From the attitude-behaviour-gap to a producer-people-gap?

The so-called attitude-behaviour-gap of ecology might have changed to a ?producer-people-gap”. In summer 2017 in Germany, the intention of private house-builders to buy an exterior insulation system based on renewable materials was measured as positive, with a mean of 5.2 on a 1–7 Likert scale. But the intentions of professionals were clearly below, e.g. craftsmen, with an average of 3.6 on the same scale – although both groups, the privates and the professionals, judged that there is a clear trend towards such products.

Because of these findings, an additional investigation of management by producers was conducted in autumn and winter 2017/2018, in which a very critical atmosphere towards renewable materials was found. It was analyzed that the managements` attitudes might not be a basic refusal of renewable material in general, but rather a fear of costs of research and development of new products.

A concept was tested, to see if it would be possible to cause an attitude change within the professional key target groups just by applying marketing instruments. Five articles in key media of this market have been published between February and May 2018. In the following evaluation (n = 150) in May 2018 significant effects of the communication have been measured: The intention of decision-makers in craftsmen`s businesses to buy an exterior insulation system based on renewable material rose significantly (0.01 Lv.) from a mean of 3.6 in 2017 to 4.4 in 2018.     

Hierarchical modeling of count data with application to nuclear fall-out

We propose a method for a Bayesian hierarchical analysis of count data that are observed at irregular locations in a bounded domain of R². We model the data as having been observed on a fine regular lattice, where we do not have observations at all the sites. The counts are assumed to be independent Poisson random variables whose means are given by a log Gaussian process. In this article, the Gaussian process is assumed to be either a Markov random field (MRF) or a geostatistical model, and we compare the two models on an environmental data set. To make the comparison, we calibrate priors for the parameters in the geostatistical model to priors for the parameters in the MRF. The calibration is obtained empirically. The main goal is to predict the hidden Poisson-mean process at all sites on the lattice, given the spatially irregular count data; to do this we use an efficient MCMC. The spatial Bayesian methods are illustrated on radioactivity counts analyzed by Diggle et al. (1998).     

Using land as a control variable in density-dependent bioeconomic models

The bioeconomic analysis of endangered species without consumptive values can be problematic when analysed with density-dependent models that assume a fixed environment size. Most bioeconomic models use harvest as a control variable, yet when modelling non-harvestable species, frequently the only variable under control of conservationists is the quantity of habitat to be made available. The authors explore the implications of this in a model developed to analyse the potential population recovery of New Zealand’s yellow-eyed penguin. The penguin faces severe competition with man for the terrestrial resources required for breeding and has declined in population to perilously low levels. The model was developed to estimate the land use required for recovery and preservation of the species and to compare the results to current tourism-driven conservation efforts. It is demonstrated that land may serve as a useful control variable in bioeconomic models and that such a model may be useful for determining whether sufficient incentives exist to preserve a species. However, the model may generate less useful results for providing a specific estimate of the optimal allocation of land to such a species.     

Single-species versus multiple-species models: the economic implications

Ecologists frequently note the importance of modelling entire ecosystems rather than individual species, but most bioeconomic models in the current literature focus on a single species. While the mathematical difficulty of modelling multiple species may be substantial, it is important to recognise the implications of the single-species assumption to a model’s results. In this paper, the authors address the economic significance of this assumption through the development of an analytical multiple-species model and demonstrate the importance of ecological interrelationships and economic values to the survival of endangered species.     

Multivariate bootstrap confidence regions for abundance vector using

Abundance vector estimation is a well investigated problem in statistical ecology. The use of simple random sampling with replacement or replicated sampling ensures good asymptotic properties of the abundance vector estimators. However, real surveys are based on small sample sizes, and assuming any specific distribution of the abundance vector estimator may be hazardous.In this paper we focus our attention on situations where the population is not too large and the sample size is small. We propose bootstrap multivariate confidence regions based on data depth. Data depth is a geometrical concept of ordering data from the center outwardly in higher dimensions. The Simplicial depth, the Tukey's depth and the Mahalanobis depth are presented. In order to build confidence regions in the presence of a skewed distribution of the abundance vector estimator, the use of Tukey's depth is suggested. The proposed method has been applied to the benthic community of Lake Lesina. A comparison with Mahalanobis depth and standard existing methods is reported.     

