A novel application of cultural consensus models to evaluate conservation education programs

Conservation professionals recognize the need to evaluate education initiatives with a flexible approach that is culturally appropriate. Cultural‐consensus theory (CCT) provides a framework for measuring the extent to which beliefs are communally held and has long been applied by social scientists. In a conservation‐education context, we applied CCT and used free lists (i.e., a list of items on a topic stated in order of cultural importance) and domain analysis (analysis of how free lists go together within a cultural group) to evaluate a conservation education program in which we used a children's picture book to increase knowledge about and empathy for a critically endangered mammal, the Javan slow loris (Nycticebus javanicus). We extracted free lists of keywords generated by students (n = 580 in 18 schools) from essays they wrote before and after the education program. In 2 classroom sessions conducted approximately 18 weeks apart, we asked students to write an essay about their knowledge of the target species and then presented a book and several activities about slow loris ecology. Prior to the second session, we asked students to write a second essay. We generated free lists from both essays, quantified salience of terms used, and conducted minimal residuals factor analysis to determine presence of cultural domains surrounding slow lorises in each session. Students increased their use of words accurately associated with slow loris ecology and conservation from 43% in initial essays to 76% in final essays. Domain coherence increased from 22% to 47% across schools. Fifteen factors contributed to the domain slow loris. Between the first and second essays, factors that showed the greatest change were feeding ecology and slow loris as a forest protector, which increased 7‐fold, and the humancentric factor, which decreased 5‐fold. As demonstrated by knowledge retention and creation of unique stories and conservation opinions, children achieved all six levels of Bloom's taxonomy of learning domains. Free from the constraints of questionnaires and surveys, CCT methods provide a promising avenue to evaluate conservation education programs.     

Sensitivity of species-distribution models to error,bias, and model design: An application to resource selection functions for woodland caribou

Models that predict distribution are now widely used to understand the patterns and processes of plant and animal occurrence as well as to guide conservation and management of rare or threatened species. Application of these methods has led to corresponding studies evaluating the sensitivity of model performance to requisite data and other factors that may lead to imprecise or false inferences. We expand upon these works by providing a relative measure of the sensitivity of model parameters and prediction to common sources of error, bias, and variability. We used a one-at-a-time sample design and GPS location data for woodland caribou (Rangifer tarandus caribou) to assess one common species-distribution model: a resource selection function. Our measures of sensitivity included change in coefficient values, prediction success, and the area of mapped habitats following the systematic introduction of geographic error and bias in occurrence data, thematic misclassification of resource maps, and variation in model design. Results suggested that error, bias and model variation have a large impact on the direct interpretation of coefficients. Prediction success and definition of important habitats were less responsive to the perturbations we introduced to the baseline model. Model coefficients, prediction success, and area of ranked habitats were most sensitive to positional error in species locations followed by sampling bias, misclassification of resources, and variation in model design. We recommend that researchers report, and practitioners consider, levels of error and bias introduced to predictive species-distribution models. Formal sensitivity and uncertainty analyses are the most effective means for evaluating and focusing improvements on input data and considering the range of values possible from imperfect models.     

Reprint of: Linking conservation and welfare: A theoretical model with application to Nepal

Theoretical articles linking conservation and welfare find a negative relationship between these two variables while empirical studies show that land protection may be positively related to welfare. Several authors attribute this empirical result to the development of ecotourism in protected areas. We thus argue that the gap between the theory and existing empirical results is partly explained by the fact that most theoretical models do not account for a productive activity on protected land. Therefore, we develop a theoretical model in which conservation allows developing an alternative sector and show that the relationship between conservation and welfare is U-shaped. We test this theoretical prediction using Nepalese data and find that conservation combined with ecotourism is indeed positively related to local welfare.     

A computer simulation study of stochastic models to investigate the population dynamics of the screech owl (otus asio) under increased mortality

The work reported in this paper complements an earlier study in which deterministic models were used examine the effects of additional mortality imposed on a Screech Owl, Otus asio, population. Interest lay in the compensatory mechanisms that the owls might be able to adopt in their population dynamics to counteract the overall effect of the additional mortality imposed, in particular when only a part of the population is affected. Stochastic models are used here to address the same questions, and to give more detailed information about the likely behaviour of the owl population than the information an average sizes provided by the deterministic approach.     

