Assessment of high (diurnal) to low (seasonal) frequency variations of isoprene emission rates using a neural network approach

Using a statistical approach based on artificial neural networks, an emission algorithm (ISO-LF) accounting for high to low frequency variations was developed for isoprene emission rates. ISO-LF was optimised using a data base (ISO-DB) specifically designed for this work, which consists of 1321 emission rates collected in the literature and 34 environmental variables, measured or assessed using National Climatic Data Center or National Centers for Environmental Predictions meteorological databases. ISO-DB covers a large variety of emitters (25 species) and environmental conditions (10° S to 60° N). When only instantaneous environmental regressors (instantaneous air temperature <i>T0</i> and photosynthetic photon flux density <i>L0</i>) were used, a maximum of 60% of the overall isoprene variability was assessed with the highest emissions being strongly underestimated. ISO-LF includes a total of 9 high (instantaneous) to low (up to 3 weeks) frequency regressors and accounts for up to 91% of the isoprene emission variability, whatever the emission range, species or climate investigated. ISO-LF was found to be mainly sensitive to air temperature cumulated over 3 weeks (<i>T21</i>) and to <i>L0</i> and <i>T0</i> variations. <i>T21</i>, <i>T0</i> and <i>L0</i> only accounts for 76% of the overall variability

Assessment of high (diurnal) to low (seasonal) frequency variations of isoprene emission rates using a neural network approach

International audienceUsing a statistical approach based on artificial neural networks, an emission algorithm (ISO-LF) accounting for high to low frequency variations was developed for isoprene emission rates. ISO-LF was optimised using a data base (ISO-DB) specifically designed for this work, which consists of 1321 emission rates collected in the literature and 34 environmental variables, measured or assessed using National Climatic Data Center or National Centers for Environmental Predictions meteorological databases. ISO-DB covers a large variety of emitters (25 species) and environmental conditions (10° S to 60° N). When only instantaneous environmental regressors (instantaneous air temperature T0 and photosynthetic photon flux density L0) were used, a maximum of 60% of the overall isoprene variability was assessed with the highest emissions being strongly underestimated. ISO-LF includes a total of 9 high (instantaneous) to low (up to 3 weeks) frequency regressors and accounts for up to 91% of the isoprene emission variability, whatever the emission range, species or climate investigated. ISO-LF was found to be mainly sensitive to air temperature cumulated over 3 weeks (T21) and to L0 and T0 variations. T21, T0 and L0 only accounts for 76% of the overall variability

A seasonal modelling approach of isoprene emissions: impact on O3 budget

2-7 mai 200

Co-producing theory of change to operationalize integrated landscape approaches

Integrated landscape approaches that engage diverse stakeholder groups in landscape governance are increasingly promoted to address linked social–ecological challenges in tropical landscapes. Recent research suggests that a transdisciplinary approach to landscape management can help identify common research needs, enhance knowledge co-production, guide evidence-based policy development, and harmonize cross-sectorial integration. Meanwhile, guiding principles for landscape approaches suggest that identifying common concerns and negotiating a process of change are fundamental to implementation and evaluation efforts. As such, the use of decision support tools such as theory of change models that build ordered sequences of actions towards a desired, and agreed, future state are increasingly advocated. However, the application of the theory of change concept to integrated landscape approaches is limited thus far, particularly within the scientific literature. Here, we address this gap by applying the principles of landscape approaches and knowledge co-production to co-produce a theory of change to address current unsustainable landscape management and associated conflicts in the Kalomo Hills Local Forest Reserve No. P.13 (KFR13) of Zambia. The participatory process engaged a diverse range of stakeholders including village head people, local and international researchers, district councillors, and civil society representatives amongst others. Several pathways, actions, and interventions were developed around the themes of deforestation, biodiversity and wildlife conservation, socio-economic development, access rights, and law enforcement. To make the theory of change actionable, participants identified a need for enhanced cross-sector and multi-level communication, capacity development, and improved governance, while a lack of commitment towards coordinated knowledge exchange and access to information along with poor policy formulation and weak enforcement of rules were among potential impediments to action. Use of theory of change can both inform evidence-based policy design (by revealing place-based challenges and proposing solutions) and support policy mechanisms that promote integration between state and non-state actors (by clarifying actor rights, roles and responsibilities). Co-developing a theory of change for integrated landscape management is inherently context specific, but the process and outcomes of this study should hold relevance across a range of contexts faced with sustainability challenges related to reconciling both conservation and development objectives

Consumption and biodiversity conservation: insights from behavioral science using the MINDSPACE approach

Consumption is defined as purchase and use of all goods and services by individuals, households, and social groups. MINDSPACE is a mnemonic that is used to set out nine robust influences on human behavior (messenger, incentives, norms, defaults, salience, priming, affect, commitment, ego). Nudges are easy and cheap changes to some aspect of the choice architecture to alter human behavior in a predictable way without forbidding any options or significantly changing their economic incentives