--- - attributes: ~ caption: 'This product estimates average annual particulate organic carbon flux (in gC m-2 yr-1) deposited on the ocean bottom between 1998 and 2001, with continental margins outlined in white at the 2,000-m depth contour. Credit: F.E. Muller-Karger, University of South Florida; R. Varela, Estación de Investigaciones Marinas de Margarita; R. Thunell, University of South Carolina; R. Luerssen, University of South Florida; C. Hu, University of South Florida; and J.J. Walsh, University of South Florida (reproduced from Geophysical Research Letters with permission from the American Geophysical Union).' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/ccsp-ocpfy2007/figure/average-annual-carbon-deposition-1998-2001.yaml identifier: average-annual-carbon-deposition-1998-2001 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: ccsp-ocpfy2007 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: 'Average Annual Carbon Deposition, 1998-2001' uri: /report/ccsp-ocpfy2007/figure/average-annual-carbon-deposition-1998-2001 url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: 'True-color images of the Earth depict the global interactions between the atmosphere, oceans, land surfaces, and snow/ice surfaces, which together comprise the global water and energy cycles of the Earth system. Credit: NASA Goddard Space Flight Center; USGS.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/ccsp-ocpfy2003/figure/blue-marble.yaml identifier: blue-marble lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: ccsp-ocpfy2003 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: The "Blue Marble" uri: /report/ccsp-ocpfy2003/figure/blue-marble url: ~ usage_limits: Free to use with credit to the original figure source. - attributes: ~ caption: 'During the wet phase of the Australia monsoon (Dec-Feb) and the build-up to the wet phase (Nov), convection is a common occurrence at Darwin. This image from the centimeter-wavelength radar operated at Darwin illustrates the intense convection that typifies the monsoon build-up period. Such convection may exhibit strong updrafts (reds and yellows in the image) reaching altitudes of 18 km or greater. Convection during the active wet phase of the monsoon exhibits weaker updrafts more representative of oceanic conditions. During TWP-ICE both types of convection will be encountered, providing a means of relating cloud properties to convective strength. Credit: P. May, Australian Bureau of Meteorology Research Centre.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/ccsp-ocpfy2006/figure/build-up-australian-monsoon-wet-phase.yaml identifier: build-up-australian-monsoon-wet-phase lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: ccsp-ocpfy2006 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: 'Build-Up to the Australian Monsoon Wet Phase ' uri: /report/ccsp-ocpfy2006/figure/build-up-australian-monsoon-wet-phase url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: 'Radiative climate forcing by long-lived greenhouse gases. Direct radiative forcing (in Wm-2) by four classes of major long-lived greenhouse gases (left panel), and percentage of the total direct forcing for each of the four (right panel). Annual averages are from NOAA’s Global Cooperative Air Sampling Network. Credit: NOAA Climate Monitoring and Diagnostics Laboratory.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/ccsp-ocpfy2004and2005/figure/climate-forcing-by-greenhouse-gases.yaml identifier: climate-forcing-by-greenhouse-gases lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: ccsp-ocpfy2004and2005 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Climate Forcing by Greenhouse Gases uri: /report/ccsp-ocpfy2004and2005/figure/climate-forcing-by-greenhouse-gases url: ~ usage_limits: Free to use with credit to the original figure source. - attributes: ~ caption: 'As part of the Cloud and Land Surface Interaction Campaign (CLASIC), three supersites were instrumented to obtain ground-based measurements to link observed carbon fluxes to atmospheric structure. Nine aircraft—including a helicopter—participated. The SGP site’s Central Facility served as the primary source of information for cloud distribution and carbon feedbacks. The other two supersites were located in pastured lands near the Little Washita Watershed and oak forests near Okmulgee State Park. This image is from a millimeter wavelength cloud radar, which probes the extent and composition of clouds to provide information about cloud boundaries and reflectivity. On the morning of June 14, the radar detected a thunderstorm as it descended on the SGP site, followed by about 5 hours of heavy rain and then brief showers throughout the rest of the day. These data represent a rather complicated case from a modeling perspective, and therefore the need to better understand interactions and feedbacks at the land surface. Credit: W. Ferrell, DOE.