This study focuses on species occupying the three strata of an Amazonian rainforest: the ground and leaf litter, the understorey and the canopy. We employed only two sampling techniques: Winkler extraction for ground-dwelling ants and direct observations for understorey and canopy species on large branches cut off by a climber. We identified 494 ant species from 10 subfamilies and 77 genera over approximately 3.0 ha (Chao1 = 607 species; 95% CI: 566-670 species). Although we found fewer arboreal ants compared to approaches using insecticide fogging, this study confirms similarities between the ant diversity in Amazonian and Mesoamerican rainforests. The functional traits of these ants (i.e., diet, nest-site preference, population size of the colony) allowed us to identify seven clusters. Cluster 1 is a "hodgepodge" grouping arboreal or ground-dwelling species with different-sized colonies (76 species). Cluster 2 primarily includes small colonies of ground-nesting generalist feeders (142 species). Cluster 3 comprises all arboreal species from the understorey inhabiting myrmecophyte domatia or palm trees plus arboreal species with medium-sized colonies (37 species). Cluster 4 includes all territorially dominant arboreal ants plus one ground-dwelling species (21 species). All fungus-growing species belong to Cluster 5, which also contains ground-nesting generalist feeders and generalist predators (148 species). All doryline army ants are grouped in Cluster 6 along with one ponerine known for its nomadic behavior (15 species). Almost all specialized predators belong to Cluster 7 (55 species); however, Cluster 5 includes two ponerine species that prey exclusively on termites. Based on a nonmetric multidimensional scaling (NMDS), we confirmed that the position of these clusters corresponded fairly well to the three forest strata. Thus, analyzing functional traits enables the trophic position of most ants and their place in the vertical strata of Neotropical rainforests to be determined.
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RBINS Staff Publications 2025
The assessment of historical data is important to understand long-term changes in the marine environment. Whereas time series analyses based on monitoring data typically span one or two decades, this work aimed to integrate 40 years of monitoring and research data on polychlorinated biphenyls (PCBs) and metals in the Belgian Part of the North Sea (BPNS). Multiple challenges were encountered: sampling locations changed over time, different analytical methods were applied, different grain size fractions were analyzed, appropriate co-factors were not always analyzed, and measurement uncertainties were not always indicated. These issues hampered the use of readily available, highly standardized trend modeling approaches like those proposed by regional sea conventions such as OSPAR, named after the Oslo and Paris conventions.Therefore, we applied alternative approaches, allowing us to include most older historical data that have been obtained during the nineteen seventies and eighties. Our approach included reproducible and quality controlled procedures from data collection up to data assessment. It included spatial clustering, data normalization and parametric linear mixed effect modeling. A Ward hierarchical clustering was applied on recently obtained contaminant data, as the basis for a spatial division of the BPNS into five distinct areas with different contamination profiles. To minimize the risk of normalization errors for the metal data analyses, four normalization approaches were applied and mutually compared: granulometric and nickel (Ni) normalization, next to two hybrid normalization methods combining aluminum (Al) and iron (Fe) normalization. The long-term models revealed decreasing trends for most metals, except zinc (Zn) for which three out of four models showed increasing concentrations in all five zones of the BPNS. Offshore sediments contained the lowest normalized mercury (Hg) and cadmium (Cd) concentrations but high arsenic (As) concentrations. Trend analysis revealed a strong decrease in PCB concentrations in the nineteen eighties and nineties, followed by a slight increase over the last decade. The extended timeframe for contaminant assessment, as applied in this study, is of added value for scientists and policy makers, as the approach allows to detect trends and effects of anthropogenic activities within the marine environment within a broad perspective.
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RBINS Staff Publications 2021