Sequential extraction of copper from soils and relationships with copper in maize

We studied copper uptake by maize grown on soils that have been contaminated with CuSO₄. In soil the total copper level ranged from 24 to 135 mg kg^–1. The copper distribution in soil fractions was assessed by sequential extraction, showing that anthropogenic copper is mainly concentrated in oxides fractions. The copper concentration of maize at the maturity stage reached values from 36.3 to 65.9 mg kg^–1 compared to copper levels usually found in non-contaminated crops (5–30 mg kg^–1). Here we demonstrate that copper can be accumulated by maize and that copper concentration in maize can be predicted by equations including copper concentration of soil fractions.     

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.     

非点源污染模型研究进展

随着点源污染的有效控制,非点源污染已成为水体污染的主要因素,如何有效地控制和管理非点源污染已成为水环境整治的一项重要任务。而计算机模型是极其有效的流域非点源污染模拟和污染负荷估算的定量化工具,为非点源污染评价、管理和控制提供了可靠依据。文章综述了非点源污染模型的发展概况及其研究不足,并对模型的发展趋势进行了分析和预测。由于非点源污染随机性大、分布范围广、形成机理模糊、管理控制难度大等特点,未来非点源污染的量化模型研究及其与量化模型有关的相应参数研究、模型与GIS集成研究将成为未来研究的主流。     

Gaps and Mismatches between Global Conservation Priorities and Spending

Abstract:  Several international conservation organizations have recently produced global priority maps to guide conservation activities and spending in their own and other conservation organizations. Surprisingly, it is not possible to directly evaluate the relationship between priorities and spending within a given organization because none of the organizations with global priority models tracks how they spend their money relative to their priorities. We were able, however, to evaluate the spending patterns of five other large biodiversity conservation organizations without their own published global priority models and investigate the potential influence of priority models on this spending. On average, countries with priority areas received greater conservation investment; global prioritization systems, however, explained between only 2 and 32% of the US$1.5 billion spent in 2002, depending on whether the United States was removed from analyses and whether conservation spending was adjusted by the per capita gross domestic product within each country. We also found little overlap in the spending patterns of the five conservation organizations evaluated, suggesting that informal coordination or segregation of effort may be occurring. Our results also highlight a number of potential gaps and mismatches in how limited conservation funds are spent and provide the first audit of global conservation spending patterns. More explicit presentation of conservation priorities by organizations currently without priority models and better tracking of spending by those with published priorities are clearly needed to help make future conservation activities as efficient as possible.     

Source-specific risk assessment for cadmium in wheat and maize: Towards an enrichment model for China

Cadmium (Cd) pollution of agricultural soil is of public concern due to its high potential toxicity and mobility. This study aimed to reveal the risk of Cd accumulation in soil and wheat/maize systems, with a specific focus on the source-specific ecological risk, human health risk and Cd enrichment model. For this we investigated more than 6100 paired soil and grain samples with 216 datasets including soil Cd contents, soil pH and grain Cd contents of 85 sites from China. The results showed that mining activities, sewage irrigation, industrial activities and agricultural practices were the critical factors causing Cd accumulation in wheat and maize cultivated sites. Thereinto, mining activities contributed to a higher Cd accumulation risk in the southwest China and Middle Yellow River regions; sewage irrigation influenced the Cd accumulation in the North China Plain. In addition, the investigated sites were classified into different categories by comparing their soil and grain Cd contents with the Chinese soil screening values and food safety values, respectively. Cd enrichment models were developed to predict the Cd levels in wheat and maize grains. The results showed that the models exhibited a good performance for predicting the grain Cd contents among safe and warning sites of wheat (R² = 0.61 and 0.72, respectively); while the well-fitted model for maize was prone to the overestimated sites (R² = 0.77). This study will provide national viewpoints for the risk assessments and prediction of Cd accumulation in soil and wheat/maize systems.