Deliverable 11: Assessment of Alternative Landscape Scenarios

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Deliverable 11: Assessment of Alternative Landscape Scenarios We employed a spatially-explicit, policy-sensitive landscape simulation model to project land-use/landcover trends 30 years into the future. Specifically, the model simulated the expansion of mechanized cultivation and cattle ranching in response to selected land-use policy alternatives and management interventions (Stickler 2009, Stickler et al. 2009). Here, we compare the biodiversity value of each scenario, drawing on the field- and satellite-based databases produced over the course of this project. The outcomes of each alternative scenario were assessed in terms of habitat quality (based on measures of habitat connectivity and habitat suitability using maps and analyses produced in Specific Objective A2) for the medium to large mammal community in the Xingu River headwaters region. Methods Scenarios Each of the modeled scenarios is based on recent, existing and/or proposed legislation (Stickler 2009) and compared with a baseline simulation and the Current landcover scenario (current forest/cerrado cover). The basic assumptions underlying each scenario, including the reference scenario, are as follows: The Business as Usual (BAU) scenario assumes that the historical rate and pattern of deforestation continues into the future, and thus serves as a baseline model against which to compare other options. The BAU scenario uses the average deforestation rate calculated for this region over the 1996-2005 period and applies it over 30 years. The reference period corresponds to that set for determining crediting levels for the Amazon Fund and the National Climate Change Policy (GOB 2009). Under the Amazon Fund, the reference scenario is estimated by extending the average rate for the 10-year period from 1996-2005 as an absolute (gross) rate into the future. In the analysis presented here, the BAU scenario is somewhat more conservative, applying the same annual rate of clearing as a percentage (net rate) of the remaining forest; thus the absolute amount cleared each year decreases proportionally with the decrease in total forest cover. This is a more realistic reference scenario for a region such as the Xingu River headwaters, as it has historically high levels of deforestation which are unlikely to be sustained at the same absolute level in the future (and already have declined since the end of the average period). Under the Amazon Fund, the reference scenario is extended only through 2020; here, however, extend the simulation through 2035 to provide an assessment of how policies aided by carbon offset to create incentives might protect ecological resources in the longer term. 1

The Current Forest Code (CFC) scenario represents the landscape under the assumption that the current Federal Forest Code were perfectly implemented and enforced. Since 1996, the Forest Code requires that properties located in the forest biome in the Legal Amazon maintain 80% of the native vegetation in a permanent legal reserve; properties in the cerrado biome are required to maintain 35% of the native vegetation in a legal reserve. Where less than this amount is present, the vegetation must be restored. In addition, vegetation within 50-m of each stream on private properties must be strictly protected or restored if it is absent. This scenario represents the law that is still in effect, not the changes that are under consideration to be signed into law by President Dilma Rousseff. The Socio-Economic Ecological Zoning Plan (ZSEE) scenario assumes that the proposed Mato Grosso state zoning plan is implemented, as described in Stickler 2009. The zoning plan has 4 major zones which determine the percent of legal reserve that is required for properties falling within each zone. The scenario modeled here also assumes that the tradable deforestation rights option included in the federal Forest Code in 1998 will be exercised (Stickler 2009). Furthermore, the scenario assumes strict protection of areas falling in any one of 3 areas described as requiring special attention and protection under the ZSEE (Stickler 2009). Finally, as in the other scenarios, all riparian areas within 50-m of streams are strictly protected and reforested. Currently, another version of the state zoning plan is under discussion, but it is unlikely that a decision with respect to the zoning plan will be made until 2013, according to state officials. This is the more conservative (with respect to forest conservation and restoration) of the 2 versions of the zoning plan. The Registry of Social-Environmental Responsibility (RSR) scenario assumes that the RSR is implemented throughout the basin and that obligations to reforest or maintain forest follow the guidelines of the ZSEE. As in the other scenarios, all riparian areas within 50-m of streams are strictly protected and reforested and all protected areas and indigenous territories are strictly protected. However, no extra areas (as in the ZSEE) are protected. Habitat Analyses Fragmentation. To evaluate differences in habitat quantity and quality among the scenarios, habitat fragmentation and the potential extent of edge effects were assessed for forest and cerrado cover associated with areas of grain or cattle production by calculating a series of simple landscape metrics for each landscape. We assessed quantity (total class area for both cerrado and forest classes), degree of fragmentation (number of patches, mean patch size), habitat quality (total core area, total edge area, edge-to-core-area ratio), and connectivity (patch nearest neighbor distance). All analyses were carried 2