A closure approach with multi-scale mixing length,and its application to wind and shear stress profiles within the atmospheric boundary layer

A method to determine flow specific first-order closure for the turbulent flux of momentum in the atmospheric boundary layer (ABL) is presented. This is based on the premise that eddy viscosity is a flow rather than a fluid property, and the physically more realistic assumption that the transfer of momentum and other scalar quantities in a turbulent flow takes place by a large, but finite number of length scales, than the often used single length scale, the ‘mixing length’. The resulting eddy viscosity is flow specific and when applied to the study of the ABL, yields the vertical profiles of shear stress and mean wind velocity in good agreement with observations. The method may be extended to other types of turbulent flows, however it should be recognized that each type of flow may yield a different eddy viscosity profile. Using the derived eddy viscosity the paper presents simple analytical solutions of the ABL equations to determine observationally consistent wind speed and shear stress profiles in the ABL for a variety of practical applications including air pollution modelling.     

A comparison of two models with Landsat data for estimating above ground grassland biomass in Inner Mongolia,China

Two models, artificial neural network (ANN) and multiple linear regression (MLR), were developed to estimate typical grassland aboveground dry biomass in Xilingol River Basin, Inner Mongolia, China. The normalized difference vegetation index (NDVI) and topographic variables (elevation, aspect, and slope) were combined with atmospherically corrected reflectance from the Landsat ETM+ reflective bands as the candidate input variables for building both models. Seven variables (NDVI, aspect, and bands 1, 3, 4, 5 and 7) were selected by the ANN model (implemented in Statistica 6.0 neural network module), while six (elevation, NDVI, and bands 1, 3, 5 and 7) were picked to fit the MLR function after a stepwise analysis was executed between the candidate input variables and the above ground dry biomass. Both models achieved reasonable results with RMSEs ranging from 39.88% to 50.08%. The ANN model provided a more accurate estimation (RMSE_r = 39.88% for the training set, and RMSE_r = 42.36% for the testing set) than MLR (RMSE_r = 49.51% for the training, and RMSE_r = 53.20% for the testing). The final above ground dry biomass maps of the research area were produced based on the ANN and MLR models, generating the estimated mean values of 121 and 147 g/m², respectively.     

A field colonization experiment with meiofauna and seagrass mimics: effect of time,distance and leaf surface area

From a conservation point of view, it is essential to know how fast an ecosystem can recover after physical disturbance. Meiofauna and especially harpacticoid copepods are abundant in seagrass beds and are therefore useful to study ecosystem recovery after disturbance. In the western Caribbean coast, a fragmented Thalassia testudinum seagrass bed was selected to conduct a colonization field experiment by means of plastic seagrass mimics. Meiofauna colonization, with special emphasis on harpacticoid copepods, was followed in relation to: (1) colonization time (2, 4, 6, 10, 14 and 21 days); (2) distance to source of colonizers (close and far series) and (3) leaf surface area to colonize (small, medium, large). Colonization was recorded after 2 days with average meiofauna densities of 480 ind/100 cm² (close) and 1350 ind/100 cm² (far) of leaf surface area, while on average 400 ind/100 cm² were collected from the natural seagrass plants. In this early phase, the meiofauna diversity was high, with on average 8 taxa. A longer period of colonization (21 days) showed an increased meiofaunal density and diversity (average density: 3220 ind/100 cm², 13 taxa). Increasing meiofauna colonization with time is probably related to the development of a biofilm making the leaf more attractive for meiofauna. The effect of distance was not so pronounced as that of time. Total absolute densities were highest in the far series (5 m away from natural seagrass patch), mainly because of nematode densities. Meiofauna diversity was lower in the far series than in the close series (at the border of the natural seagrass patch). A larger individual leaf surface area did not affect the overall meiofauna densities but had a significant positive effect on copepod densities. Larger surface areas promoted the presence of epiphytic copepod families such as Tegastidae and Dactylopusiidae. Overall, we found a rapid recovery of meiofauna in fragmented seagrass beds with primary colonizers (both nematodes and benthic opportunistic copepods) originating from the sediment and later colonizers as epiphytic copepods and their nauplii from the local seagrass regeneration pool.     

Dynamics of gonadosomatic index of fish with indeterminate fecundity between subsequent egg batches: application to Japanese anchovy Engraulis japonicus under captive conditions

The gonadosomatic index (GSI) is widely used as a simple measure of reproductive capacity, but its validity has often been questioned. This study showed the inter-spawning variation in the predicted GSI of Japanese anchovy using the gravimetric oocyte packing density method. Time course sampling showed that final oocyte maturation and subsequent ovulation occurred from afternoon to evening on the day of spawning. Oocyte in vitro assay, however, suggested that the timing of the spawning could be predetermined by midnight the day before spawning. Models predicted that the GSI of a female just after spawning gradually increases until the completion of germinal vesicle breakdown, after which it dramatically rises by 24–53 % per hour within a few hours of the onset of ovulation. This indicates that the predicted GSI of a female increases by 3.5 times within about 19 h before ovulation, even if the relative batch fecundity remains constant.     

