Ivimey Cook et al. (2023) provide a concise and useful “How to” review code for researchers in the fields of ecology and evolutionary biology, where the systematic review of code is not yet standard practice during the peer review of articles. Consequently, this article is full of tips for authors on how to make their code easier to review. This handy article applies not only to ecology and evolutionary biology, but to many fields that are learning how to make code more reproducible and shareable. Taking this step toward transparency is key to improving research rigor (Brito et al. 2020) and is a necessary step in helping make research trustable by the public (Rosman et al. 2022).

References

Brito, J. J., Li, J., Moore, J. H., Greene, C. S., Nogoy, N. A., Garmire, L. X., & Mangul, S. (2020). Recommendations to enhance rigor and reproducibility in biomedical research. GigaScience, 9(6), giaa056. https://doi.org/10.1093/gigascience/giaa056

Ivimey-Cook, E. R., Pick, J. L., Bairos-Novak, K., Culina, A., Gould, E., Grainger, M., Marshall, B., Moreau, D., Paquet, M., Royauté, R., Sanchez-Tojar, A., Silva, I., Windecker, S. (2023). Implementing Code Review in the Scientific Workflow: Insights from Ecology and Evolutionary Biology. EcoEvoRxiv, ver 5 peer-reviewed and recommended by Peer Community In Ecology. https://doi.org/10.32942/X2CG64

Rosman, T., Bosnjak, M., Silber, H., Koßmann, J., & Heycke, T. (2022). Open science and public trust in science: Results from two studies. Public Understanding of Science, 31(8), 1046-1062. https://doi.org/10.1177/09636625221100686

The loss of biodiversity is an issue of great concern, especially if the extinction of species or the loss of a large number of individuals within populations results in a loss of critical ecosystem services. We know that the most important threat to most species is habitat loss and degradation (Keil et al., 2015; Pimm et al., 2014); the latter can be caused by multiple anthropogenic activities, including pollution, introduction of invasive species and fragmentation (Brook et al., 2008; Scanes, 2018). Roads are a major cause of habitat fragmentation, isolating previously connected populations and being a direct source of mortality for animals that attempt to cross them (Spellberg, 1998).
While most studies have focused on the effect of roads on larger mammals (Bartonička et al., 2018; Litvaitis and Tash, 2008), in recent years many researchers have grown increasingly concerned about the risk of collision between bats and vehicles (Fensome and Mathews, 2016). For example, a recent publication by Medinas et al. (2021) found 509 bat casualties along a 51-km-long transect during a period of 3 years. Their study provides extremely valuable information to asses which factors primarily drive bat mortality on roads, yet it required a substantial investment of time coupled with the difficulty of detecting bat carcasses. Other studies have used acoustic monitoring as a proxy to gauge risk of collision based on estimates of bat density along roads (reviewed in Fensome and Mathews 2016); while the results of such studies are valuable, the number of passes recorded does not necessarily equal collision risk, as many species may simply avoid crossing the roads. Understanding the risk of collisions is of vital importance for adequate planning of road construction, particularly for key sites that harbor threatened bat species or unusually large populations, especially if these are already greatly impacted by other anthropogenic activities (e.g. wind turbines; Kunz et al. 2007) or unusually deadly pathogens (e.g. white-nose syndrome; Blehert et al. 2009).
The study by Roemer et al. (2020) titled “Influence of local landscape and time of year on bat-road collision risks”, is a welcome addition to our understanding of bat collision risk as it employs a more accurate assessment of bat collision risk based on acoustic monitoring and tracking of flight paths. The goal of the study of Roemer and collaborators, which was conducted at 66 study sites in the Mediterranean region, is to provide an assessment of collision risk based on bat activity near roads. They collected a substantial amount of information for several species: more than 30,000 estimated flight trajectories for 21+ species, including Barbastella barbastellus, Myotis spp., Plecotus sp., Rhinolophus ferrumequinum, Miniopterus schreibersii, Pipistrellus spp., Nyctalus leisleri, and others. They assess risk based on estimates of 1) species abundance from acoustic monitoring, 2) direction of flight paths along roads, and 3) bat-vehicle co-occurrence.
Their findings suggest that risk is habitat, species, guild, and season-specific. Roads within forested habitats posed the largest threats for most species, particularly since most flights within these habitats occurred at the zone of collision risk. They also found that bats typically fly parallel to the road axis regardless of habitat type, which they argue supports the idea that bats may use roads as corridors. The results of their study, as expected, also show that the majority of bat passes were detected during summer or autumn, depending on species, yet they provide novel findings of an increase in risky behaviors during autumn, when the number of passes at the zone of collision risk increased significantly. Their results also suggest that mid-range echolocators, a classification that is based on call design and parameters (Frey-Ehrenbold et al., 2013), had a larger portion of flights in the zone at risk, thus potentially making them more susceptible than short and long-range echolocators to collisions with vehicles.
The methods employed by Roemer et al. (2020) could further help us determine how roads pose species and site-specific threats in a diversity of places without the need to invest a significant amount of time locating bat carcasses. Their findings are also important as they could provide valuable information for deciding where new roads should be constructed, particularly if the most vulnerable species are abundant, perhaps due to the presence of important roost sites. They also show how habitats near larger roads could increase threats, providing an important first step for recommendations regarding road construction and maintenance. As pointed out by one reviewer, one possible limitation of the study is that the results are not supported by the identification of carcasses. For example, does an increase in the number of identified flights at the zone of risk really translate into an increase in the number of collisions? Regardless of the latter, the paper’s methods and results are very valuable and provide an important step towards developing additional tools to assess bat-vehicle collision risks.

