A capture-recapture model with heterogeneity and behavioural response

We develop the non-parametric maximum likelihood estimator (MLE) of the full M_bh capture-recapture model which utilizes both initial capture and recapture data and permits both heterogeneity (h) between animals and behavioural (b) response to capture. Our MLE procedure utilizes non-parametric maximum likelihood estimation of mixture distributions (Lindsay, 1983; Lindsay and Roeder, 1992) and the EM algorithm (Dempsteret al., 1977). Our MLE estimate provides the first non-parametric estimate of the bivariate capture-recapture distribution.Since non-parametric maximum likelihood estimation exists for submodels M_h (allowing heterogeneity only), Mb (allowing behavioural response only) and M₀ (allowing no changes), we develop maximum likelihood-based model selection, specifically the Akaike information criterion (AIC) (Akaike, 1973). The AIC procedure does well in detecting behavioural response but has difficulty in detecting heterogeneity.     

Replace the NOAEL and LOAEL with the BMDL01 and BMDL10

Although benchmark-dose methodology has existed for more than 20 years, benchmark doses (BMDs) still have not fully supplanted the no-observed-adverse-effect level (NOAEL) and lowest-observed-adverse-effect level (LOAEL) as points of departure from the experimental dose–response range for setting acceptable exposure levels of toxic substances. Among the issues involved in replacing the NOAEL (LOAEL) with a BMD are (1) which added risk level(s) above background risk should be targeted as benchmark responses (BMRs), (2) whether to apply the BMD methodology to both carcinogenic and noncarcinogenic toxic effects, and (3) how to model continuous health effects that aren’t observed in a natural risk-based context like dichotomous health effects. This paper addresses these issues and recommends specific BMDs to replace the NOAEL and LOAEL.

Continuous dose-response modeling and risk analysis with the gamma and reciprocal gamma distributions

Kodell and West (1993) describe two methods for calculating pointwise upper confidence limits on the risk function with normally distributed responses and using a certain definition of adverse quantitative effect. But Banga et al. (2000) have shown that these normal theory methods break down when applied to skew data. We accordingly develop a risk analysis model and associated likelihood-based methodology when the response follows either a gamma or reciprocal gamma distribution. The model supposes that the shape (index) parameter k of the response distribution is held fixed while the logarithm of the scale parameter is a linear model in terms of the dose level. Existence and uniqueness of the maximum likelihood estimates is established. Asymptotic likelihood-based upper and lower confidence limits on the risk are solutions of the Lagrange equations associated with a constrained optimization problem. Starting values for an iterative solution are obtained by replacing the Lagrange equations by the lowest order terms in their asymptotic expansions. Three methods are then compared for calculating confidence limits on the risk: (i) the aforementioned starting values (LRAL method), (ii) full iterative solution of the Lagrange equations (LREL method), and (iii) bounds obtained using approximate normality of the maximum likelihood estimates with standard errors derived from the information matrix (MLE method). Simulation is used to assess coverage probabilities for the resulting upper confidence limits when the log of the scale parameter is quadratic in the dose level. Results indicate that coverage for the MLE method can be off by as much as 15% points and converges very slowly to nominal coverage levels as the sample size increases. Coverage for the LRAL and LREL methods, on the other hand, is close to nominal levels unless (a) the sample size is small, say N < 25, (b) the index parameter is small, say k 1, and (c) the direction of adversity is to the left for the gamma distribution or to the right for the reciprocal gamma distribution.     

Analysis and prediction of ecological and ecosystem dynamics with response structure models

A method of directly using data concerning species' responses to various combinations of levels of environmental factors is outlined. Examples of its utilization to analyze (and predict) the dynamics of the ecological processes of population growth, interspecific competition, and predation are given for simple systems; a simulation is presented wherein all of these processes interact within a simple ecosystem. A technique of summarizing the pattern and detail of variation of levels of combination of important environmental factors is also introduced. Together these methods permit application of real world information about the components of the biological community and the environment toward the modeling of ecosystems and the making of predictions concerning them to whatever degree of accuracy which may be useful.There are several major advantages of this approach: (1) It makes maximum use of real world data; the limits of its precision are determined only by the adequacy of the data available (hypothetical values also may be used where real data are unavailable and/or where such hypothetical values may be useful in model and theory development). (2) It is powerful (and applicable to the dynamics of diverse kinds of systems), mathematically very simple, and has important advantages in that non-linearities, thresholds, etc. are automatically and accurately taken into account. (3) It can be expressed numerically or graphically, and therefore is especially helpful in permitting visualization of ecological processes and the results of their action.     

