While Mato Grosso has a good monitoring system for deforestation, it has been unable to accurately estimate historic emissions by converting hectares of deforested and degraded forests to emissions in tons of CO₂e. This is because the carbon stocks of the state's diverse biomes remain unknown. A 2009 Workshop on Carbon Accounting for REDD Projects held in Cuiabá generated several recommendations, including:
(1) Biomass stocks estimates must be prioritized based on sample stratification by type of forest concentrated in areas near to those where deforestation has happened recently;
(2) Measurements of the reduction of forest biomass after degradation by selective logging or fire in the shrub layer are also necessary for updating the biomass maps where such changes can be identified by satellite along the agricultural frontier;
(3) The historical series for deforestation and degradation must be revised in order to reduce uncertainties associated with differences among the emissions from such interventions. Degradation and the dynamics of forest recovery (natural regeneration) are minor components of the emission flows when compared to deforestation and should only be considered from the moment when a historical series of consistent data is available. The next step in this direction is to replace the current data on gross deforestation by information based on a historical series of satellite images in which the forest transitions, degraded areas and deforestation are visible. The time series after deforestation is also important in identifying natural regeneration and subsequent changes in land use; and
(4) The components of the historical emissions calculations (e.g., fire, decomposition) influence short term estimates (5-10 years), but they are not considered in cases in which the accounting period is longer (over 10 years) or in which the calculations are made by compromised emissions. To reduce uncertainty regarding annual emissions during the next stage, efficiency measures for burning and biomass after deforestation can be made for various types of land use (e.g., pasture, small-scale agriculture, mechanized agriculture). The assessment of open areas with different ages helps in the comparison of emissions in subsequent years after initial deforestation.
The primary drivers of deforestation in Mato Grosso are cattle ranching and intensive agriculture (in particular soy). Land is often cleared for cattle, with cleared areas later becoming soy farms when cattle ranchers move to new areas for grazing.
Metodologias de monitoramento e precisão / Monitoring methodologies and accuracy Monitoring methodologies and accuracy
The State uses two systems for monitoring deforestation: the National Institute for Space Research (INPE) PRODES and its own statewide methodology.
PRODES has been the official source for Brazilian Amazon deforestation data since 1978. PRODES data are publicly available. The system is based on Landsat images with a 1:250,000 scale, covering a minimum area of 5.76 ha.
The State methodology is based on Landsat and Spot 5 satellite images. Spot 5 images have higher resolution images, which allow the State to monitor deforestation on smaller areas than PRODES.
In addition to PRODES and DETER, Mato Grosso has worked with the civil society organization IPAM to refine the Carbon Calculator (CCal) tool which improves forest carbon estimates in the state.
Mato Grosso needs additional staff to monitor deforestation and would like to increase the frequency of deforestation monitoring to more than once per year.
The main driver of forest degradation is selective logging for activities including cattle ranching.
Mato Grosso currently uses INPE's DEGRAD for forest degradation monitoring. It is based on satellite images from LANDSAT and CBERS. DEGRAD can map areas as small as 6.25 ha.
Mato Grosso is in the process of developing a state system for monitoring degradation.
The State needs more information about degradation processes in order to integrate degradation into a REDD+ system based on accurate MRV. A historical series of data would contribute to this understanding.
Mato Grosso has implemented monitoring methodologies in two project areas: Cotriguaçu and SESC Pantanal. In Cotriguaçu, forest sampling was initially stratified at a 1:250,000 scale. Each stratum included a minimum of four plots (1ha=100x100m), where diameter at breast height measurements were recorded. The Rainfor standard protocol was used.
In SESC Pantanal, 10 forest classes were defined for systematic sampling of carbon estimates in the vegetation and soil using permanent plots, with one plot per 500 ha. The emphasis was on forest ecosystems rather than grass ecosystems. A total of 167 circular 12-meter diameter plots were established and every individual plant over 5 cm of diameter was measured in height and diameter (at 30 cm high). In each plot, 10 trees were sampled for diametric range and dry biomass, and density and carbon content were quantified. Based on the dry biomass content, allometric equations were derived for biomass estimates in relation to diameter (at 30 cm high) and height.
Mato Grosso needs to comprehensively quantify the carbon stocks of its various biomes (including savannah areas and wetlands, which may be included in the FAO or UNFCCC definitions for forest) in order to develop a statewide REDD program.