ORCID Profile
0000-0003-4375-0445
Current Organisations
Centre for Ecology & Hydrology
,
University of York
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Publisher: Wiley
Date: 10-05-2017
DOI: 10.1111/GCB.13714
Abstract: Agricultural intensification is a leading cause of global bio ersity loss, which can reduce the provisioning of ecosystem services in managed ecosystems. Organic farming and plant ersification are farm management schemes that may mitigate potential ecological harm by increasing species richness and boosting related ecosystem services to agroecosystems. What remains unclear is the extent to which farm management schemes affect bio ersity components other than species richness, and whether impacts differ across spatial scales and landscape contexts. Using a global metadataset, we quantified the effects of organic farming and plant ersification on abundance, local ersity (communities within fields), and regional ersity (communities across fields) of arthropod pollinators, predators, herbivores, and detritivores. Both organic farming and higher in-field plant ersity enhanced arthropod abundance, particularly for rare taxa. This resulted in increased richness but decreased evenness. While these responses were stronger at local relative to regional scales, richness and abundance increased at both scales, and richness on farms embedded in complex relative to simple landscapes. Overall, both organic farming and in-field plant ersification exerted the strongest effects on pollinators and predators, suggesting these management schemes can facilitate ecosystem service providers without augmenting herbivore (pest) populations. Our results suggest that organic farming and plant ersification promote erse arthropod metacommunities that may provide temporal and spatial stability of ecosystem service provisioning. Conserving erse plant and arthropod communities in farming systems therefore requires sustainable practices that operate both within fields and across landscapes.
Publisher: Canadian Science Publishing
Date: 05-2008
DOI: 10.1139/Z08-009
Abstract: Automated remote ultrasound detectors allow large amounts of data on bat presence and activity to be collected. Processing of such data involves identifying bat species from their echolocation calls. Automated species identification has the potential to provide more consistent, predictable, and potentially higher levels of accuracy than identification by humans. In contrast, identification by humans permits flexibility and intelligence in identification, as well as the incorporation of features and patterns that may be difficult to quantify. We compared humans with artificial neural networks (ANNs) in their ability to classify short recordings of bat echolocation calls of variable signal to noise ratios these sequences are typical of those obtained from remote automated recording systems that are often used in large-scale ecological studies. We presented 45 recordings (1–4 calls) produced by known species of bats to ANNs and to 26 human participants with 1 month to 23 years of experience in acoustic identification of bats. Humans correctly classified 86% of recordings to genus and 56% to species ANNs correctly identified 92% and 62%, respectively. There was no significant difference between the performance of ANNs and that of humans, but ANNs performed better than about 75% of humans. There was little relationship between the experience of the human participants and their classification rate. However, humans with year of experience performed worse than others. Currently, identification of bat echolocation calls by humans is suitable for ecological research, after careful consideration of biases. However, improvements to ANNs and the data that they are trained on may in future increase their performance to beyond those demonstrated by humans.
Publisher: MDPI AG
Date: 13-04-2022
Abstract: Background and Objectives: Now more than ever, there is an obvious need to reduce the overall burden of disease and risk of premature mortality that are associated with mental health and substance use disorders among young people. However, the current state of research and evidence-based clinical care for high-risk substance use among youth is fragmented and scarce. The objective of the study is to establish consensus for the prevention, treatment, and management of high-risk substance use and overdose among youth (10 to 24 years old). Materials and Methods: A modified Delphi technique was used based on the combination of scientific evidence and clinical experience of a group of 31 experts representing 10 countries. A semi-structured questionnaire with five domains (clinical risks, target populations, intervention goals, intervention strategies, and settings/expertise) was shared with the panelists. Based on their responses, statements were developed, which were subsequently revised and finalized through three iterations of feedback. Results: Among the five major domains, 60 statements reached consensus. Importantly, experts agreed that screening in primary care and other clinical settings is recommended for all youth, and that the objectives of treating youth with high-risk substance use are to reduce harm and mortality while promoting resilience and healthy development. For all substance use disorders, evidence-based interventions should be available and should be used according to the needs and preferences of the patient. Involuntary admission was the only topic that did not reach consensus, mainly due to its ethical implications and resulting lack of comparable evidence. Conclusions: High-risk substance use and overdoses among youth have become a major challenge. The system’s response has been insufficient and needs substantial change. Internationally devised consensus statements provide a first step in system improvement and reform.
Publisher: Elsevier BV
Date: 03-2022
DOI: 10.1016/J.TREE.2021.11.012
Abstract: Social-ecological networks (SENs) represent the complex relationships between ecological and social systems and are a useful tool for analyzing and managing ecosystem services. However, mainstreaming the application of SENs in ecosystem service research has been hindered by a lack of clarity about how to match research questions to ecosystem service conceptualizations in SEN (i.e., as nodes, links, attributes, or emergent properties). Building from different disciplines, we propose a typology to represent ecosystem service in SENs and identify opportunities and challenges of using SENs in ecosystem service research. Our typology provides guidance for this growing field to improve research design and increase the breadth of questions that can be addressed with SEN to understand human-nature interdependencies in a changing world.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Michael Pocock.