Unpacking the mechanisms captured by a correlative species distribution model to improve predictions of climate refugia.

Climate refugia are regions that animals can retreat to, persist in and potentially then expand from under changing environmental conditions. Most forecasts of climate change refugia for species are based on correlative species distribution models (SDMs) using long-term climate averages, projected to future climate scenarios. Limitations of such methods include the need to extrapolate into novel environments and uncertainty regarding the extent to which proximate variables included in the model capture processes driving distribution limits (and thus can be assumed to provide reliable predictions under new conditions). These limitations are well documented; however, their impact on the quality of climate refugia predictions is difficult to quantify. Here, we develop a detailed bioenergetics model for the koala. It indicates that range limits are driven by heat-induced water stress, with the timing of rainfall and heat waves limiting the koala in the warmer parts of its range. We compare refugia predictions from the bioenergetics model with predictions from a suite of competing correlative SDMs under a range of future climate scenarios. SDMs were fitted using combinations of long-term climate and weather extremes variables, to test how well each set of predictions captures the knowledge embedded in the bioenergetics model. Correlative models produced broadly similar predictions to the bioenergetics model across much of the species' current range - with SDMs that included weather extremes showing highest congruence. However, predictions in some regions diverged significantly when projecting to future climates due to the breakdown in correlation between climate variables. We provide unique insight into the mechanisms driving koala distribution and illustrate the importance of subtle relationships between the timing of weather events, particularly rain relative to hot-spells, in driving species-climate relationships and distributions. By unpacking the mechanisms captured by correlative SDMs, we can increase our certainty in forecasts of climate change impacts on species.

Comparative mapping in watermelon [Citrullus lanatus (Thunb.) Matsum. et Nakai].

The first single-nucleotide polymorphism (SNP) maps for watermelon [Citrullus lanatus (Thunb.) Matsum. et Nakai] were constructed and compared. Three populations were developed from crosses between two elite cultivars, Klondike Black Seeded × New Hampshire Midget (KBS × NHM), an elite cultivar and wild egusi accession, Strain II × PI 560023 (SII × Egusi) and an elite cultivar and a wild citron accession, ZWRM50 × PI 244019 (ZWRM × Citroides). The SII × Egusi and ZWRM × Citroides F(2) populations consisted of 187 and 182 individuals respectively while the KBS × NHM recombinant inbred line (RIL) population consisted of 164 lines. The length of the genetic maps were 1,438, 1,514 and 1,144 cM with average marker distances of 3.8, 4.2, and 3.4 cM for the KBS × NHM, SII × Egusi and ZWRM × Citroides populations, respectively. Shared markers were used to align the three maps so that the linkage groups (LGs) represented the 11 chromosomes of the species. Marker segregation distortion were observed in all three populations, but was highest (12.7 %) in the ZWRM × Citroides population, where Citroides alleles were favored. The three maps were used to construct a consensus map containing 378 SNP markers with an average distance of 5.1 cM between markers. Phenotypic data was collected for fruit weight (FWT), fruit length (FL), fruit width (FWD), fruit shape index (FSI), rind thickness (RTH) and Brix (BRX) and analyzed for quantitative trait loci (QTL) associated with these traits. A total of 40 QTL were identified in the three populations, including major QTL for fruit size and shape that were stable across genetic backgrounds and environments. The present study reports the first SNP maps for Citrullus and the first map constructed using two elite parents. We also report the first stable QTL associated with fruit size and shape in Citrullus lanatus. These maps, QTL and SNPs should be useful for the watermelon community and represent a significant step towards the potential use of molecular tools in watermelon breeding.

Community transcriptomic assembly reveals microbes that contribute to deep-sea carbon and nitrogen cycling.

The deep ocean is an important component of global biogeochemical cycles because it contains one of the largest pools of reactive carbon and nitrogen on earth. However, the microbial communities that drive deep-sea geochemistry are vastly unexplored. Metatranscriptomics offers new windows into these communities, but it has been hampered by reliance on genome databases for interpretation. We reconstructed the transcriptomes of microbial populations from Guaymas Basin, in the deep Gulf of California, through shotgun sequencing and de novo assembly of total community RNA. Many of the resulting messenger RNA (mRNA) contiguous sequences contain multiple genes, reflecting co-transcription of operons, including those from dominant members. Also prevalent were transcripts with only limited representation (2.8 times coverage) in a corresponding metagenome, including a considerable portion (1.2 Mb total assembled mRNA sequence) with similarity (96%) to a marine heterotroph, Alteromonas macleodii. This Alteromonas and euryarchaeal marine group II populations displayed abundant transcripts from amino-acid transporters, suggesting recycling of organic carbon and nitrogen from amino acids. Also among the most abundant mRNAs were catalytic subunits of the nitrite oxidoreductase complex and electron transfer components involved in nitrite oxidation. These and other novel genes are related to novel Nitrospirae and have limited representation in accompanying metagenomic data. High throughput sequencing of 16S ribosomal RNA (rRNA) genes and rRNA read counts confirmed that Nitrospirae are minor yet widespread members of deep-sea communities. These results implicate a novel bacterial group in deep-sea nitrite oxidation, the second step of nitrification. This study highlights metatranscriptomic assembly as a valuable approach to study microbial communities.