Understanding the Geographic Patterns of Closely-Related Species of Paspalum (Poaceae) Using Distribution Modelling and Seed Germination Traits

The sexual species of the Dilatata complex (Paspalum dasypleurum, P. flavescens, P. plurinerve, P. vacarianum, and P. urvillei) are closely related phylogenetically and show allopatric distributions, except P. urvillei. These species show microhabitat similarities and differences in germination traits. We integrated species distribution models (SDMs) and seed germination assays to determine whether germination divergences explain their biogeographic pattern. We trained SDMs in South America using species' presence-absence data and environmental variables. Additionally, populations sampled from highly favourable areas in the SDMs of these species were grown together, and their seeds germinated at different temperatures and dormancy-breaking conditions. Differences among species in seed dormancy and germination niche breadth were tested, and linear regressions between seed dormancy and climatic variables were explored. SDMs correctly classified both the observed presences and absences. Spatial factors and anthropogenic activities were the main factors explaining these distributions. Both SDMs and germination analyses confirmed that the niche of P. urvillei was broader than the other species which showed restricted distributions, narrower germination niches, and high correlations between seed dormancy and precipitation regimes. Both approaches provided evidence about the generalist-specialist status of each species. Divergences in seed dormancy between the specialist species could explain these allopatric distributions.

A Stepwise Assessment of Parsimony and Fuzzy Entropy in Species Distribution Modelling

Entropy is intrinsic to the geographical distribution of a biological species. A species distribution with higher entropy involves more uncertainty, i.e., is more gradually constrained by the environment. Species distribution modelling tries to yield models with low uncertainty but normally has to reduce uncertainty by increasing their complexity, which is detrimental for another desirable property of the models, parsimony. By modelling the distribution of 18 vertebrate species in mainland Spain, we show that entropy may be computed along the forward-backwards stepwise selection of variables in Logistic Regression Models to check whether uncertainty is reduced at each step. In general, a reduction of entropy was produced asymptotically at each step of the model. This asymptote could be used to distinguish the entropy attributable to the species distribution from that attributable to model misspecification. We discussed the use of fuzzy entropy for this end because it produces results that are commensurable between species and study areas. Using a stepwise approach and fuzzy entropy may be helpful to counterbalance the uncertainty and the complexity of the models. The model yielded at the step with the lowest fuzzy entropy combines the reduction of uncertainty with parsimony, which results in high efficiency.

Vulnerability of dynamic genetic conservation units of forest trees in Europe to climate change

A transnational network of genetic conservation units for forest trees was recently documented in Europe aiming at the conservation of evolutionary processes and the adaptive potential of natural or man-made tree populations. In this study, we quantified the vulnerability of individual conservation units and the whole network to climate change using climate favourability models and the estimated velocity of climate change. Compared to the overall climate niche of the analysed target species populations at the warm and dry end of the species niche are underrepresented in the network. However, by 2100, target species in 33-65 % of conservation units, mostly located in southern Europe, will be at the limit or outside the species' current climatic niche as demonstrated by favourabilities below required model sensitivities of 95%. The highest average decrease in favourabilities throughout the network can be expected for coniferous trees although they are mainly occurring within units in mountainous landscapes for which we estimated lower velocities of change. Generally, the species-specific estimates of favourabilities showed only low correlations to the velocity of climate change in individual units, indicating that both vulnerability measures should be considered for climate risk analysis. The variation in favourabilities among target species within the same conservation units is expected to increase with climate change and will likely require a prioritization among co-occurring species. The present results suggest that there is a strong need to intensify monitoring efforts and to develop additional conservation measures for populations in the most vulnerable units. Also, our results call for continued transnational actions for genetic conservation of European forest trees, including the establishment of dynamic conservation populations outside the current species distribution ranges within European assisted migration schemes.