out using Fragstats 3.3 spatial pattern analysis software (McGarigal et al., 2002). The proportion of edge vs. interior habitat for forest was calculated using edge influence values derived from empirical observations by researchers studying edge effects related to the effects of fire on forests in the region (Balch, 2008). We applied an edge depth value of 150 m to forest patches adjacent to agricultural areas. This was rounded to 100 m (1 pixel) due to the resolution of the land-cover maps. For forest patches adjacent to cerrado or regenerating forest or cerrado patches, edge influence was considered to be negligible relative to map resolution. Similarly, edge influence depth in cerrado was considered to be negligible as cerrado is a more open land-cover type that is well-adapted to regular fire disturbance. Risk Assessment. We assess the risk to suitable habitat for terrestrial mammals for each scenario by combining maps of biodiversity potential (Deliverable 10) and agricultural suitability (Deliverable 9) with the final landscape maps for each scenario. We identify areas where large mammal habitat is likely to be most vulnerable to clearing, fragmentation, or inaccessibility due to the expansion of industrial agriculture if forest clearing and forest expansion follow historical trends. Furthermore, we identify intact and suitable habitat areas under each scenario that are highly unsuitable for agricultural activities and thus should be targeted for protection from agricultural expansion. Finally, we identify areas of suitable habitat cleared for agriculture under scenario that are highly unsuitable for agriculture and thus should either be targeted for protection now or will require restoration in the future. The methods follow the description provided in the report for Deliverable 10, with the exception that each scenario outcome map is used, not just a map of current forest/cerrado cover, and that results are presented in tabular form. Results Habitat Fragmentation Overall, habitat quality and quantity differed between scenarios by biome, but was highest in the CFC, ZSEE, and RSR scenarios (Table 1). Riparian forest cover was highest in the CFC, ZSEE, and RSR scenarios, since the model required that all legally designated riparian zones be reforested. This is likely to important for terrestrial mammals as the riparian forests form natural corridors connecting larger blocks of forest. Forest fragmentation was 2 to 3 times higher in the BAU scenario than in the alternative policy scenarios; cerrado fragmentation was 1.4 to 1.7 times greater under the BAU scenario than in the alternative policy scenarios. Mean fragment sizes were 4- to 9-fold lower in the forest biome under the BAU scenario than under the CFC, ZSEE, RSR scenarios. A strikingly different pattern emerges in 3

comparing edge and interior habitat area among the scenarios. All of the alternative policy scenarios have more total edge habitat than the BAU scenario in both the cerrado and forest biomes. This is because each private rural property (or in the model s case, microbasins see Stickler et al. 2009) is allowed to deforest up to a certain amount (according to the scenario assumptions described above) and because of the way in which the model allocates reforestation (at the edges of exising forest or cerrado blocks), thus generating more edge. Nevertheless, total interior habitat area was as high or greater as under the Current scenario, and fragment sizes under the conservation scenarios were comparable to those of the Current scenario. Habitat Risk Assessment The area converted to agriculture in areas outside protected areas and indigenous territories that would otherwise provide suitable habitat for terrestrial mammals increases from 6490 km 2 to 34,712 km 2 (or 21%) under the Business-as-Usual (BAU) scenario (Table 2). By contrast, under the Current Forest Code (DFC), Zoning (ZSEE) plan, and RSR scenarios, only approximately 2670 km 2 of suitable habitat is converted to agriculture. Of the remaining suitable current forest and cerrado habitat (52,966 km 2 ), 32,472 km 2 are also suitable for agriculture. These are areas that should be prioritized for conservation. Under the BAU scenario, where only 24,744 km 2 of suitable, vegetated habitat remain, more than 50% (13,202 km 2 ) is also suitable for mechanized agriculture. However, if effective protection measures were to be implemented now, all of this area (and more) could be protected. Of areas already converted to agriculture (46,233 km 2 ), 7% (3022 km 2 ) are unsuitable for agriculture and suitable for biodiversity and should be targeted for reforestation. Of forested areas that are suitable for biodiversity (52,966 km 2 ), nearly half (20,495 km 2 ) are unsuitable for agriculture and should be targeted for protection. Of the 28,222 km 2 of suitable habitat cleared for agriculture under the BAU scenario, approximately 1/3 (11,975 km 2 ) is unsuitable for agriculture. Given this projection, these areas could be targeted for protection before deforestation advances. Of the 2645 km 2 of new clearing for agriculture that occurs under the Forest Code scenario, 1072 km 2 are unsuitable for agriculture, but suitable for biodiversity and thus could be prioritized for protection from clearing. Under the ZSEE and RSR scenarios under which 2644 km 2 of forests are cleared for agriculture, the area cleared that is suitable for mammals but unsuitable for agriculture is reduced by nearly 50% over the Forest Code, with approximately 575 km 2. The ZSEE and RSR scenarios take into account agricultural and economic suitability by design, thus directing agriculture to areas that are better adapted for agricultural production, while promoting forest conservation and restoration. 4

