The land carbon sink of the conterminous United States was evaluated using a bottom-up modeling framework and 30-meter land change data from 1985 to 2020. This cross-scale, cross-landscape, and cross-system approach tracked fractional land cover changes and applied regional model calibration. Results show average terrestrial and aquatic carbon sinks of +110 ± 37 and +19 ± 0.5 teragrams of carbon per year, respectively. The terrestrial carbon sink, showing no clear trend, peaked in the 1990s, with more years as a carbon source since 2000, contradicting recent national and global studies. Land change had the largest impact (−70 ± 5.5 teragrams of carbon per year), exceeding impacts of climate (−33 ± 48 teragrams of carbon per year), wildfire (−7.7 ± 2.4 teragrams of carbon per year), and erosion transport (−1.9 ± 0.13 teragrams of carbon per year). The positive CO 2 fertilization effect (+69 ± 12 teragrams of carbon per year) was insufficient to maintain the carbon sink strength. Our framework reveals key paths of carbon loss, with implications for carbon budget and energy policies in the United States and beyond.

The urgency to address ecosystem loss is paramount, as both land use change and climate change will continue to rapidly alter and degrade natural ecosystems and reduce the many services they provide. To support conservation actions that mitigate impacts from these dual threats, we have developed potential World Terrestrial Ecosystem (WTE) distributions for 2050 following IPCC best practice guidelines. This projection of ecosystem distributions builds on the previously released 2015 WTEs, a snapshot of the distribution and conservation status of 431 terrestrial ecosystem types defined as distinct combinations of 18 global climate regions, 4 global landform classes, and 8 global vegetation/land cover classes. Extending that work herein, we modeled the potential 2050 WTE distributions based on projections of five CMIP6 general circulation models (GCMs) and one global land cover change model, determined for three shared socioeconomic pathway (SSP) scenarios. The climate region modeling included projections for 2050 for both mean annual temperature and mean annual aridity. Model agreement for changes to WTEs was generally high, particularly for temperature projections. Widespread changes in ecosystem classes due to shifts in climate settings and/or land cover between 2015 and 2050 were projected, with both the magnitude and specific geography of projected change largely governed by the SSP scenario. For the three SSP scenarios (sustainable development, regional rivalry, and fossil-fueled development), geographic changes in climate setting (temperature, aridity, or both) and/or changes in vegetation/land cover are projected for 29%, 36%, and 39% of Earth’s terrestrial surface, respectively. These changes occur in areas where 31%, 36%, and 41% of the global population lives. Projected changes in ecosystem distributions related to temperature change are approximately an order of magnitude greater than for aridity change. By offering insight into potential ecosystem changes, this new resource is intended to facilitate conservation planning and priority setting aimed at improved conservation of biodiversity and ecosystem services.

Continued alteration of the nitrogen cycle exposes receiving waters to elevated nitrogen concentrations and forces drinking water treatment services to plan for such increases in the future. We developed four 2011-2050 land cover change scenarios and modeled the impact of projected land cover change on influent water quality to support long-term planning for the Minneapolis Water Treatment Distribution Service (MWTDS) using Soil Water and Assessment Tool. Projected land cover changes based on relatively unconstrained economic growth led to substantial increases in total nitrogen (TN) loads and modest increases in total phosphorus (TP) loads in spring. Changes in sediment, TN, and TP under two "constrained" growth scenarios were near zero or declined modestly. Longitudinal analysis suggested that the extant vegetation along the Mississippi River corridor upstream of the MWTDS may be a sediment (and phosphorus) trap. Autoregressive analysis of current (2008-2017) chemical treatment application rates (mass per water volume processed) and extant (2001-2011) land cover change revealed that statistically significant increases in chemical treatment rates were temporally congruent with urbanization and conversion of pasture to cropland. Using the current trend in chemical treatment application rates and their inferred relationship to extant land cover change as a bellwether, the unconstrained growth scenarios suggest that future land cover may present challenges to the production of potable water for MWTDS.

Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v2]When Models Talk: Integrated Human-Hydro-Terrestrial Modeling to Assess Delaware River Basin Water Resource Vulnerability to DroughtAuthorsHedeffEssaidiDAubreyDuggerJeniKeismanNancyBakerAdamBenthemJoelBlomquistKatherineCalvinXingyuanChenSalmeCookGalenGorskiAndrewHamiltonLivHerdmanAbigailJayeiDNoahKnowlesPMillyDianaPedrazaiDJasonPopeAndreasPreiniDPatrickReediDGregoryRouzeKevinSampsonWardSanfordGabrielSenayJaredSmithiDTerrySohliDCharulekaVaradharajanChrisVernoniDDavidYatesJacobZwartiDSee all authors Hedeff EssaidiDCorresponding Author• Submitting AuthorUS Geological SurveyiDhttps://orcid.org/0000-0003-0154-8628view email addressThe email was not providedcopy email addressAubrey DuggerNational Center for Atmospheric Researchview email addressThe email was not providedcopy email addressJeni KeismanU.S. Geological Surveyview email addressThe email was not providedcopy email addressNancy BakerUSGS Indiana Water Science Centerview email addressThe email was not providedcopy email addressAdam BenthemU.S. Geological Surveyview email addressThe email was not providedcopy email addressJoel BlomquistU.S. Geological Surveyview email addressThe email was not providedcopy email addressKatherine CalvinPacific Northwest National Laboratoryview email addressThe email was not providedcopy email addressXingyuan ChenPacific Northwest National Laboratoryview email addressThe email was not providedcopy email addressSalme CookUS Geological Survey Woods Hole Science Centerview email addressThe email was not providedcopy email addressGalen GorskiUS Geological Surveyview email addressThe email was not providedcopy email addressAndrew HamiltonCornell Universityview email addressThe email was not providedcopy email addressLiv HerdmanUSGS New York Water Science Centerview email addressThe email was not providedcopy email addressAbigail JayeiDNational Center for Atmospheric ResearchiDhttps://orcid.org/0000-0003-4909-0492view email addressThe email was not providedcopy email addressNoah KnowlesU.S. Geological Surveyview email addressThe email was not providedcopy email addressP MillyUSGS Water Mission Areaview email addressThe email was not providedcopy email addressDiana PedrazaiDUS Geological SurveyiDhttps://orcid.org/0000-0003-4483-8094view email addressThe email was not providedcopy email addressJason PopeUSGS Virginia Water Science Centerview email addressThe email was not providedcopy email addressAndreas PreiniDNational Center for Atmospheric ResearchiDhttps://orcid.org/0000-0001-6250-179Xview email addressThe email was not providedcopy email addressPatrick ReediDCornell UniversityiDhttps://orcid.org/0000-0002-7963-6102view email addressThe email was not providedcopy email addressGregory RouzeKBRInc.view email addressThe email was not providedcopy email addressKevin SampsonNational Center for Atmospheric Researchview email addressThe email was not providedcopy email addressWard SanfordUnited States Geological Survey (USGS)view email addressThe email was not providedcopy email addressGabriel SenayU.S. Geological Survey Earth Resources Observation and Science (EROS) Centerview email addressThe email was not providedcopy email addressJared SmithiDUS Geological SurveyiDhttps://orcid.org/0000-0003-3124-8255view email addressThe email was not providedcopy email addressTerry SohliDUSGS Earth Resources Observation and Science CenteriDhttps://orcid.org/0000-0002-9771-4231view email addressThe email was not providedcopy email addressCharuleka VaradharajanLawrence Berkeley National Laboratoryview email addressThe email was not providedcopy email addressChris VernoniDJoint Global Change Research InstituteiDhttps://orcid.org/0000-0002-3406-6214view email addressThe email was not providedcopy email addressDavid YatesNational Center for Atmospheric Researchview email addressThe email was not providedcopy email addressJacob ZwartiDUS Geological SurveyiDhttps://orcid.org/0000-0002-3870-405Xview email addressThe email was not providedcopy email address

Land system change has been identified as one of four major Earth system processes where change has passed a destabilizing threshold. A historical record of landscape change is required to understand the impacts change has had on human and natural systems, while scenarios of future landscape change are required to facilitate planning and mitigation efforts. A methodology for modeling long-term historical and future landscape change was applied in the Delaware River Basin of the United States. A parcel-based modeling framework was used to reconstruct historical landscapes back to 1680, parameterized with a variety of spatial and nonspatial historical datasets. Similarly, scenarios of future landscape change were modeled for multiple scenarios out to 2100. Results demonstrate the ability to represent historical land cover proportions and general patterns at broad spatial scales and model multiple potential future landscape trajectories. The resulting land cover collection provides consistent data from 1680 through 2100, at a 30-m spatial resolution, 10-year intervals, and high thematic resolution. The data are consistent with the spatial and thematic characteristics of widely used national-scale land cover datasets, facilitating use within existing land management and research workflows. The methodology demonstrated in the Delaware River Basin is extensible and scalable, with potential applications at national scales for the United States.

