To observe, characterise, identify, understand, predict... This is the approach that researchers follow every day. This sequence is tirelessly repeated as the biological model, the targeted ecosystem and/or the experimental, environmental or modelling conditions change. This way of proceeding is essential in a world of rapid change in response to the frenetic pace of intensifying pressures and forcings that impact ecosystems. To better understand our Earth and the dynamics of its components, to map ecosystems and diversity patterns, and to identify changes, humanity had to demonstrate inventiveness and defy gravity. 

Gustave Hermite and Georges Besançon were the first to launch aloft balloons equipped with radio transmitters, making possible the transmission of meteorological data to observers in real time [1]. The development of aviation in the middle of the 20th century constituted a real leap forward for the frequent acquisition of aerial observations, leading to a significant improvement in weather forecasting models. The need for systematic collection of data as holistic as possible – an essential component for the observation of complex biological systems - has resulted in pushing the limits of technological prowess. 

The conquest of space and the concurrent development of satellite observations has largely contributed to the collection of a considerable mass of data, placing our Earth under the "macroscope" - a concept introduced to ecology in the early 1970s by Howard T. Odum (see [2]), and therefore allowing researchers to move towards a better understanding of ecological systems, deterministic and stochastic patterns … with the ultimate goal of improving management actions [2,3]. Satellite observations have been carried out for nearly five decades now [3] and have greatly contributed to a better qualitative and quantitative understanding of the functioning of our planet, its diversity, its climate... and to a better anticipation of possible future changes (e.g., [4-7]).

This access to rich and complex sources of information, for which both spatial and temporal resolutions are increasingly fine, results in the implementation of increasingly complex computation-based analyses, in order to meet the need for a better understanding of ecological mechanisms and processes, and their possible changes. Steven Levitt stated that "Data is one of the most powerful mechanisms for telling stories". This is so true … Data should not be used as a guide to thinking and a critical judgment at each stage of the data exploitation process should not be neglected. 

This is what Mahood et al. [8] rightly remind us in their article "Ten simple rules for working with high-resolution remote sensing data" in which they provide the fundamentals to consider when working with data of this nature, a still underutilized resource in several topics, such as conservation biology [3]. In this unconventional article, presented in a pedagogical way, the authors remind different generations of readers how satellite data should be handled and processed. The authors aim to make the readers aware of the most frequent pitfalls encouraging them to use data adapted to their original question, the most suitable tools/methods/procedures, to avoid methodological overkill, and to ensure both ethical use of data and transparency in the research process. While access to high-resolution data is increasingly easy thanks to the implementation of dedicated platforms [4], and because of the development of easy-to-use processing software and pipelines, it is important to take the time to recall some of the essential rules and guidelines for managing them, from new users with little or no experience who will find in this article the recommendations, resources and advice necessary to start exploiting remote sensing data, to more experienced researchers.

References

[1] Jeannet P, Philipona R, and Richner H (2016). 8 Swiss upper-air balloon soundings since 1902. In: Willemse S, Furger M (2016) From weather observations to atmospheric and climate sciences in Switzerland: Celebrating 100 years of the Swiss Society for Meteorology. vdf Hochschulverlag AG. 

[2] Odum HT (2007) Environment, Power, and Society for the Twenty-First Century: The Hierarchy of Energy. Columbia University Press.

[3] Boyle SA, Kennedy CM, Torres J, Colman K, Pérez-Estigarribia PE, Sancha NU de la (2014) High-Resolution Satellite Imagery Is an Important yet Underutilized Resource in Conservation Biology. PLOS ONE, 9, e86908. https://doi.org/10.1371/journal.pone.0086908

[4] Le Traon P-Y, Antoine D, Bentamy A, Bonekamp H, Breivik LA, Chapron B, Corlett G, Dibarboure G, DiGiacomo P, Donlon C, Faugère Y, Font J, Girard-Ardhuin F, Gohin F, Johannessen JA, Kamachi M, Lagerloef G, Lambin J, Larnicol G, Le Borgne P, Leuliette E, Lindstrom E, Martin MJ, Maturi E, Miller L, Mingsen L, Morrow R, Reul N, Rio MH, Roquet H, Santoleri R, Wilkin J (2015) Use of satellite observations for operational oceanography: recent achievements and future prospects. Journal of Operational Oceanography, 8, s12–s27. https://doi.org/10.1080/1755876X.2015.1022050

