A collection of over 75 charts and maps presenting key statistics on the farm sector, food spending and prices, food security, rural communities, the interaction of agriculture and natural resources, and more. How much do you know about food and agriculture? What about rural America or conservation? ERS has assembled more than 75 charts and maps covering key information about the farm and food sectors, including agricultural markets and trade, farm income, food prices and consumption, food security, rural economies, and the interaction of agriculture and natural resources. How much, for example, do agriculture and related industries contribute to U.S. gross domestic product? Which commodities are the leading agricultural exports? How much of the food dollar goes to farmers? How do job earnings in rural areas compare with metro areas? How much of the Nation’s water is used by agriculture? These are among the statistics covered in this collection of charts and maps—with accompanying text—divided into the nine section titles.

CEEDAR is a Data Asset Register logging relevant datasets with accompanying information and metadata (where available).

This dataset has been superseded by a newer version, Composition of Foods Raw, Processed, Prepared USDA National Nutrient Database for Standard Reference, Release 28. The database consists of several sets of data: food descriptions, nutrients, weights and measures, footnotes, and sources of data. The Nutrient Data file contains mean nutrient values per 100 g of the edible portion of food, along with fields to further describe the mean value. Information is provided on household measures for food items. Weights are given for edible material without refuse. Footnotes are provided for a few items where information about food description, weights and measures, or nutrient values could not be accommodated in existing fields. Data have been compiled from published and unpublished sources. Published data sources include the scientific literature. Unpublished data include those obtained from the food industry, other government agencies, and research conducted under contracts initiated by USDA’s Agricultural Research Service (ARS). Updated data have been published electronically on the USDA Nutrient Data Laboratory (NDL) web site since 1992. Standard Reference (SR) 27 includes composition data for all the food groups and nutrients published in the 21 volumes of “Agriculture Handbook 8” (US Department of Agriculture 1976-92), and its four supplements (US Department of Agriculture 1990-93), which superseded the 1963 edition (Watt and Merrill, 1963). SR27 supersedes all previous releases, including the printed versions, in the event of any differences. Attribution for photos:Photo 1: k7246-9 Copyright free, public domain photo by Scott BauerPhoto 2: k8234-2 Copyright free, public domain photo by Scott Bauer

[Note: Integrated as part of FoodData Central, April 2019.] The database consists of several sets of data: food descriptions, nutrients, weights and measures, footnotes, and sources of data. The Nutrient Data file contains mean nutrient values per 100 g of the edible portion of food, along with fields to further describe the mean value. Information is provided on household measures for food items. Weights are given for edible material without refuse. Footnotes are provided for a few items where information about food description, weights and measures, or nutrient values could not be accommodated in existing fields. Data have been compiled from published and unpublished sources. Published data sources include the scientific literature. Unpublished data include those obtained from the food industry, other government agencies, and research conducted under contracts initiated by USDA’s Agricultural Research Service (ARS). Updated data have been published electronically on the USDA Nutrient Data Laboratory (NDL) web site since 1992. Standard Reference (SR) 28 includes composition data for all the food groups and nutrients published in the 21 volumes of "Agriculture Handbook 8" (US Department of Agriculture 1976-92), and its four supplements (US Department of Agriculture 1990-93), which superseded the 1963 edition (Watt and Merrill, 1963). SR28 supersedes all previous releases, including the printed versions, in the event of any differences. Attribution for photos: Photo 1: k7246-9 Copyright free, public domain photo by Scott Bauer Photo 2: k8234-2 Copyright free, public domain photo by Scott Bauer

A daily food plan shows what and how much your child should eat to meet his or her needs. You can create an eating plan for your preschooler using the SuperTracker's MyPlan. You will be asked to create a profile using your child’s information. You can register to save the profile if you want to. Use the Plan as a general guide to help you feed your child. It will show what and how much to offer your child to meet his or her needs.