Land-use land-cover change (LULCC) has become an important topic of research for the central United States because of the extensive conversion of the natural prairie into agricultural land, especially in the northern Great Plains. As a result, shifts in the natural climate (minimum/maximum temperature, precipitation, etc.) across the north-central United States have been observed, as noted within the Fourth National Climate Assessment (NCA4) report. Thus, it is necessary to understand how further LULCC will affect the near-surface atmosphere, the lower troposphere, and the planetary boundary layer (PBL) atmosphere over this region. The goal of this work was to investigate the utility of a new future land-use land-cover (LULC) dataset within the Weather Research and Forecasting (WRF) modeling system. The present study utilizes a modeled future land-use dataset developed by the Forecasting Scenarios of Land-Use Change (FORE-SCE) model to investigate the influence of future (2050) land use on a simulated PBL development within the WRF Model. Three primary areas of LULCC were identified within the FORE-SCE future LULC dataset across Nebraska and South Dakota. Variations in LULC between the 2005 LULC control simulation and four FORE-SCE simulations affected near-surface temperature (0.5°–1°C) and specific humidity (0.3–0.5 g kg −1 ). The differences noted in the temperature and moisture fields affected the development of the simulated PBL, leading to variations in PBL height and convective available potential energy. Overall, utilizing the FORE-SCE dataset within WRF produced notable differences relative to the control simulation over areas of LULCC represented in the FORE-SCE dataset.

First posted April 15, 2020 For additional information, contact: Customer Service, Earth Resources Observation and Science Center (EROS)U.S. Geological Survey47914 252d Street Sioux Falls, SD 57198https://www.usgs.gov/land-resources/eros/lcmap There is a pressing need to monitor and understand the rapid land change happening around the world. The U.S. Geological Survey is developing a new capability, called Land Change Monitoring, Assessment, and Projection (LCMAP), to innovate the understanding of land change. This capability is the Earth Resources Observation and Science Center's foundation for an integrated U.S. Geological Survey-wide land change science framework. LCMAP supports the development of consistent data and land cover products spanning large geographic extents, over extended periods, and at a higher frequency than in the past. LCMAP provides solutions to the science and management communities’ growing need for an improved understanding of the fundamental drivers of land change, the consequences of change in human and natural systems, and feedbacks associated with land change processes.

Land-use and climate change are significantly affecting stream ecosystems, yet understanding of their long-term impacts is hindered by the few studies that have simultaneously investigated their interaction and high variability among future projections. We modeled possible effects of a suite of 2030, 2060, and 2090 land-use and climate scenarios on the condition of 70,772 small streams in the Chesapeake Bay watershed, United States. The Chesapeake Basin-wide Index of Biotic Integrity, a benthic macroinvertebrate multimetric index, was used to represent stream condition. Land-use scenarios included four Special Report on Emissions Scenarios (A1B, A2, B1, and B2) representing a range of potential landscape futures. Future climate scenarios included quartiles of future climate changes from downscaled Coupled Model Intercomparison Project - Phase 5 (CMIP5) and a watershed-wide uniform scenario (Lynch2016). We employed random forests analysis to model individual and combined effects of land-use and climate change on stream conditions. Individual scenarios suggest that by 2090, watershed-wide conditions may exhibit anywhere from large degradations (e.g., scenarios A1B, A2, and the CMIP5 25th percentile) to small degradations (e.g., scenarios B1, B2, and Lynch2016). Combined land-use and climate change scenarios highlighted their interaction and predicted, by 2090, watershed-wide degradation in 16.2% (A2 CMIP5 25th percentile) to 1.0% (B2 Lynch2016) of stream kilometers. A goal for the Chesapeake Bay watershed is to restore 10% of stream kilometers over a 2008 baseline; our results suggest meeting and sustaining this goal until 2090 may require improvement in 11.0%-26.2% of stream kilometers, dependent on land-use and climate scenario. These results highlight inherent variability among scenarios and the resultant uncertainty of predicted conditions, which reinforces the need to incorporate multiple scenarios of both land-use (e.g., development, agriculture, etc.) and climate change in future studies to encapsulate the range of potential future conditions.

