Call for papers: Predictive biogeographySubmitted by editor on 21 December 2022.
Extended deadline: 30 November!
We are opening a call for papers for a special issue on Predictive Biogeography. Predictive biogeography is a subdiscipline of biogeography that uses known biogeographical patterns and processes to make inferences about unknown biogeographical patterns and, occasionally, unknown processes. The discipline has grown exponentially in the past 20-years, owing to increased availability of digital data, advances in computer resources and statistical models, the development of artificial intelligence, more affordable and rapid molecular techniques, novel remote sensing tools applicable at high resolution and large spatial extents, and large-scale availability of climatic and landscape variables, among others.
The growth in the discipline has prompted new synthesis and theories, which, together with the development of new methodologies and improved computational capabilities, are transforming biogeography from a traditionally descriptive science into a predictive one. These developments, combined with an unprecedented biodiversity crisis and global change, generate a new need to synthesize, innovate, and anticipate large-scale phenomena to adapt to new scenarios of change, both to protect biodiversity and to guarantee human food security and well-being.
Today, research in predictive biogeography underpins applications and discoveries in fields as varied as conservation biology, agriculture, forestry, fisheries, but also epidemiology, paleobiology, and astrobiology.
For this special issue we will be particularly interested in studies in any of those sub-disciplines and beyond, that:
Integrate spatial and temporal facets of predictions at large scales;
Integrate different data types or new technologies (e.g. remote sensing, molecular data, simulations, artificial intelligence) to study or explain large-scale patterns in ecological components, processes or diversity in a novel way;
Incorporate evolutionary dynamics or theories within a macroecological framework;
Use citizen science at large scales to study or solve applied biogeographic questions;
Conceptual studies that link any of the above-mentioned topics with existing or new theoretical frameworks that allow advancing macroecological understanding;
Theoretical, synthesis or applied studies will be welcome, in areas such as agriculture, climate change, fisheries, forestry, conservation, restoration, museolomics, astrobiology or bioterrorism, among others, as long as there is a clear connection to predictive biogeography. Manuscripts can be submitted as synthesis, research, or perspective articles, and we will strive to find a balance between all these categories to be published in the special issue. We are also particularly interested in submissions coming from underrepresented geographic areas, and encourage anyone interested to contact the editorial team for further inquiries.
A proposal including a 500-word summary, type of article (research, perspective or synthesis) and a figure, as well as authors’ full names, affiliations and an e-mail address for the contact person, should be sent as a single PDF file to christine [dot] meynard [at] inrae [dot] fr before 30 June 2023. A preselection will be made based on the summaries, and invitations to submit a full article will be sent shortly after. Only invited submissions will be considered for publication in the special issue. The deadline for full submissions will be fixed later, but will likely fall around 30 November 2023. Once received, all manuscripts will undergo the regular peer-review process. Therefore, notice that an invitation to submit a full manuscript does not guarantee its final acceptance for publication.
The editorial board for this special issue includes the following (in alphabetical order):
Miguel Araújo (National Museum of Natural Sciences, CSIC; Évora University), Nuria Galiana (National Museum of Natural Sciences, CSIC), Dominique Gravel (Université de Sherbrooke, Canada), Christine N Meynard (INRAE- France) and Sydne Record (University of Maine).