Multi-scale Modeling of Animal Movement and General Behavior Data Using Hidden Markov Models with Hierarchical Structures

Hidden Markov models (HMMs) are commonly used to model animal movement data and infer aspects of animal behavior. An HMM assumes that each data point from a time series of observations stems from one of N possible states. The states are loosely connected to behavioral modes that manifest themselves at the temporal resolution at which observations are made. Due to advances in tag technology and tracking with digital video recordings, data can be collected at increasingly fine temporal resolutions. Yet, inferences at time scales cruder than those at which data are collected and, which correspond to larger-scale behavioral processes, are not yet answered via HMMs. We include additional hierarchical structures to the basic HMM framework, incorporating multiple Markov chains at various time scales. The hierarchically structured HMMs allow for behavioral inferences at multiple time scales and can also serve as a means to avoid coarsening data. Our proposed framework is one of the first that models animal behavior simultaneously at multiple time scales, opening new possibilities in the area of animal movement and behavior modeling. We illustrate the application of hierarchically structured HMMs in two real-data examples: (i) vertical movements of harbor porpoises observed in the field, and (ii) garter snake movement data collected as part of an experimental design. Supplementary materials accompanying this paper appear online.     

Elevated levels of fragmented laminin-5 gamma2-chain in bronchoalveolar lavage fluid from dogs with pulmonary eosinophilia

Inflammation causes epithelial cell sloughing and basement membrane (BM) exposure in canine pulmonary eosinophilia (PE), leading to degradation of the epithelial cell attachment component, laminin-5 gamma2-chain, into small molecular weight fragments. The subsidence of inflammation after treatment down-regulates degradation. Laminin-5 gamma2-chain levels and molecular forms in bronchoalveolar lavage fluid (BALF) were analysed semiquantitatively by Western immunoblotting to compare PE affected (n=20) and healthy dogs (n=16) as well as PE dogs (n=6) before and after corticosteroid treatment. PE dogs expressed significantly elevated levels of total (P<0.01), 36 kDa (P<0.05) and 53 kDa (P<0.05) laminin-5 gamma2-fragments. The 36 Da fragment decreased significantly (P<0.05) after treatment. The laminin-5 gamma2-chain degradation products may be linked to epithelial cell sloughing and BM exposure or healing.     

Integrating Fire Risk Considerations in Forest Management Planning in Spain – A Landscape Level Perspective

It is reasonable to assume that there is a relationship between the spatial distribution of forest fuels and fire hazards. Therefore, if fire risk is to be included into numerical forest planning, the spatial distribution of risky and non-risky forest stands should be taken into account. The present study combines a stand-level fire risk model and landscape level optimization to solve forest planning problems in which the fire risk plays an important role. The key point of the method was to calculate forest level fire resistance metrics from stand level indices and use these metrics as objective variables in numerical optimization. This study shows that maximizing different landscape metrics produces very different landscape configurations with respect to the spatial arrangement of resistant and risky stands. The landscapes obtained by maximizing different metrics were tested with a fire spread simulator. These tests suggested that the mean fire resistance of the landscape, which is a non-spatial metric, is the most important factor affecting the burned area. However, spatial landscape metrics that decrease the continuity of fire resistance in the landscape can significantly improve the fire resistance of the landscape when used as additional objective variables.     

Substrate-Dependent Bioavailability of Deltamethrin for the Epigeal Spider Oedothorax apicatus (Blackwall) (Aranaea,Erigonidae)

Terrestrial arthropods are mainly exposed to pesticides by uptake from the substrate e.g. “residual” uptake, which depends on the bioavailability of the pesticide. The residual uptake of deltamethrin by female Oedothorax apicatus (Blackwall), a linyphiid spider, was studied in relation to dependence on soil cover, soil moisture, walking behaviour, time after spraying and deposition rate. C¹⁴-labelled deltamethrin was used to quantify the uptake processes. Data were analysed using multiple regression analysis. Uptake was markedly higher from soil covered with fungi or moss than from uncovered soil. From uncovered soils with moisture contents varying from 7 to 49% dry weight, low uptake was measured, while at 63% moisture, the uptake was high. The bioavailability half-life was 157 min. The rate of uptake decreased with distance walked. The possible consequences of these results for field experiments are discussed.     

Applied 3D texture features in ALS-based forest inventory

Airborne laser scanning (ALS) data are not usually considered to be very informative with respect to tree species, and this information is often obtained by combining such data with spectral image material. The aim was to test the ability of height, density, intensity and applied 2D and 3D texture variables derived solely from a very high-density ALS point cloud to describe the crown shape and structure characteristics required for tree species discrimination. Linear discriminant analysis was used to find optimal combinations of variables within the predictor groups, and classifications based on variables from different groups were compared. The third power of the tree diameter was used as a stem volume approximate, and rather than examining species alone, the classification was evaluated with respect to the volume approximates assigned to the predicted species. The sensitivity of pulse density to the methodology presented here was determined by simulating thinned data sets by reducing the initial pulse density. The reliability of the estimates was analysed both with functions generated using the original data and with new functions for each thinning level. Alpha shape metrics developed for describing tree crowns constructed from the 3D point clouds proved capable of discriminating between all three species groups evaluated, and several height distribution and textural variables were found to discriminate between the coniferous tree species. The results demonstrate the importance of species interpretation in forest inventories based on allometric modelling, but then indicate that species-specific estimation could be carried out using ALS-derived variables alone.     