The “pelagic larvaton” and its role in the biology of the World Ocean,with special reference to pelagic larvae of marine bottom invertebrates

Ecological subdivision of marine organisms is often based on two characteristics: presence in a defined environment, and types of locomotion (degree of free active movement) in such an environment. The use of these characteristics results in a simple scheme: (1) Inhabitants of the boundary surface “ocean-atmosphere” (a zone including not only the surface film but also the thin subsurface water layer below it and the air layer just above it, i.e., pleuston and neuston). (2) Inhabitants of the deeper water layers of the ocean i.e., excluding the zone mentioned under (1): (a) passively drifting forms with very limited locomotory capacity, moving practically in the vertical plane only (plankton); (b) actively moving forms which migrate both vertically and horizontally (nekton). (3) Inhabitants of the “bottom”-benthos (level-bottom of oceans and coastal waters, tidal zones up to the upper supralittoral, different types of drifting and floating substrata, e.g. ship bottoms, harbour structures, buoys, driftwood, sargassum, whales, etc.). This simple scheme is essentially based on characteristics of adults. If developmental stages are considered, pelagic larvae of bottom invertebrates, eggs and larvae of fishes and other forms, usually present only temporarily in the plankton, neuston, and pleuston, can be distinguished as “mero-plankton”, “mero-neuston” and “mero-pleuston”, from the permanent “holo”-components of these groups. Division into “mero”-subgroups opposes all these larvae to those of planktonic, neustonic and pleustonic forms developing within the “parental” groups and their environments. However, the last category of larvae in the light of world-wide distribution of the seasonal reproductive pattern of marine invertebrates and some other organisms — especially in temperate and high latitudes — can also be rated to some degree as “mero”-(not “holo”-) components. The present paper proposes to unite all larvae of marine invertebrates (and of other organisms) undergoing pelagic development into one biological group, the “pelagic larvaton”. The main characteristic for all forms of this group is the presence of one and the same life-cycle stage in one and the same environment. All forms of the “pelagic larvaton” are, to various degrees, biologically different from their respective adult forms. Even the pelagic larvae of the holoplanktonic species exhibit some differences. Within the “pelagic larvaton”, 3 subgroups can be distinguished on the basis of their ecological peculiarities;

1. Larvae undergoing their whole development in an environment different from that inhabited by their parents and belonging to a group different from that of their parental forms; e.g. the pelagic larvae of bottom invertebrates which develop in the plankton, neuston or pleuston.
2. Larvae undergoing development in the same general pelagic environment, but in “non-parental” ecological groups; e.g. larvae of nektonic species developing in the plankton, neuston or pleuston; larvae of planktonic species in the neuston or pleuston; larvae of neustonic and pleustonic species in the plankton.
3. Larvae undergoing development in the “parental” groups; e.g. larvae of planktonic species in the plankton, of neustonic species in the neuston, or of pleustonic species in the pleuston.

In contrast to the 5 ecological groups: benthos, plankton, nekton, neuston and pleuston, the “pelagic larvaton” represents rather a biological than an ecological group. The “pelagic larvaton” comprises the 5 ecological groups and maintains the permanent turnover of organic substances between water and bottom. This group short-circuits the interrelations between the 5 ecological groups in all possible combinations. The existence of the “pelagic larvaton” presents another illustration of the unity of the biological nature of the oceans. The present paper also discusses the specific distributional patterns of the pelagic larvae of bottom invertebrates and their biological role in the seas.     

A hierarchical Bayesian non-linear spatio-temporal model for the spread of invasive species with application to the Eurasian Collared-Dove

The spread of invasive species is a long studied subject that garners much interest in the ecological research community. Historically the phenomenon has been approached using a purely deterministic mathematical framework (usually involving differential equations of some form). These methods, while scientifically meaningful, are generally highly simplified and fail to account for uncertainty in the data and process, of which our knowledge could not possibly exist without error. We propose a hierarchical Bayesian model for population spread that accommodates data sources with errors, dependence structures between population dynamics parameters, and takes into account prior scientific understanding via non-linear relationships between model parameters and space-time response variables. We model the process (i.e., the bird population in this case) as a Poisson response with spatially varying diffusion coefficients as well as a logistic population growth term using a common reaction-diffusion equation that realistically mimics the ecological process. We focus the application on the ongoing invasion of the Eurasian Collared-Dove.     