[5] Turner W, Rondinini C, Pettorelli N, Mora B, Leidner AK, Szantoi Z, Buchanan G, Dech S, Dwyer J, Herold M, Koh LP, Leimgruber P, Taubenboeck H, Wegmann M, Wikelski M, Woodcock C (2015) Free and open-access satellite data are key to biodiversity conservation. Biological Conservation, 182, 173–176. https://doi.org/10.1016/j.biocon.2014.11.048

[6] Melet A, Teatini P, Le Cozannet G, Jamet C, Conversi A, Benveniste J, Almar R (2020) Earth Observations for Monitoring Marine Coastal Hazards and Their Drivers. Surveys in Geophysics, 41, 1489–1534. https://doi.org/10.1007/s10712-020-09594-5

[7] Zhao Q, Yu L, Du Z, Peng D, Hao P, Zhang Y, Gong P (2022) An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends. Remote Sensing, 14, 1863. https://doi.org/10.3390/rs14081863

[8] Mahood AL, Joseph MB, Spiers A, Koontz MJ, Ilangakoon N, Solvik K, Quarderer N, McGlinchy J, Scholl V, Denis LS, Nagy C, Braswell A, Rossi MW, Herwehe L, Wasser L, Cattau ME, Iglesias V, Yao F, Leyk S, Balch J (2021) Ten simple rules for working with high resolution remote sensing data. OSFpreprints, ver. 6 peer-reviewed and recommended by Peer Community in Ecology.  https://doi.org/10.31219/osf.io/kehqz

Ecosystems shelter a huge number of species, continuously interacting. Each species interact in various ways, with trophic interactions, but also non-trophic interactions, not mentioning the abiotic and anthropogenic interactions. In particular, pollination, competition, facilitation, parasitism and many other interaction types are simultaneously present at the same place in terrestrial ecosystems [1-2]. For this reason, we need today to improve our understanding of such complex interaction networks to later anticipate their responses. This program is a huge challenge facing ecologists and they today join their forces among experimentalists, theoreticians and modelers. While some of us struggle in theoretical and modeling dimensions [3-4], some others perform brilliant works to observe and/or experiment on the same ecological objects [5-6].
In this nice study [6], Magrach et al. succeed in studying relatively large plant-pollinator interaction networks in the field, in Mediterranean ecosystems. For the first time to my knowledge, they study community-wide interactions instead of traditional and easier accessible pairwise interactions. On the basis of a statistically relevant survey, they focus on plant reproductive success and on the role of pollinator interactions in such a success. A more reductionist approach based on simpler pairwise interactions between plants and pollinators would not be able to highlight the interaction network structure (the topology) possibly impacting its responses [1,5], among which the reproductive success of some (plant) species. Yet, such a network analysis requires a fine control of probable biases, as those linked to size or autocorrelation between data of various sites. Here, Magrach et al. did a nice work in capturing rigorously the structures and trends behind this community-wide functioning.
To grasp possible relationships between plant and pollinator species is a first mandatory step, but the next critical step requires understanding processes hidden behind such relationships. Here, the authors succeed to reach this step too, by starting interpreting the processes at stake in their studied plant-pollinator networks [7]. In particular, the niche complementarity has been demonstrated to play a determinant role in the plant reproductive success, and has a positive impact on it [6].
When will we be able to detect a community-wise process? This is one of my team’s objectives, and we developed new kind of models with this aim. Also, authors focus here on plant-pollinator network, but the next step might be to gather every kind of interactions into a huge ecosystem network which we call the socio-ecosystemic graph [4]. Indeed, why to limit our view to certain interactions only? It will take time to grasp the whole interaction network an ecosystem is sheltering, but this should be our next challenge. And this paper of Magrach et al. [6] is a first fascinating step in this direction.