The average American’s diet does not align with the Dietary Guidelines for Americans (DGA) provided by the U.S. Department of Agriculture and the U.S. Department of Health and Human Services (2020). The present study aimed to compare fruit and vegetable consumption among those who had and had not heard of the DGA, identify characteristics of DGA users, and identify barriers to DGA use. A nationwide survey of 943 Americans revealed that those who had heard of the DGA ate more fruits and vegetables than those who had not. Men, African Americans, and those who have more education had greater odds of using the DGA as a guide when preparing meals relative to their respective counterparts. Disinterest, effort, and time were among the most cited reasons for not using the DGA. Future research should examine how to increase DGA adherence among those unaware of or who do not use the DGA. Comparative analyses of fruit and vegetable consumption among those who were aware/unaware and use/do not use the DGA were completed using independent samples t tests. Fruit and vegetable consumption variables were log-transformed for analysis. Binary logistic regression was used to examine whether demographic features (race, gender, and age) predict DGA awareness and usage. Data were analyzed using SPSS version 28.1 and SAS/STAT® version 9.4 TS1M7 (2023 SAS Institute Inc).

Four to six-week-old larvae of Trogoderma variabile and Trogoderma inclusum were used for the experiment. Both strains were originally obtained from the field in north-central Kansas in 2016 and 2012, respectively. Colonies of these species were reared under controlled conditions in an environmental chamber set to a temperature of 27.5 °C, 65% RH, and 14:10 (L:D) h photoperiod. Both species were fed 300 g of ground dog food (SmartBlend, Lamb flavor, PurinaOne, St. Louis, MO, USA) with oats sprinkled on top and a moistened, crumpled paper towel placed on the surface in a 950-ml mason jar. Treatments The long-lasting insecticide-incorporated polyethylene netting (2 × 2 mm mesh, D-Terrance, Vestergaard Inc., Lausanne, Switzerland) included 0.4% deltamethrin, or control netting that was identical in physical properties but without insecticide. These were used with the movement assay. We assessed the movement in the vicinity of important pheromonal and food kairomones after exposure to LLIN or control netting. Food consisted of 0.01 g of organic, unbleached flour (Heartland Mills, Marienthal, KS, USA), and pheromonal stimuli included a broad spectrum, multi-species lure (PTL lure, IL-108-10, Batch#1288200321, Insects Limited, Westfield, IN, USA), including Trogoderma spp pheromone (Ranabhat et al. 2023a). In each replicate, we used a single pellet (white color), and affixed it in place so it did not move in a Petri dish using a 1 × 1 mm square of parafilm. For each replication of testing, we used a fresh lure. Movement Assay The movement of larvae after exposure to the 0.4 % deltamethrin LLIN or a control netting in response to food cues (using 0.01 g of flour) or with conspecific sex pheromones (using a single bead from a disaggregated PTL lure held in place with a small square of parafilm), was tracked in six individual arenas (100 × 15 mm D: H) with a piece of filter paper (85 mm D, Ahlstrom-Munksjö, Helsinki, Finland) lining the bottom for 30 min using a network camera (GigE, Basler AG, Ahrenburg, Germany) affixed 76 cm above and centered over the dishes. The Petri dishes were backlit using a LED light box (42 × 30 cm W:L LPB3, Litup, Shenzhen, China) to increase contrast and affixed in place with white foam board. The video was streamed to a computer and processed in Ethovision (v.14.5 Noldus Inc., Leesburg, VA, USA). Prior to use in the movement assay, larvae of T. variabile or T. inclusum were exposed to the 0.4% deltamethrin LLIN or a control netting for 1 min in a 21 × 21 cm square Petri dish, then their movement was tracked individually after a post-exposure holding duration of 1 min or 24 h. A small 1.1 cm hidden stimulus zone encircled each stimulus, midway and centered on each half of the arena wherein movement was tracked separately from each half of the arena (control vs. treatment). The total distance moved (cm), instantaneous velocity (cm/s), frequency of entering each half of the petri dish and stimulus zone, cumulative duration spent in each zone (s), and latency of entering each zone (s) over a 30 min trial period was logged after exposure to a given treatment. The control side of the arena remained empty. A total of n = 16 replicates were run per treatment combination for both species No-Choice Release-Recapture Assay A release- recapture experiment was conducted for the larvae of both T. variabile and T. inclusum where larvae were exposed to the 0.4% deltamethrin LLIN and control netting for 1 min. After exposure, treated insects were released at one corner of the sanded plastic bin (60 × 41.6 × 16.5 cm L:W:H ). A commercial pitfall trap (Dome Trap™, Trécé, Inc., Adair, OK, USA) that contained a PTL lure (used only white beads as above), or 0.01 g flour, or no stimuli (unbaited for control), was deployed in the opposite corner, diagonally across from the release point in the bin. The bins were located in a large (4.8 × 2.1 × 6 m, L:W:H) walk-in environmental chamber (Percival Instruments, Dallas County, IA, USA) set at constant conditions (27.5°C, 60% RH, and 14:10 L:D). A total of 10 larvae were released in each bin during each replicate. Treated larvae were given 24 h to disperse to the semiochemicals in each trap, and then the number of insects captured inside the trap, found on the bottom of the trap, on the stimulus half of container or on the non-stimulus half of the container were recorded. A total of n = 12 replicates were performed per treatment combination for the larvae of each species. Resources in this dataset: Resource Title: Ethovision Movement Assay File Name: ranabhat_etal_larval_dermestid_et_LLIN_olfactory_agdata_commons.csv Resource Title: No-Choice Release-Recapture Assay for Larger Cabinet Beetle File Name: ranabhat_etal_larval_dermestid_rr_lcb_LLIN_agdata_commons.csv Resource Title: No-Choice Release-Recapture Assay for Warehouse Beetle File Name: ranabhat_etal_larval_dermestid_rr_whb_LLIN_agdata_commons.csv

