Richard G. Pearson

Protected area needs in a changing climate

Range shifts due to climate change may cause species to move out of protected areas. Climate change could therefore result in species range dynamics that reduce the relevance of current fixed protected areas in future conservation strategies. Here, we apply species distribution modeling and conservation planning tools in three regions (Mexico, the Cape Floristic Region of South Africa, and Western Europe) to examine the need for additional protected areas in light of anticipated species range shifts caused by climate change. We set species representation targets and assessed the area required to meet those targets in the present and in the future, under a moderate climate change scenario. Our findings indicate that protected areas can be an important conservation strategy in such a scenario, and that early action may be both more effective and less costly than inaction or delayed action. According to our projections, costs may vary among regions and none of the three areas studied will fully meet all conservation targets, even under a moderate climate change scenario. This suggests that limiting climate change is an essential complement to adding protected areas for conservation of biodiversity.

SPECIES: A Spatial Evaluation of Climate Impact on the Envelope of Species

A model, A Spatial Evaluation of Climate Impact on the Envelope of Species (SPECIES), is presented which has been developed to evaluate the impacts of climate change on the bioclimatic envelope of plant species in Great Britain. SPECIES couples an artificial neural network with a climate–hydrological process model. The hybrid model has been successfully trained to estimate current species distributions using climate and soils data at the European scale before application at a finer resolution national scale. Using this multi-scale approach ensures encapsulation of the full extent of future climate scenarios within Great Britain without extrapolating outside of the models training dataset. Application of the model to 32 plant species produced a mean Pearson correlation coefficient of 0.841 and a mean Kappa statistic of 0.772 between observed and simulated distributions. Simulations of four climate change scenarios revealed that changes to suitable climate space in Great Britain is highly species dependent and that distribution changes may be multidirectional and temporally non-linear. Analysis of the SPECIES results suggests that the neural network methodology can provide a feasible alternative to more classical spatial statistical techniques.

Applications of ecological niche modeling for species delimitation: a review and empirical evaluation using day geckos (Phelsuma) from Madagascar

Although the systematic utility of ecological niche modeling is generally well known (e.g., concerning the recognition and discovery of areas of endemism for biogeographic analyses), there has been little discussion of applications concerning species delimitation, and to date, no empirical evaluation has been conducted. However, ecological niche modeling can provide compelling evidence for allopatry between populations, and can also detect divergent ecological niches between candidate species. Here we present results for two taxonomically problematic groups of Phelsuma day geckos from Madagascar, where we integrate ecological niche modeling with mitochondrial DNA and morphological data to evaluate species limits. Despite relatively modest levels of genetic and morphological divergence, for both species groups we find divergent ecological niches between closely related species and parapatric ecological niche models. Niche models based on the new species limits provide a better fit to the known distribution than models based upon the combined (lumped) species limits. Based on these results, we elevate three subspecies of Phelsuma madagascariensis to species rank and describe a new species of Phelsuma from the P. dubia species group. Our phylogeny continues to support a major endemic radiation of Phelsuma in Madagascar, with dispersals to Pemba Island and the Mascarene Islands. We conclude that ecological niche modeling offers great potential for species delimitation, especially for taxonomic groups exhibiting low vagility and localized endemism and for groups with more poorly known distributions. In particular, niche modeling should be especially sensitive for detecting recent parapatric speciation driven by ecological divergence, when the environmental gradients driving speciation are represented within the ecological niche models.

Extinction vulnerability of tropical montane endemism from warming and upslope displacement: a preliminary appraisal for the highest massif in Madagascar

One of the predicted biological responses to climate warming is the upslope displacement of species distributions. In the tropics, because montane assemblages frequently include local endemics that are distributed close to summits, these species may be especially vulnerable to experiencing complete habitat loss from warming. However, there is currently a dearth of information available for tropical regions. Here, we present a preliminary appraisal of this extinction threat using the herpetological assemblage of the Tsaratanana Massif in northern Madagascar (the islands highest massif), which is rich with montane endemism. We present meteorological evidence (individual and combined regional weather station data and reanalysis forecast data) for recent warming in Madagascar, and show that this trend is consistent with recent climate model simulations. Using standard moist adiabatic lapse rates, these observed meteorological warming trends in northern Madagascar predict upslope species displacement of 17–74 m per decade between 1993 and 2003. Over this same period, we also report preliminary data supporting a trend for upslope distribution movements, based on two surveys we completed at Tsaratanana. For 30 species, representing five families of reptiles and amphibians, we found overall mean shifts in elevational midpoint of 19–51 m upslope (mean lower elevation limit 29–114 m; mean upper elevation limit −8 to 53 m). We also found upslope trends in mean and median elevational observations in seven and six of nine species analysed. Phenological differences between these surveys do not appear to be substantial, but these upslope shifts are consistent with the predictions based on meteorological warming. An elevational range displacement analysis projects complete habitat loss for three species below the 2 °C ‘dangerous’ warming threshold. One of these species is not contracting its distribution, but the other two were not resampled in 2003. A preliminary review of the other massifs in Madagascar indicates potential similar vulnerability to habitat loss and upslope extinction. Consequently, we urgently recommend additional elevational surveys for these and other tropical montane assemblages, which should also include, when possible, the monitoring of local meteorological conditions and habitat change.