References

[1] Campbell, C., Yang, S., Albert, R., and Shea, K. (2011). A network model for plant–pollinator community assembly. Proceedings of the National Academy of Sciences, 108(1), 197-202. doi: 10.1073/pnas.1008204108
[2] Kéfi, S., Miele, V., Wieters, E. A., Navarrete, S. A., and Berlow, E. L. (2016). How structured is the entangled bank? The surprisingly simple organization of multiplex ecological networks leads to increased persistence and resilience. PLoS biology, 14(8), e1002527. doi: 10.1371/journal.pbio.1002527
[3] Gaucherel, C. (2019). The Languages of Nature. When nature writes to itself. Lulu editions, Paris, France.
[4] Gaucherel, C., and Pommereau, F. Using discrete systems to exhaustively characterize the dynamics of an integrated ecosystem. Methods in Ecology and Evolution, 10(9), 1615-1627. doi: 10.1111/2041-210X.13242
[5] Bennett, J. M. et al. (2018). A review of European studies on pollination networks and pollen limitation, and a case study designed to fill in a gap. AoB Plants, 10(6), ply068. doi: 10.1093/aobpla/ply068
[6] Magrach, A., Molina, F. P., and Bartomeus, I. (2020). Niche complementarity among pollinators increases community-level plant reproductive success. bioRxiv, 629931, ver. 7 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/629931
[7] Bastolla, U., Fortuna, M. A., Pascual-García, A., Ferrera, A., Luque, B., and Bascompte, J. (2009). The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature, 458(7241), 1018-1020. doi: 10.1038/nature07950

Guiding and monitoring the efficiency of conservation efforts needs robust scientific background information, of which one key element is estimating wildlife abundance and its spatial and temporal variation. As raw counts are by nature incomplete counts of a population, correcting for detectability is required (Clobert, 1995; Turlure et al., 2018). This can be done with Capture-Mark-Recapture protocols (Iijima, 2020). Techniques for marking individuals are diverse, e.g. writing on butterfly wings, banding birds, or using natural specific patterns in the individual’s body such as leopard fur or whale tail. Advancement in technology opens new opportunities for developing marking techniques, including strategies to limit mark identification errors (Burchill & Pavlic, 2019), and for using active marks that can transmit data remotely or be read automatically.

The details of such methodological developments frequently remain unpublished, the method being briefly described in studies that use it. For a few years, there has been however a renewed interest in proper publishing of methods for ecology and evolution. This study by Folk & Mennerat (2023) fits in this context, offering a nice example of detailed description and testing of a method to mark salmon ectoparasites using RFID tags. Such tags are extremely small, yet easy to use, even with automatic recording procedure. The study provides a very good basis protocol that should help researchers working for small species, in particular invertebrates. The study is complemented by a video illustrating the placement of the tag so the reader who would like to replicate the procedure can get a very precise idea of it.

References

Burchill, A. T., & Pavlic, T. P. (2019). Dude, where’s my mark? Creating robust animal identification schemes informed by communication theory. Animal Behaviour, 154, 203–208. https://doi.org/10.1016/j.anbehav.2019.05.013

Clobert, J. (1995). Capture-recapture and evolutionary ecology: A difficult wedding ? Journal of Applied Statistics, 22(5–6), 989–1008.

Folk, A., & Mennerat, A. (2023). Methods for tagging an ectoparasite, the salmon louse Lepeophtheirus salmonis (p. 2023.08.31.555695). bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.08.31.555695

Iijima, H. (2020). A Review of Wildlife Abundance Estimation Models: Comparison of Models for Correct Application. Mammal Study, 45(3), 177–188. https://doi.org/10.3106/ms2019-0082

Turlure, C., Pe’er, G., Baguette, M., & Schtickzelle, N. (2018). A simplified mark–release–recapture protocol to improve the cost effectiveness of repeated population size quantification. Methods in Ecology and Evolution, 9(3), 645–656. https://doi.org/10.1111/2041-210X.12900

