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:In the USA, historical data on the period over which industrial swine farms have operated are usually only available at the county scale and released every 5 years via the USDA Census of Agriculture, leaving the history of the swine industry and its potential legacy effects on the environment poorly understood. We developed a changepoint-based workflow that recreates the construction timelines of swine farms, specifically by identifying the construction years of swine manure lagoons from historical Landsat 5 imagery for the period of 1984 to 2012. The study focused on the Coastal Plain of North Carolina, a major pork-producing state in the USA. The algorithm successfully predicted the year of swine waste lagoon construction (+ /- 1 year) with an accuracy of approximately 94% when applied to the study area. By estimating the year of construction of 3405 swine waste lagoons in NC, we increased the resolution of available information on the expansion of swine production from the county scale to spatially-explicit locations. We further analyzed how the locations of swine waste lagoons changed in proximity to water resources over time, and found a significant increase in swine waste lagoon distances to the nearest water feature across the period of record.
Project description:BackgroundRecombination rates vary at the level of the species, population and individual. Now recognized as a transient feature of the genome, recombination rates at a given locus can change markedly over time. Existing inferential methods, predominantly based on linkage disequilibrium patterns, return a long-term average estimate of past recombination rates. Such estimates can be misleading, but no analytical framework to infer recombination rates that have changed over time is currently available.ResultsWe apply coalescent modeling in conjunction with a suite of summary statistics to show that the recombination history of a locus can be reconstructed from a time series of genetic samples. More usefully, we describe a new method, based on n-tuple dataset subsampling, to infer past changes in recombination rate from DNA sequences taken at a single time point. This subsampling strategy can correctly assign simulated loci to constant, increasing and decreasing recombination models with an accuracy of 84%.ConclusionsWhile providing an important stepping-stone to determining past recombination rates, n-tuple subsampling still exhibits a moderate error rate. Theoretical limitations indicated by coalescent theory suggest that highly accurate inference of past recombination rates will remain challenging. Nevertheless, we show for the first time that reconstructing historic recombination rates is possible in principle.
Project description:The range of the Amur leopard (Panthera pardus orientalis) has decreased dramatically over the last 100 years. This species is still under extreme risk of extinction and conservation efforts are rigorous. Understanding the long-term dynamics of the population decline would be helpful to offer insight into the mechanism behind the decline and endangerment and improve conservation perspectives and strategies. Historical data collection has been the challenge for reconstructing the historical distribution. In China, new gazetteers having systematic compilation and considerable local ecological data can be considered as an important complementary for reconstruction. Therefore, we have set up a data set (mainly based on the new gazetteers) in order to identify the historical range of the Amur Leopard from the 1950s to 2014. The result shows that the Amur leopard was historically widely distributed with large populations in Northeastern China, but it presented a sharp decline after the 1970s. The decline appeared from the plains to the mountains and northeast to southwest since the 1950s. Long-term historical data, mainly from new gazetteers, demonstrates that such resources are capable of tracking species change through time and offers an opportunity to reduce data shortage and enhance understanding in conservation.
Project description:Herbarium accession data offer a useful historical botanical perspective and have been used to track the spread of plant invasions through time and space. Nevertheless, few studies have utilised this resource for genetic analysis to reconstruct a more complete picture of historical invasion dynamics, including the occurrence of separate introduction events. In this study, we combined nuclear and chloroplast microsatellite analyses of contemporary and historical collections of Senecio madagascariensis, a globally invasive weed first introduced to Australia c. 1918 from its native South Africa. Analysis of nuclear microsatellites, together with temporal spread data and simulations of herbarium voucher sampling, revealed distinct introductions to south-eastern Australia and mid-eastern Australia. Genetic diversity of the south-eastern invasive population was lower than in the native range, but higher than in the mid-eastern invasion. In the invasive range, despite its low resolution, our chloroplast microsatellite data revealed the occurrence of new haplotypes over time, probably as the result of subsequent introduction(s) to Australia from the native range during the latter half of the 20th century. Our work demonstrates how molecular studies of contemporary and historical field collections can be combined to reconstruct a more complete picture of the invasion history of introduced taxa. Further, our study indicates that a survey of contemporary samples only (as undertaken for the majority of invasive species studies) would be insufficient to identify potential source populations and occurrence of multiple introductions.