A generalized Chao estimator with measurement error and external information

We present a generalized Chao (GC) estimator based on a subject-occasion-specific design matrix. We then extend the GC estimator to (i) external information, in the form of non-linear constraints on subpopulation sizes and (ii) measurement error. For the first, we propose a reparameterization of the estimating equations. As a result, the constrained MLE can be found with no additional computational efforts. For the second we generalize SIMEX procedure to multiple measurement methods. In simulation we show that (even incorrect) external information can substantially decrease the MSE. We illustrate with an application to a whale shark (Rhincodon typus) population, where mostly jouvenile males are observed. We use external information on gender ratio of whale sharks to correct for low catchability of females, and our multivariate SIMEX procedure to correct for measurement error in assessment of shark length. The resulting population size estimates are about 60% larger than the unconstrained–uncorrected counterparts.     

Reserve and land prices with exploration under uncertainty

Arrow and Chang (J. Econom. Environ. Manag.9, 1–10 (1982) analyze an exploration-extraction model with uncertainty about the distribution of deposits. Reserve prices do not exhibit any rising trend when the unexplored land area is big but, in order to know what happens when the unexplored area is smaller, “a probabilistic analysis not yet performed” (ibid. p. 10) is required. Their conjecture of a rising trend at less than the discount rate is confirmed. However, land prices can be expected to grow faster than reserve prices, which helps discriminate between Arrow and Chang's, and other rationalizations of the failure of resource prices to rise at the discount rate.     

Representing mediating effects and species reintroductions in Ecopath with Ecosim

Ecosystem models play an important role in supporting ecosystem approaches to management. To improve the representation of how ecosystems work, ecosystem models should be able to represent mediating effects (e.g., habitat provision) that species provide to each other as well as species (re)introductions, both common situations that can strongly influence ecosystem dynamics. We examine how such processes can be incorporated into Ecopath with Ecosim (EwE), a widely used tool for represent aquatic ecosystems with the potential to support ecosystem-based management. We used the reintroduction of sea otters (Enhydralutris) to the west coast of Vancouver Island, British Columbia, Canada as a case study. The model demonstrates how to account for benefits provided by kelp forests by contributing to primary production, increased feeding areas and food availability through prey retention. It also demonstrates how the reintroduction and range expansion of sea otters can be represented in Ecospace, and the implications of these options.     

Growth, environment and innovation—a model with production vintages and environmentally oriented research

I develop an innovative environmental new growth model driven by researchers striving for monopoly profits. Skilled labour is allocated between production vintages and two forms of research, ordinary and environmentally oriented. The intermediate sector includes fixed costs and decreasing returns, limiting the number of vintages used. I solve for planner's, laissez-faire, and regulator's solutions, and examine welfare implications and the various distortions in the model (monopoly power, knowledge spillovers, business stealing, environmental externalities). A regulator may wish: (i) to encourage environmentally oriented research; (ii) to concentrate production labour on recent (cleaner) vintages; (iii) to switch labour from production to research. An environmental sales tax may under some circumstances achieve all three—such taxes not only give incentives to reduce pollution, but also shift profits from old vintages to new, thus raising incentives to come up with newer (cleaner) vintages. An environmental tax may even lead to an increase in the rate of production growth.     

Modelling the outcrossing between genetically modified and conventional maize with equation discovery

Many studies explore the feasibility of co-existence between genetically modified (GM) and conventional (non-GM) crops. An important research topic in these studies is the process of outcrossing, i.e., the process of gene flow via pollen flow from GM to non-GM crops. In this paper, we address a new modelling approach to define the environmentally driven processes of outcrossing for maize from existing empirical datasets. In particular, we use equation discovery methodology that combines background knowledge and empirical data from several studies. We induce models that predict the degree of outcrossing rate between the donor (GM) and the recipient (non-GM) maize field from the distance between the fields and the local wind characteristics (speed, direction and duration). This results in highly accurate models, for which both variables (distance and wind) are essential and of roughly equal importance.     

