Global offshore wind power is rapidly developing and has a broad market. China has the advantage of developing offshore wind power, which is the direction of future development of China's power ...generation industry. Because of the high maintenance and repair costs as well as the large sizes of wind power structures, damage to them could cause loss of lives and property. In this paper, a health monitoring method for analyzing offshore wind power structures based on a genetic algorithm and an uncertain analytic hierarchy process (AHP) is proposed. The uncertain analytic hierarchy process (AHP) is used to establish the hierarchical model. After calculating the weight range of each part, the optimal weight is obtained through the training and optimization of genetic algorithm, and the comprehensive weight table is obtained. Finally, the grading of health condition of the whole structure can be obtained by inputting the health indicators of each part based on the statistical distribution for weighted calculation. Based on the qualitative analysis of the uncertain analytic hierarchy process and the quantitative analysis of the genetic algorithm, the method is shown to reliably monitor the health of offshore wind power structures, reduce maintenance costs, and ensure staff safety. Both simulation and actual measurement experiments are performed in this study. The simulation based on the vibration data proves that the proposed structural health monitoring method for offshore wind power structures can evaluate the grading of health condition rapidly and accurately, using data in real time. Through the training and verification of simulation data, the accuracy of prediction after training can exceed 98%. Through a verification experiment using actual measured data, the vibration data measured by the offshore wind power structure during the healthy service period are evaluated. The evaluation results are found to be consistent with the actual operation state of the wind power structure. The proposed method can be used for quick, real-time evaluations.
•The method can quickly and accurately assess the health status in the absence of fault data.•The method combines the qualitative analysis of uncertain analytic hierarchy process and genetic algorithm.•The method can continuously optimize and update the weights based on the actual measured data.•The method has been verified by actual and simulation data to enhanced its credibility.
Conservation planners use bioenergetic models to develop habitat objectives that satisfy energetic demands of waterfowl during nonbreeding periods. In turn, natural resource managers should estimate ...yield and availability of natural and cultivated waterfowl forage to monitor contributions to objectives and support adaptive resource management. Because bioenergetic models are particularly sensitive to unharvested flooded croplands, we developed a rapid methodology to estimate biomass of unharvested flooded corn (Zea mays) and tested our methodology in impounded corn fields planted and flooded in western Tennessee during autumn and winter of 2019–2021. We evaluated accuracy of our rapid assessment method and conducted simulations to assess variance‐bias trade‐offs relative to sample size. Rapid assessments lasted 20 min ± 10 minutes per field. Our rapid assessment method underestimated number of kernels per ear by 2.6% ± 0.5%. After adjusting for underestimation bias, corn biomass across all surveys was 5,500 kg/ha ± 250 kg/ha, which is similar yield to previous literature from waterfowl impoundment fields. Sampling 15 ears per field allowed field biomass to be estimated within acceptable accuracy (i.e., variance SE of mean percent error <1.8%). We recommend our rapid yield assessment method be incorporated into habitat monitoring protocols to efficiently and precisely estimate corn biomass for improved conservation planning initiatives. Additionally, our rapid assessment method allows managers to monitor field yield rapidly, enabling estimates of corn depletion and availability throughout the nonbreeding season for waterfowl to support management decisions.
Because waterfowl bioenergetic models are particularly sensitive to unharvested flooded croplands, we developed a rapid methodology to estimate biomass of unharvested flooded corn (Zea mays) and tested our methodology in impounded corn fields planted and flooded in western Tennessee during autumn and winter of 2019–2021. We recommend our rapid yield assessment method be incorporated into habitat monitoring protocols to efficiently and precisely estimate corn biomass for improved conservation planning initiatives.
Soil arsenic (As) contamination by anthropogenic and industrial activities is a problem of global concern. This pilot study demonstrates the feasibility of adapting the diffuse reflectance ...spectroscopy (DRS) approach using the visible near infrared (VisNIR) spectra for detecting soil As pollution. Further, spatial variability of soil As contamination was evaluated combining DRS based predictions and two geostatistical algorithms. The raw reflectance spectra were preprocessed using three spectral transformations for predicting soil As contamination using three multivariate algorithms. Quantitatively, better accuracy was produced by the elastic net-first derivative model (R2=0.97, residual prediction deviation=6.32, RPIQ=7.33, RMSE=0.24mgkg−1). The prediction of soil As was dependent on the close association between soil As and spectrally active soil organic matter and Fe-/Al-oxides. Moreover, the As pollution risks hotspots were reasonably identified using ordinary kriging and indicator kriging interpolations based on DRS predicted As values.
•Soil contamination with As is a serious environmental concern.•We used DRS to predict soil As content of 200 soils collected from a landfill site.•ENET model using VisNIR spectra produced best As prediction.•DRS prediction followed by kriging produced spatial variability map of soil As.•DRS prediction with indicator kriging identified As pollution hotspots.
