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The UnitedStates provides annual estimates of carbon sources and sinks as part of its National Green- house Gas Inventory (NGHGI). Within this effort, carbon stocks and ﬂuxes are reported for six landuse categories that are relevant to economic sectors and landuse policy. The goal of this study is to develop methodologies that will allow the US to align with an internationally agreed upon forestlanduse deﬁni- tion which requires forest to be able to reach 5 m in height at maturity. Models to assess height potential are available for a majority of US forests except for woodland ecosystems. We develop a set of mod- els to assess height potential in these systems. Our results suggest that ∼13.5 million ha of forests are unlikely to meet the international deﬁnition of forests due to environmental limitations to maximum attainable height. The incorporation of this height criteria in the NGHGI results in a carbon stock transfer of ∼848 Tg from the forestlanduse to woodland landuse (a sub-category of grasslands) with minimal effect on sequestration rates. The development of a forestlanduse deﬁnition sensitive to climatic factors in this study enables a landuse classiﬁcation system that can be responsive to climate change effects on land uses themselves while being more consistent across a host of international and domestic carbon reporting efforts.
At a national level, forest inventories, woody biomass assessments, agricultural surveys, land registry information and scientific research can prove useful for landclassification and model parameters. Data on temperature, rainfall, soil type and topography should also be sourced at smaller scales. In particular, data sources will include national statistical agencies, sectoral experts and universities. Global and regional level data is also valuable for forestcarbonaccounting. International land-use and land cover datasets exist, largely from remote sensing imagery, although image resolution and the accuracy of ground-referenced data are generally limited. Sources of data include international experts, international organisations publishing statistics, such as the United Nations and OECD, and international scientific journals. In particular, the FAO Forest Resources Assessment (FAO, 2006), the IPCC Agriculture, Forestry and Other LandUse (AFOLU) inventory guidance volume (IPCC, 2006), and FAO’s primer for estimating biomass (Brown, 1997) all provide parameter information that can be used in carbonaccounting.
Fire return intervals in forested US ecosystems vary, but range from decades in semi-arid interior forests to centu- ries for coastal ecosystems . There has been much debate over the role of historical land management prac- tices, such as fire suppression, in contemporary fire and forest growth patterns and a growing discussion of how wildfires will respond to climate change (e.g., [3,22,23]). The long duration of forest regrowth between fire events and the variability in the magnitude of C emission during fire highlights the uncertainty of this aspect of terrestrial C cycling. In the Kyoto protocol, the complex nature of ter- restrial sources and sinks led to a relatively narrow defini- tion of the types of terrestrial C sequestration activities that could be used to meet treaty objectives . These sequestration activities thus far have been largely con- strained to agricultural management and reforestation projects, although there has been a vigorous and ongoing debate about the appropriate scope of terrestrial C seques- tration activities . At regional and national levels, ter- restrial sinks driven by historic landuse change, such as reforestation efforts, can be sizeable  and may repre- sent an attractive target in future C mitigation negotia- tions. Similarly, fire mitigation programs such as forest thinning may reduce the severity or extent of fires, but may also have uncertain impacts on sequestered carbon (depending on the fate of C removed from forests). From this standpoint, the potential for C losses from fire repre- sents a risk to C sequestration potential and a factor that needs to be considered in discussions regarding appropri- ate credit for terrestrial sinks in atmospheric C mitigation. In this study, we evaluate the role that fire plays in carbon emissions from a number of states throughout the US. The motivation, following Amiro et al., , is, in part, to assess the degree to which fire can influence regional car- bon budgets and the year to year and state to state varia- bility of the potential impacts. This is the first study of which we are aware that includes the spatial and temporal resolution of fire CO 2 emissions for the US, and assesses the importance of these emissions compared to fossil fuel burning CO 2 emissions. We also focus on the role that fire
In addition to sequestering and storing atmospheric car- bon, US forests also generate wood products that support the energy, industry, transport and building sectors both domestically and internationally. Given that wood har- vest represents the majority of C losses from US forests, increasing the US net forest C sink would require shifts in current forest management practices as well as more refined and disaggregated information to reduce the uncer- tainty of these estimates and resolve these with correct esti- mation of net C change. For example, national debate has grown over the production of wood pellets as a renewable energy source, particularly from the southeast US, with demand driven by European policies to reduce emissions of greenhouse gases and increase the use of renewable energy. Georgia, Florida, Alabama and Virginia currently account for nearly all US wood pellet exports . Although wood pellets are claimed by the industry to be made from resi- dues at lumber mills or logging sites, the industry’s growth could lead to a substantial increase in demand on South- ern forests, potentially creating incentives to expand plan- tations. The potential of bioenergy to reduce greenhouse gas emissions inherently depends on the source of the bio- mass and its net landuse effects; bioenergy reduces green- house gas emissions only if the growth and harvesting of the biomass used for energy sequesters carbon above and beyond what would be sequestered anyway . This addi- tional carbon must result from land management changes that increase tree C uptake or from the use of biomass that would otherwise decompose rapidly.