Alternative stable states describe ecosystems that can persist in more than one configuration. An ecosystem can shift between stable states following some form of perturbation. There has been much work on predicting when ecosystems will shift between stable states, but less work on why some ecosystems are able to exist in alternative stable states in the first place. The paper by Ardichvili, Loeuille, and Dakos (2022) addresses this question using a simple model of a shallow lake. Their model is based on a trade-off between access to light and nutrient availability in the water column, two essential resources for the macrophytes they model. They then identify conditions when the ancestral macrophyte will diversify resulting in macrophyte species living at new depths within the lake. The authors find a range of conditions where alternative stable states can evolve, but the range is narrow. Nonetheless, their model suggests that for alternative stable states to exist, one requirement is for there to be asymmetric competition between competing species, with one species being a better competitor on one limiting resource, with the other being a better competitor on a second limiting resource. 

These results are interesting and add to growing literature on how asymmetric competition can aid species coexistence. Asymmetric competition may be widespread in nature, with closely related species often being superior competitors on different resources. Incorporating asymmetric competition, and its evolution, into models does complicate theoretical investigations, but Ardichvili, Loeuille, and Dakos’ paper elegantly shows how substantial progress can be made with a model that is still (relatively) simple.

References 

Ardichvili A, Loeuille N, Dakos V (2022) Evolutionary emergence of alternative stable states in shallow lakes. bioRxiv, 2022.02.23.481597, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.02.23.481597

The importance of the vertical structure of vegetation cover for the functioning, management and conservation of ecosystems has received particular attention from ecologists in the last decades. Canopy architecture has many implications for light extinction coefficient, temperature variation reduction, self-shading which are all key parameters for the structuring and functioning of different ecosystems such as grasslands [1,2], forests [3,4], phytoplankton communities [5, 6], macroalgal populations [7] and even underwater animal forests such as octocoral communities [8].

This research topic, therefore, benefits from a large body of literature and the facilitative role of self-shadowing is no longer in question. However, it is always puzzling to note that some of the most common ecosystems turn out to be amongst the least known. This is precisely the case of the Fucus serratus communities which are widespread in Northeast Atlantic along the Atlantic coast of Europe from Svalbard to Portugal, as well as Northwest Atlantic & Gulf of St. Lawrence, easily accessible at low tide, but which have comparatively received less attention than more emblematic macro-algal communities such as Laminariales.

The lack of attention paid to these most common Fucales is particularly critical as some species such as F. serratus are proving to be particularly vulnerable to environmental change, leading to a predicted northward retreat from its current southern boundary [9].

In the present study [10], the authors showed the importance of the vegetation cover in resisting tide-induced environmental stresses. The canopy of F. serratus mitigates stress levels experienced in the lower layers during emersion, while various acclimation strategies take over to maintain the photosynthetic apparatus in optimal conditions.

They hereby highlight adaptation mechanisms to the extreme environment represented by the intertidal zone. These adaptation strategies were expected and similar mechanisms had been shown at the cellular level previously [11]. The earliest studies on the subject have shown that the structure of the bottom, the movement of water, and light availability all "influence the distribution of Fucaceae and disturb the regularity of their fine zonation, which itself is caused by the most important factor, desiccation", as Zaneveld states in his review [12]. He observed that the causes of the zonal distribution of marine algae are numerous, and identified several points of interest such as the relative period of emersion, the rapidity of desiccation, the loss of water, and the thickness of the cell walls.

The present study thus highlights the existence of facilitative mechanisms associated with F. serratus canopy and nicely confirms previous work with in situ observations. It also highlights the importance of the vegetative cover in combating desiccation and introduces the dampening effect as a facilitating mechanism.

The effect of the vegetation cover can sometimes even be felt beyond its immediate area of influence. A recent study shows that ground-level ozone is significantly reduced by the combined effects of canopy shading and turbulence [4]. Below the canopy, the light intensity becomes sufficiently low which inhibits ozone formation due to the decrease in the rates of hydroxyl radical formation and the rates of conversion of nitrogen dioxide to nitrogen oxide by photolysis. In addition, reductions in light levels associated with foliage promote ozone-destroying reactions between plant-emitted species, such as nitric oxide and/or alkenes, and ozone itself. The reduction in diffusivity slows the upward transport of surface emitted species, partially decoupling the area under the canopy from the rest of the atmosphere.

