The method matters: A guide for indicator aggregation in ecological assessments

Ecological assessment requires the integration of many physical, chemical, and/or biological quality elements. The choice of the aggregation method of such partial assessments into an overall assessment can considerably affect the assessment outcome – an issue that has been controversially discussed within the scientific community for the last decade. Current practice often considers only two different aggregation methods, the weighted arithmetic mean (additive aggregation) and the one-out, all-out method (minimum aggregation). However, both have important drawbacks. Additive aggregation compensates a bad status of one quality element by a number of elements featuring good status. Minimum aggregation can lead to overly pessimistic assessment results, since only the quality element in the worst status is considered. Here, we introduce a toolbox containing current and new aggregation methods, demonstrate and discuss their properties with simple, didactical examples, and suggest in which situations best to use them. Then, we illustrate the consequences of selected aggregation schemes for ecological river assessment with the case study of the Swiss Modular Concept of stream assessment (SMC), which we apply to ten river reaches in the Mönchaltdorfer Aa catchment in Switzerland. To be able to do so, we used multi-criteria decision analysis, i.e., multi-attribute value theory, to arrange the SMC quality elements into an objectives hierarchy, and to translate their individual assessments into value functions. Our case study revealed that choosing the most appropriate aggregation method particularly matters, if objectives with significantly different qualities are aggregated. We argue that redundant objectives (i.e., quality elements), often found at the lower levels of the objectives hierarchy, should best be aggregated additively allowing for compensation to increase the statistical significance of the results. Further, we suggest that complementary sub-objectives that often occur at higher levels may be optimally aggregated with a mixture of additive and minimum aggregation. Such a mixed method will allow some compensation, but nevertheless penalize for very bad states. Since here we compare commonly used aggregation methods with some which we believe have never been discussed in an assessment context before, our study concurrently informs ecological assessment in theory and in practice.     

Brain size affects responsiveness in mating behaviour to variation in predation pressure and sex ratio

Despite ongoing advances in sexual selection theory, the evolution of mating decisions remains enigmatic. Cognitive processes often require simultaneous processing of multiple sources of information from environmental and social cues. However, little experimental data exist on how cognitive ability affects such fitness‐associated aspects of behaviour. Using advanced tracking techniques, we studied mating behaviours of guppies artificially selected for divergence in relative brain size, with known differences in cognitive ability, when predation threat and sex ratio was varied. In females, we found a general increase in copulation behaviour in when the sex ratio was female biased, but only large‐brained females responded with greater willingness to copulate under a low predation threat. In males, we found that small‐brained individuals courted more intensively and displayed more aggressive behaviours than large‐brained individuals. However, there were no differences in female response to males with different brain size. These results provide further evidence of a role for female brain size in optimal decision‐making in a mating context. In addition, our results indicate that brain size may affect mating display skill in male guppies. We suggest that it is important to consider the association between brain size, cognitive ability and sexual behaviour when studying how morphological and behavioural traits evolve in wild populations.     

Identifying optimal groundwater remediation strategies through a simulation-based PROMETHEE-TOPSIS approach: An application to a naphthalene-contaminated site

Abstract

The aim of this paper is to develop a simulation-aided PROMETHEE-TOPSIS approach for the selection of the most desirable groundwater remediation strategies. The combination methods enables a careful evaluation of the identified remediation alternatives in which their strong and weak points can be detected and a ranking is provided which facilitates the final selection for the decision-maker. The capabilities and effectiveness of the developed method are illustrated through a case study on the remedial alternative selection for a naphthalene contaminated site in Anhui, China. Four attributes (i.e., total pumping rate, total cost, mean residual contaminant concentration and maximum excess life time cancer risk) for fifty remedial alternatives in each duration are considered and analytic hierarchy process is used to determine the weight of attributes importance. The results demonstrates that the developed method could help decision makers obtain the useful ranking information strategies that covering a variety of decision-relevant remediation options, which is beneficial for public health and environmental protection.     

Epithelial-to-mesenchymal transition and different migration strategies as viewed from the neural crest

Epithelial-to-mesenchymal transition (EMT) is a dynamic process that produces migratory cells from epithelial precursors. However, EMT is not binary; rather it results in migratory cells which adopt diverse strategies including collective and individual cell migration to arrive at target destinations. Of the many embryonic cells that undergo EMT, the vertebrate neural crest is a particularly good example which has provided valuable insight into these processes. Neural crest cells from different species often adopt different migratory strategies with collective migration predominating in anamniotes, whereas individual cell migration is more prevalent in amniotes. Here, we will provide a perspective on recent work toward understanding the process of neural crest EMT focusing on how these cells undergo collective and individual cell migration.     

Implementing a spatial model of Urban Carrying Capacity Load Number (UCCLN) to monitor the environmental loads of urban ecosystems. Case study: Tehran metropolis

The non-linear, unexpected and severe responses of ecosystems to the environmental changes crossing ecological thresholds or environmental limits, necessitate the regular monitoring of the human-induced pressures to the urban ecosystems. The present study aims to introduce a spatial decision support system for sustainable environmental planning and management of urban ecosystems by establishing an Urban Carrying Capacity Load Number model (UCCLN) based on carrying capacity concepts and sustainability principles .This model, by applying 30 temporal and spatial indicators continuously monitors the environmental loads on the urban ecosystems. Environmental load was represented by load number index. It was calculated in each zone of study area (urban districts). Geographical Information System (GIS) was used to establish UCCLN model and Spatial Decision Support System (SDSS). The study area was Tehran metropolis, the capital of Iran. The results showed that none of the 115 urban districts of Tehran had optimal Total Load Number (TLN) ranging from (10 to100); 7 districts (6%) had low-to-medium range of TLN (TLN = 100–200); 11 districts (9.5%) had medium-to-high range (TLN = 200–300); 57 districts (49.5%) had high-to-very high range (TLN = 300–400); 40 districts (34.7%) had the TLN range of very high-to-critical (TLN = 400–500); and none of them had the TLN of 500. Furthermore, the results revealed that Tehran has already overshot its ecological thresholds. Not only most of the 30 indicators of environmental pressure in most of the districts (85%) had high DCC and LN scores, but also most of the 115 districts obtained high DCC, and as a result LN scores. The need for developing more efficient urban planning and management strategies to cope with the increasing environmental loads in the study area is inevitable.