Morphometric prognostic index in breast cancer

OBJECTIVE: To assess the ability of the morphometric prognostic index (MPI) in predicting clinical outcome in a group of breast cancer patients with short-term follow-up and to assess the relationship between MPI and other prognosticators. STUDY DESIGN: The study group consisted of 63 cases of breast cancer. Follow-up data were available for 48 patients. MPI values were calculated, and degree of nuclear and tubular differentiation was investigated in each tumor. S-phase fraction (SPF), estrogen and progesterone receptors were also studied. RESULTS: The group of patients with MPI values < 0.60 had percent values of disease-free survival significantly higher than did those with MPI values > or = 0.60. Furthermore, significant direct correlations were found between MPI and degree of nuclear atypia and between MPI and SPF. Significant inverse relationships were found between MPI and tumor progesterone receptor levels and between MPI and degree of histologic tubular differentiation. CONCLUSION: The validity of MPI as a prognosticator in breast cancer was confirmed, even in a limited number of patients observed in short-term follow-up. MPI seems to be a reliable and economical prognosticator in selecting breast cancer patients for adjuvant chemotherapy.     

The Potential Impact of White-Nose Syndrome on the Conservation Status of North American Bats

White-Nose syndrome (WNS) is an emergent infectious disease that has already killed around six million bats in North America and has spread over two thousand kilometers from its epicenter. However, only a few studies on the possible impacts of the fungus on bat hosts were conducted, particularly concerning its implications for bat conservation. We predicted the consequences of WNS spread by generating a map with potential areas for its occurrence based on environmental conditions in sites where the disease already occurs, and overlaid it with the geographic distribution of all hibernating bats in North America. We assumed that all intersection localities would negatively affect local bat populations and reassessed their conservation status based on their potential population decline. Our results suggest that WNS will not spread widely throughout North America, being mostly restricted to the east and southeast regions. In contrast, our most pessimistic scenario of population decline indicated that the disease would threaten 32% of the bat species. Our results could help further conservation plans to preserve bat diversity in North America.     

Evaluating,partitioning, and mapping the spatial autocorrelation component in ecological niche modeling: a new approach based on environmentally equidistant records

Most species data display spatial autocorrelation that can affect ecological niche models (ENMs) accuracy‐statistics, affecting its ability to infer geographic distributions. Here we evaluate whether the spatial autocorrelation underlying species data affects accuracy‐statistics and map the uncertainties due to spatial autocorrelation effects on species range predictions under past and future climate models. As an example, ENMs were fitted to Qualea grandiflora (Vochysiaceae), a widely distributed plant from Brazilian Cerrado. We corrected for spatial autocorrelation in ENMs by selecting sampling sites equidistant in geographical (GEO) and environmental (ENV) spaces. Distributions were modelled using 13 ENMs evaluated by two accuracy‐statistics (TSS and AUC), which were compared with uncorrected ENMs. Null models and the similarity statistics I were used to evaluate the effects of spatial autocorrelation. Moreover, we applied a hierarchical ANOVA to partition and map the uncertainties from the time (across last glacial maximum, pre‐insustrial, and 2080 time periods) and methodological components (ENMs and autocorrelation corrections). The GEO and ENV models had the highest accuracy‐statistics values, although only the ENV model had values higher than expected by chance alone for most of the 13 ENMs. Uncertainties from time component were higher in the core region of the Brazilian Cerrado where Q. grandiflora occurs, whereas methodological components presented higher uncertainties in the extreme northern and southern regions of South America (i.e. outside of Brazilian Cerrado). Our findings show that accounting for autocorrelation in environmental space is more efficient than doing so in geographical space. Methodological uncertainties were concentrated in outside the core region of Q. grandiflora's habitat. Conversely, uncertainty due to time component in the Brazilian Cerrado reveals that ENMs were able to capture climate change effects on Q. grandiflora distributions.     

A macroecological approach to evolutionary rescue and adaptation to climate change

Despite the widespread use of ecological niche models (ENMs) for predicting the responses of species to climate change, these models do not explicitly incorporate any population‐level mechanism. On the other hand, mechanistic models adding population processes (e.g. biotic interactions, dispersal and adaptive potential to abiotic conditions) are much more complex and difficult to parameterize, especially if the goal is to predict range shifts for many species simultaneously. In particular, the adaptive potential (based on genetic adaptations, phenotypic plasticity and behavioral adjustments for physiological responses) of local populations has been a less studied mechanism affecting species’ responses to climatic change so far. Here, we discuss and apply an alternative macroecological framework to evaluate the potential role of evolutionary rescue under climate change based on ENMs. We begin by reviewing eco‐evolutionary models that evaluate the maximum sustainable evolutionary rate under a scenario of environmental change, showing how they can be used to understand the impact of temperature change on a Neotropical anuran species, the Schneider's toad Rhinella diptycha. Then we show how to evaluate spatial patterns of species’ geographic range shift using such models, by estimating evolutionary rates at the trailing edge of species distribution estimated by ENMs and by recalculating the relative amount of total range loss under climate change. We show how different models can reduce the expected range loss predicted for the studied species by potential ecophysiological adaptations in some regions of the trailing edge predicted by ENMs. For general applications, we believe that parameters for large numbers of species and populations can be obtained from macroecological generalizations (e.g. allometric equations and ecogeographical rules), so our framework coupling ENMs with eco‐evolutionary models can be applied to achieve a more accurate picture of potential impacts from climate change and other threats to biodiversity.     

