21603 research outputs found
Sort by
The impact of animal welfare regulations on pork trade: evidence from European countries
No full textWe analyse the impact of stricter national animal welfare (AW) regulations on imports and exports of pork between 13 European countries during the period 1991-2020, a period in which EU directives and national actions related to AW regulations significantly affected pig farming practices. We exploit the fact that some countries have stronger AW regulations for pigs compared with EU's regulations and other countries' regulations. Our analyses utilize a new detailed dataset capturing the dynamics of pig AW regulations over time for several EU member states, taking into account multiple aspects of pig AW that can have significant cost impacts for pork producers. We focus on countries with relatively stringent AW legislation for pigs and countries that are major pork producers. Using panel regression, long-differenced IV, and event study approaches, we find that an increase in the relative stringency of pig AW regulations in a country is associated with a reduction in pork exports. We find mixed evidence suggesting that stricter AW regulations for pigs reduced pork imports. Our results have important implications for other jurisdictions that plan to mandate AW regulations for pigs in the near future
Influence of landscape composition and structure on habitat selection of a large herbivore in managed forests along a latitudinal gradient
No full textLarge herbivores are keystone species in forest ecosystems, influencing forest structure and biodiversity through their selective browsing. Therefore, understanding herbivore habitat selection across spatiotemporal scales in managed forest landscapes is crucial for wildlife and forest management. This study examines how landscape structure (patch size and contiguity, distance to the nearest road) and composition (habitat type and heterogeneity) influence the seasonal habitat selection of moose (Alces alces) across five ecological zones. Using GPS data from 392 adult moose across 21 study sites (56-670N) in Sweden, we combined Hidden Markov Models and Integrated Step-Selection Analysis to apply a patch-landscape approach that considers animals' behavior-specific responses at the scale of individual habitat patches and the broader landscape matrix. This approach allowed us to assess the role of small-scale habitat features and their spatial arrangement within the larger landscape context for moose movement and patch selection, thereby considering both landscape structure and composition. We found a dominance of landscape composition (i.e. habitat type) shaping moose selection at the patch scale, but also context-specific relevance of landscape structure (e.g. distance to the nearest road, patch size and contiguity). Moose preferred deciduous-mixed and young forests and generally avoided proximity to roads. Individuals occasionally selected for large and well-connected forest patches. Our findings highlight that forest management should prioritize preserving and connecting young and mixed-deciduous forest patches to facilitate moose access to their preferred habitats, thereby helping to distribute moose (and potentially browsing pressure) across forest patches within the managed landscape
Balancing detection probability and survey effort in multistate occupancy models: A camera trap simulation analysis
No full textCamera trapping has become crucial in wildlife research, enabling detailed observations of elusive and nocturnal species with limited human interference. The use of occupancy modeling to analyze camera trap data is rapidly increasing, aiding in the assessment of species distribution, multispecies dynamics, and the presence of different states of a species (e.g., reproducing or non-reproducing), while considering imperfect detection. Multistate occupancy models, which capture these different states, are particularly effective tools. However, the design of camera trap studies-typically involving large grids with a limited number of cameras and animal observations-often results in sparse data and low detection probabilities, impacting model performance (e.g., convergence) and inference reliability (e.g., accuracy and precision) in basic occupancy models. The effect of these factors on more complex models (e.g., multistate occupancy models) remains largely unexplored. Here, we conducted a series of simulations with varying detection probabilities, numbers of sites, and survey periods for both single- and multistate occupancy models, to evaluate the impact of these factors on model performance and reliability. Our results revealed that multistate models require higher detection probabilities compared to the single-state models. Additionally, minimum needed detection probabilities decreased as the number of surveys increased for all models. Furthermore, the number of sites required was substantially higher for multistate models compared to single-state models. We conclude that when detection probabilities are low, occupancy models encounter difficulties in fitting and produce unreliable results. Strategies such as deploying clustered cameras, targeted camera placement (e.g., at frequent wildlife paths) or using bait to increase detection rates could be used to address these issues but may introduce other biases. The gained model performance from higher detection probabilities might outweigh these biases. Moreover, different data aggregation strategies in combination with increasing the length of the study can increase detection probabilities, addressing reliability issues; however, this is not always feasible due to time constraints (e.g., season-based research questions). This study highlights key thresholds and considerations for improving the use of multistate occupancy models using camera trap data, aiding in the design of more effective wildlife research studies