FSIS’ FoodKeeper application educates users about food and beverages storage to help them maximize the freshness and quality of these items. By helping users understand food storage, the application empowers consumers to choose storage methods that extend the shelf life of their items. By doing so users will be able to keep items fresh longer than if they were not stored properly.

The mission of FNS is to provide children and needy families better access to food and a more healthful diet through its food assistance programs and comprehensive nutrition education efforts. These dataset provides a summary of all the FNS School Food Program combined into one dataset. It contains cash payments and commodity costs for the National School Lunch Program, School Breakfast Program and the Special Milk Program. (format: html, xls)

The ERS Food Expenditure Series annually measures total U.S. food expenditures, including purchases by consumers, governments, businesses, and nonprofit organizations. The ERS Food Expenditure Series contributes to the analysis of U.S. food production and consumption by constructing a comprehensive measure of the total value of all food expenditures by final purchasers. This series annually measures total U.S. food expenditures, including purchases by consumers, governments, businesses, and nonprofit organizations. Because the term expenditure is often associated with household decisionmaking, it is important to recognize that ERS's series also includes nonhousehold purchases. For example, the series includes the dollar value of domestic food purchases by military personnel and their dependents at military commissary stores and exchanges, the value of commodities and food dollars donated by the Federal government to schools, and the value of food purchased by airlines for serving during flights.

Find the calorie content of any food or beverage using the Food-a-pedia, looking at the Nutrition Facts label, or checking product or restaurant websites

USDA's National Household Food Acquisition and Purchase Survey (FoodAPS) will provide unique and detailed data about household food choices that are not available from any other survey. FoodAPS is a nationally representative survey of household food purchases and acquisitions.

Total and marginal budget shares and income and price elasticities are estimated, using 2005 ICP data, for nine broad consumption groups and eight food subgroups across 144 countries.