National scale forest resource inventories in the U.S. have evolved from a timber-centric focus toward a more inclusive sampling of forest ecosystem attributes such as C stocks of standing dead trees. Likewise, the estimation procedures associated with such a forest inventory evo- lution need to be inclusive of tree attributes beyond those required by the forest products industry (e.g., board foot volumes of growing stock live trees). Devel- oping SDT biomass and C stock estimates within the construct of an inventory system traditionally designed to estimate growing stock volume requires: 1) the devel- opment of a SDT decay class system which is both qua- litative for ease of use in the field and quantitative to account for structural loss by tree component and spe- cies, 2) the development of DRF for SDT species in each decay class, with specific emphasis on advanced decay classes, and 3) the development of a flexible SDT estimation procedure which incorporates initial struc- tural loss and density reduction information and allows for continual refinement.
People care about land cover pattern for a variety of reasons. Society is informed in the popular press about land cover patterns through headline issues such as urban sprawl and forest fragmentation. Spatial ecologists care about pattern because the spatial arrangement of the environment affects the flows of matter, energy, and information across the landscape, thus impacting ecological processes. Resource managers consider land cover pattern because it affects the production of ecological goods and services; the same amount of a land cover can be arranged in different ways with consequences for biodiversity, water quality, recreation experience, and other amenities. Landuse planners describe landscape context partly in terms of the land cover patterns that contribute to a “sense of place” for human occupation. Assessment scientists consider land cover pattern as a leading indicator in risk assessment; when landscape patterns change, the ecological and social processes embedded within landscapes change, putting goods and services at risk. In summary, there is a widespread appreciation that land cover pattern is an important environmental attribute.
Decision trees represent another group of classification algorithms. Decision trees have not been used widely by the remote sensing community despite their non-parametric nature and their attractive properties of simplicity in handling the non- normal, non-homogeneous and noisy data. Hansen et al.  have suggested classification trees as an alternative to traditional land cover classifiers. Ghose et al.  have used decision trees for classifying pixels in IRS-1C/LISS III multispectral imagery, and have compared performance of the decision tree classifier with the maximum likelihood classifier. More recently ensemble methods such as Random Forest have been suggested for land cover classification. The Random Forest algorithm has been used in many data mining applications, however, its potential is not fully explored for analyzing remotely sensed images. Random Forest is based on tree classifiers. Random Forest grows many classification trees. To classify a new feature vector, the input vector is classified with each of trees in the forest. Each tree gives a classification, and we say that the tree “votes” for that class. The forest chooses the classification having the most votes over all the trees in the forest. Among many advantages of Random Forest the significant ones are: unexcelled accuracy among current algorithms, efficient implementation on large data sets, and an easily saved structure for future use of pre-generated trees . Gislason et al.  have used Random Forests for classification of multisource remote sensing and geographic data. The Random Forest approach should be of great interest for multisource classification since the approach is not only nonparametric but it also provides a way of estimating the importance of the individual variables in classification. In ensemble classification, several classifiers are trained and their results combined through a voting process. Many ensemble methods have been proposed. Most widely used such methods are boosting and bagging .
Stainback and Alavalapati  suggest that in even-aged plantation forestry, risk from natural disturbance reduces the incentive that a carbon market would provide to land- owners for increasing rotation age and thus carbon stocks. Previous research has suggested that for forests historically characterized by frequent, low severity fire, thinning the forest can reduce the risk of carbon loss from wildfire [11,12]. Thus, FRCC_DEP can be altered, making this car- bon valuation method robust to site-specific management actions, providing incentive in terms of increased carbon market value for landowners to engage in high severity fire risk reduction measures.
If pesticides are necessary, spot treat or use baits that target specific pests. Always read and follow label instructions when applying lawn care prod- ucts. Also try to limit fertilizers to only what is rec- ommended for good plant growth. For specific directions in fertilizer application, take a soil sam- ple to your county Extension office for analysis. Note: a major pollutant of ground water is too much nitrogen, commonly resulting from applying too much lawn chemicals. These pollutants can harm fish, wildlife, and humans if left out of bal- ance. Remember, what we do today will impact us tomorrow.
