Evolution of spit morphology: a case study using a remote sensing and statistical based approach

The dynamics and factors responsible for morphological changes of spits viz., Uliyargoli-Padukere, Oddu Bengre and Kodi Bengre, southern Karnataka, India, are investigated using multi-dated satellite images and topographic maps during the last 95-years (1910–2005). Variations and overall rate of changes in length, area and coefficient of determination (R²) of each spit are calculated separately for two periods (1910 and 1967 as base years) to find out whether there is any significant trend in the case of change in length and area in all the three spits that are under study. Linear trend lines are fitted using a least squares method and the statistical significance is considered at 80 % level of confidence. The results recorded significant changes in spit morphology, especially in length and area if 1910 and 1967 are considered separately as base years, are may be due to non-availability of data set between 1910 and 1967 period. The study reveals that coastal processes, such as SW-monsoon influenced strong currents and longshore drifts are the main process for formation and growth of spits, whereas rivers influence/drift also plays significant role. The statistical uncertainty estimation in spits morphology is prevalent wherever the coast is affected by human interventions. The study demonstrates that combined use of satellite imagery and statistical techniques can be effectively used to understand the evolution of spits morphology.     

Modelling dependence structures of extreme wind speed using bivariate distribution: a Bayesian approach

When investigating extremes of weather variables, it is seldom that a single weather station determines the damage, and extremes may be caused from the combined behaviour of several weather stations. To investigate joint dependence of extreme wind speed, a bivariate generalised extreme value distribution (BGEVD) was considered from frequentist and Bayesian approaches to analyse the extremes of component-wise monthly maximum wind speed at selected weather stations in South Africa. In the frequentist approach, the parameters of extreme value distributions (EVDs) were estimated with maximum likelihood, whereas in the Bayesian approach the Markov Chain Monte Carlo (MCMC) technique was used with the Metropolis–Hastings algorithm. The results showed that when fitted to component-wise maxima of extreme weather variables, the BGEVD provided apparent benefits over the univariate method, which allowed information to be pooled across stations and resulted in improved precision of the estimates for the parameters and return levels of the distributions. The paper also discusses a method to construct informative priors empirically using historical data of the underlying process from weather characteristics of four pairs of surrounding weather stations at various distances. The results from the Bayesian analysis showed that posterior inference might be affected by the choice of priors that were used to formulate the informative priors. From the results, it could be inferred that the Bayesian approach provides a satisfactory estimation strategy in terms of precision, compared with the frequentist approach, because it accounts for uncertainty in parameters and return level estimations.     

Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach

Macroalgae are a major benthic component of coral reefs and their dynamics influence the resilience of coral reefs to disturbance. However, the relative importance of physical and ecological processes in driving macroalgal dynamics is poorly understood. Here we develop a Bayesian belief network (BBN) model to integrate many of these processes and predict the growth of coral reef macroalgae. Bayesian belief networks use probabilistic relationships rather than deterministic rules to quantify the cause and effect assumptions. The model was developed using both new empirical data and quantified relationships elicited from previous studies. We demonstrate the efficacy of the BBN to predict the dynamics of a common Caribbean macroalgal genus Dictyota. Predictions of the model have an average accuracy of 55% (implying that 55% of the predicted categories of Dictyota cover were assigned to the correct class). Sensitivity analysis suggested that macroalgal dynamics were primarily driven by top–down processes of grazing rather than bottom–up nutrification. BBNs provide a useful framework for modelling complex systems, identifying gaps in our scientific understanding and communicating the complexities of the associated uncertainties in an explicit manner to stakeholders. We anticipate that accuracies will improve as new data are added to the model.     

Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia

The quality of climate models has largely been overlooked as a possible source of uncertainty that may affect the outcomes of species distribution models, especially in the tropics, where comparatively few climatic stations are available. We compared the geographical discrepancies and potential conservation implications of using two different climate models (Saga and Worldclim) in combination with the species modelling approach Maxent in Bolivia. We estimated ranges of selected bird and fern species biogeographically restricted to either humid montane forest of the northern Bolivian Andes or seasonal dry tropical forests (in the Andes and southern lowlands). Saga and Worldclim predicted roughly similar climate patterns of temperature that were significantly correlated. Precipitation layers of both climate models were also roughly similar, but showed important differences. Species ranges estimated with Worldclim and Saga likewise produced different results. Ranges of species endemic to humid montane forests estimated with Saga had higher AUC (Area under the curve) values than those estimated with Worldclim, which for example predicted the occurrence of humid montane forest bird species near Lake Titicaca, an area that is clearly unsuitable for these species. Likewise, Worldclim overpredicted the occurrence of fern and bird species in the lowlands of the Chapare region and well south of the Andean Elbow, where more seasonal biomes occur. By contrast, Saga predictions were coherent with the known distribution of humid montane forests in the northern Bolivian Andes. Estimated ranges of species endemic to seasonal dry tropical forests predicted with Saga and Worldclim were not statistically different in most cases. However, detailed comparisons revealed that Saga was able to distinguish fragments of seasonal dry tropical forests in rain-shadow valleys of the northern Bolivian Andes, whereas Worldclim was not. These differences highlight the neglected influence of climate layers on modelling results and the importance of using the most accurate climate data available when modelling species distributions.     

Bayesian hierarchical spatio-temporal modelling of trends and future projections in the ocean wave climate with a \text{ CO }_2 regression component

Bad weather and rough seas continue to be a major cause for ship losses and is thus a significant contributor to the risk to maritime transportation. This stresses the importance of taking severe sea state conditions adequately into account, with due treatment of the uncertainties involved, in ship design and operation in order to enhance safety. Hence, there is a need for appropriate stochastic models describing the variability of sea states. These should also incorporate realistic projections of future return levels of extreme sea states, taking into account long-term trends related to climate change and inherent uncertainties. The stochastic ocean wave model presented in this paper exploits the flexible framework of Bayesian hierarchical space-time models. It allows modelling of complex dependence structures in space and time and incorporation of physical features and prior knowledge, yet at the same time remains intuitive and easily interpreted. Furthermore, by taking a Bayesian approach, the uncertainties of the model parameters are also taken into account. A regression component with $\text{ CO }_2$ as an explanatory variable has been introduced in order to extract long-term trends in the data. The model has been fitted by monthly maximum significant wave height data for an area in the North Atlantic ocean. The different components of the model will be outlined in the paper, and the results will be discussed. Furthermore, a discussion of possible extensions to the model will be given.     

Metal contamination of surface soils of industrial city Sialkot,Pakistan: a multivariate and GIS approach

In this study concentrations of selected metals viz., Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Na, Ni, Pb and Zn in surface soils of Sialkot city known worldwide for tanneries and pharmaceutical industries were measured to assess the status of urban soil pollution and to identify sources of contamination. Hierarchical cluster analysis (HACA) indicated concentrations of Mg and Ca related to parent rock material, Cd, Co, and Pb with traffic related activities, Cr, Cu, Ni and Zn either associated with automobiles activities or industrial pollution and Fe, K and Na related with anthropogenic activities or lithogenous materials. Correlation analyses and principal component analysis based on factor analysis confirmed the results of HACA. Spatial distribution maps exhibited relatively higher concentrations of Cd, Co, Cu, Ni, Pb, Cr and Zn along traffic routes in the city and streams. The results highlighted concentration of Cd, Ni, Cr, Zn, and Pb measured in urban soil exceeded the permissible limit of surface soils and advocated an imperative need for detailed baseline investigations of spatial distribution of heavy metals and other contaminants for the formulation of geochemical database that should be made available to stakeholder involved in monitoring, assessment and conservation of soil contamination for future planning and management of the Sialkot city.     