Diet changes in food futures improve Swedish environmental and health outcomes
No full textAligning national food systems with global goals is required for sustainable transitions. We examine if realistic, context-specific dietary changes, mindful of Swedish food culture and in line with future scenarios, are sufficient to meet ambitious environmental goals. Here, we quantified diets based on the four Swedish Food Futures scenarios, which reflect prospects of technological development, behavioral change, import trends, and values. Scenario diet nutritional intakes and environmental impacts were quantified and related to health targets and nationally adapted climate, cropland, and biodiversity boundaries. Dietary changes in scenario diets reduced environmental impacts by 30% compared to current diets. No scenario stayed within the strictest climate boundary without removal of energy-related food chain emissions-resulting in 50-60% additional impact reduction. Food chain waste reduction by 50% resulted in an additional 8-10% reduction in impacts. Dietary changes can make substantial contributions to staying within global climate, cropland, and biodiversity boundaries and meet health targets, but improvements in production and waste reductions are also required
RNAi-biofungicides: a quantum leap for tree fungal pathogen management
No full textFungal diseases threaten the forest ecosystem, impacting tree health, productivity, and biodiversity. Conventional approaches to combating diseases, such as biological control or fungicides, often reach limits regarding efficacy, resistance, non-target organisms, and environmental impact, enforcing alternative approaches. From an environmental and ecological standpoint, an RNA interference (RNAi) mediated double-stranded RNA (dsRNA)-based strategy can effectively manage forest fungal pathogens. The RNAi approach explicitly targets and suppresses gene expression through a conserved regulatory mechanism. Recently, it has evolved to be an effective tool in combating fungal diseases and promoting sustainable forest management approaches. RNAi bio-fungicides provide efficient and eco-friendly disease control alternatives using species-specific gene targeting, minimizing the off-target effects. With accessible data on fungal disease outbreaks, genomic resources, and effective delivery systems, RNAi-based biofungicides can be a promising tool for managing fungal pathogens in forests. However, concerns regarding the environmental fate of RNAi molecules and their potential impact on non-target organisms require an extensive investigation on a case-to-case basis. The current review critically evaluates the feasibility of RNAi bio-fungicides against forest pathogens by delving into the accessible delivery methods, environmental persistence, regulatory aspects, cost-effectiveness, community acceptance, and plausible future of RNAi-based forest protection products
Effect-Based Assessment of Runoff Water Streams in Stormwater Manufactured Barriers
No full textStormwater and urban runoff have been identified as one of the major sources of chemical pollution in the aquatic environment. Although traditionally treated with man-made stormwater ponds to prevent flooding as well as to foster the remediation of some pollutants, the biological activities and removal efficiencies of toxic micropollutants are largely unknown. In this study, two stormwater ponds were studied during different hydrological conditions by means of a battery (n = 6) of cell-based bioassays, whereby the toxic pressure of the inlet and outlet water could be assessed. While no activities were observed for the oxidative stress reporter gene or androgenic activation or inhibition, clear agonistic and antagonistic estrogenic as well as aryl hydrocarbon activation responses were observed. Our observations further indicate that the efficiency of the ponds' ability to lower this bioactivity from inlet to outlet was highly variable, with several cases where higher activity was observed in the outgoing water than in the ingoing water, indicating poor management of the stormwater and the need for improved treatment approaches before the stormwater is discharged into recipient water bodies
Comparative Environmental Assessment of Three Urine Recycling Scenarios: Influence of Treatment Configurations and Life Cycle Modeling Approaches
No full textUrine recycling is an emerging promising approach for enhancing resource recovery and mitigating environmental impacts in sanitation systems. This study presents a comparative life cycle assessment (LCA) of a urine dehydration system implemented at three levels of decentralization: (i) toilet-level units within bathrooms; (ii) basement-level units serving multiple households; and (iii) centralized neighborhood-scale facilities using dedicated sewers for off-site processing. Each configuration is assessed using both consequential and attributional system models across five impact categories: global warming potential, acidification, freshwater and marine eutrophication, and cumulative energy demand. The basement-level system consistently shows the lowest impacts, with up to 50% lower global warming potential than the other configurations. Centralized treatment is the most energy-efficient per liter of urine treated, but the sewer infrastructure burden offsets this advantage. Sensitivity analysis shows that substituting sulfuric acid for citric acid and achieving >52% heat recovery can yield net-negative emissions at the basement level. The choice of the LCA system model strongly affects results: attributional with substitution yields net-negative impacts, whereas consequential provides more conservative but robust estimates. The findings underscore the need for methodological transparency in LCA and provide guidance for scaling sustainable decentralized urine recycling