There are four hierarchical mandates of the RFS (Figure 10). The criteria for each category relate to the eligible feedstocks and the GHG emission reductions relative to petroleum-based fuel. The overall mandate is the broadest one in scope (meaning the lowest threshold of GHG reduction) and it rises to 36 billion gallons by 2022. The advanced mandate is a subset of the overall mandate that has a higher GHG reduction threshold and expressly disallows one feedstock, namely ethanol made from corn starch. We assume that ethanol from sugar cane will count as an advanced biofuel, although final rules are not issued so we cannot be certain at this point. As a sub-mandate of the overall mandate, any biofuel that qualifies as an advanced biofuel automatically also counts against the overall mandate, but the reverse is not true in that a biofuel that meets the criteria of the overall does not automatically meet the advanced biofuel mandate criteria. The advanced biofuel mandate rises to 21 billion gallons by 2022. The difference between the overall and advanced biofuel mandates, which is the maximum volume that could be met by non-advanced biofuels, peaks at 15 billion gallons in 2015. The fact that the most common US biofuel today, ethanol from corn starch, counts against the overall mandate but not the advanced mandate has certain implications. If more advanced mandate is used than is strictly required, then less corn-based ethanol need be used in order to meet the mandate.
The study highlighted the movement of land away from major crops competing for land with feedstock crops. The authors stated that, “Due to the high tariff on ethanol in the U.S, increased U.S. demand for ethanol translates into a U.S. ethanol production expansion which was seen to have global effects on land allocation as higher coarse grain prices transmit worldwide.” Changes in U.S. coarse grain prices also affect U.S. wheat and oilseed prices, which in turn affect world markets. They concluded that expansion in Brazilian ethanol use primarily affects land used for sugarcane production in Brazil and to a lesser extent in other sugar-producing countries, but with small impacts on other land uses in most countries. They found that a 1-percent increase in U.S. ethanol use would result in a 0.009 percent increase in world crop area. Most of the increase in world crop area is through an increase in world corn area. Brazil and South Africa respond the most, with multipliers of 0.031 and 0.042, respectively. Their results suggest an impact
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The Great Plains of the UnitedStates has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes. We developed a scenario-based modeling framework to analyze potential future land-use change in the Great Plains. A unique scenario construction process, using an integrated modeling framework, historical data, workshops, and expert knowledge, was used to develop quantitative demand for future land-use change for four IPCC scenarios at the ecoregion level. The FORE-SCE model ingested the scenario information and produced spatially explicit land-use maps for the region at relatively ﬁne spatial and thematic resolutions. Spatial modeling of the four scenarios provided spatial patterns of land-use change consistent with underlying assumptions and processes associated with each scenario. Economically oriented scenarios were characterized by signiﬁcant loss of natural land covers and expansion of agricultural and urban land uses. Environmentally oriented scenarios experienced modest declines in natural land covers to slight increases. Model results were assessed for quantity and allocation disagreement between each scenario pair. In conjunction with the U.S. Geological Survey’s Biological Carbon Sequestration project, the scenario-based modeling framework used for the Great Plains is now being applied to the entire UnitedStates.
forest (forestland). Land that is at least 10 percent stocked by forest trees of any size, or land formerly having such tree cover, and not currently developed for a nonforest use. The minimum area for classification as forestland is 1 ac. Roadside, streamside, and shelterbelt strips of timber must be at least 120-ft wide to qualify as forestland. Unimproved roads and trails, streams and other bodies of water, or natural clearings in forested areas are classified as forest, if less than 120 ft in width or 1 ac in size. Grazed woodlands, reverting fields, and pastures that are not actively maintained are included if the above qualifications are satisfied. Forestland includes three subcategories: timberland, reserved forestland, and other forestland.
participation, arguing “peace is best preserved by giving energy to the government or information to the people. This last is the most certain and the most legitimate engine of government… *Citizens+ are the only sure reliance for the preservation of our liberty” (1787). Educating the public was synonymous with good governance, providing a safeguard against what Jefferson feared was an illegitimate limitation of the individual citizen’s political role. Instead of active participants in decision-making, democratic elites believed “citizens were economic beings in the ﬁrst place… In fact, when Hamilton created his national bank, modeled after the Bank of England created a century earlier, he used the epithet ‘mind your business’ on national coins—a phrase later changed to ‘In God We Trust’” (Theobold 1999). Contempt for citizen involvement among elites was equally matched by more open, participatory democratic approaches.
