The Rimba Raya Biodiversity Reserve REDD Project

offset to an unknown degree the enhanced security of animportant, at-­‐risk biodiversity area that would eventually belost without the project (on-­‐site positive impacts).Given that the areas to be protected by the project – namely,nearby TPNP and the associated buffer zone – are widelyacknowledged as the most important biodiversity reservoirs insouthern Kalimantan, and that they are both highly threatened,any rational evaluation strongly suggests that net impacts will beoverwhelmingly positive.B3. Biodiversity Impact MonitoringB3.1. Preliminary Biodiversity Monitoring PlanDevelop an initial plan for selecting biodiversity variables to bemonitored and the frequency of monitoring and reporting to ensurethat monitoring variables are directly linked to the project’s biodiversityobjectives and to anticipated impacts (positive and negative).Four broad categories of monitoring activities that addressbiodiversity management goals of the project include: (i) changein forest cover and condition; (ii) plant and wildlife population;(iii) quality and condition of aquatic habitats – including riversand lakes – and of terrestrial wetland ecosystems such asmarshes and inundated grasslands; and (iv) fires.Forest Cover and ConditionAs most biodiversity management goals are linked to themaintenance and protection of forests, monitoring the extentand condition of forest cover in the Project zone will be a toppriority. This portion of the plan also links directly tomaintenance and monitoring of carbon stocks, so the ultimatedesign of a forest cover and condition monitoring system must besufficiently robust to describe change within acceptable levels ofprecision as required by the CCBA and VCS at the verificationstage.Forest cover and condition monitoring can be achieved through acombination of remote sensing methods and field observation.Medium-­‐resolution imagery (e.g. Landsat 7) should be obtainedand analyzed every six months, supplemented with high-­resolution(Ikonos, QuickBird, or aerial photography) imageryobtained and analyzed on an annual basis. Forest cover andcondition classes should be analyzed using at least three classes,e.g. > 70%, 70-­‐50% and < 50% canopy cover. These classes canbe defined first through image classification, but should then beinvestigated intensively on the ground during the first year to testthat degradation classes based on image analysis in factcorrespond to real difference in canopy cover, perhaps usingbasal area as an easily measured proxy.Accurate interpretation of satellite imagery to classify forestcover and condition classes may require ecosystem-­‐specificmethods (e.g., peat swamp vs. kerangas vs. lowland dipterocarpforest) in order to increase global accuracy across the ProjectZone.Another form of field data collection that should be incorporatedinto a forest cover and condition monitoring plan is ground-­‐basedforest observation patrols. Because potential forest loss ordegradation can take place at a spatial scale finer than what canbe readily detected by satellite image analysis, a set of267