Explore the Saudi Arabia Merchandise Export dataset for insights into non-oil exports, agricultural products, construction materials, petrochemicals, and more . Non-oil Exports, Agricultural, Animal and food products, Construction materials, Total, Refined products, Other goods, Total Exports, Petrochemicals, Exports, Value, Commodity, Oil Exports, Crude Oil, petrochemical, Construction, Agriculture, Animal, Food, Good, Non-Oil, non oil, SAMA Annual Saudi ArabiaFollow data.kapsarc.org for timely data to advance energy economics research..Other Goods : Including re-exports

My Cookbook is an online tool that helps you compile your favorite recipes in one central place and search SNAP, household, and quantity recipes. You can also submit personal recipes to the repository and browse submitted cookbooks. My Cookbook also provides USDA Foods Fact Sheets.

This database collates 3552 development indicators from different studies with data by country and year, including single year and multiple year time series. The data is presented as charts, the data can be downloaded from linked project pages/references for each set, and the data for each presented graph is available as a CSV file as well as a visual download of the graph (both available via the download link under each chart).

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.

Pyrethroid exposures and intake doses. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: No contains PII, but all raw data have been provided in the paper (without PII). Format: Contains PII; however all raw data are provided in the paper (without PII). This dataset is associated with the following publication: Morgan, M. Dietary Pyrethroid Exposures and Intake Doses for 188 Duplicate-Single Solid Food Items Consumed by North Carolina Adults. Toxics. MDPI AG, Basel, SWITZERLAND, 8(1): 6, (2020).

The Supplemental Nutrition Assistance Program (SNAP) Retailer Locator is designed to help recipients find SNAP local stores that welcome SNAP benefits. The tool is intended to offer assistance to program recipients, State eligibility workers, community organizations - such as food banks - and others providing assistance to those in need. SNAP Retail Locator tool will make it easier for SNAP participants, especially those who may be new and unfamiliar with the program, to gain access to food. The locator is available at http://www.fns.usda.gov/snap/retailerlocator.htm

U.S. consumers demand variety, quality, and convenience in the foods they consume. As Americans have become wealthier and more ethnically diverse, the American food basket reflects a growing share of tropical products, spices, and imported gourmet products. Seasonal and climatic factors drive U.S. imports of popular types of fruits and vegetables and tropical products, such as cocoa and coffee. In addition, a growing share of U.S. imports can be attributed to intra-industry trade, whereby agricultural-processing industries based in the United States carry out certain processing steps offshore and import products at different levels of processing from their subsidiaries in foreign markets. This data set provides import values of edible products (food and beverages) entering U.S. ports and their origin of shipment. Data are from the U.S. Department of Commerce, U.S. Census Bureau. Food and beverage import values are compiled by calendar year into food groups corresponding to major commodities or level of processing. At least 10 years of annual data are included, enabling users to track long-term growth patterns.

Recent USDA/ARS patented technologies on food processing and products that are available for licensing are described, including summary, contact, benefits, and applications. Updated June 2018.

From the Agricultural Research Service Contains: - USDA National Nutrient Database for Standard Reference (Release 28, released September 2015, slightly revised May 2016) - USDA Branded Food Products Database Internet Archive URL: https://web.archive.org/web/*/https://ndb.nal.usda.gov/ndb/

[Note: Integrated as part of FoodData Central, April 2019.] The USDA National Nutrient Database for Standard Reference (SR) is the major source of food composition data in the United States and provides the foundation for most food composition databases in the public and private sectors. This is the last release of the database in its current format. SR-Legacy will continue its preeminent role as a stand-alone food composition resource and will be available in the new modernized system currently under development. SR-Legacy contains data on 7,793 food items and up to 150 food components that were reported in SR28 (2015), with selected corrections and updates. This release supersedes all previous releases.

Data on occupational health & safety, key nutrition targets (global and by country) and community investment.