A new regeneration approach to cation resins with aluminum salts: application of desalination by its mixed bed

A novel method for the regeneration of cation exchange resins by aluminum (Al) salts was investigated in order to improve the regeneration efficiency of resins and reduce the dosage of regenerant. The influences of Al³⁺ concentration and the pH of regeneration solution on resin transformation had been studied. The desalination experiments were carried out to evaluate the characteristics of the Al form resins. Experimental results showed that the regeneration rate of resins was strictly dependent on Al3+ concentration and the pH of the solution. Compared to the conventional regeneration method, the Al form mixed bed exhibited the same desalination capability as the H form mixed bed (MB), and the total organic carbon (TOC) removal was up to 90%, clearly higher than that of the H form. Al salt solution could be utilized repeatedly to regenerate Al form resins.     

A fuzzy goal programming with interval target model and its application to the decision problem of renewable energy planning

Environmental and Ecological Statistics - Optimizing sustainable renewable energy portfolios is one of the most complicated decision making problems in energy policy planning. This process involves...     

Method of estimating the standing stock of Trochus niloticus incorporating Landsat satellite data,with application to the trochus resources of the Bourke Isles,Torres Strait,Australia

The habitat of Trochus niloticus in the Bourke Isles, Torres Strait, was classified into areas of a Landsat image, using high-ratio values of green (Band 2) to red (Band 3) light, along the windward reef margins. These shallow-water (< 15 m) areas have a coral and rubble/algal pavement cover, which constitutes the optimal habitat for this gastropod. The habitat was sampled to estimate the abundance of T. niloticus. The proportion of commercial-sized individuals was estimated by measuring the basal width of all individuals in a sample. A multistage sample design incorporating three spatial scales -100 m² (transect), 1500 m² (site) and 1 km² (reef) — was used to provide variance estimates for sample-design optimisation and to provide data on the spatial variation of abundance. Most variation (68%) in abundance was within reefs and was attributable to differences in reef cover. Variations in abundance and time costs for sampling 2 and 4 m transects were compared; the 2 m transect was more efficient than the 4 m transect. The abundance estimates were combined with habitat-area estimates and the proportion of commerical-sized individuals was estimated at a standing stock of 186000 (24% precision), or 14 t of commerical-sized T. niloticus.     

Using regression models to evaluate the formation of trihalomethanes and haloacetonitriles via chlorination of source water with low SUVA values in the Yangtze River Delta region,China

The purpose of this study was to develop the multiple regression models to evaluate the formation of trihalomethanes (THMs) and haloacetonitriles (HANs) during chlorination of source water with low specific ultraviolet absorbance (SUVA) in Yangtze River Delta, China. The results showed that the regression models of THMs exhibited good accuracy and precision, and 86–97 % of the calculated values fell within ±25 % of the measured values. While the HANs models showed relatively weak evaluation ability, as only 75–83 % of the calculated values were within ±25 % of the measured values. The organic matter [dissolved organic carbon (DOC) or UV absorbance at 254 nm] and bromide exerted the most important influence on the formation of HANs. While for THMs, besides the organic matter and bromide, reaction time was also a key factor. Comparing the models for total THMs (T-THMs) in this study with others revealed that the regression models from the low SUVA waters may have low DOC coefficients, but high bromide coefficients as compared with those from the high SUVA waters.     

The application of artificial neural networks to flow and phosphorus dynamics in small streams on the Boreal Plain,with emphasis on the role of wetlands

Historically, management strategies in Canada's boreal forest have focused on forest polygons and terrestrial biodiversity to address ecological considerations in forest management. The Forest Watershed and Riparian Disturbance (FORWARD) project examines the problem from a watershed perspective rather than a forest polygon viewpoint. The main objective of this study was to devise an artificial neural network (ANN) modeling tool that can predict flow and total phosphorus (TP) concentration for ungauged watersheds (where daily flow is not monitored). This dictates that all inputs should be easily accessed via a public domain database, like the Environment Canada weather database, without the need to install flow gauges in each modeled watershed. Daily flow and TP concentration for two of the project watersheds were modeled using ANNs. The two watersheds (1A Creek, 5.1 km² and Willow Creek, 15.6 km²) were chosen to reflect variations in wetland area and composition in the study area. Flow was modeled with a feed-forward multilayer perceptron ANN trained with the error back-propagation algorithm. Simulated values for flow were then used, as inputs, to model TP concentration using the same neural networks algorithm. One hidden layer with three slabs; each operating with a different activation function was utilized to simulate the conceptual differences between base flow, snowmelt, and storm events. Time domain analysis was conducted to identify possible model time-lagged inputs reflecting the time dependency of the modeled variables. Spectral analysis was used to address data hystereses. Our results highlight the capabilities of ANN in modeling complex ecosystems and highly correlated variables. Results also indicated that more research towards the phosphorus dynamics in wetlands is required to better represent the impact of wetland area and composition on the water-phase phosphorus in ANN modeling.     