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:Chrysotile-containing joint compound was commonly used in construction of residential and commercial buildings through the mid 1970s; however, these products have not been manufactured in the United States for more than 30 years. Little is known about actual human exposures to chrysotile fibers that may have resulted from use of chrysotile-containing joint compounds, because few exposure and no health-effects studies have been conducted specifically with these products. Because limited amounts of historical joint compounds are available (and the stability or representativeness of aged products is suspect), it is currently impossible to conduct meaningful studies to better understand the nature and magnitude of potential exposures to chrysotile that may have been associated with historical use of these products. Therefore, to support specific exposure and toxicology research activities, two types of chrysotile-containing joint compounds were produced according to original formulations from the late 1960s. To the extent possible, ingredients were the same as those used originally, with many obtained from the original suppliers. The chrysotile used historically in these products was primarily Grade 7RF9 from the Philip Carey mine. Because this mine is closed, a suitable alternate was identified by comparing the sizes and mineral composition of asbestos structures in a sample of what has been represented to be historical joint compound (all of which were chrysotile) to those in samples of three currently commercially available Grade 7 chrysotile products. The re-created materials generally conformed to original product specifications (e.g. viscosity, workability, crack resistance), indicating that these materials are sufficiently representative of the original products to support research activities.
Project description:Characterization of shale cores with low and anisotropic permeability is complicated, due to the presence of multiscale pore structure and thin layers, and defies conventional methods. To accurately reproduce the morphology of multiscale pore structure of the shale core, a novel core-scale reconstructing method is proposed to reconstruct 3D digital-experimental models by means of the combination of SEM, EDS images, nitrogen adsorption and pressure pulse decay experiment result. In this method, the multiscale and multicomponent reconstructing algorithm is introduced to build the representative multiscale model for each layer, which can describe the complex 3D structures of nano organic pores, micro-nano inorganic pores, micro slits and several typical minerals. Especially, to reproduce the realistic morphology for shale, the optimization algorithm based on simulated annealing algorithm uses the experimental data as constrain conditions to adjust and optimize the model for each layer. To describe the bedding characteristics of the shale core, bedding fractures are constructed by analysis of the mineral distribution in the interface of two layers, and then the representative models for different layers are integrated together to obtain the final core-scale digital-experimental model. Finally, the model is validated by computing its morphological and flow properties and comparing them with those of the actual 3D shale sample. This method provide a way for systematically and continuously describe the multiscale and anisotropic pore structure (from nm-cm) of the shale core, and will be helpful for understanding the quality of the shale reservoir.
Project description:BackgroundThe lack of classification by educational attainment in death and population exposure data at older ages is an important constraint for studying changes and patterns of mortality disparities by education in Denmark and Sweden. The missing educational distribution of population also restricts analyses aiming at estimating contributions of compositional change to the improvements in national longevity. This study proposes a transparent approach to solve the two methodological issues allowing to obtain robust education-specific mortality estimates and population weights.MethodsUsing nonparametric approach, we redistribute the unknown cases and extrapolate the mortality curves of these sub-populations with the help of population-level data on an aggregate level from the Human Mortality Database.ResultsWe present reconstructed and harmonized education-specific abridged and complete life tables for Sweden and Denmark covering 5-year-long periods from 1991-1995 to 2011-2015. The newly estimated life tables are in good agreement with the national life tables and show plausible age- and education-specific patterns. The observed changes in life expectancy by education suggest about the widening longevity gap between the highest and lowest educated for males and females in both countries.ConclusionsThe proposed simple and transparent method can be applied in similar country-specific cases showing large proportions of missing education or other socio-economic characteristics at older ages.
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.