A coupled phylogeographical and species distribution modelling approach recovers the demographical history of a Neotropical seasonally dry forest tree species

We investigated here the demographical history of Tabebuia impetiginosa (Bignoniaceae) to understand the dynamics of the disjunct geographical distribution of South American seasonally dry forests (SDFs), based on coupling an ensemble approach encompassing hindcasting species distribution modelling and statistical phylogeographical analysis. We sampled 17 populations (280 individuals) in central Brazil and analysed the polymorphisms at chloroplast (trnS‐trnG, psbA‐trnH, and ycf6‐trnC intergenic spacers) and nuclear (ITS nrDNA) genomes. Phylogenetic analyses based on median‐joining network showed no haplotype sharing among population but strong evidence of incomplete lineage sorting. Coalescent analyses showed historical constant populations size, negligible gene flow among populations, and an ancient time to most recent common ancestor dated from ~4.7 ± 1.1 Myr BP. Most divergences dated from the Lower Pleistocene, and no signal of important population size reduction was found in coalescent tree and tests of demographical expansion. Demographical scenarios were built based on past geographical range dynamic models, using two a priori biogeographical hypotheses (‘Pleistocene Arc’ and ‘Amazonian SDF expansion’) and on two additional hypotheses suggested by the palaeodistribution modelling built with several algorithms for distribution modelling and palaeoclimatic data. The simulation of these demographical scenarios showed that the pattern of diversity found so far for T. impetiginosa is in consonance with a palaeodistribution expansion during the last glacial maximum (LGM, 21 kyr BP), strongly suggesting that the current disjunct distribution of T. impetiginosa in SDFs may represent a climatic relict of a once more wide distribution.     

Global richness patterns of venomous snakes reveal contrasting influences of ecology and history in two different clades

Recent studies addressing broad-scale species richness gradients have proposed two main primary drivers: contemporary climate and evolutionary processes (differential balance between speciation and extinction). Here, we analyze the global richness patterns of two venomous snake clades, Viperidae and Elapidae. We used ordinary least squares multiple regression (OLS) and partial regression analysis to investigate to what extent actual evapotranspiration (AET; summarizing current environmental conditions) and biogeographical regions (representing evolutionary effects) were associated with species richness. For viperids, AET explained 45.6% of the variance in richness whereas the effect of this variable for elapids was almost null (0.5%). On the other hand, biogeographic regions were the best predictors of elapid richness (56.5%), against its relatively small effect (25.9%) in viperid richness. Partial regressions also revealed similar patterns for independent effects of climate and history in both clades. However, the independent historical effect in Elapidae decreased from 45.2 to 17.8% when we excluded Australia from the analyses, indicating that the strong historical effect that had emerged for the global richness pattern was reflecting the historical process of elapid radiation into Australia. Even after excluding Australia, the historical signal in elapid richness in the rest of the globe was still significant and much higher than that observed in viperid richness at a global scale (2.7% after controlling for AET effects). Differences in the evolutionary age of these two clades can be invoked to explain these contrasting results, in that viperids probably had more time for diversification, generating richness responses to environmental gradients, whereas the pattern of distribution of elapid richness can be more directly interpreted in an evolutionary context. Moreover, these results show the importance of starting to adopt deconstructive approaches to species richness, since the driving factors of these patterns may vary from group to group according to their evolutionary history. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Hidden patterns of phylogenetic non‐stationarity overwhelm comparative analyses of niche conservatism and divergence

Aim Despite the importance of the niche concept in ecological and evolutionary theory, there are still many discussions about its definition and operational evaluation, especially when dealing with niche divergence and conservatism in an explicit phylogenetic context. Here we evaluate patterns of niche evolution in 67 New World Carnivora species, measured using Hellinger distances based on MAXENT models of species distribution. We show how inferences on niche conservatism or divergence depend on the way phylogenetic patterns are analysed using matrix comparison techniques. Innovation Initially we used the simplest approach of Mantel tests to compare Hellinger distances ( N ) derived from MAXENT and phylogenetic distances ( P ) among species. Then we extended the Mantel test to generate a multivariate correlogram, in which phylogenetic patterns are analysed at multiple levels in the phylogeny and can reveal nonlinearity in the relationship between divergence and time. Finally, we proposed a new approach to generate ‘local’ (or ‘specific’) leverages of components for Mantel correlation, evaluating the non‐stationarity in the relationship between N and P for each species. This new approach was used to show if some lineages are more prone to niche shift or conservatism than others. Main conclusions Standard Mantel tests indicated a poor correspondence between N and P matrices, discarding the idea of niche conservatism for Carnivora, but the correlogram supports that closely related species tend to be more similar than expected by chance. Moreover, the variance among Hellinger distances between pairs of closely phylogenetically related species is much larger than for the entire clade. Phylogenetic non‐stationarity analysis shows that in some Carnivora families the niche tends to divergence (Mustelidae and Canidae), whereas in others it tends to conservatism (Procyonidae and Mustelidae) at short phylogenetic distances. Our analyses clearly show that misleading results may appear if niche divergence is analysed only by simple matrix correlations not taking into account complex patterns of phylogenetic nonlinearity and non‐stationarity.     

A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers

Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12- BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in http://ecoclimate.org/.