Ecofriendly approach of urban solid waste management: a case study of Jalgaon city, Maharashtra

In India, the traditional methods are used for urban solid waste management. These practices are associated with degradation of the urban environment Hence, an environmentally sound garbage management system is required for the urban waste management. The concept of waste minimization needs to be adopted in such systems. It is possible to implement certain corrective measures at collection, storage, transport and disposal of urban solid waste to minimize the adverse impacts on the environment The present investigations are emphasized on generation, characterzation and ecofriendly disposal of solid waste generated in Jalgaon city, Maharashtra. In the present study the waste generation at source was studied in the various income groups of the city. The per capita waste generation was studied by sampling the waste directly from the source of generation. The study reveals that the waste generation is large in the high-income group followed by middle and low-income group public. Further the physicochemical characterization of the waste was also studied. The data generated will help to develop environmentally sound and economically feasible solid waste management system for Ihe city.     

Severity of zinc and iron malnutrition linked to low intake through a staple crop: a case study in east-central Pakistan

Environmental Geochemistry and Health - Micronutrients deficiency in soil–plant and human is well-addressed; however, little is known about their spatial distribution, magnitude of deficiency...     

On the latent state estimation of nonlinear population dynamics using Bayesian and non-Bayesian state-space models

Nonlinear state-space models have been increasingly applied to study population dynamics and data assimilation in environmental sciences. State-space models can account for process error and measurement error simultaneously to correct for the bias in the estimates of system state and model parameters. However, few studies have compared the performance of different nonlinear state-space models for reconstructing the state of population dynamics from noisy time series. This study compared the performance of the extended Kalman filter (EKF), unscented Kalman filter (UKF) and Bayesian nonlinear state-space models (BNSSM) through simulations. Synthetic population time series were generated using the theta logistic model with known parameters, and normally distributed process and measurement errors were introduced using the Monte Carlo simulations. At higher levels of nonlinearity, the UKF and BNSSM had lower root mean square error (RMSE) than the EKF. The BNSSM performed reliably across all levels of nonlinearity, whereas increased levels of nonlinearity resulted in higher RMSE of the EKF. The Metropolis–Hastings algorithm within the Gibbs algorithm was used to fit the theta logistic model to synthetic time series to estimate model parameters. The estimated posterior distribution of the parameter θ indicated that the 95% credible intervals included the true values of θ (=0.5 and 1.5), but did not include 1.0 and 0.0. Future studies need to incorporate the adaptive Metropolis algorithm to estimate unknown model parameters for broad applications of Bayesian nonlinear state-space models in ecological studies.     

Evaluation of the performance of rural wastewater treatment plants using chemical measurements in combination with statistical techniques: a case study

The performance of a wastewater treatment plant was assessed statistically using multivariate cluster and principle component analysis. This was after measuring some physico-chemical properties in the influent, effluent, downstream, and upstream waters over a 4-month period. The cluster analysis grouped the sampling sites into three clusters: relatively non-polluted (upstream), medium polluted (downstream), and polluted (influent and effluent). The polluted water was further subdivided into very highly (influent) and highly (effluent) polluted. The grouping of influent and effluent into one cluster was due to some water quality parameters such as amount of copper, lead, and phosphates that are not efficiently removed by the plant. Using principal component analysis, samples from the same site taken over a period of 4 months were scattered, indicating inconsistencies in the performance of the plant. This was more pronounced during the rainy season, suggesting that increased water volumes from open sewers make the already poorly performing plant worse. The major loading factors found by principle component analysis were phosphate, lead, iron, zinc, copper, pH, and conductivity. Generally, the wastewater treatment system was found to be efficient in removing heavy metals and these were found in the sludge, but not anions. The mean percentage metal removal could be arranged in the following decreasing order: iron (85%)?>?zinc (57%)?>?copper (40%) and lead (38%) following the concentrations (mg?kg^?1) found in the sludge: iron (11,300)?>?zinc (820)?>?copper (180)?>?lead (20)?>?cadmium (3). Phosphate and iron concentrations in the effluent were found to be above the South African Bureau of Standards (SABS) recommendations. The major cause of poor performance is the high volume of the wastewater, exceeding the capacity of the plant 10 times.     

Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble prediction

Selection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and regression tree (CRT), habitat suitability index (HSI), forest structure database (FS), and habitat association database (HA). We focused our comparison on models for five priority forest-breeding species in the Central Hardwoods Bird Conservation Region: Acadian Flycatcher, Cerulean Warbler, Prairie Warbler, Red-headed Woodpecker, and Worm-eating Warbler. Lacking complete knowledge on the distribution and abundance of each species with which we could illuminate differences between approaches and provide strong grounds for recommending one approach over another, we used two approaches to compare models: rank correlations among model outputs and comparison of spatial correspondence. In general, rank correlations were significantly positive among models for each species, indicating general agreement among the models. Worm-eating Warblers had the highest pairwise correlations, all of which were significant (P < 0.05). Red-headed Woodpeckers had the lowest agreement among models, suggesting greater uncertainty in the relative conservation value of areas within the region. We assessed model uncertainty by mapping the spatial congruence in priorities (i.e., top ranks) resulting from each model for each species and calculating the coefficient of variation across model ranks for each location. This allowed identification of areas more likely to be good targets of conservation effort for a species, those areas that were least likely, and those in between where uncertainty is higher and thus conservation action incorporates more risk. Based on our results, models developed independently for the same purpose (conservation planning for a particular species in a particular geography) yield different answers and thus different conservation strategies. We assert that using only one habitat model (even if validated) as the foundation of a conservation plan is risky. Using multiple models (i.e., ensemble prediction) can reduce uncertainty and increase efficacy of conservation action when models corroborate one another and increase understanding of the system when they do not.     

Energy-economic theory and mathematical models for combining the systems of man and nature, case study: The urban region of Miami, Florida

This paper presents a study of the urban region of Miami, Fla. with consideration of energy flow and the relationship between energy theory and economics. Much of this work is based on the theories and work of Dr Howard T. Odum at the University of Florida. A theory of energy quality is presented which is an attempt to relate energies of different concentrations in their ability to do work. This theory allows comparison of the systems of man and nature. Another theory is proposed which seeks to describe the ability of a region to compete based on its flows of natural and fossil fuel energies.Economic, natural system, and energy data were compiled for the Miami urban region from 1950–1972. Cross-correlation of this data showed significant levels of correlation between the rate of change of fossil fuel use and the rates of change of population, budget, sales tax, income, building structure, and number of telephones. Calculation of several urban indicators for 1972 showed a fossil fuel energy density of 300 kcal/m²/day in the urbanized area, a per capita energy consumption of 53.8 × 10⁶ kcal/capita/year, a ratio of natural to fossil fuel energies of 0.25, a developed area of 260 miles² (673.4 km²), and a rate of development of 6.5 miles² (16.8 km²) per year.An overall model of Miami is presented with flows and storages quantified for 1972. Based on this model a simpler model was simulated on an analog computer. This model consisted of a system of first-order in time, non-linear differential equations which included fossil fuel energy flows, main economic flows, external price functions, building structure, natural energies, and population. This model was simulated for several linearly increasing future price functions and several sets of future energy functions.Natural energies within the region were calculated by determining the land areas associated with various ecosystem types. Estimating the productivities of these systems on a per area basis allowed calculation of total energy flows. The energies associated with winds, tides, waves, and fresh/salt water concentration gradients were also determined. It was found that the ratio of natural to fossil fuel energy changed from 1.77 in 1950 to 0.25 in 1972.     

Slope,aspect and climate: Spatially explicit and implicit models of topographic microclimate in chalk grassland

The slope and aspect of a vegetated surface strongly affects the amount of solar radiation intercepted by that surface. Solar radiation is the dominant component of the surface energy balance and influences ecologically critical factors of microclimate, including near-surface temperatures, evaporative demand and soil moisture content. It also determines the exposure of vegetation to photosynthetically active and ultra-violet wavelengths. Spatial variation in slope and aspect is therefore a key determinant of vegetation pattern, species distribution and ecosystem processes in many environments. Slope and aspect angle may vary considerably over distances of a few metres, and fine-scale species’ distribution patterns frequently follow these topographic patterns. The availability of suitable microclimate at such scales may be critical for the response of species distributions to climatic change at much larger spatial scales. However, quantifying the relevant microclimatic gradients is not straightforward, as the potential variation in solar radiation flux under clear-sky conditions is modified by local and regional variations in cloud cover, and interacts with long-wave radiation exchange, local meteorology and surface characteristics.     