Non-indigenous species (NIS) are recognized as a global threat to biodiversity and monitoring their presence and impacts is considered a prerequisite for marine environmental management and ...sustainable development. However, monitoring for NIS seldom takes place except for a few baseline surveys. With the goal of serving the requirements of the EU Marine Strategy Framework Directive and the EU Regulation on the prevention and management of the introduction and spread of invasive alien species, the paper highlights the importance of early detection of NIS in dispersal hubs for a rapid management response, and of long-term monitoring for tracking the effects of NIS within recipient ecosystems, including coastal systems especially vulnerable to introductions. The conceptual framework also demonstrates the need for port monitoring, which should serve the above mentioned requirements but also provide the required information for implementation of the International Convention for the Control and Management of Ships Ballast Water and Sediments. Large scale monitoring of native, cryptogenic and NIS in natural and man-made habitats will collectively lead to meeting international requirements. Cost-efficient rapid assessments of target species may provide timely information for managers and policy-advisers focusing on particular NIS at particular localities, but this cannot replace long-term monitoring. To support legislative requirements, collected data should be verified and stored in a publicly accessible and routinely updated database/information system. Public involvement should be encouraged as part of monitoring programs where feasible.
•Monitoring of non-indigenous and cryptogenic species/populations needs to be initiated.•Monitoring should focus on bridgehead sites and dispersal hubs.•Monitoring methods should be internationally harmonized.•Rapid assessments of particular species may provide timely but limited information.•Monitoring data should be assembled in open access continually updated databases.
•Three different tree biodiversity rapid assessment methods for cocoa fields tested.•A stepwise approach with stakeholder engagement was used to evaluate results.•Method with similar size plots set ...up on four directions was the most accurate.•The method can be applied at large-scale with few resources to collect data.•Farmers can report accurately on tree species and participate in data collection.
Biodiversity is recognized as an essential part of sustainable development efforts, however reducing biodiversity loss is a key global challenge that requires updated data on biodiversity status at different scales. Cocoa agroforests include tree species besides cocoa, a practice beneficial to biodiversity, ecosystem conservation and farming households. We present a stepwise procedure to test and select a method that rapidly assesses biodiversity in cocoa agroforests based primarily on species richness and counts of non-cocoa trees. Three rapid assessment methodologies (RapidBAM) with different sampling procedures were tested in three phases: calibration, testing and evaluation. Results showed the method using the lowest number of sample plots with a minimum area coverage and a consistent sampling time (regardless of farm context) provided the most accurate and straightforward assessment. Farmers accurately reported qualitatively on species, complimenting quantitative data produced by RapidBAM. Collecting biodiversity data with RapidBAM proved valuable to collect data at large-scales and is applicable to different landscapes. Monitoring biodiversity with fewer required resources than conventional methods is a relevant outcome, which can help defining efficient biodiversity-friendly farming practices.
Building resilience is a critical response to climate change. Developing countries are the most vulnerable to climate change, yet planning rarely considers how broader community development ...interventions can enhance resilience and support development. One solution is resilience assessment. However, few assessment frameworks exist that are sufficiently simple to empower communities to build resilience and take ownership of adaptation efforts. This article provides an example of a 27-question framework applied with two Cambodian communes (communities) to assess and understand trends in resilience over time. It is structured around community development outcomes of economic development, environmental quality, infrastructure that matches demands, community self-reliance and capacity to adapt to climate change; it also assesses how inputs and planning contribute to these outcomes. Longitudinal analyses reveal improvements over time driven primarily by commodity values. However, the sustainability of some of these improvements is questionable given volatile commodity markets and land degradation. Oversensitivity in the assessment is acknowledged as awareness increases over time, which can be conflated with poor performance. Maladaptive pathways may be unavoidable without building resilience by attending to broader community development issues, e.g. psychological wellbeing and education on alternative livelihoods. This article makes a significant contribution to community resilience by providing a simple resilience assessment framework that has demonstrably empowered communes to adapt to change. It is novel in the use of assessment design and process principles that build reflection on the drivers of resilience and development. Critical issues remain in the power dynamics of aid dependence, weakening of family bonds and patron-client relationships that affect resilience building in Cambodia.
•Simple assessment tools can identify changes in resilience.•Planning and asset accumulation build resilience.•Resilience building may provide critical development praxis pathway.•Sustained resilience building also requires community development.
Contaminants of Emerging Concern (CECs) have been documented across the seven continents, including Antarctica, and are likely an impediment to the sustainable management of natural resources. Most ...studies to date have relied on sweeping chemistry surveys, reliant upon sophisticated instrumentation. This approach is expensive, relies on limited laboratory capacity, and generates results that are spatially and temporally constrained. Here we review existing approaches that can overcome these limitations by focusing on effects-based monitoring. Passive samplers can generate long-term records regarding the occurrence of CECs. As samples are concentrated, their analysis can be achieved using equipment that will be more common and less expensive. A second approach involves rapid test methods for single compounds, including test strips, ELISA assays, and mobile phone-based analytic tools. These can provide inexpensive CEC presence data for many field sites and can be used to stratify sampling and thereby reduce cost. Identifying the presence of a single compound can often shed light on the likely presence of entire groups of chemicals. Pairing these chemistry-derived approaches with geospatial modeling to predict CEC presence and concentrations across watersheds has already been applied in several large watersheds. Utilizing available ecotoxicological knowledge bases provides an opportunity to link modeled CEC occurrence and concentrations with likely adverse biological responses. Finally, confirmatory on-site exposure experiments can corroborate the presence or absence of biological effects hypothesized from the above chain of evidence to provide natural resource managers with information to make conservation decisions.
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