Temperature-dependent phenology of Plutella xylostella (Lepidoptera: Plutellidae)

Temperature-dependent population growth of diamondback moth (DBM) Plutella xylostella (L.), a prolific insect pest of crucifer vegetables, was studied under six constant temperatures in the laboratory. The objective of the study was to predict the impacts of temperature changes on the population of DBM at high-resolution scales along altitudinal gradients and under climate change scenarios. Non-linear functions were fitted on the data for modeling the development, mortality, longevity and oviposition of the pest. The best-fitted functions for each life stage were compiled for estimating the life table parameters of the species by stochastic simulations. To quantify the impacts on the pest, three indices (establishment, generation and activity) were computed using the estimates of life table parameters and temperature data obtained at local scale (current scenario 2013) and downscaled climate change data (future scenario 2055) from the AFRICLIM database. To measure and represent the impacts of temperature change along the altitude on the pest; the indices were mapped along the altitudinal gradients of Kilimanjaro and Taita Hills, in Tanzania and Kenya, respectively. Potential impact of the changes between climate scenarios 2013 and 2055 was assessed. The data files included in this database were utilized for the above analysis to develop temperature dependent phenology of Plutella xylostella to assess current and future distribution along eastern African Afromontanes.

Classification of coral reef types in Torres Strait (GIS files in zip-archive 319 kB)

Coral reefs represent major accumulations of calcium carbonate (CaCO3). The particularly labyrinthine network of reefs in Torres Strait, north of the Great Barrier Reef (GBR), has been examined in order to estimate their gross CaCO3 productivity. The approach involved a two-step procedure, first characterising and classifying the morphology of reefs based on a classification scheme widely employed on the GBR and then estimating gross CaCO3 productivity rates across the region using a regional census-based approach. This was undertaken by independently verifying published rates of coral reef community gross production for use in Torres Strait, based on site-specific ecological and morphological data. A total of 606 reef platforms were mapped and classified using classification trees. Despite the complexity of the maze of reefs in Torres Strait, there are broad morphological similarities with reefs in the GBR. The spatial distribution and dimensions of reef types across both regions are underpinned by similar geological processes, sea-level history in the Holocene and exposure to the same wind/wave energetic regime, resulting in comparable geomorphic zonation. However, the presence of strong tidal currents flowing through Torres Strait and the relatively shallow and narrow dimensions of the shelf exert a control on local morphology and spatial distribution of the reef platforms. A total amount of 8.7 million tonnes of CaCO3 per year, at an average rate of 3.7 kg CaCO3 m-2 yr-1 (G), were estimated for the studied area. Extrapolated production rates based on detailed and regional census-based approaches for geomorphic zones across Torres Strait were comparable to those reported elsewhere, particularly values for the GBR based on alkalinity-reduction methods. However, differences in mapping methodologies and the impact of reduced calcification due to global trends in coral reef ecological decline and changing oceanic physical conditions warrant further research. The novel method proposed in this study to characterise the geomorphology of reef types based on classification trees provides an objective and repeatable data-driven approach that combined with regional census-based approaches has the potential to be adapted and transferred to different coral reef regions, depicting a more accurate picture of interactions between reef ecology and geomorphology.

Probabilistic models for the prediction of a ship performance in dynamic ice

We introduce two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is probable to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models to datasets were utilized. First, the data from the Automatic Identification System about the performance of a selected ship was used. Second, a numerical ice model HELMI, developed in the Finnish Meteorological Institute, provided information about the ice field. The relations between the ice conditions and ship movements were established using Bayesian learning algorithms. The case study presented in this paper considers a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. We expect this new approach to facilitate the safe and effective route selection problem for ice-covered waters where the ship performance is reflected in the objective function.

