A core challenge facing ecologists is to work through an ever-increasing amount of data. The accelerating decline in biodiversity worldwide, mounting pressure of anthropogenic impacts, and increasing demand for actionable indicators to guide effective policy means that monitoring will only intensify, and rely on tools that can generate even more information (Gonzalez et al., 2023). How, then, do we handle this new volume and diversity of data?

This is the question Royaux et al. (2024) are tackling with their contribution. By introducing both a conceptual ("How should we think about our work?") and an operational ("Here is a tool to do our work with") framework, they establish a series of best practices for the analysis of ecological data.

It is easy to think about best practices in ecological data analysis in its most proximal form: is it good statistical practice? Is the experimental design correct? These have formed the basis of many recommendations over the years (see e.g. Popovic et al., 2024, for a recent example). But the contribution of Royaux et al. focuses on a different part of the analysis pipeline: the computer science (and software engineering) aspect of it.

As data grows in volume and complexity, the code needed to handle it follows the same trend. It is not a surprise, therefore, to see that the demand for programming skills in ecologists has doubled recently (Feng et al., 2020), prompting calls to make computational literacy a core component of undergraduate education (Farrell & Carrey, 2018). But beyond training, an obvious way to make computational analysis ecological data more reliable and effective is to build better tools. This is precisely what Royaux et al. have achieved.

They illustrate their approach through their experience building Galaxy-Ecology, a computing environment for ecological analysis: by introducing a clear taxonomy of computing concepts (data exploration, pre-processing, analysis, representation), with a hierarchy between them (formatting, data correction, anonymization), they show that we can think about the pipeline going from data to results in a way that is more systematized, and therefore more prone to generalization.

We may buckle at the idea of yet another ontology, or yet another framework, for our work, but I am convinced that the work of Royaux et al. is precisely what our field needs. Because their levels of atomization (their term for the splitting of complex pipelines into small, single-purpose tasks) are easy to understand, and map naturally onto tasks that we already perform, it is likely to see wide adoption. Solving the big, existential challenges of monitoring and managing biodiversity at the global scale requires the adoption of good practices, and a tool like Galaxy-Ecology goes a long way towards this goal.

References

Farrell, K.J., and Carey, C.C. (2018). Power, pitfalls, and potential for integrating computational literacy into undergraduate ecology courses. Ecol. Evol. 8, 7744-7751.
https://doi.org/10.1002/ece3.4363

Feng, X., Qiao, H., and Enquist, B. (2020). Doubling demands in programming skills call for ecoinformatics education. Frontiers in Ecology and the Environment 18, 123-124.
https://doi.org/10.1002/fee.2179
 
Gonzalez, A., Vihervaara, P., Balvanera, P., Bates, A.E., Bayraktarov, E., Bellingham, P.J., Bruder, A., Campbell, J., Catchen, M.D., Cavender-Bares, J., et al. (2023). A global biodiversity observing system to unite monitoring and guide action. Nat. Ecol. Evol., 1-5. 
https://doi.org/10.1038/s41559-023-02171-0
 
Popovic, G., Mason, T.J., Drobniak, S.M., Marques, T.A., Potts, J., Joo, R., Altwegg, R., Burns, C.C.I., McCarthy, M.A., Johnston, A., et al. (2024). Four principles for improved statistical ecology. Methods Ecol. Evol. 15, 266-281.
https://doi.org/10.1111/2041-210X.14270
 
Coline Royaux, Jean-Baptiste Mihoub, Marie Jossé, Dominique Pelletier, Olivier Norvez, Yves Reecht, Anne Fouilloux, Helena Rasche, Saskia Hiltemann, Bérénice Batut, Marc Eléaume, Pauline Seguineau, Guillaume Massé, Alan Amossé, Claire Bissery, Romain Lorrilliere, Alexis Martin, Yves Bas, Thimothée Virgoulay, Valentin Chambon, Elie Arnaud, Elisa Michon, Clara Urfer, Eloïse Trigodet, Marie Delannoy, Gregoire Loïs, Romain Julliard, Björn Grüning, Yvan Le Bras (2024) Guidance framework to apply best practices in ecological data analysis: Lessons learned from building Galaxy-Ecology. EcoEvoRxiv, ver.3 peer-reviewed and recommended by PCI Ecology. 
https://doi.org/10.32942/X2G033

In a progressively human-dominated planet (Venter et al., 2016), the fate of many species will depend on the extent to which they can persist in anthropogenic landscapes. In Western Europe, where only small areas of primary habitat remain (e.g. Sabatini et al., 2018), semi-natural areas are crucial habitats to many native species, yet they are threatened by the expansion of human activities, including agricultural expansion and intensification (Rigal et al., 2023). 

