Global biodiversity indicators reflect the modeled impacts of protected area policy change

Global biodiversity indicators can be used to measure the status and trends of biodiversity relating to Convention on Biological Diversity (CBD) targets. Whether such indicators can support decision makers by distinguishing among policy options remains poorly evaluated. We tested the ability of two CBD indicators, the Living Planet Index and the Red List Index, to reflect projected changes in mammalian populations in sub-Saharan Africa in response to potential policies related to CBD targets for protected areas (PAs). We compared policy scenarios to expand the PA network, improve management effectiveness of the existing network, and combinations of the two, against business as usual. Both indicators showed that more effective management would provide greater benefits to biodiversity than expanding PAs alone. The indicators were able to communicate outcomes of modeled scenarios in a simple quantitative manner, but behaved differently. This work highlights both the considerable potential of indicators in supporting decisions, and the need to understand how indicators will respond as biodiversity changes

MammalNet: A Large-scale Video Benchmark for Mammal Recognition and Behavior Understanding

Monitoring animal behavior can facilitate conservation efforts by providing key insights into wildlife health, population status, and ecosystem function. Automatic recognition of animals and their behaviors is critical for capitalizing on the large unlabeled datasets generated by modern video devices and for accelerating monitoring efforts at scale. However, the development of automated recognition systems is currently hindered by a lack of appropriately labeled datasets. Existing video datasets 1) do not classify animals according to established biological taxonomies; 2) are too small to facilitate large-scale behavioral studies and are often limited to a single species; and 3) do not feature temporally localized annotations and therefore do not facilitate localization of targeted behaviors within longer video sequences. Thus, we propose MammalNet, a new large-scale animal behavior dataset with taxonomy-guided annotations of mammals and their common behaviors. MammalNet contains over 18K videos totaling 539 hours, which is ~10 times larger than the largest existing animal behavior dataset. It covers 17 orders, 69 families, and 173 mammal categories for animal categorization and captures 12 high-level animal behaviors that received focus in previous animal behavior studies. We establish three benchmarks on MammalNet: standard animal and behavior recognition, compositional low-shot animal and behavior recognition, and behavior detection. Our dataset and code have been made available at: https://mammal-net.github.io.Comment: CVPR 2023 proceedin

Local extinction and colonisation in native and exotic fish in relation to changes in land use

Distribution patterns of many native and exotic fish species are well documented, yet little is known about the temporal dynamics of native and exotic diversity in relation to changes in land use. We hypothesised that colonisation rates would be higher for exotic fish species and that extinction rates would be higher for native species in large stream systems. We also predicted that cold-water species would be more impacted than thermally tolerant species. To test these hypotheses, we used generalised linear mixed models to compare changes in native and exotic fish species richness over 10 years in a French drainage basin subjected to landscape alterations. Exotic fish were more susceptible to local extinction than the native ones. Extinction was greater among cold-tolerant species and at higher elevations. Colonisation by exotic species was higher at lower elevations. Although a decade of expanding urbanisation affected fish colonisation, agricultural lands experienced higher extinction rates. In the context of global changes in land use and population pressure, our study suggests that the temporal dynamics of fish diversity are driven by landscape alterations as well as by the thermal tolerance of species

Phytocannabinoid-dependent mTORC1 regulation is dependent upon inositol polyphosphate multikinase activity

BACKGROUND AND PURPOSE: Cannabidiol (CBD) has been shown to differentially regulate the mechanistic target of rapamycin complex 1 (mTORC1) in preclinical models of disease, where it reduces activity in models of epilepsies and cancer and increases it in models of multiple sclerosis (MS) and psychosis. Here, we investigate the effects of phytocannabinoids on mTORC1 and define a molecular mechanism. EXPERIMENTAL APPROACH: A novel mechanism for phytocannabinoids was identified using the tractable model system, Dictyostelium discoideum. Using mouse embryonic fibroblasts, we further validate this new mechanism of action. We demonstrate clinical relevance using cells derived from healthy individuals and from people with MS (pwMS). KEY RESULTS: Both CBD and the more abundant cannabigerol (CBG) enhance mTORC1 activity in D. discoideum. We identify a mechanism for this effect involving inositol polyphosphate multikinase (IPMK), where elevated IPMK expression reverses the response to phytocannabinoids, decreasing mTORC1 activity upon treatment, providing new insight on phytocannabinoids' actions. We further validated this mechanism using mouse embryonic fibroblasts. Clinical relevance of this effect was shown in primary human peripheral blood mononuclear cells, where CBD and CBG treatment increased mTORC1 activity in cells derived from healthy individuals and decreased mTORC1 activity in cells derived from pwMS. CONCLUSION AND IMPLICATIONS: Our findings suggest that both CBD and the abundant CBG differentially regulate mTORC1 signalling through a mechanism dependent on the activity of the upstream IPMK signalling pathway, with potential relevance to the treatment of mTOR-related disorders, including MS

