BackgroundClimate is often considered as a key ecological factor limiting the capability of expansion of most species and the extent of suitable habitats. In this contribution, we implement Species Distribution Models (SDMs) to study two parapatric amphibians, Lissotriton vulgaris meridionalis and L. italicus, investigating if and how climate has influenced their present and past (Last Glacial Maximum and Holocene) distributions. A database of 901 GPS presence records was generated for the two newts. SDMs were built through Boosted Regression Trees and Maxent, using the Worldclim bioclimatic variables as predictors.ResultsPrecipitation-linked variables and the temperature annual range strongly influence the current occurrence patterns of the two Lissotriton species analyzed. The two newts show opposite responses to the most contributing variables, such as BIO7 (temperature annual range), BIO12 (annual precipitation), BIO17 (precipitation of the driest quarter) and BIO19 (precipitation of the coldest quarter). The hypothesis of climate influencing the distributions of these species is also supported by the fact that the co-occurrences within the sympatric area fall in localities characterized by intermediate values of these predictors. Projections to the Last Glacial Maximum and Holocene scenarios provided a coherent representation of climate influences on the past distributions of the target species. Computation of pairwise variables interactions and the discriminant analysis allowed a deeper interpretation of SDMs’ outputs. Further, we propose a multivariate environmental dissimilarity index (MEDI), derived through a transformation of the multivariate environmental similarity surface (MESS), to deal with extrapolation-linked uncertainties in model projections to past climate. Finally, the niche equivalency and niche similarity tests confirmed the link between SDMs outputs and actual differences in the ecological niches of the two species.ConclusionsThe different responses of the two species to climatic factors have significantly contributed to shape their current distribution, through contractions, expansions and shifts over time, allowing to maintain two wide allopatric areas with an area of sympatry in Central Italy. Moreover, our SDMs hindcasting shows many concordances with previous phylogeographic studies carried out on the same species, thus corroborating the scenarios of potential distribution during the Last Glacial Maximum and the Holocene emerging from the models obtained.Electronic supplementary materialThe online version of this article (10.1186/s12983-017-0239-4) contains supplementary material, which is available to authorized users.

Boosted Regression Trees (BRT) is one of the modelling techniques most recently applied to biodiversity conservation and it can be implemented with presence-only data through the generation of artificial absences (pseudo-absences). In this paper, three pseudo-absences generation techniques are compared, namely the generation of pseudo-absences within target-group background (TGB), testing both the weighted (WTGB) and unweighted (UTGB) scheme, and the generation at random (RDM), evaluating their performance and applicability in distribution modelling and species conservation. The choice of the target group fell on amphibians, because of their rapid decline worldwide and the frequent lack of guidelines for conservation strategies and regional-scale planning, which instead could be provided through an appropriate implementation of SDMs. Bufo bufo, Salamandrina perspicillata and Triturus carnifex were considered as target species, in order to perform our analysis with species having different ecological and distributional characteristics. The study area is the “Gran Sasso—Monti della Laga” National Park, which hosts 15 Natura 2000 sites and represents one of the most important biodiversity hotspots in Europe. Our results show that the model calibration ameliorates when using the target-group based pseudo-absences compared to the random ones, especially when applying the WTGB. Contrarily, model discrimination did not significantly vary in a consistent way among the three approaches with respect to the tree target species. Both WTGB and RDM clearly isolate the highly contributing variables, supplying many relevant indications for species conservation actions. Moreover, the assessment of pairwise variable interactions and their three-dimensional visualization further increase the amount of useful information for protected areas’ managers. Finally, we suggest the use of RDM as an admissible alternative when it is not possible to individuate a suitable set of species as a representative target-group from which the pseudo-absences can be generated.

Climate change is currently affecting both biodiversity and human activities; land use change and greenhouse gas emissions are the main drivers. Many agricultural services are affected by the change, which in turn reflects on the basic provisioning services, which supply food, fibre and biofuels. Biofuels are getting increasing interest because of their sustainability potential. Jatropha curcas gained popularity as a biodiesel crop, due to its ease of cultivation even in harsh environmental conditions. Notwithstanding its high economic importance, few studies are available about its co‐occurrence with pests of the genus Aphthona in sub‐Saharan Africa, where these insects feed on J. curcas, leading to relevant economic losses. Using ecological niche modelling and GIS post‐modelling analyses, we infer the current and future suitable territories for both these taxa, delineating areas where J. curcas cultivations may occur without suffering the presence of Aphthona, in the context of future climate and land use changing. We introduce an area‐normalized index, the ‘Potential‐Actual Cultivation Index’, to better depict the ratio between the suitable areas shared both by the crop and its pest, and the number of actual cultivations, in a target country. Moreover, we find high economic losses (~−50%) both in terms of carbon sequestration and in biodiesel production when J. curcas co‐occur with the Aphthona cookei species group.

The alternation of glacial and interglacial cycles of the Quaternary period contributed in shaping the current species distribution. Cold-adapted organisms experienced range expansion and contraction in response to the temperature decrease and increase, respectively. In this study, a fragment of the mitochondrial marker COI was used to investigate the phylogeography of Cryptocephalusbarii, a cold-adapted alpine leaf beetle species endemic of Orobie Alps, northern Italy. The relationships among populations, their divergence time, and the most probable migration model were estimated and are discussed in light of the Pleistocene climate oscillations. Through a species distribution modelling analysis, the current habitat suitability was assessed and the distribution in a future global warming scenario predicted. The main divergence events that led to the actual population structure took place from ~750,000 to ~150,000 years ago, almost following the pattern of the climate oscillations that led to the increase of the connections between the populations during cold periods and the isolation on massifs in warm periods. The most supported migration model suggests that the species survived to past adverse climatic conditions within refugia inside and at the limit of the actual range. The species distribution modelling analysis showed that C.barii is extremely sensitive to air temperature variations, thus the increase of temperature caused by global warming will reduce the suitable areas within the species range, leading to its possible extinction in the next 50 years. Cryptocephalusbarii is a representative case of how cold adapted and limited distributed species have been and could be affected by climate change, that highlights the implementation of conservation actions.

The common ragweed Ambrosia artemisiifolia has spread throughout Europe since the 1800s, infesting croplands and causing severe allergic reactions. Recently, the ragweed leaf beetle Ophraella communa was found in Italy and Switzerland; considering that it feeds primarily on A. artemisiifolia in its invaded ranges, some projects started biological control of this invasive plant through the adventive beetle. In this context of a ‘double’ invasion, we assessed the influence of climate change on the spread of these alien species through ecological niche modelling. Considering that A. artemisiifolia mainly lives in agricultural and urbanized areas, we refined the models using satellite remote-sensing data; we also assessed the co-occurrence of the two species in these patches. A. artemisiifolia is predicted to expand more than O. communa in the future, with the medium and high classes of suitability of the former increasing more than the latter, resulting in lower efficacy for O. communa to potentially control A. artemisiifolia in agricultural and urbanized patches. Although a future assessment was performed through the 2018 land-cover data, the predictions we propose are intended to be a starting point for future assessments, considering that the possibility of a shrinkage of target patches is unlikely to occur.