A new study by Mallet and colleagues (Mallet et al., 2023) investigates the extent to which bird species in the Camargue region are able to use the margins of agricultural fields as substitutes for their preferred semi-natural habitats. Located in the delta of the Rhône River in Southern France, the Camargue is internationally recognized for its biodiversity value, classified as a Biosphere Reserve by UNESCO and as a Wetland of International Importance under the Ramsar Convention (IUCN & UN-WCMC, 2023). Mallet and colleagues tested three specific hypotheses: that grass strips (grassy field boundaries, including grassy tracks or dirt roads used for moving agricultural machinery) can function as substitute habitats for grassland species; that reed strips along drainage ditches (common in the rice paddy landscapes of the Camargue) can function as substitute habitats to wetland species; and that hedgerows can function as substitute habitats to species that favour woodland edges. They did so by measuring how the local abundances of 14 bird species (nine typical of forest edges, 3 of grasslands, and two of reedbeds) respond to increasing coverage of either the three types of field margins or of the three types of semi-natural habitat. 

This is an elegant study design, yet – as is often the case with real field data – results are not as simple as expected. Indeed, for most species (11 out of 14) local abundances did not increase significantly with the area of their supposed primary habitat, undermining the assumption that they are strongly associated with (or dependent on) those habitats. Among the three species that did respond positively to the area of their primary habitat, one (a forest edge species) responded positively but not significantly to the area of field margins (hedgerows), providing weak evidence to the habitat compensation hypothesis. For the other two (grassland and a wetland species), abundance responded even more strongly to the area of field margins (grass and reed strips, respectively) than to the primary habitat, suggesting that the field margins are not so much a substitute but valuable habitats in their own right. 

It would have been good conservation news if field margins were found to be suitable habitat substitutes to semi-natural habitats, or at least reasonable approximations, to most species. Given that these margins have functional roles in agricultural landscapes (marking boundaries, access areas, water drainage), they could constitute good win-win solutions for reconciling biodiversity conservation with agricultural production. Alas, the results are more complicated than that, with wide variation in species responses that could not have been predicted from presumed habitat affinities. These results illustrate the challenges of conservation practice in complex landscapes formed by mosaics of variable land use types. With species not necessarily falling neatly into habitat guilds, it becomes even more challenging to plan strategically how to manage landscapes to optimize their conservation. The results presented here suggest that species’ abundances may be responding to landscape variables not taken into account in the analyses, such as connectivity between habitat patches, or maybe positive and negative edge effects between land use types. That such uncertainties remain even in a well-studied region as the Camargue, and for such a well-studied taxon such as birds, only demonstrates the continued importance of rigorous field studies testing explicit hypotheses such as this one by Mallet and colleagues. 

References

IUCN, & UN-WCMC (2023). Protected Planet. Protected Planet. https://www.protectedplanet.net/en 

Mallet, P., Béchet, A., Sirami, C., Mesléard, F., Blanchon, T., Calatayud, F., Dagonet, T., Gaget, E., Leray, C., & Galewski, T. (2023). Field margins as substitute habitat for the conservation of birds in agricultural wetlands. bioRxiv, 2022.05.05.490780, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.05.05.490780 

Rigal, S., Dakos, V., Alonso, H., Auniņš, A., Benkő, Z., Brotons, L., Chodkiewicz, T., Chylarecki, P., de Carli, E., del Moral, J. C. et al. (2023). Farmland practices are driving bird population decline across Europe. Proceedings of the National Academy of Sciences, 120, e2216573120. https://doi.org/10.1073/pnas.2216573120 

Sabatini, F. M., Burrascano, S., Keeton, W. S., Levers, C., Lindner, M., Pötzschner, F., Verkerk, P. J., Bauhus, J., Buchwald, E., Chaskovsky, O., Debaive, N. et al. (2018). Where are Europe’s last primary forests? Diversity and Distributions, 24, 1426–1439. https://doi.org/10.1111/ddi.12778 

Venter, O., Sanderson, E. W., Magrach, A., Allan, J. R., Beher, J., Jones, K. R., Possingham, H. P., Laurance, W. F., Wood, P., Fekete, B. M., Levy, M. A., & Watson, J. E. M. (2016). Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, 12558. https://doi.org/10.1038/ncomms12558