Biology subjects

Bang, A.

Publications and source records attributed to Bang, A..

4 recordsLinked to original sources

bioRxiv2026

AnthropInsect: a global database of insect traits and anthropogenic associations.

Insect research remains hindered by limited data availability and fragmented knowledge compared to other, better-documented taxonomic groups. Yet, both the macroecological and the insect research communities highlight the need to integrate large-scale ecological trait datasets for insects. Insects and humans are interconnected through diverse relationships, ranging from beneficial interactions, such as the use of insects as nutritional resources, to adverse impacts, including their role in to the emergence and spread of biological invasions. Understanding the traits of insects associated with human use, movement and impact is therefore important for linking insects to ecosystem function and global change. We present AnthropInsect, one of the largest database on insect traits to date, which uniquely includes variables describing human-insect associations. AnthropInsect describes species through 35 variables grouped into five categories: (i) taxonomic descriptors; (ii) ecological descriptors (native bioregions and habitat); (iii) human-insect associations (edibility and invasive status); (iv) functional traits (behavior, morphology, life history and feeding); (v) and macroecological descriptors of native-range geography and climate. AnthropInsect currently includes 5867 species across six major orders: Coleoptera, Lepidoptera, Hemiptera, Hymenoptera, Orthoptera and Blattodea. Data extracted from peer-reviewed, grey literature and from existing databases were standardized and validated with expert knowledge to ensure accuracy. By providing traits data with information on insect-human interactions, this rigorously curated resource supports global research in entomology, ecology, conservation, and global change.

ecology↗

bioRxiv2024

Extinction potential from invasive alien species

Biological invasions threaten biodiversity, ecosystem services, human health, and cultural heritage, yet their impacts are often underappreciated, leading to insufficient management efforts and suboptimal conservation results. We argue that the lack of quantitative, continuous metrics of impact of invasive alien species (IAS) contribute this lack of appreciation. To bridge this knowledge-action gap, we propose the Extinction Potential Metric (EPM), a suite of quantitative metrics designed to assess the ecological damage caused by IAS. The EPM score of an IAS is the number of current and future species extinctions attributable to this IAS over the next 50 years under a business-as-usual scenario. EPM includes three variants: EPM-A (absolute EPM), EPM-R (relative EPM, which accounts for other anthropogenic pressures), and EPM-U (EPM for Unique species, adjusted for phylogenetic uniqueness of impacted native species), to capture different dimensions of IAS impacts. We applied EPM to evaluate the impact of IAS on 2178 amphibians, 920 birds, 865 reptiles, and 473 mammals. Our analyses revealed that the impact of the worst IAS was between 90 and 380 times higher than any IAS with an impact of 1 extinct native species. Importantly, several of the most impactful IAS disproportionately affect evolutionarily unique native species. The EPM framework offers a standardised approach for measuring ecological impacts of IAS but also other anthropogenic pressures at different spatial, temporal, and taxonomic scales. EPM could also guide the development of standardised indicators for assessing the impacts of other anthropogenic stressors. Ultimately, EPM will pave the way to answer ecological questions important to design better conservation policies, to enhance the management of biological invasions and reach global biodiversity conservation goals.

ecology↗

bioRxiv2021

The economic burden of protecting islands from invasive alien species

Biological invasions represent a key threat to island ecosystems, with pronounced impacts across environments and economies. The ecological impacts have received substantial focus, but the economic costs have lacked synthesis at spatial and temporal scales. Here we utilise the InvaCost database, the most comprehensive global assessment of published economic costs of invasive species, to assess reported spend by cost types and socioeconomic sectors, and to examine temporal trends in spending, across islands that differ in their political geography - nation states, overseas territories or offshore islands of continental countries. We based this assessment on 1473 unique cost entries comprising 2914 annual costs totalling almost US$100 million in area-corrected costs between 1965-2020. We find that offshore islands of continental countries incur the greatest total and management costs. However, nation states incurred the greatest damage costs whilst substantially financing management actions, and spent an overall greater proportion of their GDP. In contrast, spending within overseas territories was significantly lower in all respects. The most impacted sector was authorities and stakeholders, demonstrating the key role of government in addressing island invasions. Temporal trends revealed continual increases in spending across all island types. This likely reflects ongoing introduction rates globally alongside an increased recognition of the importance of islands as biodiversity hotspots, and an appetite to tackle invasive species at larger and more socially complex scales. However, the high economic costs of invasions on islands substantiates the need to prevent them in order to avoid this dire threat to biodiversity and its burden on limited conservation resources.

ecology↗

bioRxiv2020

Super-selective reconstruction of causal and direct connectivity with application to in-vitro iPSC neuronal networks

Despite advancements in the development of cell-based in-vitro neuronal network models, the lack of appropriate computational tools limits their analyses. Methods aimed at deciphering the effective connections between neurons from extracellular spike recordings would increase utility of in-vitro local neural circuits, especially for studies of human neural development and disease based on induced pluripotent stem cells (hiPSC). Current techniques allow statistical inference of functional couplings in the network but are fundamentally unable to correctly identify indirect and apparent connections between neurons, generating redundant maps with limited ability to model the causal dynamics of the network. In this paper, we describe a novel mathematically rigorous, model-free method to map effective - direct and causal - connectivity of neuronal networks from multi-electrode array data. The inference algorithm uses a combination of statistical and deterministic indicators which, first, enables identification of all existing functional links in the network and then, reconstructs the directed and causal connection diagram via a super-selective rule enabling highly accurate classification of direct, indirect and apparent links. Our method can be generally applied to the functional characterization of any in-vitro neuronal networks. Here, we show that, given its accuracy, it can offer important insights into the functional development of in-vitro iPSC-derived neuronal cultures.

neuroscience↗