Foliar nutrient and metal levels of crops in the Mount Cameroon area—reference values for plant nutrition and environmental monitoring

The growing population number and traffic loads, increasing environmental pressures, agricultural intensification, and the establishment of Mount Cameroon National Park demand farsighted environmental management in the region and the definition of a favorable ecological status. Since plants grow in the interface between soils and the atmosphere they can be used as passive biomonitors for the environmental quality. At the same time, the accumulation of nutrients and pollutants in crops is linked to human health, so that foliar elemental levels can be used as an integrative measure for environmental pollution and impact assessment. In the present study, we collected leaf samples of plantain, cassava, cocoyam, and maize on 28 sites at the southern flanks of Mt. Cameroon and determined 20 chemical elements. Air pollution in the study area comes from biomass and waste burning mainly, but emissions from traffic and a large refinery were believed to also play a significant role. However, spatial patterns in foliar elemental concentrations reflected the geochemistry rather than specific sources of pollution. Significant differences in foliar metal and nutrient levels were observed between the four species, indicating a different demand and uptake of specific elements. The results were compared to published data on nutrient concentrations in the tested species and the so-called reference plant. The data can be used as a baseline for future studies in plant nutrition and the environmental monitoring in inner tropical regions where these crops are grown.     

A Novel Formulation for Designing a Monitoring Strategy: Application to the Design of a River Quality Monitoring System

In this work, we propose a technique to automatically optimize the monitoring of any distributed indicator (concentration of a substance along a river, blood pressure of a patient over time, etc.) for which a reliable estimate is previously available. From a mathematical point of view, the problem is based on obtaining a reliable estimate of the chosen indicator (e.g., by numerical simulation), and then solving a multi-objective optimization problem (with mixed real and integer variables) whose solution must provide an efficient and satisfactory monitoring strategy. As an illustrative case, we show the steps to follow in order to implement that strategy when designing a system for monitoring water quality in a river. Finally, we present and analyze the results when applying the proposed technique to study a real case in the Neuse River (North Carolina, USA).     

Spatial Validation of Land Use Change Models Using Multiple Assessment Techniques: A Case Study of Transition Potential Models

Using land use and cover change (LUCC) models for the urban growth planning, environmental assessment, and decision-making needs the establishment of an appropriate level of confidence in their performance. The objective of this research is to explore the importance of using multiple assessment techniques in order to fairly evaluate the performance of land use models. An application is conducted by using the Land Change Modeler for Ecological Sustainability (LCM) which is an empirical and transition potential model. LCM is applied to model the agricultural to developed areas transition in Rennes metropolitan area (France). The land demand is estimated using the Markov Chain model; whereas, the transition potential map is implemented using the Multi-Layer Perceptron Neural Network (MLP) method based on historical changes and driving variables. The model performance is assessed based on a variety of the most commonly used validation techniques. At the study area level, the correctness and disagreement analysis shows that LCM performs better at predicting the amount than the allocation of developed areas. Additionally, landscape metrics reveal that LCM tends to predict a fragmented urban form, which seems evident because of the large number of the individual urban patches. At the municipality level, the error budget analysis shows that the model performance, which varies highly between different subareas, needs to be improved. Moreover, the cross-tabulation between the transition potential map and both the observed and the predicted agricultural to developed areas transitions reveals that the order of the transition potential values does not perfectly fit the observed change; whereas, the predicted change is not solely limited to areas with high potential.     

A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations

Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.     

An Approach to Reaeration Coefficient Modeling in Local Surface Water Quality Monitoring

Reaeration coefficient (k ₂) for River Atuwara, Ogun State, Nigeria was calculated from dissolved oxygen and biochemical oxygen demand data collected over period of 3 months covering the two prevailing climatic seasons in the country. Both the Akaike and Bayesian information criteria were used in the selection and analysis of ten models to identify the most suitable reaeration coefficient (k ₂) model for Atuwara River. Models that passed the confidence limit were subjected to model evaluation using measures of agreement between observed and predicted data such as percent bias, Nash–Sutcliffe efficiency, and root mean square observation standard deviation ratio. The used approach yield better results than empirical models developed for local conditions while it is also useful in conserving scarce resources.