Genomic prediction of grain yield in commercial Finnish oat (Avena sativa) and barley (Hordeum vulgare) breeding programmes

Genomic selection has been adopted in many plant breeding programmes. In this paper, we cover some aspects of information necessary before starting genomic selection. Spring oat and barley breeding data sets from commercial breeding programmes were studied using single, multitrait and trait-assisted models for predicting grain yield. Heritabilities were higher when estimated using multitrait models compared to single-trait models. However, no corresponding increase in prediction accuracy was observed in a cross-validation scenario. On the other hand, forward prediction showed a slight, but not significant, increase in accuracy of genomic estimated breeding values for breeding cohorts when a multitrait model was applied. When a correlated trait was used in a trait-assisted model, on average the accuracies increased by 9%–14% for oat and by 11%–28% for barley compared with a single-trait model. Overall, accuracies in forward validation varied between breeding cohorts and years for grain yield. Forward prediction accuracies for multiple cohorts and multiple years’ data are reported for oat for the first time.     

Effects of perennial fodder crops on soil structure in agricultural headlands

In agricultural headlands, rooting and yield of crops may be limited because of soil‐structure changes as a consequence of multiple passes of turning machinery. We hypothesized that perennial forage crops can substantially alter soil structure in agricultural headlands. On one experimental field and two commercial farms on Haplic Luvisols from respectively loess and sandy loess in the Lower Rhine Bay (Germany), we investigated how 4 y of continuously grown grass/clover or alfalfa affected soil structure and the performance of subsequent spring wheat. Compared with a crop rotation with annual plowing to 30 cm soil depth, perennial forage crops led to increased soil C content (+1.3% to +22.8%) and N content (+4.2% to +15.1%), higher densities of medium and coarse biopores at a depth of 35 cm, more large water‐stable soil macroaggregates, higher biomass and abundance of anecic earthworms, and higher grain yield and grain protein content of spring wheat grown as the following crop. Root‐length density of spring wheat in the subsoil was not affected by the preceding perennial fodder crops in two of the three field trials. We concluded that besides increasing N input to the soil, perennial cropping of grass/clover or alfalfa has effects on soil structure that may substantially reduce yield losses in agricultural headlands.     

Abundance of ammonia oxidizing microbes and denitrifiers in different soil horizons of an agricultural soil in relation to the cultivated crops

The role of subsoils and their microbial communities for the nutrient supply for plants is to a large extent unknown, especially in comparison to well investigated topsoil layers. Therefore, in this study, the influence of three different plant species with different rooting systems and different N uptake strategies on ammonium and nitrate levels and microbial communities involved in ammonia oxidation and denitrification was investigated in different soil horizons. Overall, our results show a higher genetic potential for both processes in topsoils than in subsoils independent of the present plant. Although we found accumulation of N in top and subsoils in plots with legumes, we could not observe an impact of the higher nitrate content on the genetic potential of denitrification and ammonia oxidation. However, differences in the ratios of ammonia oxidizing archaea to bacteria and also between denitrifying bacteria harboring genes for copper- (nirK) or cytochrome- (nirS) dependent nitrite reductase in top and subsoil samples reveal different ecophysiologies of microbes involved in N turnover in top and subsoil habitats.     

Barley roots are not constrained to large-sized biopores in the subsoil of a deep Haplic Luvisol

Using the profile wall method, we determined the root-length density (RLD) of barley roots growing in large-sized biopores (diameter >2 mm) and in the bulk soil of a Haplic Luvisol down to 200 cm of soil depth. The maximum bulk density in the soil profile (1.52 g?cm^?3) was recorded in the Bt horizon (41–115 cm of soil depth). The proportion of RLD in biopores over the total RLD increased with increasing soil depth down to the 45–75 or 75–105 cm of soil layer but then decreased again in deeper soil. In contrast to earlier investigations, the maximum percentage of RLD in biopores recorded in this study was only 25 %. Root sampling from individually dissected biopores confirmed that roots did not predominantly grow in biopores. Results suggest that roots can use biopores as preferred pathways for growth through rather compact soil layers, whereas they can possibly leave the biopore and re-enter the bulk soil in deeper, less compact layers.     

Empirical and optimal stomatal controls on leaf and ecosystem level CO2 and H2O exchange rates

Linkage between the leaf-level stomatal conductance (g_s) response to environmental stimuli and canopy-level mass exchange processes remains an important research problem to be confronted. How various formulations of g_s influence canopy-scale mean scalar concentration and flux profiles of CO₂ and H₂O within the canopy and how to derive ‘effective’ properties of a ‘big-leaf’ that represents the eco-system mass exchange rates starting from leaf-level parameters were explored. Four widely used formulations for leaf-level g_s were combined with a leaf-level photosynthetic demand function, a layer-resolving light attenuation model, and a turbulent closure scheme for scalar fluxes within the canopy air space. The four g_s models were the widely used semi-empirical Ball-Berry approach, and its modification, and two solutions to the stomatal optimization theory for autonomous leaves. One of the two solutions to the optimization theory is based on a linearized CO₂-demand function while the other does not invoke such simplification. The four stomatal control models were then parameterized against the same shoot-scale gas exchange data collected in a Scots pine forest located at the SMEAR II-station in Hyytiälä, Southern Finland. The predicted CO₂ (F_c) and H₂O fluxes (F_e) and mean concentration profiles were compared against multi-level eddy-covariance measurements and mean scalar concentration data within and above the canopy. It was shown that F_c comparisons agreed to within 10% and F_e comparisons to within 25%. The optimality approach derived from a linearized photosynthetic demand function predicted the largest CO₂ uptake and transpiration rates when compared to eddy-covariance measurements and the other three models. Moreover, within each g_s model, the CO₂ fluxes were insensitive to g_s model parameter variability whereas the transpiration rate estimates were notably more affected. Vertical integration of the layer-averaged results as derived from each g_s model was carried out. The sensitivities of the up-scaled bulk canopy conductances were compared against the eddy-covariance derived canopy conductance counterpart. It was shown that canopy level g_s appear more sensitive to vapor-pressure deficit than shoot-level g_s.