Discrimination of Ephedra plants with diffuse reflectance FT-NIRS and multivariate analysis

The secondary metabolites of different Ephedra plants are various. Therefore, the discrimination of different Ephedra plants is significant. An objective, easy-to-use, rapid and pollution-free approach is proposed for discriminating Ephedra plants of different species, habitats and picking times on the basis of diffuse reflectance Fourier transform near infrared spectroscopy (FT-NIRS) measurements and multivariate analysis. The Fourier transform near infrared diffuse reflectance spectra (NIRDRS) were acquired from 37 pulverized samples of Ephedra plants put in glass vials in the near infrared (NIR) region between 10 000 and 4000 cm⁻¹, averaging 64 scans per spectrum at a resolution of 4 cm⁻¹. After spectra processing and data pre-processing, spectral data were analyzed respectively with three multivariate analysis techniques: discriminant analysis (DA), self-organizing map (SOM) and back-propagation artificial neural network (BP-ANN). The proposed method could distinguish not only the Ephedra plants of three species and two habitats but also the plants picked at different times of day without special sample treatment and the use of chemical reagents. The performance indexes of the DA model were 84.2-91.9% and the prediction accuracies of both the SOM and the BP-ANN models reached 93.3-100.0%.     

Multi-objective analysis of dam release flows in rivers downstream from hydropower reservoirs

This paper assesses dam releases from hydropower reservoirs in order to optimize power production and fish habitat protection. A multi-objective programming model includes output from 2-D hydraulic simulation for habitat assessment to optimize power production and fish habitat suitability as a Pareto set. To identify the optimal Pareto set two different approaches are used and compared: ε-constraint methods and non-dominant-sorting genetic algorithm (NSGA II). To formulate the ecological objective the river habitat quality is quantified by the weighted usable area (WUA). The relation between the WUA and the river flow-rate is obtained by using a 2D hydraulic model in which the hydraulic characteristics of river current – depth and velocity – are calculated by a finite difference numerical integration of two-dimensional shallow water equations on a boundary fitted non orthogonal curvilinear mesh. This approach allows the integration of motion equations on geometrically complex domains as those representing the morphology of natural watercourses. The performance of the proposed methodology is analyzed in a case study of a stretch of the Piave river downstream of the dam of the Pieve di Cadore reservoir (Belluno, Italy).     

Effect of habitat destruction on cooperation in public goods games

We explore the evolution of cooperation in a public goods game where the habitat destruction is taken into account. A model of ordinary differential equations is proposed, in which incorporate the habitat destroyed. And we focus on the impact of different levels of habitat destruction on cooperation. Our results show that the fraction of cooperation receives the biggest boost for moderate habitat destruction, and decreases to zero very quickly for a higher degree of habitat destruction. Similarly, our results suggest that low or moderate habitat degradation can promote the evolution of cooperators, and once habitat degradation is too severe, the fraction of cooperators will decline dramatically. Furthermore, we investigate the cooperation level with different multiplication factor, and results demonstrate that the cooperation increases monotonously with the increasing of the multiplication factor. Our findings may provide many more insights for understanding the emergence and maintenance of cooperation in the complex biological and social systems.     

The diffusive Lotka–Volterra competition model in fragmented patches I: Coexistence

It is an ecological imperative that we understand how changes in landscape heterogeneity affect population dynamics and coexistence among species residing in increasingly fragmented landscapes. Decades of research have shown the dispersal process to have major implications for individual fitness, species’ distributions, interactions with other species, population dynamics, and stability. Although theoretical models have played a crucial role in predicting population level effects of dispersal, these models have largely ignored the conditional dependency of dispersal (e.g., responses to patch boundaries, matrix hostility, competitors, and predators). This work is the first in a series where we explore dynamics of the diffusive Lotka–Volterra (L–V) competition model in such a fragmented landscape. This model has been extensively studied in isolated patches, and to a lesser extent, in patches surrounded by an immediately hostile matrix. However, little attention has been focused on studying the model in a more realistic setting considering organismal behavior at the patch/matrix interface. Here, we provide a mechanistic connection between the model and its biological underpinnings and study its dynamics via exploration of nonexistence, existence, and uniqueness of the model’s steady states. We employ several tools from nonlinear analysis, including sub-supersolutions, certain eigenvalue problems, and a numerical shooting method. In the case of weak, neutral, and strong competition, our results mostly match those of the isolated patch or immediately hostile matrix cases. However, in the case where competition is weak towards one species and strong towards the other, we find existence of a maximum patch size, and thus an intermediate range of patch sizes where coexistence is possible, in a patch surrounded by an intermediate hostile matrix when the weaker competitor has a dispersal advantage. These results support what ecologists have long theorized, i.e., a key mechanism promoting coexistence among competing species is a tradeoff between dispersal and competitive ability.     