Simulating the fate of Florida Snowy Plovers with sea-level rise: Exploring research and management priorities with a global uncertainty and sensitivity analysis perspective

Changes in coastal habitats due to sea-level rise provide an uncertain, yet significant threat to shoreline dependent birds. Rising sea levels can cause habitat fragmentation and loss which can result in considerable reduction in their foraging and nesting areas. Computational models and their algorithmic assumptions play an integral role in exploring potential mitigation responses to uncertain and potentially adverse ecological outcomes. The presence of uncertainty in metapopulation models is widely acknowledged but seldom considered in their development and evaluation, specifically the effects of uncertain model inputs on the model outputs. This paper was aimed to (1) quantify the contribution of each uncertain input factor to the uncertainty in the output of a metapopulation model which evaluated the effects of long-term sea-level rise on the population of Snowy Plovers (Charadrius alexandrinus) found in the Gulf Coast of Florida, and (2) determine the ranges of model inputs that produced a specific output for the purpose of formulating environmental management decisions. This was carried out by employing global sensitivity and uncertainty analysis (GSA) using two generic (model independent) methods, the qualitative screening Morris method and a quantitative variance-based Sobol’ method coupled with Monte Carlo filtering. The analyses were applied to three density dependence scenarios: assuming a ceiling-type density dependence, assuming a contest-type density dependence, and assuming that density dependence is uncertain as to being ceiling- or contest-dependent. The sources of uncertainty in the outputs depended strongly on the type of density dependence considered in the model. In general, uncertainty in the outputs highly depended on the uncertainty in stage matrix elements (fecundity, adult survival, and juvenile survival), dispersal rate from central areas with low current populations (the “Big Bend” area of Florida) to the northern, panhandle populations, the maximum growth rate, and density dependence type. Our results showed that increasing the maximum growth rate to a value of 1.2 or larger will increase the final average population of Snowy Plovers assuming a contest-type density dependence. Results suggest that studies that further quantify which density dependence relationship best describes Snowy Plover population dynamics should be conducted since this is the main driver of uncertainty in model outcomes. Furthermore, investigating the presence of Snowy Plovers in the Big Bend region may be important for providing connection between the panhandle and peninsula populations.     

紫花苜蓿对铅污染土壤修复能力及其机理的研究

以10 mmol/L Pb(NO3)2处理紫花苜蓿幼苗10 d,分析了Pb在紫花苜蓿幼苗根、茎、叶中的积累情况,Pb在根表皮细胞中的亚细胞区域化特点,以及Pb在紫花苜蓿体内的主要存在形式。结果表明,Pb在紫花苜蓿幼苗中积累量(M)特点为:M根 >M茎 >M叶。同时X-ray微区分析显示,胞间隙是紫花苜蓿积累Pb浓度最高的部位,细胞壁和液泡次之,胞质中最低。Pb的存在形式分析表明Pb在紫花苜蓿体内主要以难溶的形式存在,另外BSO能够加剧Pb污染对紫花苜蓿幼苗Pn和生长的抑制作用,显示了紫花苜蓿对Pb的耐受与植物络和素的形成有关。这些都表明紫花苜蓿对Pb具有一定的耐受机制,避免其对胞质代谢的毒性。同时紫花苜蓿具有很高的生物量和对Pb较高的富集作用,因此是一种很有利用价值的土壤铅污染修复植物。     

Formation of Soluble Complexes of Metals with Humic Acid and Its Environmental Significance

In order to investigate the role of functional groups present in humic acid(s) (HA) during complex formation, water soluble complexes between HA isolated from soil and metals (Pb, Ca, As, Ni, Cr, Co, Cu, Cd, Fe, Mn, Mg and Zn) were prepared and subjected to infrared (IR) spectroscopy. the IR data revealed the involvement of the - OH group of humic acid in complex formation with all metals except copper and arsenic, whereas the - COOH group of HA was found to be the preferred site of binding for all the metals. the significance of findings in relation to detoxification of environmental pollutants is discussed in this paper.     

Sediment microbial fuel cell with floating biocathode for organic removal and energy recovery

A sediment microbial fuel cell (SMFC) with three dimensional floating biocathode (FBC) was developed for the electricity generation and biodegradation of sediment organic matter in order to avoid negative effect of dissolved oxygen (DO) depletion in aqueous environments on cathode performance and search cost-effective cathode materials. The biocathode was made from graphite granules with microbial attachment to replace platinum (Pt)-coated carbon paper cathode in a laboratory-scale SMFC (3 L in volume) filled with river sediment (organic content 49±4 g·kg^-1 dry weight). After start-up of 10 days, the maximum power density of 1.00W·m^-3 (based on anode volume) was achieved. The biocathode was better than carbon paper cathode catalyzed by Pt. The attached biofilm on cathode enhanced power generation significantly. The FBC enhanced SMFC performance further in the presence aeration. The SMFC was continuously operated for an over 120-day period. Power generation peaked within 24 days, declined gradually and stabilized at a level of 1/6 peak power output. At the end, the sediment organic matter content near the anode was removed by 29% and the total electricity generated was equal to 0.251 g of chemical oxygen demand (COD) removed.     