Water footprint statistics based on peer-reviewed reserach and Global Water Footprint Assessment standard, providing data on blue, green adn grey footrpints, disaggregated by product type, country (and in some cases sub-national region). Data sets include Product water footprint (crops and derived products, biofuels, farm animals and animal products, industrial products) National Water Footrpints (national production and consumption), international virtual water flow statistics (flows from trade, savings from trade), monthly blue water gridded footprint of production (30x30 arc minute), water scarcity statistics (blue water scarcity at montly 30x30 arc), Pollution due to nitrogen and phosphorous (5x5 arc minute 2002-2010), United States Production footprint at national, state and county scale (2010-12), China Water Footprint of 22 crops at 5x5 arc minute (1961-2009)

Policysupport.org is home to a range of web-based policy support systems developed, since 2003, collaboratively by AmbioTEK CIC, and applied by King's College London and a range of other partners as specified for each system. The systems are based on the common ecoengine framework for developing web based policy support systems (AmbioTEK) and SimTerra databases (AmbioTEK) but are very varied in their applications (King's College London). Applications in the Policy Support Suite include: WaterWorld: a testbed for the development and implementation of land and water related policies for sites and regions globally, enabling their intended and unintended consequences to be tested in silico before they are tested in vivo. WaterWorld can also be used to understand the hydrological and water resources baseline and water risk factors associated with specific activities under current conditions and under scenarios for land use, land management and climate change. It incorporates detailed spatial datasets at 1-square km and 1 hectare resolution for the entire world, spatial models for biophysical and socio-economic processes along with scenarios for climate, land use and economic change. A series of interventions (policy options) are available which can be implemented and their consequences traced through the socio-economic and biophysical systems. The model integrates with a range of geobrowsers for immersive visualisation of outcomes. AguAAndes: a testbed for the development and implementation of land and water related policies in the Andes, enabling intended and unintended consequences to be tested in silico before they are tested in vivo . It incorporates detailed spatial datasets at 1-square km and 1 hectare resolution for the entire Andes, spatial models for biophysical and socioeconomic processes along with scenarios for climate, land use and economic change. A series of interventions (policy options) are available which can be implemented and their consequences traced through the socio-economic and biophysical systems. CompAndes: a web based tool based on AguAAndes and is developed as a Negotiation Support System (NSS) for negotiations around benefit sharing mechanisms for water. This NSS is a testbed for negotiations around benefit sharing mechanisms for water focusing on sustaining equitable flows of water for all through appropriate land, ecosystem and water management. It is focused on enabling the intended and unintended consequences of benefit sharing mechanisms to be tested in silico before they are tested in vivo. Co$ting Nature: a web based tool for natural capital accounting and analysing the ecosystem services provided by natural environments (i.e. nature's benefits), identifying the beneficiaries of these services and assessing the impacts of human interventions. This PSS is a testbed for the development and implementation of conservation strategies focused on sustaining and improving ecosystem services. MENARA: a web based policy support system for understanding strength, weakness, opportunity and threat (SWOT) at scales from pixel through regional to national considering environment, water, energy, food, economy and population. It is an horizon scanning tool to identify material threats, opportunities and choke points that may precipitate conflict and is designed to help to think through locally appropriate policy responses. FIESTA-FOGINT: a research model to quantify fog inputs in absolute terms and as a proportion of rainfall. Commonly applied to tropical montane cloud affected forests. Also maps the distribution of these forests. EcoActuary: a testbed for the development and implementation of green and grey infrastructure investments focused on reducing the risk to insured assets of multi-hazard risks, including flooding and drought. It incorporates detailed spatial datasets at 1-square km and 1 hectare resolution for the entire world, spatial models for biophysical and socioeconomic processes along with scenarios for climate, land use and economic change. A series of investments can be implemented and their consequences traced through the socio-economic and biophysical systems. An actuary determines the probability (and financial consequences) of risks. They work with accountants, underwriters (and catastrophe modellers) to set insurance rates (premiums). The Eco:Actuary determines mitigation of risk by specific configurations of green infrastructure (GI) and by asset adaptation. It helps understand the asset value protected by GI, alongside other GI co-benefits (ecosystem services). The Eco:Actuary helps advise risk reduction, resilience to avoid losses.