By analogy with the work of Makar et al [4], and in the light of the results provided by the authors of this study, one may wonder whether the canopy dampening of F. serratus communities (and other common fucoids widely distributed on our coasts) might not also influence atmospheric chemistry, both at the Earth's surface and in the atmospheric boundary layer. The lack of accumulation of reactive oxygen species under the canopy found by the authors is consistent with this hypothesis and suggests that the damping effect of F. serratus may well have much wider consequences than expected.

References

[1] Jurik TW, Kliebenstein H (2000) Canopy Architecture, Light Extinction and Self-Shading of a Prairie Grass, Andropogon Gerardii. The American Midland Naturalist, 144, 51–65. http://www.jstor.org/stable/3083010

[2] Mitchley J, Willems JH (1995) Vertical canopy structure of Dutch chalk grasslands in relation to their management. Vegetatio, 117, 17–27. https://doi.org/10.1007/BF00033256

[3] Kane VR, Gillespie AR, McGaughey R, Lutz JA, Ceder K, Franklin JF (2008) Interpretation and topographic compensation of conifer canopy self-shadowing. Remote Sensing of Environment, 112, 3820–3832. https://doi.org/10.1016/j.rse.2008.06.001

[4] Makar PA, Staebler RM, Akingunola A, Zhang J, McLinden C, Kharol SK, Pabla B, Cheung P, Zheng Q (2017) The effects of forest canopy shading and turbulence on boundary layer ozone. Nature Communications, 8, 15243. https://doi.org/10.1038/ncomms15243

[5] Shigesada N, Okubo A (1981) Analysis of the self-shading effect on algal vertical distribution in natural waters. Journal of Mathematical Biology, 12, 311–326. https://doi.org/10.1007/BF00276919

[6] Barros MP, Pedersén M, Colepicolo P, Snoeijs P (2003) Self-shading protects phytoplankton communities against H2O2-induced oxidative damage. Aquatic Microbial Ecology, 30, 275–282. https://doi.org/10.3354/ame030275

[7] Ørberg SB, Krause-Jensen D, Mouritsen KN, Olesen B, Marbà N, Larsen MH, Blicher ME, Sejr MK (2018) Canopy-Forming Macroalgae Facilitate Recolonization of Sub-Arctic Intertidal Fauna and Reduce Temperature Extremes. Frontiers in Marine Science, 5. https://doi.org/10.3389/fmars.2018.00332

[8] Nelson H, Bramanti L (2020) From Trees to Octocorals: The Role of Self-Thinning and Shading in Underwater Animal Forests. In: Perspectives on the Marine Animal Forests of the World (eds Rossi S, Bramanti L), pp. 401–417. Springer International Publishing, Cham. https://doi.org/10.1007/978-3-030-57054-5_12

[9] Jueterbock A, Kollias S, Smolina I, Fernandes JMO, Coyer JA, Olsen JL, Hoarau G (2014) Thermal stress resistance of the brown alga Fucus serratus along the North-Atlantic coast: Acclimatization potential to climate change. Marine Genomics, 13, 27–36. https://doi.org/10.1016/j.margen.2013.12.008

[10] Migné A, Duong G, Menu D, Davoult D, Gévaert F (2021) Dynamics of Fucus serratus thallus photosynthesis and community primary production during emersion across seasons: canopy dampening and biochemical acclimation. HAL, hal-03079617, ver. 4 peer-reviewed and recommended by Peer community in Ecology. https://hal.archives-ouvertes.fr/hal-03079617

[11] Lichtenberg M, Kühl M (2015) Pronounced gradients of light, photosynthesis and O2 consumption in the tissue of the brown alga Fucus serratus. New Phytologist, 207, 559–569. https://doi.org/10.1111/nph.13396

[12] Zaneveld JS (1937) The Littoral Zonation of Some Fucaceae in Relation to Desiccation. Journal of Ecology, 25, 431–468. https://doi.org/10.2307/2256204