Abstract
Abstract The present paper examined the applicability of a holistic stochastic dynamic methodology (SDM) in predicting the tendencies of simple ecological indicators as a response to the changes in agricultural hedgerow networks. Although considerable effort has been made to identify appropriate agri-environmental indicators, yet most of them are far too complex to be comprehensively measured and quantified by non-specialists. The ecological integrity of the typical hedgerows can be partly assessed by the observation of the occurrence of passerine indicators. Since the conventional measures’ regarding bird studies requires high-specialization levels, we proposed alternative simple, suitable and intuitive indicators capable of responding with comparable rigour to key changes in such agro-ecosystems. The dynamic model developed was preceded by a conventional multivariate statistical procedure performed to discriminate the significant relationships between conceptually isolated key-components of the studied hedgerows. The final model provided some basis to analyse the responses of simple passerine indicators to the agricultural scenarios that will characterize the region. Overall, the simulation results are encouraging since they seem to demonstrate the SDM reliability in capturing the habitat dynamics of the studied agro-ecosystems by predicting the behavioural pattern for simple measures, roughly associated with bird occurrence, habitat food resources and breeding conditions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.