AimIn the face of global environmental change, identifying the factors that shape the ecological niches of species and understanding the mechanisms behind them can help to draft effective conservation plans. The differences in the ecological factors that shape species distributions may then help to highlight differences between closely related taxa. We investigate the applicability of ecological niche modelling and the comparison of species distributions in ecological niche space to detect areas with priority for biodiversity conservation and to analyse differences in the ecological niche spaces used by closely related taxa.Location United States of America, Mexico and Central America.Methods We apply ordination and ecological niche modelling techniques to assess the main environmental drivers of the distribution of Mexican white pines (Pinus: Pinaceae). Furthermore, we assess the similarities and differences of the ecological niches occupied by closely related taxa. We analyse whether Mexican white pines occupy similar or equivalent ecological niches.Results All the studied taxa presented different responses to the environmental factors, resulting in a unique combination of niche conditions. Our stacked habitat suitability maps highlighted regions in southern Mexico and northern Central America as highly suitable for most species and thus with high conservation value. By quantitatively assessing the niche overlap, similarity and equivalency of Mexican white pines, our results prove that the distribution of one species cannot be implied by the distribution of another, even if these taxa are considered closely related.Main conclusions The fact that each Mexican white pine is constrained by a unique set of environmental conditions, and thus, their non-equivalence of ecological niches has direct implications for conservation as this highlights the inadequacy of one-fits all type of conservation measure.

Recent diversification followed by secondary contact and hybridization may explain complex patterns of intra- and interspecific morphological and genetic variation in the North American hard pines (Pinus section Trifoliae), a group of approximately 49 tree species distributed in North and Central America and the Caribbean islands. We concatenated five plastid DNA markers for an average of 3.9 individuals per putative species and assessed the suitability of the five regions as DNA bar codes for species identification, species delimitation, and phylogenetic reconstruction. The ycf1 gene accounted for the greatest proportion of the alignment (46.9%), the greatest proportion of variable sites (74.9%), and the most unique sequences (75 haplotypes). Phylogenetic analysis recovered clades corresponding to subsections Australes, Contortae, and Ponderosae. Sequences for 23 of the 49 species were monophyletic and sequences for another 9 species were paraphyletic. Morphologically similar species within subsections usually grouped together, but there were exceptions consistent with incomplete lineage sorting or introgression. Bayesian relaxed molecular clock analyses indicated that all three subsections diversified relatively recently during the Miocene. The general mixed Yule-coalescent method gave a mixed model estimate of only 22 or 23 evolutionary entities for the plastid sequences, which corresponds to less than half the 49 species recognized based on morphological species assignments. Including more unique haplotypes per species may result in higher estimates, but low mutation rates, recent diversification, and large effective population sizes may limit the effectiveness of this method to detect evolutionary entities.

Pinus subsection Ponderosae includes approximately 17 tree species distributed from western Canada to Nicaragua. We inferred phylogenetic relationships of multiple accessions for all widely recognized species from 3.7 kb of cpDNA sequence (matK, trnD-trnY-trnE spacer, chlN-ycf1 spacer, and ycf1). The sister relationship between subsections Ponderosae and Australes was corroborated with high branch support, and several clades, most with lower branch support, were identified within subsection Ponderosae. Pinus jeffreyi was sister to P. coulteri, P. sabiniana, and P. torreyana. Californian accessions of P. ponderosa and P. washoensis occurred in a clade separate from P. arizonica and P. scopulorum from the southwestern United States. Western Mexican species P. cooperi and P. durangensis had cpDNA sequences identical to one or more accessions of P. arizonica and P. scopulorum, and together these taxa were closely related to clades of P. engelmannii-P. devoniana (Mexico) and P. douglasiana-P. yecorensis-P. maximinoi (western Mexico to Guatemala). A well supported clade of taxa from Mexico and Central America included P. pseudostrobus, P. montezumae, P. hartwegii, P. maximinoi (one of three accessions), P. nubicola, and P. donnell-smithii. Chloroplast DNA sequences were nonmonophyletic for most species, although the degree of support varied.

Aim Remote sensing data have been used in a growing number of studies to directly predict species richness or to improve the performance of species distribution models (SDMs), but their suitability for stacked species distribution models (S-SDMs) remains unclear. In this case study, we evaluated the potential and limitations of remotely sensed data in S-SDMs and addressed the commonly observed overestimation of species richness by S-SDMs.Location Mexico.Methods Phenological and statistical metrics were derived from remotely sensed time series data (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)) of the Terra-MODIS enhanced vegetation index and land surface temperature products. In a series of climatic and remote sensing-based SDMs, the distribution ranges of 40 species of the genus Pinus (Pinaceae) were modelled based on presence-only herbarium and field data using the maximum entropy algorithm and summed to estimate species richness. Three different species-specific thresholds were applied to convert continuous model predictions into binary maps. Modelled species richness was compared to independent data from the Mexican National Forest Inventory. ResultsThe inclusion of remote sensing data led to significantly better predictions of species richness in comparison to the climate-based models for the summed suitabilities and all thresholds considered. Both climatic and remote sensing-based models allowed us to identify the areas with the highest pine species richness based on presence-only data. Remote sensing-based models compare closely with climate-derived patterns, but provide better spatial resolution and more detailed information on local habitat availability. Main conclusionsThe results of this case study provide general guidance for the potential and limitations of using remote sensing data in S-SDMs. Our results confirmed that remote sensing data may not only have the capability for improving individual SDMs, but also can be a potential tool for reducing the overestimation of species richness by S-SDMs. This approach opens up new possibilities for species richness predictions in areas where biological survey data are scarce and where no species richness inventory data exist.

Our analyses document cytonuclear discordance in Pinus subsection Australes. We attribute this discordance to ancient and recent introgression and present a phylogenetic hypothesis in which mostly hierarchical relationships are overlain by gene flow.