A novel biome concept and classification system based on bioclimate and vegetation – a Neotropical assay

The knowledge of biomes as large-scale ecosystem units has benefited from advances in the ecological and evolutionary sciences. Despite this, a universal biome classification system that also allows a standardized nomenclature has not yet been achieved. We propose a comprehensive and hierarchical classification method and nomenclature to define biomes based on a set of bioclimatic variables and their corresponding vegetation structure and ecological functionality. This method uses three hierarchical biome levels: Zonal biome (Macrobiome), Biome and Regional biome. Biome nomenclature incorporates both bioclimatic and vegetation characterization (i.e. formation). Bioclimate characterization basically includes precipitation rate and thermicity. The description of plant formations encompasses vegetation structure, physiognomy and foliage phenology. Since the available systems tend to underestimate the complexity and diversity of tropical ecosystems, we have tested our approach in the biogeographical area of the Neotropics. Our proposal includes a bioclimatic characterization of the main 16 Neotropical plant formations identified. This method provides a framework that (1) enables biome distribution and changes to be projected from bioclimatic data; (2) allows all biomes to be named according to a globally standardized scheme; and (3) integrates various ecological biome approaches with the contributions of the European and North American vegetation classification systems. Taxonomic reference: Jørgensen et al. (2014). Dedication: This work is dedicated to the memory of and in homage to Prof. Dr. Salvador Rivas-Martínez.

Tree cover change proves stability and instability in tropical ecosystems

Terrestrial tropical ecosystems’ resilience is determined predominantly based on space-for-time substitution, which assumes that the current ‘static’ frequency distribution of ecosystems’ tree cover structure across space also holds across time. However, dynamic and temporal aspects are increasingly important to explicitly account for under ongoing rapid climate change. Here, we empirically study ecosystem stability and instability using remote sensing-derived tree cover change (ΔTC) over the last two decades. We find that considerable ΔTC predominantly takes place in intermediate tree cover ecosystems (i.e., areas with 30-60% tree cover), whereas high (>75%) and low (<10%) tree cover ecosystems only experience limited ΔTC. Our results further suggest that root zone storage capacity, which defines the adaptive capacity of the ecosystem to absorb water stress perturbations, does mediate the relationship between ecosystems’ stability and ΔTC by instigating investment in ecosystems subsoil structure. Based on these analyses, we propose a modified forest resilience metric using both precipitation and root zone storage capacity, which reveals that the Congo rainforests are more resilient than if only precipitation is considered. This study emphasises the importance of temporal dynamics and adaptation of ecosystems in inferring and assessing the risk of forest-savannah transitions under change.

Resin Use by Stingless Bees: A Review

Stingless bees (Meliponini) are highly social bees that are native to tropical and sub-tropical ecosystems. Resin use is vital to many aspects of stingless bee colony function. Stingless bees use resin to build essential nest structures, repel predators, and kill would-be invaders. Furthermore, resin-derived compounds have been found to enrich the cuticular chemical profiles of many stingless bee species, and resin may play an important role in shaping the microbial communities associated with stingless bees and their nests. Despite its importance for colony function, previous reviews of resin use by stingless bees are lacking. This topic grows increasingly urgent as changes in beekeeping and land use practices occur, potentially diminishing stingless bees’ ability to incorporate resin into the nest environment. In this article, we review existing literature on resin use by stingless bees and discuss potential areas of future research.

A Regional Earth System Data Lab for Understanding Ecosystem Dynamics: An Example from Tropical South America

Tropical ecosystems experience particularly fast transformations largely as a consequence of land use and climate change. Consequences for ecosystem functioning and services are hard to predict and require analyzing multiple data sets simultaneously. Today, we are equipped with a wide range of spatio-temporal observation-based data streams that monitor the rapid transformations of tropical ecosystems in terms of state variables (e.g., biomass, leaf area, soil moisture) but also in terms of ecosystem processes (e.g., gross primary production, evapotranspiration, runoff). However, the underexplored joint potential of such data streams, combined with deficient access to data and processing, constrain our understanding of ecosystem functioning, despite the importance of tropical ecosystems in the regional-to-global carbon and water cycling. Our objectives are: 1. To facilitate access to regional “Analysis Ready Data Cubes” and enable efficient processing 2. To contribute to the understanding of ecosystem functioning and atmosphere-biosphere interactions. 3. To get a dynamic perspective of environmental conditions for biodiversity. To achieve our objectives, we developed a regional variant of an “Earth System Data Lab” (RegESDL) tailored to address the challenges of northern South America. The study region extensively covers natural ecosystems such as rainforest and savannas, and includes strong topographic gradients (0–6,500 masl). Currently, environmental threats such as deforestation and ecosystem degradation continue to increase. In this contribution, we show the value of the approach for characterizing ecosystem functioning through the efficient implementation of time series and dimensionality reduction analysis at pixel level. Specifically, we present an analysis of seasonality as it is manifested in multiple indicators of ecosystem primary production. We demonstrate that the RegESDL has the ability to underscore contrasting patterns of ecosystem seasonality and therefore has the potential to contribute to the characterization of ecosystem function. These results illustrate the potential of the RegESDL to explore complex land-surface processes and the need for further exploration. The paper concludes with some suggestions for developing future big-data infrastructures and its applications in the tropics.