumans et al. 2002). The Patuxent Landscape Model (PLM; Costanza et al. 2002) is a spatially explicit process-based model that addresses the effects of both the magnitude and spatial patterns of human settlements and agricultural practices on hydrology, plant productivity, and nutrient cycling in the landscape, also at an annual time-step. Finally, valuation of ecosystem service information for land-use decisions has been estimated directly through an agent-based modeling framework (Heckbert et al. 2010, 2014, Groeneveld et al. 2017).
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