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/usgcrp-ocpfy2009/figure/cloud-boundaries-reflectivity.yaml identifier: cloud-boundaries-reflectivity lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: usgcrp-ocpfy2009 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Cloud Boundaries and Reflectivity uri: /report/usgcrp-ocpfy2009/figure/cloud-boundaries-reflectivity url: ~ usage_limits: Free to use with credit to the original figure source. - attributes: ~ caption: 'a. Forest aboveground biomass (ABG) is mapped at 1-km spatial resolution. The study region was bounded at 30° North latitude and 40°South latitude to cover forests of Latin America and sub-Saharan Africa, and from 60° to 155° East and West longitude. The map was colored based on 25 – 50 Mg/ha AGB classes to better show the overall spatial patterns of forest biomass in tropical regions. Histogram distributions of forest area (at 10% tree cover) for each biomass class were calculated by summing the pixels over Latin America in b. Africa in c. and Asia in d. Similarly, total AGB for each class was computed by summing the values in each region with distributions provided for Latin America in e. Africa in f. and Asia in g. [Mg = Million metric tons]. (circa 2000)' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/usgcrp-ocpfy2012/figure/distribution-forest-aboveground-biomass.yaml identifier: distribution-forest-aboveground-biomass lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: usgcrp-ocpfy2012 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Distribution of Forest Aboveground Biomass uri: /report/usgcrp-ocpfy2012/figure/distribution-forest-aboveground-biomass url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: 'Maps show the reported cases of Lyme disease in 2001 and 2014 for the areas of the country where Lyme disease is most common (the Northeast and Upper Midwest). Both the distribution and the numbers of cases have increased (see Ch. 5: Vector-Borne Diseases). (Figure source: adapted from CDC 2015)6066212c-7cfd-46af-8255-e6c75647167a' chapter_identifier: executive-summary create_dt: 2014-08-27T12:00:00 href: https://data.globalchange.gov/report/usgcrp-climate-human-health-assessment-2016/chapter/executive-summary/figure/es-changes-in-lyme-disease-case-report-distribution.yaml identifier: es-changes-in-lyme-disease-case-report-distribution lat_max: -67.0 lat_min: -98.0 lon_max: 48.0 lon_min: 36.0 ordinal: 6 report_identifier: usgcrp-climate-human-health-assessment-2016 source_citation: ~ submission_dt: ~ time_end: 2014-12-31T23:59:59 time_start: 1996-01-01T00:00:00 title: Changes in Lyme Disease Case Report Distribution uri: /report/usgcrp-climate-human-health-assessment-2016/chapter/executive-summary/figure/es-changes-in-lyme-disease-case-report-distribution url: ~ usage_limits: ~ - attributes: ~ caption: 'These maps show the percentage change in several metrics of extreme precipitation by NCA4 region, including (upper left) the maximum daily precipitation in consecutive 5-year periods; (upper right) the amount of precipitation falling in daily events that exceed the 99th percentile of all non-zero precipitation days (top 1% of all daily precipitation events); (lower left) the number of 2-day events with a precipitation total exceeding the largest 2-day amount that is expected to occur, on average, only once every 5 years, as calculated over 1901–2016; and (lower right) the number of 2-day events with a precipitation total exceeding the largest 2-day amount that is expected to occur, on average, only once every 5 years, as calculated over 1958–2016. The number in each black circle is the percent change over the entire period, either 1901–2016 or 1958–2016. Note that Alaska and Hawai‘i are not included in the 1901–2016 maps owing to a lack of observations in the earlier part of the 20th century. (Figure source: CICS-NC / NOAA NCEI). Based on figure 7.4 in Chapter 7.' chapter_identifier: executive-summary create_dt: 2017-06-26T13:20:16 href: https://data.globalchange.gov/report/climate-science-special-report/chapter/executive-summary/figure/extreme-precipitation-increased-across-much-united-states.yaml identifier: extreme-precipitation-increased-across-much-united-states lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: climate-science-special-report source_citation: ~ submission_dt: 2017-10-25T19:05:06 time_end: ~ time_start: ~ title: Extreme Precipitation Has Increased Across Much of the United States uri: /report/climate-science-special-report/chapter/executive-summary/figure/extreme-precipitation-increased-across-much-united-states url: ~ usage_limits: Free to use with credit to the original figure source. - attributes: ~ caption: 'North American forest disturbance intensity, 1990 to 2000, mapped from about 2,200 Landsat images. Colors represent the percent of each 500 x 500 m cell disturbed during the mapping period. Credit: J. Masek, NASA/ Goddard Space Flight Center.