Trade-offs between time, predation risk and life history, and their implications for biogeography: A systems modelling approach with a primate case study

Group sizes are often considered to be the result of a trade-off between predation risk and the costs of feeding competition. We develop a model to explore the interaction between different ecological constraints on group sizes, using a primate (baboons) case study. The model uses climatic correlates of time budgets to predict maximum ecologically tolerable group size, and climatic predictors of predation risk (reflected mainly in predator density and female body mass) to predict minimum tolerable group size for any given habitat. As well as defining the range of sustainable group sizes for a given habitat, the model also allows us to reliably predict our exemplar taxon's biogeographical distribution across Africa. We also explore the life history implications of the model to ask whether baboons form group sizes which maximise survival or fecundity in the classic trade off between these two key life history variables. Our results indicate that, within the range of study sites in our sample, baboons prefer to maximise fecundity. However, the data indicate that in higher predation risk habitats they would switch to maximising survival at the expense of fecundity. We argue that this is due to the fact that interbirth interval and developmental rates have a ceiling that cannot be breached. Thus, while females can shorten interbirth intervals to compensate for increased predation risk, there is a limit to how much these life history variables can be altered, and when this is reached the best strategy is to maximise survivorship.     

Fishing sustainability via inclusion of man in predator-prey models: A case study in Lago Preto, Manacapuru, Amazonas

We modeled a fishery's system with two types of fishermen, commercial and subsistence fishermen, who exploit the fish stock at the Amazonian floodplain lakes. In the first model, we combined the Lotka-Volterra equations with Verhulst's Logistic model, by inserting hydrological cycle oscillations. The second model was based on the equations proposed by Berryman, which reflect the predator's functional response in relation to the prey's population behavior, taking into account the hydrological cycle. In both models, commercial fishermen and local direct consumers (called riverside dwellers - riverines - in the model), were considered the only predators acting upon fishing stocks. Primary data were collected in 48 riverside homes throughout 2006. The total number of interviewees corresponds to 69.6% of the universe of homes in the community defined as study area. The riverines were the predators that showed capacity to eliminate the opponent predators (commercial fishermen). The best scenery obtained regarding the number of prey, was the one that showed only commercial fishermen in the region. On the other hand, the simulations show that the coexistence is possible among predators, and between predators and their prey. The seasonal model with functional response provides a better response in relation to the system's current situation and to the established modeling conditions than the Lotka-Volterra seasonal model. The seasonal model with functional response also showed a better response pattern in all scenarios, with oscillations taking place more gradually, both for variations associated with the flooding pulse and for relations between predators and prey.     

Echolocation call design and limits on prey size: a case study using the aerial-hawking bat Nyctalus leisleri

The echolocation calls used by Nyctalus leisleri during search phase in open air space are between 9 and 14 ms long, with the peak energy between 24 and 28 kHz. The pulses are shallowly frequency-modulated with or without an initial steep frequency-modulated component. The diet consists primarily of small flies (Diptera), including many chironomids (wingspan 9–12 mm) and yellow dung flies (Scatophaga; wingspan 24 mm), but also of some larger insects such as dung beetles (Coleoptera; Scarabaeoidea), caddis-flies (Trichoptera) and moths (Lepidoptera). The echo target strength of some prey items was measured. Contrary to models based on standard targets such as spheres or disks, the echo strength of real insects was found to be virtually independent of the emitted frequency within the 20–100 kHz frequency range. A model was used to calculate probable detection distances of the prey by the bat. Using narrow-band calls of 13.7 ± 2.7 ms duration, a bat would detect the two smallest size classes of insect at greatest range using calls of 20 kHz. The results may therefore explain why many species of large and medium sized aerial-hawking bats use low-frequency calls and still eat mostly relatively small insects. The data and model challenges the assumption that small prey are unavailable to bats using low-frequency calls.     

