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Managing wildlife populations for conservation, control or harvesting involves uncertainty. Nevertheless, decisions need to be made based on the available evidence. The two main sources of uncertainty in population modelling are parameter estimates and structural uncertainty. Structural uncertainty in models is not included as often as parameter uncertainty.We present an approach where parameter and structural uncertainty (strength of density dependence) is included within a model, using the over-wintering English population of cormorants Phalacrocorax carbo L. Because of the damage caused to inland fishery interests by cormorants, there was a change in UK government policy in autumn 2004, increasing the numbers of birds that can be shot under licence.A stochastic Monte Carlo annual population model was produced to examine the effect of changes to the numbers of birds shot each year. Indices of annual population size were converted to population estimates and used to determine annual growth rates and strength of density dependence.There is strong evidence for density dependence in the data, which suggests the population is currently slightly above carrying capacity, with a mean growth rate of 4–6% per annum. The 1300 birds shot under licence in 2004/05 represent about 4·5% of the English population, and if this level of culling continues, the population would be expected to decline by 9% by 2007, compared to the long-term average. The a priori preferred model, which included all uncertainty, gave predictions for 2004/05 and 2005/06 in close agreement with field data.The model was used to produce short-term population projections, with the understanding that Adaptive Resource Management (ARM) will be adopted to iteratively update the parameters and model each year, feeding back into the numbers of available licences.Synthesis and applications. We recommend the approach used in this study of including parameter and structural uncertainty within a single model, where possible, with the proportion of iterations that ...

8 páginas, 4 figuras, 2 tablas. Contains public sector information licensed under the Open Government Licence v3.0. ; In wildlife disease management there are few diseases for which vaccination is a viable option. The human vaccine BCG has been used for the control of bovine tuberculosis in badgers since 2010 and is expected to increase. Understanding the long-term effects of repeated vaccination campaigns on disease prevalence is vital, but modelling thus far has generally assumed that a vaccine provides perfect protection to a proportion of the population, and that animals exposed to a repeated vaccination have a second independent chance of becoming protected. We held a workshop with experts in the field to obtain consensus over the main pathways for partial protection in the badger, and then simulated these using an established model. The available data supported the possibility that some individuals receive no benefit from the BCG vaccine, others may result in a delayed disease progression and in the remaining animals, vaccine protected the individual from any onward transmission. Simulating these pathways using different levels of overall efficacy demonstrated that partial protection leads to a reduced effect of vaccination, but in all of the identified scenarios it was still possible to eradicate disease in an isolated population with no disease introduction. We also identify those potential vaccination failures that require further investigation to determine which of our proposed pathways is the more likely. ; This work was funded by Department for Environment, Food and Rural Affairs(Defra), UK [project SE3325]. ; Peer reviewed

External Scientific Report. ; The 2nd ENETWILD Annual General Meeting took place on 5-6th October 2021, bringing together experts, stakeholders and ENETWILD collaborators in online workshop discussions. First, workshop discussions contributed to the analysis and proposal of approaches for a harmonized European-wide wildlife monitoring framework able of sustaining coordinated decision-making. Secondly, participants identified the key challenges that managers face in making decisions for wildlife in Europe and data needs for policies. Finally, we illustrated these challenges with the case of wild boar as a model species widely distributed across Europe. Inputs from the participants were collated into a plan of proposed steps and objectives for the mid-term (5-year time frame) to achieve progress on harmonised, coordinated, and integrated wildlife monitoring at the European level, which requires the contribution of experts from the early stages. Specific proposed actions include the creation of a trans-disciplinary authority at the European level, effective points of reference for data collection and sharing at different administrative levels and countries, a standing committee to coordinate and exchange experience and capacities on data collection between countries, and expert groups for problem solving, with proper EU financial support, establishing regular policy meetings. . To provide useful results, wildlife monitoring must ensure proper design and data analysis for subsequent science-based management and best allocation of management resources. The 'Observatory' approach (a representative network of intensively monitored sites) can provide long-term systematic and representative insights, normally more feasible for comparative studies, providing less biases and support for decision-making. For international decision-making by wildlife managers and politicians based on scientific knowledge and interdisciplinary research, experts should define the foundations of a common European wildlife decision-making framework (inter-institutional and inter-sectorial). The development of a European legislation on wildlife management may represent an opportunity for addressing the abovementioned steps, identifying data priorities matching the needs of the various European Directorates, Agencies, and monitoring frameworks. ; EFSA-Q-2020-00669. ; Peer reviewed

Each year, more than 167 million pigs in the European Union (EU) are tested for Trichinella spp. under the current meat hygiene regulations. This imposes large economic costs on countries, yet the vast majority of these pigs test negative and the public health risk in many countries is therefore considered very low. This work reviewed the current Trichinella status across the EU as well as the national level of monitoring and reporting. It also reviewed which animal species were affected by Trichinella and in which species it should be surveyed. This information was used to design a cost-effective surveillance programme that enables a standardised monitoring approach within the EU. The proposed surveillance programme relies on identifying sub-populations of animals with a distinct risk. Low-risk pigs are finisher pigs that originate from so-called controlled housing. All other pigs are considered high-risk pigs. Controlled housing is identified by the application of a specific list of management and husbandry practices. We suggest that member states (MS) be categorised into three classes based on the confidence that Trichinella can be considered absent, in the specified sub-population of pigs above a specified design prevalence which we set to 1 per million pigs. A simple and transparent method is proposed to estimate this confidence, based on the sensitivity of the surveillance system, taking into account the sensitivity of testing and the design prevalence. The probability of detecting a positive case, if present, must be high (> 95 or > 99%) to ensure that there is a low or negligible risk of transmission to humans through the food chain. In MS where the probability of a positive pig is demonstrated to be negligible, testing of fattening pigs from a sub-population consisting of pigs from controlled housing can be considered unnecessary. Furthermore, reduced testing of finishers from the sub-population consisting of pigs from non-controlled housing might even be considered, if conducted in conjunction with a proportionate sampling scheme and a risk-based wildlife surveillance programme where applicable. The proposed surveillance programme specifies the required number of samples to be taken and found negative, in a MS. A MS with no data or positive findings will initially be allocated to class 1, in which all pigs should be tested. When a MS is able to demonstrate a 95% or 99% confidence that Trichinella is absent, the MS will be allocated to class 2 or 3, in which the testing requirement is lower than in class 1

Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth,upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea-ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems. ; This work has been partially funded by the European Commission funded projects MyOcean, MyOcean2 and COMBINE; by the GEMINA project-funded bythe Italian Ministry for Environment; by the NERC-funded VALOR project; by the NERC-funded NCEO program; by the Research Program on Climate Change adaptation of the Ministry of Education, Culture, Sports, Science and Technology of the Japanese government; by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101); by NASA's Modeling Analysis and Prediction Program under WBS 802678.02.17.01.25 and by the NASA Physical Oceanography Program; by the NOAA's Climate Observation Division (COD); by the LEFE/GMMC French national program. ; Published ; s80-s97 ; 4A. Clima e Oceani ; JCR Journal ; open