Index Of The Forest Movie
Adele Strecker
The FLII finds that most remaining high-integrity forest landscapes are found in Canada, Russia, Rocky Mountains, Alaska, the Amazon, the Guianas, southern Chile, Central Africa, and New Guinea. Low integrity forests, on the other hand, are found in Western and Central Europe, the American Southeast, South-East Asia west of New Guinea, the Andes, much of China and India, the Albertine Rift, West Africa, Mesoamerica, and the Atlantic Forests of Brazil.
The results are meant to help decision-makers at all levels achieve their commitments to the Sustainable Development Goals (SDGs), United Nations Convention on Biological Diversity (CBD), Convention to Combat Desertification (UNCCD), and the Framework Convention on Climate Change (UNFCCC).[1]
The first three components are fuel moisture codes, which are numeric ratings of the moisture content of the forest floor and other dead organic matter. Their values rise as the moisture content decreases. There is one fuel moisture code for each of three layers of fuel: litter and other fine fuels; loosely compacted organic layers of moderate depth; and deep, compact organic layers.
The remaining three components are fire behavior indices, which represent the rate of fire spread, the fuel available for combustion, and the frontal fire intensity; these three values rise as the fire danger increases
The diagram below illustrates the components of the FWI System. Calculation of the components is based on consecutive daily observations of temperature, relative humidity, wind speed, and 24-hour precipitation. The six standard components provide numeric ratings of relative potential for wildland fire.
The Fine Fuel Moisture Code (FFMC) is a numeric rating of the moisture content of litter and other cured fine fuels. This code is an indicator of the relative ease of ignition and the flammability of fine fuel.
The Duff Moisture Code (DMC) is a numeric rating of the average moisture content of loosely compacted organic layers of moderate depth. This code gives an indication of fuel consumption in moderate duff layers and medium-size woody material.
The Drought Code (DC) is a numeric rating of the average moisture content of deep, compact organic layers. This code is a useful indicator of seasonal drought effects on forest fuels and the amount of smoldering in deep duff layers and large logs.
The Initial Spread Index (ISI) is a numeric rating of the expected rate of fire spread. It is based on wind speed and FFMC. Like the rest of the FWI system components, ISI does not take fuel type into account. Actual spread rates vary between fuel types at the same ISI.
The Buildup Index (BUI) is a numeric rating of the total amount of fuel available for combustion. It is based on the DMC and the DC. The BUI is generally less than twice the DMC value, and moisture in the DMC layer is expected to help prevent burning in material deeper down in the available fuel.
The Daily Severity Rating (DSR), an additional component of the FWI system, is a numeric rating of the difficulty of controlling fires. It is based on the Fire Weather Index but it more accurately reflects the expected effort required for fire suppression.
The Forest Drought Response Index (ForDRI) is a new combined indicator tool to monitor forest drought conditions1. The ForDRI presents a weekly depiction of drought-related forest stress across the continental U.S. ForDRI was developed by the National Drought Mitigation Center (NDMC) at the University of Nebraska-Lincoln (UNL) in collaboration with the U.S. Department of Agriculture (USDA), U.S. Forest Service (USFS), and Center for Advanced Land Management Information Technologies (CALMIT) at UNL.
The United States Department of Agriculture (USDA) provides leadership on food, agriculture, natural resources, rural development, nutrition, and related issues based on public policy, the best available science, and effective management.
The Center for Advanced Land Management Information Technologies (CALMIT) is widely recognized for its research and education excellence in the use of remote sensing and other spatial technologies such as geographic information systems (GIS) to advance our scientific understanding and management of natural resources and agriculture.
Healthy forests are essential for a healthy Colorado. Forest health depends on a stable climate and robust ecosystems. The Forest Health Index (FHI) tracks these conditions for 38 forested watersheds across Colorado.
We monitor 12 indicators of forest health, such as temperature, precipitation, and fire risk. Each year we compare present and historic conditions. We assign each indicator a score based on how much current conditions differ from the past.
As a result, the indicators we look at include a broad range of physical environmental indicators, such as climatic and ecological measurements, as well as records on human activity and management practices in and around the forest.
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The Keetch-Byram Drought Index (KBDI) assesses the risk of fire by representing the net effect of evapotranspiration and precipitation in producing cumulative moisture deficiency in deep duff and upper soil layers.
