Data sharing among protected areas shows advantages in habitat suitability modelling performance
Mattia Falaschi
A B D , Stefano Scali B , Roberto Sacchi C and Marco Mangiacotti B C
+ Author Affiliations
- Author Affiliations
A Department of Environmental Science and Policy, University of Milan, Via Celoria 26, 20133 Milan, Italy.
B Natural History Museum of Milan, Corso Venezia 55, 20121 Milan, Italy.
C Department of Earth and Environmental Sciences, University of Pavia, 27100 Pavia, Italy.
D Corresponding author. Email: matt_fala@hotmail.it
Wildlife Research 48(5) 404-413 https://doi.org/10.1071/WR20196
Submitted: 18 November 2020 Accepted: 28 December 2020 Published: 17 March 2021
Abstract
Context: Most of the effort dedicated to the conservation of biodiversity in the European Union is applied through the establishment and maintenance of the Natura 2000 network, the world’s most extensive network of conservation areas. European Member State must actively manage these sites and report the state of the species listed in the Annexes of the Habitat and Birds Directives. Fulfilling these duties is a challenging task, especially when money available for conservation is limited. Consequently, how to optimise the use of the available economic resources is a primary goal for reserve managers.
Aims: In the present study, we focussed on data-sharing, and we analysed whether data-sharing among institutions may boost the performance of habitat suitability models (HSMs).
Methods: We collected presence data about three species of reptiles in three different protected areas of northern Italy. Then, we built HSMs under the following two different data-sharing policies: data-sharing of species’ occurrence among the different managers of the protected areas, and not sharing the occurrence data among the different managers. To evaluate how sharing the occurrence data influences the reliability of HSMs in various situations, we compared model performances under several sampling-effort levels.
Key results: Results show that data-sharing is usually the best strategy. In most cases, models built under the data-sharing (DS) strategy showed better performance than did data-un-sharing (DU) models. The data-sharing strategy showed advantages in model performance, notably at low levels of sampling effort.
Conclusions: Overcoming administrative barriers and share data among different managers of protected areas allows obtaining more biologically meaningful results.
Implications: Data-sharing among protected areas could allow improving the reliability of future management actions within the Natura 2000 network.
Keywords: common wall lizard, green whip snake, habitat suitability models, Habitats Directive, Natura 2000 network, resource optimisation, western green lizard.
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