Heavy-metal fractionation and distribution in soil profiles short-term-irrigated with sewage wastewater

Six soil profiles irrigated and non-irrigated with sewage wastewater were investigated for soil pH, electrical conductivity (EC), organic matter (OM), and CaCO₃. The distributions and chemical fractions of Cu, Zn, Cd, and Pb, and their lability were also studied. The results indicated that pH, EC, OM, and CaCO₃, as well as metal fractionation in soil profiles were affected by wastewater irrigation, especially in the surface layer. The surface layer (0-15 cm) irrigated with wastewater exhibited a 0.6 unit decrease in soil pH, a 40.6% decrease in CaCO₃, and a 200% increase in EC as compared with that of the non-irrigated soil. The soil OM increased from 0.04% to 0.35% in the surface layer. The irrigation of soil with wastewater resulted in transformation of metals from the carbonate fraction (CARB) towards the exchangeable (EXCH), Fe-Mn oxide (ERO), and organic (OM) fraction for Zn, towards the EXCH, the OM, and residual fraction for Cu, and towards the exchangeable (EXCH) fraction for Cd. It was concluded that the use of sewage wastewater led to salt accumulation and an increase in the readily labile fraction of Zn, Cu, and Cd in the surface layer. Therefore, this reason may limit the use of wastewater under arid and semi-arid conditions.     

Regression analysis of forest inventory data with time and space dependencies

In this paper the data of a forest health inventory are analyzed. Since 1983 the degree of defoliation, together with various explanatory variables (covariates) concerning stand, site, soil and weather, are recorded by the second of the two authors, in the forest district of Rothenbuch (Spessart, Bavaria). The focus is on the space and time dependencies of the data. The mutual relationship of space-time functions and the set of covariates is evaluated. For this we use generalized linear models (GLMs) for ordinal response variables and semiparametric estimation approaches. By using goodness-of-fit measures it turns out that (i) the contribution of space-time functions is quantitatively comparable with that of the set of covariates, (ii) the contribution of space-time functions is small compared with the contribution of a set of variables describing the last-year and neighboring response values. By applying appropriate residual methods a detailed analysis of the individual sites in the area can be carried out. This analysis reveals where the predictive power of the covariates fail to explain the observed defoliation.     

Combining state and transition models with dynamic Bayesian networks

Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks - so-called dynamic Bayesian networks (DBNs) - for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.     

Irrigation with domestic wastewater: responses on growth and yield of ladyfinger Abelmoschus esculentus and on soil nutrients

Domestic wastewater is generated continuously and in large quantities. It can serve as an alternative water nutrient source for irrigation. In the present study Abelmoschus esculentus L. (Ladyfinger) was irrigated using untreated wastewater (T1), treated wastewater (T2) and rainwater (T3) in pot experiments. The effect was seen on nutrient fortication, growth and yield of the plant and the nutrient status of the soil. Additionally the build up of Cr, Cu and Zn from the irrigation water were anlayzed in different parts of the plant biomass and in the soil. The sapling survival rate was found to be 87% in T1 followed by T2 and T3. Root shoot ratio under different treatments was found in the order T3 (0.46) >T2 (0.35) >T1 (0.31). The chlorophyll a, b and carotene content in the leaves (mg g(-1)) was found to be 6.3, 0.5, 0.9 under T1, 4.8, 0.4, 0.8 under T2 and 3.2, 0.3, 0.5 under T3 respectively and all the three varied in the order T1>T2>T3. The same trend was found in case of total dry matter (g) T1 (6.3) >T2 (3.7) >T3 (2.3) at p < or = 0.05. There was a considerable increase in nutrients in the soil under T1 and T2 as compared to T3 after final harvest. The organic matter (%), NO3-N and PO4(3-) (mg kg(-1)) content post harvest soil was found to be 3.4, 71, 90 under T1 and 2.9, 52, 63 under T2 respectively. Also, there was an increase in cations Na, K, Ca and Mg in the soil irrigated with T1 and T2 after the final harvest. Thus irrigation with wastewater generally increased soil fertility. Only a small percentage of the heavy metal was bioaccumulated by the plant parts from the irrigation water. There was hardly any metal accumulation in fruits. Bulk of the metal ions remained in the soil.     

