Identification of invasion hotspots that support multiple invasive alien species (IAS) is a pre-requisite for control and management of invasion. However, till recently it remained a methodological challenge to precisely determine such invasive hotspots. We identified the hotspots of alien species invasion in India through Ecological Niche Modelling (ENM) using species occurrence data from the Global Biodiversity Information Facility (GBIF). The predicted area of invasion for selected species were classified into 4 categories based on number of model agreements for a region i.e. high, medium, low and very low. About 49% of the total geographical area of India was predicted to be prone to invasion at moderate to high levels of climatic suitability. The intersection of anthropogenic biomes and ecoregions with the regions of 'high' climatic suitability was classified as hotspot of alien plant invasion. Nineteen of 47 ecoregions of India, harboured such hotspots. Most ecologically sensitive regions of India, including the 'biodiversity hotspots' and coastal regions coincide with invasion hotspots, indicating their vulnerability to alien plant invasion. Besides demonstrating the usefulness of ENM and open source data for IAS management, the present study provides a knowledge base for guiding the formulation of an effective policy and management strategy for controlling the invasive alien species.

Lists of species underpin many fields of human endeavour, but there are currently no universally accepted principles for deciding which biological species should be accepted when there are alternative taxonomic treatments (and, by extension, which scientific names should be applied to those species). As improvements in information technology make it easier to communicate, access, and aggregate biodiversity information, there is a need for a framework that helps taxonomists and the users of taxonomy decide which taxa and names should be used by society whilst continuing to encourage taxonomic research that leads to new species discoveries, new knowledge of species relationships, and the refinement of existing species concepts. Here, we present 10 principles that can underpin such a governance framework, namely (i) the species list must be based on science and free from nontaxonomic considerations and interference, (ii) governance of the species list must aim for community support and use, (iii) all decisions about list composition must be transparent, (iv) the governance of validated lists of species is separate from the governance of the names of taxa, (v) governance of lists of accepted species must not constrain academic freedom, (vi) the set of criteria considered sufficient to recognise species boundaries may appropriately vary between different taxonomic groups but should be consistent when possible, (vii) a global list must balance conflicting needs for currency and stability by having archived versions, (viii) contributors need appropriate recognition, (ix) list content should be traceable, and (x) a global listing process needs both to encompass global diversity and to accommodate local knowledge of that diversity. We conclude by outlining issues that must be resolved if such a system of taxonomic list governance and a unified list of accepted scientific names generated are to be universally adopted.