FRA 2015 Key outputs
Why do FRA numbers change between assessments?
It is tempting to compare the results of FRA 2015 with the results from previous assessments. While this can be useful in seeking to understand the reasons for change, it is a very difficult task that in many cases is not possible. FRA 2015 reports 25 years of forest change - which is the longest period covered by any of the FRA-related reports since 1948. While some might expect data standards, variables and methods to remain constant over long periods, the reality is that they do not. New inventories and remote sensing results provide new insights into past forest area and resource information.
Countries can change data for previous years when they have new evidence that improves previously reported data. These updates mean that values for the same reporting year are likely to change for many variables from one assessment to the next. For example, a country may have reported planted forest area for the year 1990 in FRA 2000, 2005, 2010 and 2015. It is possible that those reports could be different for the year 1990 in each assessment. This rarely occurs, but it is possible.
New values for previous years may be provided for a variety of reasons, including: 1)new data collection methods or new forest inventories become available; 2) country boundaries have changed; 3)mistakes are discovered; 4) new definitions are used at national level or; 5) data gaps have been filled. Each of these can cause substantial change in data for past years. This may result in global, regional or national values that for the same reporting year are different from one assessment to the next.
FAO has noted that the values reported in one FRA cannot readily be compared with one another (FAO, 2010) because of the changes in definitions and national-scale monitoring and assessment methods. It is important to note that FRA 2015 is no different in this regard from previous assessments. We urge users to not compare values from FRA 2015 with those from FRA 2000, FRA 2005 and FRA 2010. For analyses of results for periods prior to 1990
Comparing results from the Global Forest Resources Assessment and remote sensing
Understanding forest dynamics is necessary for the sound management of forests, for both production and conservation. This includes an understanding of the extent of forest area, information about what the forest contains and how the forest resource is managed. Forest monitoring provides this information.
Information on forest dynamics is routinely provided by countries through the Global Forest Resources Assessment (FRA) of the Food and Agriculture Organization of the United Nations (FAO). FRA reports generally come from a combination of ground-based measurement/assessment and remote sensing at the national scale. FRA results have pointed to steady decreases in deforestation rates over recent decades as well as the concentration of net forest loss in the tropics. Recently scientists monitoring tree cover from space have reported, however, that deforestation has instead been increasing, especially in the tropics.
These apparently opposing assessments of forest loss are unfortunate - primarily because they do not report on the same thing- therefore the differences are misleading. Fortunately, it can be shown that they are primarily due to the use of different definitions of forest. To put it simply, while the FAO and International Panel on Climate Change (IPCC) approaches focus on the forest rather than the trees, the remote sensing-based approach presented in many global remote sensing analyses report tree cover change only.
FRA reporting first provided the data that pointed to forest loss in the tropics as well as the basis for understanding the role of forests in climate change. Because deforestation is associated with changes in land use rather than tree cover alone, the United Nations Framework Convention on Climate Change (UNFCCC) employs a definition of national forests in line with FAO’s definition for key mechanisms such as the Kyoto Protocol and REDD+.
Have the recent satellite-based efforts helped advance the science? Absolutely. Are they opening new ways for countries to be able to better identify their own forests and trends with the help of advanced technologies? Certainly.
Have these new methods helped clarify trends in historical deforestation? Here the answer is a resounding no. As noted above, remote sensing information generally does well at seeing tree cover in most forest types, but is still unable to see the forest – which is substantially more complicated than tree cover. This is evidenced by the fact that the differences between Landsat-based global forest estimates are often greater than the differences between ground-based FRA reporting and Landsat-based remote sensing estimates. This is true even for remote sensing results from the same university (e.g. see Kim et al. and Hansen (2013) cited in Beuchle et al, 2015).
Temporary losses of tree cover are mistakenly seen as deforestation by satellites, country reports –despite the criticism of data quality for some reports —can critically differentiate between forest cut-and-growth cycles, including degradation on the one hand and deforestation on the other. They also differentiate between forest and other tree crops such as oil palm or fruit trees, which are all counted as "forest" in most global remote sensing studies of tree cover change.
Additionally, satellite images used to date do not provide sufficiently robust information on tree species, stocking rates, stem diameters, height or biomass that are essential in understanding forests. In addition national assessments report other aspects of forests and forest management that are not possible to collect from space, including forest tenure and access rights, the status of sustainable forest management, legal and institutional frameworks for forest conservation and sustainable use, etc. Ground surveys and expert judgment is needed for all of that – elements that are not possible in global Landsat analyses of tree cover. Understanding of this set of complex forest characteristics is best made by countries themselves which generally work hard to provide the best possible information regarding their forests.
Comparing the results coming from two different methodologies, remote sensing and FRA, is therefore inappropriate. We urge caution in the use of global remote sensing products alone as a measure of understanding forest loss and gain.