Big Data to the rescue? Ongoing efforts to infuse climate change predictions into conservation management
Ongoing global environmental change is driving an increasing demand for the use of big data and climate change projections in conservation management to “prepare for the future”. The availability of biodiversity data, remote sensing, and the informatics revolution are indeed opening up new possibilities for improved biodiversity mapping, analysis tools, monitoring systems and better predictions of ecosystem responses to climate change. General principles can be (and are being) developed to reorient management goals from static baseline conditions to instead promote dynamic ecosystem processes, and to highlight the need for coordinating conservation efforts and priorities across larger spatial scales. However, these principles also need to be translated to local scale predictions and recommendations. How are Big Data and climate change predictions changing conservation management, and how can the new challenges be tackled?
We will illustrate some of the opportunities and hurdles in infusing future predictions to conservation through a series of examples from projects worldwide as well as some lessons learned from a regional initiative that uses modelling approaches and Big Data synthesis to inform management decisions in California. In particular, we will focus on how these initiatives are attempting to 1) match the spatial scale of models, data and processes used for predictions (e.g. in species distribution models) to the spatial scale of management (often much finer), and 2) accommodate uncertainties in predictions stemming from climate change scenarios and modelling methods for specific recommendations useful in decision-making. We will argue that, as the era of Big Data develops, addressing these challenges present new exciting research avenues in the intersection between large biodiversity databases, remote sensing, informatics and applied conservation.