Strengths, challenges, and variations - insights into biosecurity practices in Swedish poultry production following HPAI outbreaks
No full textThis study investigated quantitatively and qualitatively the implementation of biosecurity in commercial poultry production in Sweden during 2020 and 2021 when outbreaks of highly pathogenic avian influenza (HPAI) occurred. The study included case and non-case farms located in areas subjected to HPAI restriction zones with broiler parent breeders, layer pullets, laying hens, broilers, and meat turkeys with at least 2,000 birds. General biosecurity routines were investigated focusing on the wild bird-poultry interface. Data collection was based on face-to-face interviews and on-farm observations on 15 farms with HPAI outbreaks and 33 matched non-case farms using a questionnaire and the biosecurity scoring tool Biocheck.UGent (https://biocheckgent.com) to assess general biosecurity practices. Data were analyzed to identify differences related to poultry categories, geographical region, farm size and HPAI disease status. Additionally, qualitative data were examined using thematic analysis to explore barriers to biosecurity implementation. The findings indicated that while biosecurity levels were generally high, there was significant variation among farms with category-specific strengths and challenges. Common weaknesses observed included inadequate infrastructure such as anteroom layout, limited training of farmworkers, suboptimal hand hygiene, and difficulties in maintaining good hygiene during the storage and introduction of roughage, such as hay and straw, into barns. Moreover, farmyards often lacked designated clean and dirty areas. The qualitative analysis identified several factors affecting the implementation of biosecurity, and key qualitative themes were conflicting priorities, compliance based on perceived risk, and feelings of powerlessness. A need for specific knowledge on effective biosecurity measures against HPAI was expressed as well as lack of knowledge among farmworkers. The farm infrastructure could both facilitate and hamper effective biosecurity depending on its design. A risk-based approach meant adapting biosecurity based on the perceived risk of outbreaks and risk connected to different introduction routes. The conflicts of interest raised were often in relation to animal welfare and environmental considerations. The main conclusions were that there is high heterogeneity in biosecurity among Swedish poultry farms, with implementation affected by multiple factors
A simple model of the turnover of organic carbon in a soil profile: model test, parameter identification and sensitivity
No full textSimulation models are potentially useful tools to test our understanding of the processes involved in the turnover of soil organic carbon (SOC) and to evaluate the role of management practices in maintaining stocks of SOC. We describe here a simple model of SOC turnover at the soil profile scale that accounts for two key processes determining SOC persistence (i.e. microbial energy limitation and physical protection due to soil aggregation). We tested the model and evaluated the identifiability of key parameters using topsoil SOC contents measured in three treatments with contrasting organic matter inputs (i.e. fallow, mineral fertilized and cropped, with and without straw addition) in a long-term field trial. The estimated total input of organic matter (OM) in the treatment with straw added was roughly three times that of the treatment without straw addition, but only 12 % of the additional OM input remained in the soil after 54 years. By taking microbial energy limitation and enhanced physical protection of root residues into account, the model could explain the differences in C persistence among the three treatments, whilst also accurately matching the time-courses of SOC contents using the same set of model parameters. Models that do not explicitly consider microbial energy limitation and physical protection would need to adjust their parameter values (either decomposition rate constants or the retention coefficient) to match this data.We also performed a sensitivity analysis to identify the most influential parameters in the model determining soil profile stocks of OM at steady-state. Input distributions for soil and crop parameters in the model were defined for the agricultural production region in east-central Sweden that includes Uppsala. This analysis showed that model parameters affecting SOC decomposition rates, including the rate constant for microbial-processed SOC and the parameters regulating physical protection and microbial energy limitation, are more sensitive than parameters determining OM inputs. The development of pedotransfer approaches to estimate SOC decomposition rates from soil properties would therefore support predictive applications of the model at larger spatial scales