The wildlife trade is a major cause of species loss and a pathway for disease transmission. Socioeconomic drivers of the wildlife trade are influential at the local scale yet rarely accounted for in multinational agreements aimed at curtailing international trade in threatened species. In recent decades (1998–2018), approximately 421,000,000 threatened (i.e., CITES-listed) wild animals were traded between 226 nations/territories. The global trade network was more highly connected under conditions of greater international wealth inequality, when rich importers may have a larger economic advantage over poorer exporting nations/territories. Bilateral trade was driven primarily by socioeconomic factors at the supply end, with wealthier exporters likely to supply more animals to the global market. Our findings suggest that international policies for reducing the global wildlife trade should address inequalities between signatory states, possibly using incentive/compensation-driven programs modeled after other transnational environmental initiatives (e.g., REDD+).

Studies of ecosystem functions are gaining traction in the scientific community along with a growing consensus that losses in ecosystem functions have widespread consequences. Food webs, which are networks comprising all trophic interactions (represented by links) between taxa present in a community (represented by nodes), are important aspects of ecosystem functioning, yet a clear understanding of the factors and mechanisms influencing their assembly and structure is lacking. In our study, we addressed this fundamental question by investigating the respective roles of (1) environmental filtering and (2) biotic filtering, in governing food web structure. We did this by assessing the relationship between the network structure of five high‐resolution empirical tropical food webs and associated environmental and biotic covariates. Our data suggest that only environmental filtering is important in shaping food webs. Further, we found that the underlying ecological mechanism is a function of bottom‐up influences comprising resource levels, and to a lesser degree, resource type (i.e., terrestrial organic matter) available. Specifically, our data suggest high‐nutrient environments favor greater food web complexity. In the general context of community assembly, our findings add to existing knowledge of the process by demonstrating that environmental conditions previously shown to influence species assemblages can also drive trends in prevailing species interactions.

No abstract

Recent biodiversity surveys in the lentic habitats of Singapore revealed that non-native cichlids (at least 14 species from different origins) were the most abundant species in the reservoirs of Singapore. To understand the diversity and distribution patterns in six reservoirs (two inland and four coastal), we investigated the species richness and abundances of these cichlids. We also investigated foodwebs to characterise the trophic relationships of cichlids relative to the aquatic community using stable isotope and gut content analyses in each reservoir. Based on various sampling methods (electrofishing, netting and trapping), a total of 5,675 individual cichlids representing 14 species and two hybrids were caught. The three most abundant species (contributing to 66.8% of all cichlids) included the green chromide, Etroplus suratensis, the eartheater cichlid, Geophagus altifrons, and the Orinoco peacock bass, Cichla orinocensis. Based on a canonical correspondence analysis, we found that the distribution and abundances of cichlids appeared to be related to abiotic parameters such as salinity and dissolved oxygen, and that species richness and abundances of cichlids differed between coastal and inland reservoirs. We also found that the trophic positions of different cichlid species varied within and across the reservoirs surveyed, where sympatry between highly specialised as well as generalist cichlid species was commonly observed. This was reflected in both the gut contents as well as the empirical foodwebs generated. While we are unable to determine source and timing of the introductions of these cichlids, we are at least confident that many of the cichlids have already established in these six reservoirs. We postulate that the establishment success and the co-existence of this non-native group has come about through their ability to adapt to the conditions within each reservoir, and this is related to the life history strategies, feeding and behavioural patterns that these different cichlid species display.

Food webs summarise trophic interactions of the biotic components within an ecosystem, which can influence nutrient dynamics and energy flows, ultimately affecting ecosystem functions and services. Food webs represent the hypothesised trophic links between predators and prey and can be presented as empirical food webs, in which the relative strength/importance of the respective links are quantified. Some common methods used in food web research include gut content analysis (GCA) and stable isotope analysis (SIA). We combine both methods to construct empirical food web models as a basis for monitoring and studying ecosystem-level outcomes of natural (e.g. species turnover in fish assemblage) and intentional environmental change (e.g. biomanipulation). We present 12 food webs from tropical reservoir communities in Singapore and summarise the topology of each with widely-used network indices (e.g. connectance, link density). Each reservoir was surveyed over 4–6 sampling occasions, during which, representative animal groups (i.e. fish species and taxonomic/functional groups of zooplankton and benthic macroinvertebrates) and all likely sources of primary production (i.e. macrophytes, periphyton, phytoplankton and riparian terrestrial plants) were collected. We analysed gut content in fishes and bulk isotope (d13C and d15N) profiles of all animals (i.e. fishes and invertebrates) and plants collected. Both sets of information were used to estimate the relative strength of trophic relationships using Bayesian mixing models. We document our protocol here, alongside a script in the R programming language for executing data management/analyses/visualisation procedures used in our study. These data can be used to glean insights into trends in inter- and intra-specific or guild interactions in analogous freshwater lake habitats.