An optimization approach for sustainable release of e-flows for lake restoration and preservation: Model development and a case study of Baiyangdian Lake, China

In this paper, we describe the development of a model for the sustainable release of e-flows from the regional water resource infrastructure (e.g., reservoirs, rivers with available water) for lake restoration and preservation, and use the model in a case study of Baiyangdian Lake, China. First, we define the sustainable environmental flows (e-flows), with an emphasis on the ecological importance of temporal variation in factors such as water level (depth). By analyzing historical data on the suitable range of water levels in the lake, we evaluated fluctuations using canonical correspondence analysis and frequency distribution analysis. The temporal variations required by the ecosystem of the lake were also assessed. Based on this approach, we developed an optimization model for sustainable release of e-flows. We used the adaptive genetic algorithm approach to solve the model and determine the required release of e-flows. Scenario analysis then provided a range of potential management strategies for the e-flows. The optimal results are helpful to the lake managers to establish sustainable e-flow release schemes for the lake restoration and preservation.     

Diversity, host affinity, and distribution of seed-infecting fungi: a case study with Cecropia

Recruitment limitation has been proposed as an important mechanism contributing to the maintenance of tropical tree diversity. For pioneer species, infection by fungi significantly reduces seed survival in soil, potentially influencing both recruitment success and adult distributions. We examined fresh seeds of four sympatric Cecropia species for evidence of fungal infection, buried seeds for five months in common gardens below four C. insignis crowns in central Panama, and measured seed survival and fungal infection of inviable seeds. Seed survival varied significantly among species and burial sites, and with regard to local (Panama) vs. foreign (Costa Rica) maternal seed sources. Fresh seeds contained few cultivable fungi, but > 80% of soil-incubated seeds were infected by diverse Ascomycota, including putative pathogens, saprophytes, and endophytes. From 220 isolates sequenced for the nuclear internal transcribed spacer region (ITS), 26 of 73 unique genotypes were encountered more than once. Based on the most common genotypes, fungal communities demonstrate host affinity and are structured at the scale of individual crowns. Similarity among fungal communities beneath a given crown was significantly greater than similarity among isolates found under different crowns. However, the frequency of rare species suggests high fungal diversity and fine-scale spatial heterogeneity. These results reveal complex plant-fungal interactions in soil and provide a first indication of how seed survival in tropical forests may be affected by fungal community composition.     

Temperature and discharge variations in natural mineral water springs due to climate variability: a case study in the Piedmont Alps (NW Italy)

Environmental Geochemistry and Health - In the context of global climate change, understanding the relationships between climate and groundwater is increasingly important. This study in the NW Alps...     

水功能区划在流域排污权初始分配中的应用——以沙颖河流域为例

排污权交易是治理环境污染问题的有效手段,排污权初始分配则是排污权交易制度实施的基础,在流域水功能区划基础上研究排污权初始分配问题,将有助于流域排污权交易制度的有效实施.结合我国现行行政特征和流域水功能区划成果,以行政单元作为排污权初始分配主体开展排污权初始分配研究.选取沙颍河流域为例,根据淮河水利委员会制定的沙颍河流域水功能区划及COD、氨氮限排总量要求,以COD、氨氮作为排污权初始分配的客体,通过等比例削减方法对沙颍河流域内的行政单元进行了排污权初始分配,得到了流域内各行政单元的COD、氨氮初始排放权,并将分配结果与区域社会经济发展水平等进行了比较研究,研究认为将水功能区划应用于排污权初始分配研究是一种有效的尝试.在此基础上探讨了关于排污权初始分配的政策可行性、初始分配的方法及地方政府定位等几方面问题,目的在于为将来的排污权分配研究工作提供一些思考和建议.