Project description:Historical precipitation records are fundamental for the management of water resources, yet rainfall observations typically span 100-150 years at most, with considerable uncertainties surrounding earlier records. Here, we analyse some of the longest available precipitation records globally, for England and Wales, Scotland and Ireland. To assess the credibility of these records and extend them further back in time, we statistically reconstruct (using independent predictors) monthly precipitation series representing these regions for the period 1748-2000. By applying the Standardized Precipitation Index at 12-month accumulations (SPI-12) to the observed and our reconstructed series we re-evaluate historical meteorological droughts. We find strong agreement between observed and reconstructed drought chronologies in post-1870 records, but divergence in earlier series due to biases in early precipitation observations. Hence, the 1800s decade was less drought prone in our reconstructions relative to observations. Overall, the drought of 1834-1836 was the most intense SPI-12 event in our reconstruction for England and Wales. Newspaper accounts and documentary sources confirm the extent of impacts across England in particular. We also identify a major, "forgotten" drought in 1765-1768 that affected the British-Irish Isles. This was the most intense event in our reconstructions for Ireland and Scotland, and ranks first for accumulated deficits across all three regional series. Moreover, the 1765-1768 event was also the most extreme multi-year drought across all regional series when considering 36-month accumulations (SPI-36). Newspaper and other sources confirm the occurrence and major socio-economic impact of this drought, such as major rivers like the Shannon being fordable by foot. Our results provide new insights into historical droughts across the British Irish Isles. Given the importance of historical droughts for stress-testing the resilience of water resources, drought plans and supply systems, the forgotten drought of 1765-1768 offers perhaps the most extreme benchmark scenario in more than 250-years.

Project description:Natural history collections and tropical tree diversity are both treasure troves of biological and evolutionary information, but their accessibility for scientific study is impeded by a number of properties. DNA in historical specimens is generally highly fragmented, complicating the recovery of high-grade genetic material. Furthermore, our understanding of hyperdiverse, wide-spread tree assemblages is obstructed by extensive species ranges, fragmented knowledge of tropical tree diversity and phenology, and a widespread lack of species-level diagnostic characters, prohibiting the collecting of readily identifiable specimens which can be used to build, revise or strengthen taxonomic frameworks. This, in turn, delays the application of downstream conservation action. A sizable component of botanical collections are sterile-thus eluding identification and are slowing down progress in systematic treatments of tropical biodiversity. With rapid advances in genomics and bioinformatic approaches to biodiversity research, museomics is emerging as a new field breathing life into natural collections that have been built up over centuries. Using MIGseq (multiplexed ISSR genotyping by sequencing), we generated 10,000s of short loci, for both freshly collected materials and museum specimens (aged >100 years) of Lithocarpus-a widespread tropical tree genus endemic to the Asian tropics. Loci recovery from historical and recently collected samples was not affected by sample age and preservation history of the study material, underscoring the reliability and flexibility of the MIGseq approach. Phylogenomic inference and biogeographic reconstruction across insular Asia, highlights repeated migration and diversification patterns between continental regions and islands. Results indicate that co-occurring insular species at the extremity of the distribution range are not monophyletic, raising the possibility of multiple independent dispersals along the outer edge of Wallacea. This suggests that dispersal of large seeded tree genera throughout Malesia and across Wallacea may have been less affected by large geographic distances and the presence of marine barriers than generally assumed. We demonstrate the utility of MIGseq in museomic studies using non-model taxa, presenting the first range-wide genomic assessment of Lithocarpus and tropical Fagaceae as a proof-of-concept. Our study shows the potential for developing innovative genomic approaches to improve the capture of novel evolutionary signals using valuable natural history collections of hyperdiverse taxa.

Project description:Frequently, vital rates are driven by directional, long-term environmental changes. Many of these are of great importance, such as land degradation, climate change, and succession. Traditional demographic methods assume a constant or stationary environment, and thus are inappropriate to analyze populations subject to these changes. They also require repeat surveys of the individuals as change unfolds. Methods for reconstructing such lengthy processes are needed. We present a model that, based on a time series of population size structures and densities, reconstructs the impact of directional environmental changes on vital rates. The model uses integral projection models and maximum likelihood to identify the rates that best reconstructs the time series. The procedure was validated with artificial and real data. The former involved simulated species with widely different demographic behaviors. The latter used a chronosequence of populations of an endangered cactus subject to increasing anthropogenic disturbance. In our simulations, the vital rates and their change were always reconstructed accurately. Nevertheless, the model frequently produced alternative results. The use of coarse knowledge of the species' biology (whether vital rates increase or decrease with size or their plausible values) allowed the correct rates to be identified with a 90% success rate. With real data, the model correctly reconstructed the effects of disturbance on vital rates. These effects were previously known from two populations for which demographic data were available. Our procedure seems robust, as the data violated several of the model's assumptions. Thus, time series of size structures and densities contain the necessary information to reconstruct changing vital rates. However, additional biological knowledge may be required to provide reliable results. Because time series of size structures and densities are available for many species or can be rapidly generated, our model can contribute to understand populations that face highly pressing environmental problems.

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Re: "Validation of a method for reconstructing historical rates of smoking prevalence".

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