The lack of communication between biodiversity databases results in mismatched species occurrences records and maps from different sources. This means that only a portion of these records aligns with data that details the interactions between species.

A recent study comparing data from the International Union for the Conservation of Nature (IUCN), the Global Biodiversity Information Facility (GBIF), and a dataset of foodweb interactions from the Serengeti ecosystem in East Africa uncovered several mismatches. This could indicate a shortfall of data for nine predator-prey relationships.

The range maps of some predator mammals reveal a significant discrepancy with those of their prey, leading to doubts about the actual presence of these predators in areas without prey. This phenomenon is particularly apparent in the case of specialized predators in the Serengeti ecosystem, such as the serval cat and the black-backed jackal.

The discrepancy in range maps for the golden jackal is likely a result of conflicting taxonomic information among datasets. Its scientific classification has been the subject of extensive discussion, and the databases may not yet reflect the latest updates.

Species occurrence data play a crucial role in ecological studies aimed at comprehending and forecasting the distribution of biodiversity. Such analysis forms the basis of conservation policies, climate change mitigation efforts, public health regulations, and numerous other important initiatives.”

This is only feasible because these data are often provided under a license that enables anybody to use them and are properly stored in databases like IUCN and GBIF.

But these statistics have several shortcomings: The GBIF statistics are known to be skewed (due to historically biased scientific activities), the IUCN is known to underestimate the distribution of rare species, and there are very few large-scale interaction data available.

The basis of this study was straightforward: if a predator lacks a food source, it is highly unlikely that it will persist in a given location. Hence, the range map of a predator should overlap almost exactly with that of its prey. Deviations from this pattern could indicate inaccuracies in the estimation of predator or prey distribution or a lack of knowledge regarding the species’ dietary habits.

With this as their starting point, Gracielle, Gabriel, Francis, Fredric, Norma, and Timothée gathered to analyze the data provided by the IUCN and to evaluate the connections between species by utilizing the Serengeti foodweb.

“We are all interested in macroecology of interactions and species distribution modelling, and we think these things should be studied together,” says Gracielle Higino, “but we know that in order to integrate these two things, our available datasets need to talk.”

The authors split the African continent into grids of around 50 km2, then developed local foodwebs based on the regional Serengeti food web and IUCN range maps to see whether range maps and ecological interaction data were “talking” to each other.

This allowed them to identify a link between a top predator and a herbivore inside each grid. When such a link could not be made, the grid cell was deemed mismatched, and the existence of a top predator or the absence of information on its prey was called into doubt.

For interaction and occurrence data, this approach may also be used to map priority sampling sites. This would help with the monitoring of biodiversity in light of climate change and habitat loss as well as another interesting use for ecological data: species diet prediction.

Geographical data (like range maps) and ecological data (like foodwebs) don’t match up because of biases. Incentives to open data are a way to fix this problem.

In order to reduce error propagation in ecological models, which might be brought on by skewed occurrence maps and lacking interaction networks, the researchers think that more access to data is crucial.

“Open science is a very core practice for all of us. We think open access to data and information is extremely important, and we want it to be done the right way. It is imperative that open ecological data are consistent and redundant across databases, which we didn’t quite see in our study,” adds Higino.

Due to the rapid loss of ecological interactions as a result of environmental changes, it is imperative that access to data is made openly available to support the development of effective conservation and public health policies.

Source: 10.7717/peerj.14620

Image Credit: Brent Stirton/Getty Images Reportage