Evaluating knowledge integration and co-production in a 2-year collaborative learning process with smallholder dairy farmer groups

Although knowledge integration and co-production are integral to transdisciplinary approaches to foster sustainable change in social–ecological systems, this type of research is usually not evaluated based on assessments of the learning process. While participants are meant to be central in such approaches, too often, their perspectives are not central to the evaluation. Moreover, there is limited empirical information about how new knowledge is transformed into action. We respond to these knowledge gaps by analyzing (A) farmers’ perspectives on the collaborative learning process and (B) how farmers’ new knowledge can serve as the basis for changed actions. Theoretically, we are guided by second-order cybernetics and have integrated the Control Loop Model with Learning Loops to extend Kirkpatrick (Evaluating training programs: the four levels, 2nd edn. Berrett-Koehler Publisher, San Francisco, 1998) four-level evaluation scheme. We apply this to evaluate a 2-year collaborative learning process with two smallholder dairy farmer groups in Nakuru County, Kenya that aimed to co-develop local sustainable pathways to reduce milk losses. Results showed that farmers learned by (1) implementing corrective actions based on known cause–effect relations (single-loop learning); (2) discovering new cause–effect relations and testing their effect (double-loop learning); and (3) further questioning and changing their aims (triple-loop learning). Highlighting the importance of knowledge integration and co-production, this collaboration between farmers, researchers, and field assistants improved the farmers’ ability to respond, adapt, and intentionally transform their farming system in relation with complex sustainability challenges. Results demonstrate that the potential of our evaluation scheme to better reflect learning and empowerment experienced by actors involved in transdisciplinary research for sustainability.     

The environmental Kuznets curve and CO2 emissions in the USA

Environmental Science and Pollution Research - In this paper, we analyze the existence of the environmental Kuznets curve as reported by Kuznets (Am Econ Rev 5:1–28, 1955) by using the...     

Movements of spotted seals (<Emphasis Type="Italic">Phoca largha</Emphasis>) in the Sea of Okhotsk according to satellite tagging data

For the first time, satellite tagging of spotted seals (Phoca largha) has been performed in three regions of the Sea of Okhotsk: Chkalov Island in Sakhalin Bay, Ptichy Island, and the Bolshaya River mouth on the western coast of Kamchatka. As a result, regions inhabited by the seals in different periods of their life cycle and differences in the pattern of water area use by animals from different regions have been revealed. The seals from the western Kamchatka coast have covered greater distances during the observation period, compared to the animals from Sakhalin Bay. In the reproductive period, the seals from the western coast spread over the entire northern part of the Sea of Okhotsk, whereas the animals from the Sakhalin Bay move only to the Tatar Strait, the Sea of Japan. None of tagged seals has been located in the “reproductive center” at the eastern coast of Sakhalin. The seals tagged in different regions of the Sea of Okhotsk have never been located in the same place during the entire annual cycle, suggesting that the sea is inhabited by two reproductively isolated groups of ringed seals.     

Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches

Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325–1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R² (LL R²) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design.     

Water,sanitation, hygiene and waste disposal practices as COVID-19 response strategy: insights from Bangladesh

Environment, Development and Sustainability - The COVID-19 pandemic has caused a global emergence, and the absence of a proven vaccine or medicine has led to the implementation of measures to...     

Recycling food and agriculture by-products to mitigate climate change: a review

Food loss and waste is a major issue affecting food security, environmental pollution, producer profitability, consumer prices, and climate change. About 1.3 billion tons of food products are yearly lost globally, with China producing approximately 20 million tons of soybean dregs annually. Here, we review food and agricultural byproducts with emphasis on the strategies to convert this waste into valuable materials. Byproducts can be used for animal and plant nutrition, biogas production, food, extraction of oils and bioactive substances, and production of vinegar, wine, edible coatings and organic fertilizers. For instance, bioactive compounds represent approximately 8–20% of apple pomace, 5–17% of orange peel, 10–25% of grape seeds, 3–15% of pomegranate peel, and 2–13% of date palm seeds. Similarly, the pharmaceutical industry uses approximately 6.5% of the total output of gelatin derived from fish bones and animal skin. Animals fed with pomegranate peel and olive pomace improved the concentration of deoxyribonucleic acid and protein, the litter size, the milk yield, and nest characteristics. Biogas production amounts to 57.1% using soybean residue, 53.7% using papaya peel, and 49.1% using sugarcane bagasse.

     

Trauma demography and clinical epidemiology of motorcycle crash–related head injury in a neurosurgery practice in an African developing country

Objective: Though motor vehicle crashes (MVCs) were the main cause of head trauma from road traffic injuries (RTIs), motorcycle crashes (MCCs) are now a major cause of RTI-related head injury (HI) in many developing countries.

Methods: Using a prospective database of HIs from a neurosurgical practice in a sub-Saharan African developing country, a cross-sectional survey was conducted for the trauma demography and clinical epidemiology of this MCC-related HI.

Results: Motorcycle crashes accounted for 57% (473/833) of all RTI-related HIs in this registry. The victims, with a mean age of 33.1 years (SD = 18.3), consisted mainly of males (83.1%), those of low socioeconomic status (>90%), and those aged between 20 and 40 years old (56%). MCCs involved only riders in 114 cases (114/473, 32.1%), of which 69% were motorcycle–motorcycle crashes. The HI was moderate–severe in 50.8%; clinical symptomatology of significant HI included loss of consciousness (92%), anisocoria (35%), Abbreviated Injury Scale head (AIS–head) score > 3 (28%), and CT-Rotterdam score > 3 (30%). Extracranial systemic injury involved the limbs most frequently, with an Injury Severity Score (ISS) >25 in 49%. The fatality rate was 24%.

MCC-related HI among pedestrian victims involved more vulnerable age groups (the young and elderly) but have lower mean ISS compared to motorcycle passengers (mean ISS = 23.5 [11.6] vs. 27.4 [13.0]; 95% confidence interval [CI], 1.27–6.49; P = .004). In addition, compared to a contemporary cohort of MVC-related HIs in our registry, MCC victims were older (mean age 34.8 years [18.0] vs. 30.8 [18.4]; P = .002); had higher proportions of certain extracranial trauma like long bone fractures (71 vs. 29%; P = .02); and suffered fewer surgical brain lesions (25.5 vs. 17.2%; P = .004).

Conclusions: Motorcycle crashes are now a significant threat to the heads, limbs, and lives of vulnerable road users in developing countries.