Making robust policy decision using global biodiversity indicators

In order to influence global policy effectively, conservation scientists need to be able to provide robust predictions of the impact of alternative policies on biodiversity and measure progress towards goals using reliable indicators. We present a framework for using biodiversity indicators predictively to inform policy choices at a global level. The approach is illustrated with two case studies in which we project forwards the impacts of feasible policies on trends in biodiversity and in relevant indicators. The policies are based on targets agreed at the Convention on Biological Diversity (CBD) meeting in Nagoya in October 2010. The first case study compares protected area policies for African mammals, assessed using the Red List Index; the second example uses the Living Planet Index to assess the impact of a complete halt, versus a reduction, in bottom trawling. In the protected areas example, we find that the indicator can aid in decision-making because it is able to differentiate between the impacts of the different policies. In the bottom trawling example, the indicator exhibits some counter-intuitive behaviour, due to over-representation of some taxonomic and functional groups in the indicator, and contrasting impacts of the policies on different groups caused by trophic interactions. Our results support the need for further research on how to use predictive models and indicators to credibly track trends and inform policy. To be useful and relevant, scientists must make testable predictions about the impact of global policy on biodiversity to ensure that targets such as those set at Nagoya catalyse effective and measurable change

Investigating the impact of poverty on colonization and infection with drug-resistant organisms in humans: a systematic review

Background Poverty increases the risk of contracting infectious diseases and therefore exposure to antibiotics. Yet there is lacking evidence on the relationship between income and non-income dimensions of poverty and antimicrobial resistance. Investigating such relationship would strengthen antimicrobial stewardship interventions. Methods A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Ovid, MEDLINE, EMBASE, Scopus, CINAHL, PsychINFO, EBSCO, HMIC, and Web of Science databases were searched in October 2016. Prospective and retrospective studies reporting on income or non-income dimensions of poverty and their influence on colonisation or infection with antimicrobial-resistant organisms were retrieved. Study quality was assessed with the Integrated quality criteria for review of multiple study designs (ICROMS) tool. Results Nineteen articles were reviewed. Crowding and homelessness were associated with antimicrobial resistance in community and hospital patients. In high-income countries, low income was associated with Streptococcus pneumoniae and Acinetobacter baumannii resistance and a seven-fold higher infection rate. In low-income countries the findings on this relation were contradictory. Lack of education was linked to resistant S. pneumoniae and Escherichia coli. Two papers explored the relation between water and sanitation and antimicrobial resistance in low-income settings. Conclusions Despite methodological limitations, the results suggest that addressing social determinants of poverty worldwide remains a crucial yet neglected step towards preventing antimicrobial resistance

Guidance on the Selection of Appropriate Indicators for Quantification of Antimicrobial Usage in Humans and Animals

An increasing variety of indicators of antimicrobial usage has become available in human and veterinary medicine, with no consensus on the most appropriate indicators to be used. The objective of this review is therefore to provide guidance on the selection of indicators, intended for those aiming to quantify antimicrobial usage based on sales, deliveries or reimbursement data. Depending on the study objective, different requirements apply to antimicrobial usage quantification in terms of resolution, comprehensiveness, stability over time, ability to assess exposure and comparability. If the aim is to monitor antimicrobial usage trends, it is crucial to use a robust quantification system that allows stability over time in terms of required data and provided output; to compare usage between different species or countries, comparability must be ensured between the different populations. If data are used for benchmarking, the system comprehensiveness is particularly crucial, while data collected to study the association between usage and resistance should express the exposure level and duration as a measurement of the exerted selection pressure. Antimicrobial usage is generally described as the number of technical units consumed normalized by the population at risk of being treated in a defined period. The technical units vary from number of packages to number of individuals treated daily by adding different levels of complexity such as daily dose or weight at treatment. These technical units are then related to a description of the population at risk, based either on biomass or number of individuals. Conventions and assumptions are needed for all of these calculation steps. However, there is a clear lack of standardization, resulting in poor transparency and comparability. By combining study requirements with available approaches to quantify antimicrobial usage, we provide suggestions on the most appropriate indicators and data sources to be used for a given study objective

Knowledge, attitudes and practice survey about antimicrobial resistance and prescribing among physicians in a hospital setting in Lima, Peru

BACKGROUND: Misuse of antimicrobials (AMs) and antimicrobial resistance (AMR) are global concerns. The present study evaluated knowledge, attitudes and practices about AMR and AM prescribing among medical doctors in two large public hospitals in Lima, Peru, a middle-income country. METHODS: Cross-sectional study using a self-administered questionnaire RESULTS: A total of 256 participants completed the questionnaire (response rate 82%). Theoretical knowledge was good (mean score of 6 +/- 1.3 on 7 questions) in contrast to poor awareness (< 33%) of local AMR rates of key-pathogens. Participants strongly agreed that AMR is a problem worldwide (70%) and in Peru (65%), but less in their own practice (22%). AM overuse was perceived both for the community (96%) and the hospital settings (90%). Patients' pressure to prescribing AMs was considered as contributing to AM overuse in the community (72%) more than in the hospital setting (50%). Confidence among AM prescribing was higher among attending physicians (82%) compared to residents (30%, p < 0.001%). Sources of information considered as very useful/useful included pocket-based AM prescribing guidelines (69%) and internet sources (62%). Fifty seven percent of participants regarded AMs in their hospitals to be of poor quality. Participants requested more AM prescribing educational programs (96%) and local AM guidelines (92%). CONCLUSIONS: This survey revealed topics to address during future AM prescribing interventions such as dissemination of information about local AMR rates, promoting confidence in the quality of locally available AMs, redaction and dissemination of local AM guidelines and addressing the general public, and exploring the possibilities of internet-based training