The southeastern Amazon region has been intensively occupied by human settlements over the past three decades. To evaluate the effects of human settlements on land-cover and land-use (LCLU) changes over time in the study site, we evaluated multitemporal Landsat images from the years 1984, 1994, 2004, 2013 and Sentinel to the year 2017. Then, we defined the LCLU classes, and a detailed "from-to" change detection approach based on a geographic object-based image analysis (GEOBIA) was employed to determine the trajectories of the LCLU changes. Three land-cover (forest, montane savanna and water bodies) and three land-use types (pasturelands, mining and urban areas) were mapped. The overall accuracies and kappa values of the classification were higher than 0.91 for each of the classified images. Throughout the change detection period,~47% (19,320 km 2 ) of the forest was preserved mainly within protected areas, while almost 42% (17,398 km 2 ) of the area was converted from forests to pasturelands. An intrinsic connection between the increase in mining activity and the expansion of urban areas also exists. The direct impacts of mining activities were more significant throughout the montane savanna areas. We concluded that the GEOBIA approach adopted in this study combines the advantages of quality human interpretation and the capacities of quantitative computing.to improve image classification accuracy [5]. Primarily, GEOBIA has been able to be applied due to the advent of very high (spatial)-resolution images that show mainly land-cover and land-use (LCLU) changes within urban areas [6], forests [7], and agriculture areas [8], where image objects are digitally constructed from dozens to hundreds of pixels [9,10]. However, the use of GEOBIA has been increasingly expanded to include moderate-resolution images if a higher hierarchical image-object level is applied [11][12][13][14].In a global and regional context, the investigation of variations in the LCLU constitute a broad field in terms of the diversity of remote sensing methods that are available to map and monitor the different types of human-driven changes in the environments. Although many change detection techniques have been developed at the per-pixel level, new insights have been obtained from GEOBIA and hybrid methods centered on "from-to" change trajectories to better qualify and quantify LCLU change patterns [15].In the Amazon region, the dynamics of forest conversion to pastureland are well documented using a per-pixel approach [2], and the findings of these studies are mainly provided in annual reports on the Satellite Monitoring System of the Brazilian Amazon Forest (PRODES) (www.dpi.inpe. br/prodesdigital/prodes). Nevertheless, information is lacking regarding the conversion of forests and montane savanna regions to mining infrastructure, with the exception of a few studies on gold mining using high-resolution images [16]. Recent publications have demonstrated the influence of mining projects on the LCLU changes in the Brazilian Amazon from "pixel-to-...
The Global South has witnessed increasing sampling of its immense biological diversity during the past century. However, the diversity of many regions remains unknown, even at pristine and highly threatened places, such as in the Atlantic Forest; and for bioindicator, umbrella, and flagship groups. The present study reports the first butterfly list of the Parque Estadual Intervales, São Paulo, Brazil and surroundings, a key protected area in the last massive continuous of the Atlantic Forest. We compiled data from museums and four years of field work, under three sampling methods. We also aimed at providing resources to support conservation efforts by analyzing 27 years of climatic data (detailed in the Supplementary Material, in English and in Portuguese), discussing our results also for non-academics, and producing scientific outreach and educational material. A companion article dealt with the experiences of science outreach and capacity development, and illustrated the butterfly catalogue of the species sampled in the park. We found 312 species that sum to 2,139 records. The museum had 229 species (432 records), and we sampled 142 species (1,682 individuals), in a total effort of 36,679 sampling hours (36,432 trap and 247 net and observation hours). The richest families were Nymphalidae (148 species) and Hesperiidae (100 species). Most species were sampled exclusively by active methods (79.8%), but other sources (passive sampling, citizen science, etc.) also found unique records. We found the highest diversity metrics from January to May, and we demonstrated that winter months had less richness and abundance. We illustrated the 20 species common to all regions, and listed those that were found more than seven months in the year, as well as the most abundant species in trap sampling, with forest dwellers as well as species common to open and fragmented areas. The dominant species in our trap datasets was the iridescent white morpho, Morpho epistrophus (Fabricius, 1796), and we suggest it to become the park butterfly mascot.
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