Forest Plantation and the loss of Atlantic forests: challenges for conservation

Integrating remote sensing and UAV imagery for detection of invasive Hovenia dulcis Thumb. (Rhamnaceae) in urban Atlantic Forest remnants

The invasive species Hovenia dulcis is considered the main invasive species in the Atlantic Forest, capable of altering environmental conditions at a local scale and provoking profound changes in the composition of the plant community. Combining drone and satellite images can make forest monitoring more efficient, enabling a more targeted and effective response to contain the spread of invasive species. This research aimed to use high-resolution CBERS-4A satellite combined with drone images to detect invasive trees in forested areas of the Atlantic Forest. An object-oriented, supervised automatic classification was performed using the Dzetsaka Classification Tool and the Gaussian Mixture Model method. Additionally, georeferenced orthomosaics obtained by drones, totaling 150 ha, were used to confirm the identification of the invasive species. The entire forest area was surveyed to determine the tree community, where 72 random sample plots, each with a fixed area of 100 m2, were established. The calculated indices, such as the Shannon index (H') = 3.65 and uniformity (J') = 78%, demonstrate that the plant community has a high diversity of species. However, the invasive H. dulcis had the highest number of sampled individuals (146), being the species with the highest relative density (9.14) within the community and the second highest in relative frequency (5.10%), coverage importance value (8.85%), and importance value index (7.60%). The methodology employed to identify the invasive species through satellite, and drone images allowed for rapid and precise data collection and quantification of the invasive species, covering an area of 86.44 ha of the forest fragment, which corroborates the field data.

Landscape degradation drives metal bioaccumulation in bats from Atlantic Forest cacao region, Brazil

Agricultural landscapes worldwide are heavily sprayed with agrochemicals to increase crop productivity. These agrochemicals release bio-accumulative pollutants such as heavy metals that often persist in the environment with harmful impacts on biota. In a prime endangered Atlantic Forest biome, in Bahia, Brazil, agroforestry of cacao (Theobroma cacao) provides a livelihood for small farmers and suitable habitats for forest species. However, landscape transformation to pasture and monoculture expose vulnerable communities to scarcely evaluated pollutants with unknown effects on the health of humans and animals. We assessed the bioaccumulation of manganese (Mn), lead (Pb), and copper (Cu) by analyzing hair samples of 326 bats representing 28 species across 15 cacao agroforestry and 2 forest remnants. Bats from regions heavily disturbed by pastures and monocultures showed higher levels of Pb (41.20 µg/g) and Mn (0.44 µg/g) compared to those from areas where forest or cacao agroforestry dominates the landscape. Local grassland covers increased Pb bioaccumulation, while forest cover reduced it. Cacao agroforestry appeared to increase Cu exposure, likely due to fungicide use. This study pioneers the evaluation of heavy metal accumulation in bats inhabiting cacao agroforestry and Atlantic Forest remnants, highlighting the need for sustainable agricultural practices to protect wildlife and ecosystem health.

Monitoring arthropods under the scope of LIFE-SNAILS project: I - Santa Maria Island baseline data with implementation of the Index of Biotic Integrity

Background

The database we introduce is a pivotal component of the LIFE SNAILS project (Support and Naturalisation in Areas of Importance for Land Snails). This initiative is dedicated to safeguarding three endangered species of terrestrial molluscs, specifically, two snails (Oxychilusagostinhoi Martins 1981 and Leptaxisminor Backhuys, 1975) and a semi-slug (Plutoniaangulosa (Morelet, 1860)), all of which are single island endemics from Santa Maria Island and face significant threats towards their populations.In this study, we established a comprehensive database derived from a long-term arthropod monitoring campaign utilising SLAM (Sea, Land, Air, Malaise) traps. Although molluscs were not the primary focus, our findings serve as a credible proxy for evaluating the overall habitat quality for endemic invertebrates, with arthropods serving as principal indicators. From September to December of 2022, a total of 11 SLAM traps were installed and monitored monthly in eleven sites of mixed forests of Santa Maria Island.

New information

Based on the 33 available samples (11 sites x 3 sampling periods), we recorded a total of 118 taxa of arthropods (of which 94 were identified at species or subspecies level), belonging to three classes, 14 orders and 62 families. From the 94 identified taxa, a total of 21 species were endemic, 31 native non-endemic, 32 introduced and 10 indeterminate. We also provide additional information of the habitat quality (Index of Biotic Integrity), including general habitat and dominant species composition.We registered three new records to the Island, the native bug Piezodoruslituratus (Fabricius, 1794) (Hemiptera, Pentatomidae), the Azorean endemic beetle Phloeosinusgillerforsi Bright, 1987 (Coleoptera, Curculionidae) and the exotic ant Hypoponerapunctatissima (Roger, 1859) (Hymenoptera, Formicidae) and one new record for the Azores Archipelago, the native beetle Cephenniumvalidum Assing & Meybohm, 2021 (Coleoptera, Staphylinidae, Scydmaeninae).This publication not only contributes to the conservation of highly threatened endemic molluscs, through an assessment of habitat quality, based on arthropod communities and habitat description (e.g. native or exotic vegetation), but also provides an updated inventory of arthropods from Santa Maria Island.