Strontium and its relationship with trace elements Mg,Cu, Co,and Mo in human blood and serum

The aim of the study was to assess the influence of exposure to strontium on human blood and serum concentrations of magnesium, copper, cobalt, and molybdenum. Inductively coupled plasma–mass spectrometry (ICP-MS) was used to analyze the elemental content of whole blood and blood serum of 97 healthy men including 70 workers in a thermal power plant and 27 control subjects from the rural area of Dragash (Kosovo), an environment without pollution. The results showed that chronic moderate exposure to strontium decreases the levels of copper in blood (BCu) and serum (SCu), of cobalt in blood (BCo) and serum (SCo), and of molybdenum in blood (BMo). All changes in blood and serum concentrations of these essential elements were significant but remained within the normal range. The results suggest that strontium may induce adverse health effects in humans.     

Comparison of light- and SST-based geolocation with satellite telemetry in free-ranging albatrosses

Light-based archival tags are increasingly being used on free-ranging marine vertebrates to study their movements using geolocation estimates. These methods use algorithms that incorporate threshold light techniques to determine longitude and latitude. More recently, researchers have begun using sea surface temperature (SST) to determine latitude in temperate regions. The accuracy and application of these algorithms have not been validated on free-ranging birds. Errors in both geolocation methods were quantified by double-tagging Laysan (Phoebastria immutabilis Rothschild) and black-footed (P. nigripes Audubon) albatrosses with both leg-mounted archival tags that measured SST and ambient light, and satellite transmitters. Laysan albatrosses were captured and released from breeding colonies on Tern Island, northwestern Hawaiian Islands (23°52N, 166°17W) and Guadalupe Island, Mexico (28°31N, 118°10W) and black-footed albatrosses from Tern Island. Studies were carried out between December 2002 and March 2003. For all birds combined, the mean ± SD great circle (GC) distance between light-based locations and satellite-derived locations was 400±298 km (n=131). Errors in geolocation positions were reduced to 202±171 km (n=154) when light-based longitude and SST-based latitude (i.e. SST/light) were used to establish locations. The SST/light method produced comparable results for two Laysan albatross populations that traveled within distinctly different oceanic regions (open ocean vs more coastal) whereas light-based methods produced greater errors in the coastal population. Archival tags deployed on black-footed albatrosses returned a significantly higher proportion of lower-quality locations, which was attributed to interference of the light sensor on the tag. Overall, the results demonstrate that combining measures of light-based longitude and SST-based latitude significantly reduces the error in location estimates for albatrosses and can provide valid latitude estimates during the equinoxes, when light-based latitude measurements are indeterminate.Communicated by J.P. Grassle, New Brunswick     

Mass exchange in a shallow channel flow with a series of groynes: LES study and comparison with laboratory and field experiments

The exchange of dissolved matter between a straight open channel and a series of shallow embayments present at one of its sides is investigated using large eddy simulation (LES). The direct link between the mechanism of mass exchange and the dynamics of coherent structures is demonstrated. It is shown that for the geometrical configuration considered in the present study, the mass exchange process is very non-uniform over the depth in the vicinity of the channel–embayment interface. Most of the contaminant is ejected from the embayments close to the free surface. The amount of contaminant re-entrained into the embayments situated downstream of the one in which contaminant was introduced is quantified. The mass exchange coefficient predicted by LES does not vary significantly with the embayment rank and is in very good agreement with the one predicted by the model proposed by Weitbrecht et al. (J Hydraul Eng 134(2):173–183, 2008) based on the value of a dimensionless morphometric groyne-field parameter. Field experiments were purposely performed in a natural stream with embayments whose length over width ratios were close to the ratio in the LES study. The concentration fields predicted by LES are compared with video-records of colored dye used to visualize the mass exchange in the field experiment. It is shown that, for both LES and the field experiment, the dominant passage frequency of the eddies inside the interfacial mixing layer is well predicted by the analytical model of Sukhodolov and Sukhodolova (in: Cowen et al (eds) Hydraulic measurements & experimental methods. Proceedings of international conference, Lake Placid, USA, pp 172–177, 2007). The model is then used to scale the time in the LES animations and field video-records showing the temporal evolution of the concentration field. The results of the comparison indicate several similarities in the mixing process, despite the differences in the bathymetry and the large difference in the Reynolds number between LES and the field experiment. This proves the usefulness of performing detailed LES and laboratory studies in well-controlled environments to understand mass-exchange processes around river groyne fields.