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/usgcrp-ocpfy2010/figure/forest-disturbance-mapped-from-space.yaml identifier: forest-disturbance-mapped-from-space lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: usgcrp-ocpfy2010 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Forest Disturbance Mapped from Space uri: /report/usgcrp-ocpfy2010/figure/forest-disturbance-mapped-from-space url: ~ usage_limits: Free to use with credit to the original figure source. - attributes: ~ caption: 'Landsat images, from 1986 and 2004, reveal the effects of center-pivot irrigation in a desert region in Saudi Arabia known as Wadi As-Sirhan. In the satellite images, these irrigated fields appear as green dots. This region was once so barren that it could barely support the towns Al’Isawiyah and Tubarjal shown in the upper left of each image. Following the introduction of center-pivot irrigation, the barren desert was gradually transformed into a greener, food-producing landscape. The irrigation system draws water from an ancient underground aquifer. Credit: USGS / EROS Data Center.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/ccsp-ocpfy2008/figure/landsat-saudi-arabian-irrigation.yaml identifier: landsat-saudi-arabian-irrigation lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: ccsp-ocpfy2008 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Landsat and Saudi Arabian Irrigation uri: /report/ccsp-ocpfy2008/figure/landsat-saudi-arabian-irrigation url: ~ usage_limits: Free to use with credit to the original figure source. - attributes: ~ caption: 'These graphs illustrate the observed association between ground-level ozone concentrations and temperature in Atlanta and New York City (May to Octover 1988-1990). The projected higher temperature across the US int eh 21st century will likely increase the occurence of high ozone concentrations, especially because extremely hot days frequently have stagnant air circulation patterns, although this will also depend on emission of ozone precursors and meteorological factors. Ground-level ozone can exacerbate respiratory diseases and cause short-term reductions in lung function. (Maximum Daily Ozone Chart provided by USEPA.)' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/nca1/figure/maximum-ozone-concentrations-versus-maximum-temperature.yaml identifier: maximum-ozone-concentrations-versus-maximum-temperature lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: nca1 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: 'Maximum Ozone Concentrations versus Maximum Temperature ' uri: /report/nca1/figure/maximum-ozone-concentrations-versus-maximum-temperature url: ~ usage_limits: Free to use with credit to the original figure source. - attributes: ~ caption: 'Redeployment of the Global Climate Change Impacts in the United States - 2009 Report. Online access allows stakeholders to navigate the report in a more interactive manner. ' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/usgcrp-ocpfy2013/figure/nca2009-web-deployment.yaml identifier: nca2009-web-deployment lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: usgcrp-ocpfy2013 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: NCA 2009 Web Deployment uri: /report/usgcrp-ocpfy2013/figure/nca2009-web-deployment url: ~ usage_limits: Free to use with credit to the original figure source. - attributes: ~ caption: 'The risks to food access would be lowest under the economic conditions described in SSP 1 and SSP 5 for a given scenario of climate change, with poorer nations being at higher risk across almost all food affordability and allocation categories for all SSPs. Shading represents higher or lower risks for each SSP from climate change. Risks reflect the informed judgment of the authors of this report based on the available literature.' chapter_identifier: executive-summary create_dt: ~ href: https://data.globalchange.gov/report/usda-climate-change-global-food-security-us-food-system-2015/chapter/executive-summary/figure/relative-risks-food-access-different-ssps.yaml identifier: relative-risks-food-access-different-ssps lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: usda-climate-change-global-food-security-us-food-system-2015 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Relative risks to food access for different SSPs uri: /report/usda-climate-change-global-food-security-us-food-system-2015/chapter/executive-summary/figure/relative-risks-food-access-different-ssps url: ~ usage_limits: ~ - attributes: ~ caption: 'Carbon dioxide measurements and experiments — (a) AmeriFlux tower; (b) Free Air CO2 Enrichment (FACE); (c) ElevatedCO2 concentration experiment. Credits: AmeriFlux – Oak Ridge National Laboratory; FACE – Brookhaven National Laboratory; Smithsonian Environmental Research Center.