Impacts of climate change on high priority fruit fly species in Australia

Tephritid fruit flies are among the most destructive horticultural pests posing risks to Australia’s multi-billion-dollar horticulture industry. Currently, there are 11 pest fruit fly species of economic concern in Australia. Of these, nine are native to this continent (Bactrocera aquilonis, B. bryoniae, B. halfordiae, B. jarvisi, B. kraussi, B. musae, B. neohumeralis, B. tryoni and Zeugodacus cucumis), while B. frauenfeldi and Ceratitis capitata are introduced. To varying degrees these species are costly to Australia’s horticulture through in-farm management, monitoring to demonstrate pest freedom, quarantine and trade restrictions, and crop losses. Here, we used a common species distribution model, Maxent, to assess climate suitability for these 11 species under baseline (1960–1990) and future climate scenarios for Australia. Projections indicate that the Wet Tropics is likely to be vulnerable to all 11 species until at least 2070, with the east coast of Australia also likely to remain vulnerable to multiple species. While the Cape York Peninsula and Northern Territory are projected to have suitable climate for numerous species, extrapolation to novel climates in these areas decreases confidence in model projections. The climate suitability of major horticulture areas currently in eastern Queensland, southern-central New South Wales and southern Victoria to these pests may increase as climate changes. By highlighting areas at risk of pest range expansion in the future our study may guide Australia’s horticulture industry in developing effective monitoring and management strategies

Potential impacts of climate change on habitat suitability for the Queensland fruit fly

Anthropogenic climate change is a major factor driving shifts in the distributions of pests and invasive species. The Queensland fruit fly, Bactrocera tryoni Froggatt (Qfly), is the most economically damaging insect pest of Australia's horticultural industry, and its management is a key priority for plant protection and biosecurity. Identifying the extent to which climate change may alter the distribution of suitable habitat for Qfly is important for the development and continuation of effective monitoring programs, phytosanitary measures, and management strategies. We used Maxent, a species distribution model, to map suitable habitat for Qfly under current climate, and six climate scenarios for 2030, 2050 and 2070. Our results highlight that south-western Australia, northern regions of the Northern Territory, eastern Queensland, and much of south-eastern Australia are currently suitable for Qfly. This includes southern Victoria and eastern Tasmania, which are currently free of breeding populations. There is substantial agreement across future climate scenarios that most areas currently suitable will remain so until at least 2070. Our projections provide an initial estimate of the potential exposure of Australia's horticultural industry to Qfly as climate changes, highlighting the need for long-term vigilance across southern Australia to prevent further range expansion of this species

Patterns of Pacific decadal variability recorded by Indian Ocean corals

We investigate Pacific Decadal Oscillation (PDO) signals recorded by two bimonthly resolved coral δ18O series from La Réunion and Ifaty (West Madagascar), Indian Ocean from 1882 to 1993. To isolate the main PDO frequencies, we apply a band pass filter to the time series passing only periodicities from 16 to 28 years. We investigate the covariance patterns of the coral time series with sea surface temperature (SST) and sea level pressure (SLP) of the Indian and Pacific Oceans. In addition, the empirical orthogonal functions of the filtered SST and SLP fields (single and coupled) are related to the filtered coral times series. The covariance maps show the typical PDO pattern for SST and SLP, confirming the coupling between the Indian and Pacific Oceans. Both corals show the strongest signal in boreal summer. The La Réunion (Ifaty) coral better records SST (SLP) than SLP (SST) pattern variability. We suggest that the filtered La Réunion coral δ18O represents δ18O of seawater that varies with the South Equatorial Current, which, in turn, is linked with the SST PDO. The filtered Ifaty coral δ18O represents SST and is remotely linked with the SLP PDO variability. A combined coral record of the Ifaty and La Réunion boreal summer δ18O series explains about 64% of the variance of the coupled SST/SLP PDO time series

Evolutionarily conserved bias of amino-acid usage refines the definition of PDZ-binding motif

<p>Abstract</p> <p>Background</p> <p>The interactions between PDZ (PSD-95, Dlg, ZO-1) domains and PDZ-binding motifs play central roles in signal transductions within cells. Proteins with PDZ domains bind to PDZ-binding motifs almost exclusively when the motifs are located at the carboxyl (C-) terminal ends of their binding partners. However, it remains little explored whether PDZ-binding motifs show any preferential location at the C-terminal ends of proteins, at genome-level.</p> <p>Results</p> <p>Here, we examined the distribution of the type-I (x-x-S/T-x-I/L/V) or type-II (x-x-V-x-I/V) PDZ-binding motifs in proteins encoded in the genomes of five different species (human, mouse, zebrafish, fruit fly and nematode). We first established that these PDZ-binding motifs are indeed preferentially present at their C-terminal ends. Moreover, we found specific amino acid (AA) bias for the 'x' positions in the motifs at the C-terminal ends. In general, hydrophilic AAs were favored. Our genomics-based findings confirm and largely extend the results of previous interaction-based studies, allowing us to propose refined consensus sequences for all of the examined PDZ-binding motifs. An ontological analysis revealed that the refined motifs are functionally relevant since a large fraction of the proteins bearing the motif appear to be involved in signal transduction. Furthermore, co-precipitation experiments confirmed two new protein interactions predicted by our genomics-based approach. Finally, we show that influenza virus pathogenicity can be correlated with PDZ-binding motif, with high-virulence viral proteins bearing a refined PDZ-binding motif.</p> <p>Conclusions</p> <p>Our refined definition of PDZ-binding motifs should provide important clues for identifying functional PDZ-binding motifs and proteins involved in signal transduction.</p

Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications

The Anscombe-Aumann (AA) model, originally introduced to give a normative basis to expected utility, is nowadays mostly used for another purpose: to analyze deviations from expected utility due to ambiguity (unknown probabilities). The AA model makes two ancillary assumptions that do not refer to ambiguity: expected utility for risk and backward induction. These assumptions, even if normatively appropriate, fail descriptively. This paper relaxes these ancillary assumptions to avoid the descriptive violations, while maintaining AA\xe2\x80\x99s convenient mixture operation. Thus, it becomes possible to test and apply all AA-based ambiguity theories descriptively while avoiding confounds due to violated ancillary assumptions. The resulting tests use only simple stimuli, avoiding noise due to complexity. We demonstrate the latter in a simple experiment where we find that three assumptions about ambiguity, commonly made in AA theories, are violated: reference independence, universal ambiguity aversion, and weak certainty independence. The second, theoretical, part of the paper accommodates the violations found for the first ambiguity theory in the AA model\xe2\x80\x94Schmeidler\xe2\x80\x99s CEU theory\xe2\x80\x94by introducing and axiomatizing a reference dependent generalization. That is, we extend the AA ambiguity model to prospect theory

Toward Smart Implant Synthesis: Bonding Bioceramics of Different Resorbability to Match Bone Growth Rates

This work was partially funded by the European Union (Project MARMED - 2011-1/164), the Spanish Government and FEDER (CICYT MAT2006-10481) by Xunta de Galicia (CN2012/292)