Integrating bioclimate with population models to improve forecasts of species extinctions under climate change

Climate change is already affecting species worldwide, yet existing methods of risk assessment have not considered interactions between demography and climate and their simultaneous effect on habitat distribution and population viability. To address this issue, an international workshop was held at the University of Adelaide in Australia, 25–29 May 2009, bringing leading species distribution and population modellers together with plant ecologists. Building on two previous workshops in the UK and Spain, the participants aimed to develop methodological standards and case studies for integrating bioclimatic and metapopulation models, to provide more realistic forecasts of population change, habitat fragmentation and extinction risk under climate change. The discussions and case studies focused on several challenges, including spatial and temporal scale contingencies, choice of predictive climate, land use, soil type and topographic variables, procedures for ensemble forecasting of both global climate and bioclimate models and developing demographic structures that are realistic and species-specific and yet allow generalizations of traits that make species vulnerable to climate change. The goal is to provide general guidelines for assessing the Red-List status of large numbers of species potentially at risk, owing to the interactions of climate change with other threats such as habitat destruction, overexploitation and invasive species.

The sensitivity and vulnerability of terrestrial habitats and species in Britain and Ireland to climate change.

Abstract Climate change is having an increasing impact on the distribution and functioning of species and habitats. This has important implications for conservation practice and policy. The aim of this study was to model the direct impacts of climate change on terrestrial environments in Britain and Ireland in order to understand the possible changes in the distribution of species and the composition of habitats. A model, based on an artificial neural network, was used to predict changes in the bioclimate envelope of species, under the UKCIP98 climate change scenarios. A total of 50 species, representing several taxa, were modelled. Many species demonstrated a consistent response to climate change, either increasing or losing suitable climate space, although some had a variable response with losses starting to occur under the high scenarios. The percentage change in the bioclimate envelope of the species was calculated. This showed that montane species and habitats were the most sensitive to climate change. Other habitats from upland areas or species with northern distributions were also sensitive to losses, while species gaining suitable climate space represented a variety of habitats. Sensitivity needs to be viewed alongside vulnerability, the ability of the species or habitat to adapt to climate change. Montane species and habitats were the most vulnerable, with limited adaptation possibilities. Other vulnerable habitats, for which species modelling was carried out, include lowland raised bog, lowland calcareous grassland and native pine woodland. The potential impacts of climate change should be taken into account when planning conservation measures for these sensitive and vulnerable species and habitats.

The correlation between reading and mathematics ability at age twelve has a substantial genetic component

Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve.

Indels, structural variation, and recombination drive genomic diversity in Plasmodium falciparum

The malaria parasite Plasmodium falciparum has a great capacity for evolutionary adaptation to evade host immunity and develop drug resistance. Current understanding of parasite evolution is impeded by the fact that a large fraction of the genome is either highly repetitive or highly variable and thus difficult to analyze using short-read sequencing technologies. Here, we describe a resource of deep sequencing data on parents and progeny from genetic crosses, which has enabled us to perform the first genome-wide, integrated analysis of SNP, indel and complex polymorphisms, using Mendelian error rates as an indicator of genotypic accuracy. These data reveal that indels are exceptionally abundant, being more common than SNPs and thus the dominant mode of polymorphism within the core genome. We use the high density of SNP and indel markers to analyze patterns of meiotic recombination, confirming a high rate of crossover events and providing the first estimates for the rate of non-crossover events and the length of conversion tracts. We observe several instances of meiotic recombination within copy number variants associated with drug resistance, demonstrating a mechanism whereby fitness costs associated with resistance mutations could be compensated and greater phenotypic plasticity could be acquired.

A Genome-wide Association Analysis of a Broad Psychosis Phenotype Identifies Three Loci for Further Investigation

Background Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories. Methods 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls). Results No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortium’s panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10–14) and explained approximately 2% of the phenotypic variance. Conclusions Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data.BACKGROUND Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories. METHODS 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls). RESULTS No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortiums panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10(-14)) and explained approximately 2% of the phenotypic variance. CONCLUSIONS Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data.

Genome-wide association study of intraocular pressure identifies the GLCCI1/ICA1 region as a glaucoma susceptibility locus

To discover quantitative trait loci for intraocular pressure, a major risk factor for glaucoma and the only modifiable one, we performed a genome-wide association study on a discovery cohort of 2175 individuals from Sydney, Australia. We found a novel association between intraocular pressure and a common variant at 7p21 near to GLCCI1 and ICA1. The findings in this region were confirmed through two UK replication cohorts totalling 4866 individuals (rs59072263, Pcombined = 1.10 × 10−8). A copy of the G allele at this SNP is associated with an increase in mean IOP of 0.45 mmHg (95%CI = 0.30–0.61 mmHg). These results lend support to the implication of vesicle trafficking and glucocorticoid inducibility pathways in the determination of intraocular pressure and in the pathogenesis of primary open-angle glaucoma.