Large-scale terrestrial carbon (C) estimating studies using methods such as atmospheric inversion, biogeochemical modeling, and field inventories have produced different results. The goal of this study was to integrate fine-scale processes including land use and land cover change into a large-scale ecosystem framework. We analyzed the terrestrial C budget of the conterminous United States from 1971 to 2015 at 1-km resolution using an enhanced dynamic global vegetation model and comprehensive land cover change data. Effects of atmospheric CO2 fertilization, nitrogen deposition, climate, wildland fire, harvest, and land use/land cover change (LUCC) were considered. We estimate annual C losses from cropland harvest, forest clearcut and thinning, fire, and LUCC were 436.8, 117.9, 10.5, and 10.4 TgC/year, respectively. C stored in ecosystems increased from 119,494 to 127,157 TgC between 1971 and 2015, indicating a mean annual net C sink of 170.3 TgC/year. Although ecosystem net primary production increased by approximately 12.3 TgC/year, most of it was offset by increased C loss from harvest and natural disturbance and increased ecosystem respiration related to forest aging. As a result, the strength of the overall ecosystem C sink did not increase over time. Our modeled results indicate the conterminous US C sink was about 30% smaller than previous modeling studies, but converged more closely with inventory data.

The Land Change Monitoring, Assessment, and Projection (LCMAP) initiative uses temporally dense Landsat data and time series analyses to characterize landscape change in the United States from 1985 to present. LCMAP will be used to explain how past, present, and future landscape change affects society and natural systems. Here, we describe a modeling framework for producing high-resolution (spatial and thematic) landscape projections at a national scale, using a unique parcel-based modeling framework. The methodology was tested by modeling 11 land use scenarios and 3 climate realizations for the U.S. Great Plains. Results demonstrate 1) an ability to balance competing land-use demands from quite variable, complex scenarios, 2) urban growth that matches theoretical future patterns, 3) the value of remote sensing data sources for model parameterization and for deriving landscape parcels, and 4) a pragmatic approach that facilitates the development of high thematic- and spatial-resolution projections at a national scale.

•We developed a unique set of landscape projections for the Great Plains that use real land-management parcels to represent landscape patterns at high spatial and thematic resolution.•Both anthropogenic land use and natural vegetation respond in the model to projected changes in groundwater availability and climate change.•Thirty-three scenario combinations were modeled, facilitating landscape planning and mitigation efforts under a range of possible landscape futures.•Change in rangeland from 2014 to 2100 varied from an increase of 4.3% for the Special Report on Emissions Scenarios (SRES) B2 scenario, to a decline of 23.6% for the SRES A1B scenario.•The spatially and thematically detailed projections are designed for the assessment of landscape interactions with water flow and water quality, species distribution and abundance modeling, greenhouse gas assessments, and other ecosystem services.

Growing demands for temporally specific information on land surface change are fueling a new generation of maps and statistics that can contribute to understanding geographic and temporal patterns of change across large regions, provide input into a wide range of environmental modeling studies, clarify the drivers of change, and provide more timely information for land managers. To meet these needs, the U.S. Geological Survey has implemented a capability to monitor land surface change called the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative. This paper describes the methodological foundations and lessons learned during development and testing of the LCMAP approach. Testing and evaluation of a suite of 10 annual land cover and land surface change data sets over six diverse study areas across the United States revealed good agreement with other published maps (overall agreement ranged from 73% to 87%) as well as several challenges that needed to be addressed to meet the goals of robust, repeatable, and geographically consistent monitoring results from the Continuous Change Detection and Classification (CCDC) algorithm. First, the high spatial and temporal variability of observational frequency led to differences in the number of changes identified, so CCDC was modified such that change detection is dependent on observational frequency. Second, the CCDC classification methodology was modified to improve its ability to characterize gradual land surface changes. Third, modifications were made to the classification element of CCDC to improve the representativeness of training data, which necessitated replacing the random forest algorithm with a boosted decision tree. Following these modifications, assessment of prototype Version 1 LCMAP results showed improvements in overall agreement (ranging from 85% to 90%).

Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land use change model to project parcel-based agricultural change across a large region in the United States Great Plains. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using real parcel boundaries based on contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent. The conceptual approach is practical and scalable, with potential use for national-scale projections.

Understanding the effects of management practices on soil organic carbon (SOC) is important for designing effective policies to mitigate greenhouse gas emissions in agriculture. In the Midwest United States, management practices in the croplands have been improved to increase crop production and reduce SOC loss since the 1980s. Many studies of SOC dynamics in croplands have been performed to understand the effects of management, but the results are still not conclusive. This study quantified SOC dynamics in the Midwest croplands from 1980 to 2012 with the General Ensemble Biogeochemical Modelling System (GEMS) and available management data. Our results showed thatthe total SOC in the croplands decreased from 1190 Tg C in 1980 to 1107 TgC in 1995, and then increased to 1176 TgC in 2012. Continuous cropping and intensive tillage may have driven SOC loss in the early period. The increase of crop production and adoption of conservation tillage increased the total SOC so that the decrease in the total SOC stock after 32 years was only 1%. The small change in average SOC did not reflect the large spatial variations of SOC change in the region. Major SOC losses occurred in the north and south of the region, where SOC baseline values were high and cropland production was low. The SOC gains took place in the central part of the region where SOC baseline values were moderate and, cropland production was higher than the other areas. We simulated multiple land-use land-cover (LULC) change scenarios and analyzed the results. The analysis showed that among all the LULC changes, agricultural technology that increased cropland production had the greatest impact on SOC changes, followed by the tillage practices, changes in crop species, and the conversions of cropland to other land use. Information on management practice induced spatial variation in SOC can be useful for policy makers and farm managers to develop long-term management strategies for increasing SOC sequestration in different areas. (C) 2017 Elsevier B.V. All rights reserved.

First posted June 30, 2017 For additional information, contact: John Wesley Powell Center U.S. Geological Survey2150 Centre AvenueBuilding CFort Collins, CO 80526-8118https://powellcenter.usgs.gov/ The U.S. Geological Survey (USGS) has a long history of advancing the traditional Earth science disciplines and identifying opportunities to integrate USGS science across disciplines to address complex societal problems. The USGS science strategy for 2007–2017 laid out key challenges in disciplinary and interdisciplinary arenas, culminating in a call for increased focus on a number of crosscutting science directions. Ten years on, to further the goal of integrated science and at the request of the Executive Leadership Team (ELT), a workshop with three dozen invited scientists spanning different disciplines and career stages in the Bureau convened on February 7–10, 2017, at the USGS John Wesley Powell Center for Analysis and Synthesis in Fort Collins, Colorado.The workshop focused on identifying "grand challenges" for integrated USGS science. Individual participants identified nearly 70 potential grand challenges before the workshop and through workshop discussions. After discussion, four overarching grand challenges emerged:Natural resource security,Societal risk from existing and emerging threats,Smart infrastructure development, andAnticipatory science for changing landscapes.Participants also identified a "comprehensive science challenge" that highlights the development of integrative science, data, models, and tools—all interacting in a modular framework—that can be used to address these and other future grand challenges:Earth Monitoring, Analyses, and Projections (EarthMAP)EarthMAP is our long-term vision for an integrated scientific framework that spans traditional scientific boundaries and disciplines, and integrates the full portfolio of USGS science: research, monitoring, assessment, analysis, and information delivery.The Department of Interior, and the Nation in general, have a vast array of information needs. The USGS meets these needs by having a broadly trained and agile scientific workforce. Encouraging and supporting cross-discipline engagement would position the USGS to tackle complex and multifaceted scientific and societal challenges in the 21st Century.

Half of Earth's land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decisionmaking processes work in specific contexts.

全球气候与环境变化研究需要详细的关于过去、现在和未来的土地利用信息.本研究探讨了通过降尺度的方法来生成1 km分辨率2010～2100年全球土地利用数据集的方法.主要的输入数据为30 m分辨率的2010年全球地表覆盖产品(FROM-GLC), 同时结合0.5°的全球土地利用数据(LUH)和不同分辨率的地理空间异质性要素(包括地形、气候、土壤和社会经济条件等),通过元胞自动机模型来生成未来4种RCP情景的1 km土地利用的动态比例产品.