4.2 Land-use Change Effect on Land-use Emissions for the U.S. and the World
The land-use emissions profile for the reference in Figure 6 are the result of the existing (2010) land cover and changes to it over time. To understand these land-use change emissions
trajectories, we first look at the reference land-use profile for the U.S. and the ROW shown in Figure 8. The negative U.S. land-use emissons are a consequence of it having a large and stable forest mass. We divide forestland into managed and natural parts. The managed forests are the forest areas that are used to produce forestry products, such as timber, paper pulp, etc, and tend to have a lower density of carbon stocks than natural forests due to the removal of carbon from previous disturbances such as timber harvests (Lu et al., 2015). Natural forests are assumed to be undisturbed and can only produce forest products after they are first converted to managed forests with timber harvests or have been converted to agricultural land. Current land management practices and regulations are assumed to protect the area of natural forests and its carbon stocks in the U.S., and such protections are expected to continue in the future. The potential impact of natural disturbances (wildfires, insect infestations, wind and ice damage) on the carbon dynamics of natural forests are problematic (Zhang et al. 2012, 2015) and have not been considered in our simulations. EPPA is calibrated to reflect this inertia in the system, which is seen as the natural forests staying untouched in our projection. Instead, the expansion of croplands and pastures in the U.S. come at the expense of natural grasslands and managed forests, which have a lower carbon density than natural forests. In addition, regrowth of trees in managed forests tend to enhance carbon sequestration (Lu et al., 2015). This maintains the U.S. sink in the reference.
may help elucidate the dynamics between coarse/fine woody debris carbon stocks and climate at the continental scale. Forest woody detritus carbon stocks are found in the largest amounts in climates that are moist enough to sup- port productive forests while at the same time are cool enough to reduce decay rates. This hypothesis was evi- denced by the "snow, fully humid, cool summer" climatic region (Dfc) having the highest mean total dead and downed wood carbon stock of 9.73 tonnes ha^-1. The cli- matic region with the lowest mean forest dead and downed wood carbon stock was that of "arid desert" (BW) where the hot temperatures increase decay rates and the lack of moisture reduces forest productivity. These results are similar to those found at smaller scales [9,16-18]. Coarse and fine woody debris carbon stocks vary individ- ually with climatic regions/variables. The cool, moist cli- matic regions of the Pacific Northwest and high elevations in the Rocky Mountains have the greatest disparity between coarse and fine woody debris carbon stocks with coarse woody debris stocks exceeding fine woody debris stocks by 4.45 tonnes ha^-1 on average. In contrast, the humid and hot climatic regions in the southeastern UnitedStates had fine woody debris carbon stocks exceed- ing coarse woody debris stocks by 0.70 tonnes ha^-1 on average. Furthermore, fine woody debris carbon stocks were less correlated with climatic variables than coarse woody debris carbon stocks. Given the ephemeral nature of fine woody debris carbon stocks with their rapid decay and turnover, it is proposed that fine woody debris carbon stocks may be relatively unaffected by increases in global temperature. Studies at smaller scales proposed that forest litter carbon stocks were unaffected by changes in temper- ature [1,7,19,20]. Future fine woody debris carbon stocks may be more affected by tree species shifts than climate shifts , an indirect effect of global climate change
State relationship laws vary greatly among the relevant states. Generally, they regulate matters such as good faith requirements, anti-discrimination between franchisees, permissible grounds for termination or non-renewal of the franchise, and required notice and cure periods for most defaults. Because of the differences in state registration, disclosure and relationship laws and regulatory policies, it is often necessary to attach state-specific addenda to the UFOC in order to comply with state law and to gain registration.
wood harvested in the UnitedStates (Haynes et al. 2007). A robust body of re- search shows that these landowners respond to price signals, public policies, and various incentives and disincentives to producing wood. For instance, a meta-analysis of forest management practices of family forest own- ers found that among the drivers typically studied, policy variables are most likely to be identified as drivers of landowner behavior, followed by plot/resource conditions, own- ers’ characteristics, and market drivers, al- though the differences in the importance of the various drivers are small (Beach et al. 2005). This and many other studies make it clear that in addition to markets, public pol- icies and other nonmarket factors are impor- tant drivers of landowner behavior (Perez- Garcia et al. 2001, Langpap 2006, Zobrist and Lippke 2007, Zhang and Flick 2010, Joshi and Mehmood 2011, Miller et al. 2012, Van Deusen et al. 2012, Aguilar et al. 2013, Becker et al. 2013, Latta et al. 2013, Rozance and Rabotyagov 2014). Research on factors that influence landowner behav- ior suggests substantial potential for affect- ing landowner behavior in ways that could have important carbonimplications. Poli- cies that provide incentives for landowners to expand forest area, make forests more productive, and store more carbon could have important carbon benefits. On the other hand, policies that increase transaction costs to landowners or devalue forest bio- mass could have negative carbon conse- quences, by reducing incentives for invest- ments in working forests, reducing biomass supplies, limiting afforestation activities, and leading to increased conversion of for- ests to other land uses. The potential for landowner response to disincentives could be especially important in the case of mate- rials collected for energy due to their low value, as revealed in a survey of loggers and landowners in North Carolina (Fielding et al. 2012).