The KBDI attempts to measure the amount of precipitation necessary to return the soil to full field capacity. The index ranges from zero, the point of no moisture deficiency, to 800, the maximum drought that is possible, and represents a moisture regime from 0 to 8 inches of water through the soil layer. At 8 inches of water, the KBDI assumes saturation. At any point along the scale, the index number indicates the amount of net rainfall that is required to reduce the index to zero, or saturation.
Burgan, R.E.; Hardy, C.C.; Ohlen, D.O.; Fosnight, G.; Treder, R. 1999. Ground sample data for the national land cover characteristics database. United States Department of Agriculture, Forest Service, General Technical Report RMRS-GTR-41, Rocky Mountain Research Station,Ogden, Utah. 12 pages.
Burgan, R.E.; Hartford, R.A. 1993. Monitoring vegetation greenness with satellite data. United States Department of Agriculture, Forest Service, General Technical Report INT-297, Intermountain Forest and Range Experiment Station, Ogden, Utah. 13 pages.
Burgan, Robert E.; Hartford, Roberta A.; Eidenshink, Jeffery C. 1996. Using NDVI to assess departure from average greenness and its relation to fire business. Gen. Tech. Rep. INT-GTR-333. Ogden, UT:U.S. Department of Agriculture, Forest Service, Intermountain Research Station. 8 p.
Latham, Don J.; Schlieter, Joyce A. 1989. Ignition probabilities of wildland fuels based on simulated lightning discharges. Res. Pap. INT-411. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Research Station. 16 pp.
As the climate becomes hotter and drier in the Southwest United States, forests are experiencing more drought, wildfires, and pest pressure. Forested ecosystems provide essential services such as providing habitat, clean water, and economic and cultural benefits. Forest managers rely on resources and decision-support tools to help forests adapt to a changing climate. However, forest tools and resources are often created with limited coordination. This lack of coordination, along with the sheer number of resources available, leads to an inability on the part of decision-makers to assess options and choose the most appropriate action for their specific objectives.
In response to this challenge and in collaboration with the South Central and Southwest Climate Adaptation Science Centers (CASCs), the USDA Southwest Climate Hub has developed the Forest Resource Index for Decisions in Adaptation or FRIDA. FRIDA is an online library of decision-support tools and resources to help support climate change adaptation decision-making and forest stewardship in the Southwest. FRIDA allows managers and decision-makers to easily query based on their objectives and area(s) of interest. Users can filter resources by topic, region/state, resource platform, and vegetation type to efficiently find the most relevant region-specific tools and resources to best fit their needs.
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Many global environmental agendas, including halting biodiversity loss, reversing land degradation, and limiting climate change, depend upon retaining forests with high ecological integrity, yet the scale and degree of forest modification remain poorly quantified and mapped. By integrating data on observed and inferred human pressures and an index of lost connectivity, we generate a globally consistent, continuous index of forest condition as determined by the degree of anthropogenic modification. Globally, only 17.4 million km2 of forest (40.5%) has high landscape-level integrity (mostly found in Canada, Russia, the Amazon, Central Africa, and New Guinea) and only 27% of this area is found in nationally designated protected areas. Of the forest inside protected areas, only 56% has high landscape-level integrity. Ambitious policies that prioritize the retention of forest integrity, especially in the most intact areas, are now urgently needed alongside current efforts aimed at halting deforestation and restoring the integrity of forests globally.
Deforestation is a major environmental issue1, but far less attention has been given to the degree of anthropogenic modification of remaining forests, which reduces ecosystem integrity and diminishes many of the benefits that these forests provide2,3. This is worrying since modification is potentially as significant as outright forest loss in determining overall environmental outcomes4. There is increasing recognition of this issue, for forests and other ecosystems, in synthesis reports by global science bodies such as the global assessment undertaken by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services5, and it is now essential that the scientific community develop improved tools and data to facilitate the consideration of levels of integrity in decision-making. Mapping and monitoring this globally will provide essential information for coordinated global, national, and local policy-making, planning, and action, to help nations and other stakeholders achieve the Sustainable Development Goals (SDGs) and implement other shared commitments such as the United Nations Convention on Biological Diversity (CBD), Convention to Combat Desertification (UNCCD), and Framework Convention on Climate Change (UNFCCC).
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