Assessment of the effect of climate changes in the Late Pleistocene and Holocene on niche conservatism of an arvicolid specialist

Evaluation of Land Suitability Methods with Reference to Neglected and Underutilised Crop Species: A Scoping Review

In agriculture, land use and land classification address questions such as "where", "why" and "when" a particular crop is grown within a particular agroecology. To date, there are several land suitability analysis (LSA) methods, but there is no consensus on the best method for crop suitability analysis. We conducted a scoping review to evaluate methodological strategies for LSA. Secondary to this, we assessed which of these would be suitable for neglected and underutilised crop species (NUS). The review classified LSA methods reported in articles as traditional (26.6%) and modern (63.4%). Modern approaches, including multi-criteria decision-making (MCDM) methods such as analytical hierarchy process (AHP) (14.9%) and fuzzy methods (12.9%); crop simulation models (9.9%) and machine learning related methods (25.7%) are gaining popularity over traditional methods. The MCDM methods, namely AHP and fuzzy, are commonly applied to LSA while crop models and machine learning related methods are gaining popularity. A total of 67 parameters from climatic, hydrology, soil, socio-economic and landscape properties are essential in LSA. Unavailability and the inclusion of categorical datasets from social sources is a challenge. Using big data and Internet of Things (IoT) improves the accuracy and reliability of LSA methods. The review expects to provide researchers and decision-makers with the most robust methods and standard parameters required in developing LSA for NUS. Qualitative and quantitative approaches must be integrated into unique hybrid land evaluation systems to improve LSA.

The globally invasive small Indian mongoose Urva auropunctata is likely to spread with climate change

Invasive alien species represent one of the major factors of global loss of biodiversity and disruption of natural ecosystems. The small Indian mongoose, Urva auropunctata, is considered one of the wild carnivore species with the greatest negative impact on global biodiversity. Understanding of the factors underpinning the species' distribution and potential dispersion in a context of climate change thus appears crucial in the conservation of native ecosystems. Here we modelled the current and future climatically favourable areas for the small Indian mongoose using Ecological Niche Modelling based on data sets filtrated in environmental spaces. Projections from these models show extensive current favourable geographical areas, covering continental and insular regions within tropical and sub-tropical latitudes. Moreover, predictions for 2050 reveal that climate change is likely to expand current favourable areas north of the current favourable spaces, particularly in Eastern Europe. This climate-induced expansion is particularly worrisome given that the species is already spreading in the Balkan region. Our projections suggest that it is very likely that the small Indian mongoose will have an increasing influence on ecosystems and biodiversity in Europe by 2050.