Evidence of sodium limitation in ants and termites in a Neotropical savanna

Nutritional ecology of ropical ecosystems like Neotropical savannas, which are of high conservation concern, is understudied. Sodium is essential for heterotrophs but availability often falls short relative to plant consumer requirements. Savanna plant consumers like ants and termites should be sodium-limited due to high temperatures, nutrient-poor soils, and lack of oceanic sodium deposition. We tested the hypothesis that Neotropical savanna ants and termites are sodium-limited. Termites were tested by supplementing 0.25 m2 plots with H2O (control), 0.1%, 0.5%, or 1.0% NaCl and measuring termite presence and artificial substrate mass loss after 1 week. Ants were tested by collecting ants that recruited to H2O (control), 0.1%, 0.5%, and 1.0% NaCl and 1.0%, 10%, and 20% sugar baits on paired diurnal–nocturnal transects. Termites were 16 times more likely to occur on 1% NaCl than H2O plots and wood-feeding termites were most frequent. However, the decomposition rate did not differ among treatments. Ant bait use increased with increasing NaCl concentration and 1% NaCl usage was similar to sugar bait usage. Ants were 3.7 times more active nocturnally than diurnally, but contrary to predictions bait type (water, sugar or NaCl) usage did not differ between day and night. Together, these results provide strong evidence of sodium limitation in Neotropical savannas.

Activity patterns of medium and large mammals in two savanna ecosystems in the Colombian Llanos

Neotropical savannas have undergone continuous processes of landscape transformation (e.g., agriculture, oil, gas, and hydrocarbon industry) and very little is known about the ecology and natural history of key biological groups such as terrestrial mammals while the information on behavioral aspects of mammalian species in these ecosystems is very scarce. Here, we aimed to describe the activity patterns of medium and large mammals in two savanna ecosystems in the Colombian Llanos. A set of 60 camera traps was installed in the two ecosystems for 35 days (2100 camera days). We described the activity patterns of nine predominantly nocturnal species. We found no difference in circadian distributions of mammals between ecosystems. Cuniculus paca Linnaeus 1758 and Dasyprocta fuliginosa Wagler 1832 showed patterns of exclusion probably due to competition whereas other species like Tamandua tetradactyla Linnaeus1758 and Myrmecophaga tridactyla Linnaeus 1758 displayed similar activity patterns. We highlight the importance of savannas for the conservation of these species and discuss the relevance of studies on activity patterns for mammal ecology and conservation in Neotropical savannas.

Geographic Object-Based Image Analysis Framework for Mapping Vegetation Physiognomic Types at Fine Scales in Neotropical Savannas

Regional maps of vegetation structure are necessary for delineating species habitats and for supporting conservation and ecological analyses. A systematic approach that can discriminate a wide range of meaningful and detailed vegetation classes is still lacking for neotropical savannas. Detailed vegetation mapping of savannas is challenged by seasonal vegetation dynamics and substantial heterogeneity in vegetation structure and composition, but fine spatial resolution imagery (<10 m) can improve map accuracy in these heterogeneous landscapes. Traditional pixel-based classification methods have proven problematic for fine spatial resolution data due to increased within-class spectral variability. Geographic Object-Based Image Analysis (GEOBIA) is a robust alternative method to overcome these issues. We developed a systematic GEOBIA framework accounting for both spectral and spatial features to map Cerrado structural types at 5-m resolution. This two-step framework begins with image segmentation and a Random Forest land cover classification based on spectral information, followed by spatial contextual and topological rules developed in a systematic manner in a GEOBIA knowledge-based approach. Spatial rules were defined a priori based on descriptions of environmental characteristics of 11 different physiognomic types and their relationships to edaphic conditions represented by stream networks (hydrography), topography, and substrate. The Random Forest land cover classification resulted in 10 land cover classes with 84.4% overall map accuracy and was able to map 7 of the 11 vegetation classes. The second step resulted in mapping 13 classes with 87.6% overall accuracy, of which all 11 vegetation classes were identified. Our results demonstrate that 5-m spatial resolution imagery is adequate for mapping land cover types of savanna structural elements. The GEOBIA framework, however, is essential for refining land cover categories to ecological classes (physiognomic types), leading to a higher number of vegetation classes while improving overall accuracy.