Modeling effects of toxin exposure in fish on long-term population size, with an application to selenium toxicity in bluegill (Lepomis macrochirus)

A primary goal in ecotoxicology is the prediction of population-level effects of contaminant exposure based on individual-level response. Assessment of toxicity at the population level has predominately focused on the population growth rate (PGR), but the PGR may not be a relevant toxicological endpoint for populations at equilibrium. Equilibrium population size may be a more meaningful endpoint than the PGR because a population with smaller equilibrium size is more susceptible to the negative effects of environmental variability. We address the individual-to-population extrapolation problem with modeling utilizing classical mathematical theory. We developed and analyzed a general model applicable to many freshwater fish species, that includes density-dependent juvenile survival and additional juvenile mortality due to toxicity exposure, and we quantified effect on equilibrium population size as a means of assessing toxicity. Individual-level effects are typically greater than population-level effects until the individual effect is large, due to compensatory density-dependent relationships. These effects are sensitive to the recruitment potential of a population, in particular the low-density first-year survival rate S_b. Assuming high S_b could result in underestimating effects of population-level toxicity. The equilibrium size depends directly on S_b, the reproductive potential, the toxin concentration at which mean mortality is 50% (LC₅₀), and the rate at which individual mortality increases with increasing toxin concentration. More experimental data are needed to decrease the uncertainty in estimating these parameters. We then used existing data for selenium toxicity in bluegill sunfish to parameterize a simulation version of the model as an example to assess the effects of environmental stochasticity on toxicity response. Effects of environmental variability resulted in simulated extinctions at much lower toxin concentrations than predicted deterministically.     

Stomach contents and size-frequency distributions of two coexisting sea star species,Astropecten aranciacus and A. bispinosus,with reference to competition

Stomach contents of the sea star species Astropecten aranciacus (L.) and A. bispinosus (Otto) consisted of roughly the same sort of prey, mostly bivalves and irregular sea urchins. However, the two predators ingested prey of different size classes. The stomach contents of A. bispinosus reflected the size distribution of the benthic macrofauna, while larger prey was more frequent in the stomach contents of A. aranciacus. As the density of prey in the investigated area is low, A. aranciacus and A. bispinosus are likely to compete for food. Possible mechanisms reducing the effect of competition are discussed.     

Assessing the parameterisation of the settling flux in a depth-integrated model of the fate of decaying and sinking particles, with application to fecal bacteria in the Scheldt Estuary

The fate of reactive tracers is often modelled by depth-averaged equations. When integrating the depth-resolved equations, it appears that the term describing the settling of particles is dependent on the concentration just above the bottom. Because in a depth-averaged framework this quantity is not available, the settling term needs to be parameterised. The most natural choice is to make the settling flux dependent on the average concentration. This approximation is acceptable if the water column is well mixed, but these conditions are not necessarily met in real applications. Therefore, this study aims at assessing and understanding the error made by using a depth-averaged model in a range of realistic conditions. For the definition of these conditions, typical values for the Scheldt Estuary and the Dutch-Belgian coast were taken. The realistic inspiration for the reactive tracer in this study is the fecal bacterium Escherichia coli, whose own dynamics are characterised by settling and gradual decay by mortality. In an attempt to understand the relative importance of several factors like settling, mortality, mixing and stratification on the error made by a depth-averaged approach, a number of simplified test cases were investigated. It follows that, as expected, the error is acceptable if the situation is mixing-dominated. However, the effect of mortality and stratification was less obvious in advance. For instance, it appeared that errors can also be significant if settling and mortality have the same characteristic timescales. Stratification often has the effect to increase the error made by the depth-averaged model.     

A density-gradient column for determining the specific gravity of fish eggs,with particular reference to eggs of the mackerel Scomber scombrus

A new method is described for determining the specific gravity of fish eggs. The technique requires the preparation of a stable column of a continuously graded solution of sea-water salts such that a specimen introduced into the column settles at a level of known specific gravity, where it is in hydrostatic equilibrium with the fluid in the column. The method allows the simultaneous measurement of specific gravity of a number of specimens continuously throughout development and is suitable for use aboard a vessel at sea. Differences of specific gravity may be resolved to a precision of better than 4x10^-5; as an example of use of the method, the specific gravity of eggs of the mackerel Scomber scombrus L. declined during development within the range 1.0205 to 1.0245; unfertilized eggs displayed a continuous increase of specific gravity.