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Among specific applications of species distribution models (SDMs), the use of SDMs probabilistic maps for guiding field surveys is increasingly applied. This approach is particularly used for poorly known and/or cryptic species in order to better assess their distribution. One of the most interesting aspects of these applications is that predictions could be clearly validated by real data, subsequently obtained in the field. Despite this important difference from other applications, to our knowledge, the efficiency of different algorithms, metrics for model evaluation and algorithm-specific settings have not yet been sufficiently investigated. This research performs a literature survey to investigate which species, study area characteristics, variables, techniques and settings were used or suggested by previous authors. We then applied the most common approaches to guide field surveys for a set of 70 vascular plants in an endemic-rich area of Sardinia (Italy) of approx. 9000 ha, the flora of which was deeply investigated during the last two years. Our main aims were: (1) to use pre-model records for predicting the potential occurrence of plant species with different sample size, detectability and habitat preference, (2) to apply results for guiding searches for new populations of poorly known species, (3) to calculate the model performance according to independent real presence/absence data (testAUC) and (4) to compare different modelling data input and settings on the testAUC basis. By emphasizing the importance of field verification, both the review and the worked example supported the reliability of SDMs for a wide range of species to understand where species could potentially be present and therefore to optimise resources for the search of new species localities. This study may help understand and summarise the most applied methodological approaches and to highlight future directions for this practical application. Without underrating the importance of most common recommendations, practitioners are encouraged to test the ability of this SDMs' application with their own data. Indeed, large gaps in species' types (e.g. insects) and in regions covered by these kind of studies (e.g. many African and Asian territories) were found. Furthermore, eventual biases due to lack of data, experience or staff, have in this experimental case less irreparable consequences than others, such as conservation assessments based on future projections, which cannot be otherwise adjusted by explicit data from ground validation.

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Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids thus fail to reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions are controlled and most terrestrial species reside. Here we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0-5 and 5-15 cm depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all of the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding 2 m gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (3.6 ± 2.3°C warmer than gridded air temperature), whereas soils in warm and humid environments are on average slightly cooler (0.7 ± 2.3°C cooler). The observed substantial and biome-specific offsets underpin that the projected impacts of climate and climate change on biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining global gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

The importance of robust systems for classifying biogeographical patterns has been emphasized for its usefulness in\ud designing conservation strategies. For such purposes, the distribution patterns of the endemic flora have often been used.\ud Several studies have identified phytogeographical units within Sardinia (western Mediterranean); however, the main part of\ud the island remains unstudied. Thus, the aim of this study is to lay out a comprehensive biogeographical scheme for Sardinia\ud based on endemic vascular plant distributions, together with geological and geomorphological units. We georeferenced, in\ud a 1-km2 grid cell, the presence of 290 vascular endemic taxa from the literature, herbarium specimens and field\ud investigators’ research. Sardinia was subdivided into 31 homogeneous units through the integration of geological and\ud geomorphological maps and, subsequently, a presence–absence matrix of endemic taxa in each unit was built. Hierarchical\ud cluster analysis was performed to define two levels of biogeographical units (i.e. sectors and subsectors). For each unit the\ud exclusive and differential endemic taxa were identified. For sectors, indicator species were explored by the Indicator Value\ud (Ind Val) analysis and relationships were analysed by quantitative interaction web. A total of six sectors and 22 subsectors\ud were identified. The highest endemic plant richness was found in the Campidanese-Turritano, Sulcitano-Iglesiente and\ud Supramontano sectors, and in the Gennargenteo, Barbaricino, Iglesiente and Sulcitano subsectors. All sectors were\ud characterized by the presence of exclusive, differential and indicator taxa. The interaction analysis showed the highest\ud uniqueness in endemic flora in the Supramontano and Sulcitano-Iglesiente sectors, which hosted a high number of\ud exclusive endemic species. Mostly mountainous sectors/subsectors had higher endemic-species richness compared with\ud lowland ones. The study showed the relevance of geology and geomorphology, together with accurate data on endemic\ud distribution, to define consistent phytogeographical units. Furthermore, the biogeographical scheme presented here helps to\ud define area-based conservation strategies in Sardini