On the stability and Hopf bifurcation of a delay-induced predator–prey system with habitat complexity

We study the effect of the degree of habitat complexity and gestation delay on the stability of a predator–prey model. It is observed that there is stability switches, and Hopf bifurcation occurs when the delay crosses some critical value. By applying the normal form theory and the center manifold theorem, the explicit formulae which determine the stability and direction of the bifurcating periodic solutions are determined. The qualitative dynamical behavior of the model system is verified with the published data of Paramecium aurelia (prey) and Didinium nasutum (predator) interaction. It is observed that the quantitative level of abundance of system populations depends crucially on the delay parameter if the gestation period exceeds some critical value. However, the fluctuations in the population levels can be controlled completely by increasing the degree of habitat complexity.     

Habitat fragmentation effects on biodiversity patterns

We study the effects of habitat fragmentation on biodiversity patterns by means of a simple spatial model which considers selective geographic colonization, diffusion and mutation. In our model, regions of the lattice are characterized by the amount of resources available to populations of species which are going to colonize that regions. We simulate the fragmentation of the habitat by assuming that a proportion p of the sites is not available for colonization, that is, there is no resource availability in those sites. We analyse the patterns of the species-area relationship and the abundance distribution considering two sample methods, in order to simulate the cases in which the habitats are distributed in islands and continents. We have observed that the pattern of the species-area curve is changed when different sample methods are considered. We have also verified that the abundance distribution is bimodal when small mutation probabilities are considered.     

Conditional Logistic Regression With Longitudinal Follow-up and Individual-Level Random Coefficients: A Stable and Efficient Two-Step Estimation Method

The analysis of data generated by animal habitat selection studies, by family studies of genetic diseases, or by longitudinal follow-up of households often involves fitting a mixed conditional logistic regression model to longitudinal data composed of clusters of matched case-control strata. The estimation of model parameters by maximum likelihood is especially difficult when the number of cases per stratum is greater than one. In this case, the denominator of each cluster contribution to the conditional likelihood involves a complex integral in high dimension, which leads to convergence problems in the numerical maximization. In this article we show how these computational complexities can be bypassed using a global two-step analysis for nonlinear mixed effects models. The first step estimates the cluster-specific parameters and can be achieved with standard statistical methods and software based on maximum likelihood for independent data. The second step uses the EM-algorithm in conjunction with conditional restricted maximum likelihood to estimate the population parameters. We use simulations to demonstrate that the method works well when the analysis is based on a large number of strata per cluster, as in many ecological studies. We apply the proposed two-step approach to evaluate habitat selection by pairs of bison roaming freely in their natural environment. This article has supplementary material online.     

Rapid qualitative and quantitative evaluation of deer antler (Cervus elaphus) using near-infrared reflectance spectroscopy

Near-infrared (NIR) spectroscopy has been applied for both the qualitative and quantitative evaluation of the velvet deer antler. The most important parameters of determining the quality of velvet antler are the habitat (the country of origin) and ash content. Conventionally, the habitat is determined by examining the appearance of samples (by human eye), which lacks objectivity. Ash content is measured by an ignition method (measurement ash residue), however, it is too slow (4–5 h) to be used for rapid at-site measurement. Velvet antlers from three different habitats (China, New Zealand, and Russia), albeit the same species of Cervus elaphus, were evaluated in this paper. Soft independence modeling of class analogies (SIMCA) and partial least squares (PLS) were used for classification of habitat and determination of ash content. The habitat was successfully identified with over 80% accuracy, and the ash content prediction result using PLS regression showed good correlation with the reference ignition method with a standard error of prediction (SEP) of 1.264%.