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/ccsp-ocpfy2003/figure/carbon-dioxide-measurements-experiments-a.yaml identifier: carbon-dioxide-measurements-experiments-a lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: ccsp-ocpfy2003 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Carbon Dioxide Measurements and Experiments (a) uri: /report/ccsp-ocpfy2003/figure/carbon-dioxide-measurements-experiments-a url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: 'Significant changes in growing season have been detected in many of the 19 ecoregions across Kazakhstan. Credit: G. Henebry, University of Nebraska-Lincol' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/ccsp-ocpfy2006/figure/changes-growing-season-kazakhstan.yaml identifier: changes-growing-season-kazakhstan lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: ccsp-ocpfy2006 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: 'Changes in Growing Season: Kazakhstan' uri: /report/ccsp-ocpfy2006/figure/changes-growing-season-kazakhstan url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: 'These data compare two algorithms used to infer the global climatology. Chlorophyll a concentrations differ, approaching 100% at high latitudes. The right-hand panel shows the global estimate of colored dissolved organic material (CDOM). Credit: D.A. Siegel, University of California, Santa Barbara; S. Maritorena, University of California, Santa Barbara; N.B. Nelson, University of California, Santa Barbara; M.J. Behrenfeld, Oregon State University; and C.R. McClain NASA/Goddard Space Flight Center (reproduced from Geophysical Research Letters with permission from the American Geophysical Union).' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/ccsp-ocpfy2007/figure/characterization-carbon-matter-ocean-ecosystems.yaml identifier: characterization-carbon-matter-ocean-ecosystems lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: ccsp-ocpfy2007 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Characterization of Carbon Matter in Ocean Ecosystems uri: /report/ccsp-ocpfy2007/figure/characterization-carbon-matter-ocean-ecosystems url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: Schematic of major components needed to understand the climate system and climate change. chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/ccsp-ocpfy2004and2005/figure/climate-system-climate-change.yaml identifier: climate-system-climate-change lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: ccsp-ocpfy2004and2005 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: The Climate System and Climate Change uri: /report/ccsp-ocpfy2004and2005/figure/climate-system-climate-change url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: 'This figure illustrates the typical January–March weather anomalies and atmospheric circulation during moderate to strong (top) El Niño and (bottom) La Niña. These influences over the United States often occur most strongly during the cold season. From Figure 5.2 in Chapter 5.' chapter_identifier: executive-summary create_dt: 2016-11-30T16:27:38 href: https://data.globalchange.gov/report/climate-science-special-report/chapter/executive-summary/figure/es_el-nino-la-nina_v1---in-es-1-box.yaml identifier: es_el-nino-la-nina_v1---in-es-1-box lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: climate-science-special-report source_citation: ~ submission_dt: 2017-10-02T18:32:18 time_end: ~ time_start: ~ title: Large-Scale Patterns of Natural Variability Affect U.S. Climate uri: /report/climate-science-special-report/chapter/executive-summary/figure/es_el-nino-la-nina_v1---in-es-1-box url: ~ usage_limits: Free to use with credit to the original figure source. - attributes: ~ caption: 'Precipitation and temperature changes affect fresh and marine water quantity and quality primarily through urban, rural, and agriculture runoff. This runoff in turn affects human exposure to water-related illnesses primarily through contamination of drinking water, recreational water, and fish or shellfish (see Ch. 6: Water-Related Illness).' chapter_identifier: executive-summary create_dt: 2014-10-30T14:42:00 href: https://data.globalchange.gov/report/usgcrp-climate-human-health-assessment-2016/chapter/executive-summary/figure/es-links-between-climate-change-water-quantity-and-quality-and-human-exposure-to-water-related-illness.yaml identifier: es-links-between-climate-change-water-quantity-and-quality-and-human-exposure-to-water-related-illness lat_max: N/A lat_min: N/A lon_max: N/A lon_min: N/A ordinal: 7 report_identifier: usgcrp-climate-human-health-assessment-2016 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: 'Links between Climate Change, Water Quantity and Quality, and Human Exposure to Water-Related Illness' uri: /report/usgcrp-climate-human-health-assessment-2016/chapter/executive-summary/figure/es-links-between-climate-change-water-quantity-and-quality-and-human-exposure-to-water-related-illness url: ~ usage_limits: Free to use with credit to the original figure source. - attributes: ~ caption: 'A soil core from the Florida scrub experiment. Credit: B. Hungate, Northern Arizona University.