References Balch, J.K. 2008. Effects of Recurrent Fire on Transitional Forest Dynamics in the Amazon s Wildfire Frontier in Mato Grosso, Brazil. PhD dissertation, Yale University, New Haven, CT. Stickler, C.M. 2009. Defending public interests in private forests: land-use policy alternatives for the Xingu River headwaters region of southeastern Amazônia. PhD dissertation, University of Florida, Gainesville, FL. Stickler, C.M., Nepstad, D.C., Coe, M.T., Rodrigues, H.O., McGrath, D.G., Walker, W.S., Soares-Filho, B.S., Davidson, E.A. 2009. The potential ecological costs and co-benefits of REDD: a critical review and case study from the Amazon region. Global Change Biology 15, 2803-2824. 5

Current BAU CFC ZSEE RSR Figure 1. Maps depicting the Xingu River headwaters region under 4 alternative scenarios, as well as the current landscape. 6

Table 1. Comparison of habitat quantity and quality (fragmentation) in the Xingu River headwaters region with Current forest cover, and under four simulations of future forest cover under business-asusual (BAU), Current Forest Code (CFC), Zoning plan (ZSEE), and RSR assumptions. Current BAU CFC ZSEE RSR Riparian Zone Riparian forest cover (km 2 ) 12,931 9697 15,509 15,509 15,509 Total Landscape Vegetation cover (km 2 ) Forest 107,789 64,602 116,395 110,902 110,902 Cerrado 17,037 6305 13,149 15,209 15,434 Number of fragments Forest 13,427 46,510 12,958 13,770 13,652 Cerrado 13,285 26,702 18,138 15,573 15,122 Mean distance to nearest neighbor fragment (m) Forest 361 465 379 363 370 Cerrado 406 442 371 378 361 Mean fragment size (ha) Forest 803 139 898 805 799 Cerrado 128 24 73 98 80 Total interior habitat area (km 2 ) Forest 99,978 56,977 105,287 98,973 98,934 Cerrado 12,737 3569 7433 9753 10,019 Total edge habitat area (km 2 ) Forest 7810 7624 11,108 11,930 11,968 Cerrado 4300 2736 5716 5456 5415 7

Table 2. Comparison of risk for suitable terrestrial mammal habitat in the Xingu River headwaters region under four simulations of future forest cover under business-as-usual (BAU), Current Forest Code (CFC), Zoning plan (ZSEE), and RSR assumptions, relative to Current forest cover. Current (km 2 ) BAU (km 2 ) CFC (km 2 ) ZSEE (km 2 ) RSR (km 2 ) Biodiversity Unsuitable Suitable Unsuitable Suitable Unsuitable Suitable Unsuitable Suitable Unsuitable Suitable Total Agriculture 39,743 6,490 38,111 34,712 32,353 9,136 35,790 9,135 35,692 9,222 Forest 32,578 52,966 34,209 24,744 39,960 50,315 36,524 50,316 36,622 50,229 Suitable for Agriculture Agriculture 17,142 3,022 13,250 11,975 17,267 4,094 16,801 3,589 16,802 3,611 Forest 21,367 20,495 25,259 11,541 21,240 19,421 21,706 19,926 21,704 19,904 Unsuitable for Agriculture Agriculture 22,600 3,468 24,861 22,737 15,087 5,042 18,989 5,547 18,890 5,611 Forest 11,211 32,472 8,950 13,202 18,720 30,894 14,818 30,390 14,918 30,325 8