Chemical and Sr isotopic compositions of pore fluids and marine carbonates from ODP Hole 130-807A

The 87Sr/86Sr ratios and Sr concentrations in sediment and pore fluids are used to evaluate the rates of calcite recrystallization at ODP Site 807A on the Ontong Java Plateau, an 800-meter thick section of carbonate ooze and chalk. A numerical model is used to evaluate the pore fluid chemistry and Sr isotopes in an accumulating section. The deduced calcite recrystallization rate is 2% per million years (%/Myr) near the top of the section and decreases systematically in older parts of the section such that the rate is close to 0.1/age (in years). The deduced recrystallization rates have important implications for the interpretation of Ca and Mg concentration profiles in the pore fluids. The effect of calcite recrystallization on pore fluid chemistry is described by the reaction length, L, which varies by element, and depends on the concentration in pore fluid and solid. When L is small compared to the thickness of the sedimentary section, the pore fluid concentration is controlled by equilibrium or steady-state exchange with the solid phase, except within a distance L of the sediment-water interface. When L is large relative to the thickness of sediment, the pore fluid concentration is mostly controlled by the boundary conditions and diffusion. The values of L for Ca, Sr, and Mg are of order 15, 150, and 1500 meters, respectively. L_Sr is derived from isotopic data and modeling, and allows us to infer the values of L_Ca and L_Mg. The small value for L_Ca indicates that pore fluid Ca concentrations, which gradually increase down section, must be equilibrium values that are maintained by solution-precipitation exchange with calcite and do not reflect Ca sources within or below the sediment column. The pore fluid Ca measurements and measured alkalinity allow us to calculate the in situ pH in the pore fluids, which decreases from 7.6 near the sediment-water interface to 7.1+/-0.1 at 400-800 mbsf. While the calculated pH values are in agreement with some of the values measured during ODP Leg 130, most of the measurements are artifacts. The large value for L_Mg indicates that the pore fluid Mg concentrations at 807A are not controlled by calcite-fluid equilibrium but instead are determined by the changing Mg concentration of seawater during deposition, modified by aqueous diffusion in the pore fluids. We use the pore fluid Mg concentration profile at Site 807A to retrieve a global record for seawater Mg over the past 35 Myr, which shows that seawater Mg has increased rapidly over the past 10 Myr, rather than gradually over the past 60 Myr. This observation suggests that the Cenozoic rise in seawater Mg is controlled by continental weathering inputs rather than by exchange with oceanic crust. The relationship determined between reaction rate and age in silicates and carbonates is strikingly similar, which suggests that reaction affinity is not the primary determinant of silicate dissolution rates in nature.

30 years of synoptic observations from Neumayer Station with links to datasets

The analysis of research data plays a key role in data-driven areas of science. Varieties of mixed research data sets exist and scientists aim to derive or validate hypotheses to find undiscovered knowledge. Many analysis techniques identify relations of an entire dataset only. This may level the characteristic behavior of different subgroups in the data. Like automatic subspace clustering, we aim at identifying interesting subgroups and attribute sets. We present a visual-interactive system that supports scientists to explore interesting relations between aggregated bins of multivariate attributes in mixed data sets. The abstraction of data to bins enables the application of statistical dependency tests as the measure of interestingness. An overview matrix view shows all attributes, ranked with respect to the interestingness of bins. Complementary, a node-link view reveals multivariate bin relations by positioning dependent bins close to each other. The system supports information drill-down based on both expert knowledge and algorithmic support. Finally, visual-interactive subset clustering assigns multivariate bin relations to groups. A list-based cluster result representation enables the scientist to communicate multivariate findings at a glance. We demonstrate the applicability of the system with two case studies from the earth observation domain and the prostate cancer research domain. In both cases, the system enabled us to identify the most interesting multivariate bin relations, to validate already published results, and, moreover, to discover unexpected relations.

Population genetic and dispersal modeling data for Bathymodiolus mussels from the Mid-Atlantic Ridge

The zip folder comprises a text file and a gzipped tar archive. 1) The text file contains individual genotype data for 90 SNPs, 9 microsatellites and the mitochondrial ND4 gene that were determined in deep-sea hydrothermal vent mussels from the Mid-Atlantic Ridge (genus Bathymodiolus). Mussel specimens are grouped according to the population (pop)/location from which they have been sampled (first column). The remaining columns contain the respective allele/haplotype codes for the different genetic loci (names in the header line). The data file is in CONVERT format and can be directly transformed into different input files for population genetic statistics. 2) The tar archive contains NetCDF files with larval dispersal probabilities for simulated annual larval releases between 1998 and 2007. For each simulated vent location (Menez Gwen, Lucky Strike, Rainbow, Vent 1-10) two NetCDF files are given, one for an assumed pelagic larval duration of 1 year and the other one for an assumed pelagic larval duration of 6 months (6m).