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/usgcrp-ocpfy2009/figure/florida-scrub-experiment.yaml identifier: florida-scrub-experiment lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: usgcrp-ocpfy2009 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Florida Scrub Experiment uri: /report/usgcrp-ocpfy2009/figure/florida-scrub-experiment url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: 'Testing early results from "Experiment 0" of an Integrated Earth Systems Model. Preliminary studies illustrate the significance of potential carbon management strategies when land is considered within an Integrated Earth System Model. In the case where only fossil fuel carbon is valued (above of two forest cover images), a shift toward deforestation occurs in comparison with the IPCC Representative Concentration Pathway (RCP) case.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/usgcrp-ocpfy2012/figure/forest-cover-model-results.yaml identifier: forest-cover-model-results lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: usgcrp-ocpfy2012 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Forest Cover Model Results uri: /report/usgcrp-ocpfy2012/figure/forest-cover-model-results url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: 'Examples of the GLS 2005 images for Saskatchewan. These images illustrate the four data layers in this global data set of Landsat imagery: the 1970s, 1990, 2000, and 2005. All four data layers were geometrically corrected to the terrain using the 2000 Landsat-7 data layer as the rectification basis. These data are now being distributed free of charge through NASA and the USGS. Credit: G. Gutman, NASA/Headquarters; J. Masek, NASA/Goddard Space Flight Center; C. Justice and S. Franks, University of Maryland; R. Byrnes and R. Headley, USGS.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/usgcrp-ocpfy2010/figure/global-land-survey-examples.yaml identifier: global-land-survey-examples lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: usgcrp-ocpfy2010 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Global Land Survey Examples uri: /report/usgcrp-ocpfy2010/figure/global-land-survey-examples url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: 'Spatial distribution and intensity of selectively logged areas summarized into 25 by 25 km grid cells in 1992, 1996, and 1999 for the Amazon Basin of Brazil. Credit: E.A.T. Matricardi, D.L. Skole, and W.H. Chomentowski, Michigan State University; M.A. Cochrane, South Dakota State University; and M. Pedlowski, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Brazil (reproduced from the International Journal of Remote Sensing with permission from the publisher Taylor & Francis Group).' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/ccsp-ocpfy2008/figure/logged-areas-amazon-basin.yaml identifier: logged-areas-amazon-basin lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: ccsp-ocpfy2008 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Logged Areas in the Amazon Basin uri: /report/ccsp-ocpfy2008/figure/logged-areas-amazon-basin url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: "Joint Vulnerability Assessments by the USDA's Forest Service and DOI's National Park Service. Image: Patrick Gonzales. " chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/usgcrp-ocpfy2013/figure/nps-forest-service-landscape-collaborative-projects.yaml identifier: nps-forest-service-landscape-collaborative-projects lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: usgcrp-ocpfy2013 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: NPS & Forest Service Landscape Collaborative Projects uri: /report/usgcrp-ocpfy2013/figure/nps-forest-service-landscape-collaborative-projects url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source. - attributes: ~ caption: 'Schematic diagram of the potential health effects of climate variability and change. (Source, Patz et al., 2000) *Moderating influences include non-climate factors that affect climate-related health outcomes, such as : population growth and demographic change; standard of living; access to heatlh care; improvements in heatlh care; and public health infrastructure. **Adaptation measure include actions to reduce risks of adverse helath outcomes, such as: vaccination programs; disease surveillance; monitoring; use of protective technologies (e.g., air conditioning, pesticides, water filtration/treatment); use of climate forecasts; and development of weather warning systems; emergency management and disaster preparedness programs; and public education.' chapter_identifier: ~ create_dt: ~ href: https://data.globalchange.gov/report/nca1/figure/potential-health-effects-climate-variability-change.yaml identifier: potential-health-effects-climate-variability-change lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: nca1 source_citation: ~ submission_dt: ~ time_end: ~ time_start: ~ title: Potential Health Effects of Climate Variability and Change uri: /report/nca1/figure/potential-health-effects-climate-variability-change url: ~ usage_limits: Copyright protected. Obtain permission from the original figure source.