References

[1] Bartonička T, Andrášik R, Duľa M, Sedoník J, Bíl M (2018) Identification of local factors causing clustering of animal-vehicle collisions. The Journal of Wildlife Management, 82, 940–947. https://doi.org/10.1002/jwmg.21467
[2] Blehert DS, Hicks AC, Behr M, Meteyer CU, Berlowski-Zier BM, Buckles EL, Coleman JTH, Darling SR, Gargas A, Niver R, Okoniewski JC, Rudd RJ, Stone WB (2009) Bat White-Nose Syndrome: An Emerging Fungal Pathogen? Science, 323, 227–227. https://doi.org/10.1126/science.1163874
[3] Brook BW, Sodhi NS, Bradshaw CJA (2008) Synergies among extinction drivers under global change. Trends in Ecology & Evolution, 23, 453–460. https://doi.org/10.1016/j.tree.2008.03.011
[4] Fensome AG, Mathews F (2016) Roads and bats: a meta-analysis and review of the evidence on vehicle collisions and barrier effects. Mammal Review, 46, 311–323. https://doi.org/10.1111/mam.12072
[5] Frey‐Ehrenbold A, Bontadina F, Arlettaz R, Obrist MK (2013) Landscape connectivity, habitat structure and activity of bat guilds in farmland-dominated matrices. Journal of Applied Ecology, 50, 252–261. https://doi.org/10.1111/1365-2664.12034
[6] Keil P, Storch D, Jetz W (2015) On the decline of biodiversity due to area loss. Nature Communications, 6, 8837. https://doi.org/10.1038/ncomms9837
[7] Kunz TH, Arnett EB, Erickson WP, Hoar AR, Johnson GD, Larkin RP, Strickland MD, Thresher RW, Tuttle MD (2007) Ecological impacts of wind energy development on bats: questions, research needs, and hypotheses. Frontiers in Ecology and the Environment, 5, 315–324. https://doi.org/10.1890/1540-9295(2007)5[315:EIOWED]2.0.CO;2
[8] Litvaitis JA, Tash JP (2008) An Approach Toward Understanding Wildlife-Vehicle Collisions. Environmental Management, 42, 688–697. https://doi.org/10.1007/s00267-008-9108-4
[9] Medinas D, Marques JT, Costa P, Santos S, Rebelo H, Barbosa AM, Mira A (2021) Spatiotemporal persistence of bat roadkill hotspots in response to dynamics of habitat suitability and activity patterns. Journal of Environmental Management, 277, 111412. https://doi.org/10.1016/j.jenvman.2020.111412
[10] Pimm SL, Jenkins CN, Abell R, Brooks TM, Gittleman JL, Joppa LN, Raven PH, Roberts CM, Sexton JO (2014) The biodiversity of species and their rates of extinction, distribution, and protection. Science, 344. https://doi.org/10.1126/science.1246752
[11] Roemer C, Coulon A, Disca T, Bas Y (2020) Influence of local landscape and time of year on bat-road collision risks. bioRxiv, 2020.07.15.204115, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2020.07.15.204115
[12] Scanes CG (2018) Chapter 19 - Human Activity and Habitat Loss: Destruction, Fragmentation, and Degradation. In: Animals and Human Society (eds Scanes CG, Toukhsati SR), pp. 451–482. Academic Press. https://doi.org/10.1016/B978-0-12-805247-1.00026-5
[13] Spellerberg I (1998) Ecological effects of roads and traffic: a literature review. Global Ecology & Biogeography Letters, 7, 317–333. https://doi.org/10.1046/j.1466-822x.1998.00308.x

As biodiversity has become a major global concern for a variety of stakeholders, and society in general, assessments of biodiversity trends at all spatial scales have flourished in the past decades. To assess trends, one needs data, and the more precise the data, the more precise the trend. Or, if precision is not perfect, uncertainty in the data must be acknowledged and accounted for. Such considerations have already been raised in ecology, most notably regarding the value of species distribution data to model the current and future distribution of species (Rocchini et al., 2011, Duputié et al., 2014, Tessarolo et al., 2021), leading to serious doubts regarding the value of public databases (Maldonado et al., 2015). And more recently similar issues have been raised regarding databases of species traits (Augustine et al., 2024), emphasizing the importance of good data practice and traceability.

Science is by nature a self-correcting human process, with many steps of the scientific activity prone to errors and misinterpretations. Collation of ecological data, sadly, is proof of this. Spurred by the astonishing results of Hallmann et al. (2017) regarding the decline of insect biomass, and to more precisely answer the question of biodiversity trends in insects and settle an ongoing debate (Cardinale et al., 2018), van Klink et al. (2020, 2021) established the InsectChange database. Several perceptive comments have already been made regarding the possible issues in the methods and interpretations of this study (Desquilbet et al., 2020, Jähnig et al., 2021, Duchenne et al., 2022). However, the biggest issue might have been finally unearthed by Gaume & Desquilbet (2024): with poorly curated data, the InsectChange database is unlikely to support most of the initial claims regarding insect biodiversity trends.

The compilation of errors and inconsistencies present in InsectChange and evinced by Gaume & Desquilbet (2024) is stunning to say the least, with a mix of field and experimental data combined without regard for experimental manipulation of environmental factors, non-standardised transformations of abundances, the use of non-insect taxa to compute insect trends, and inadequate geographical localizations of samplings. I strongly advise all colleagues interested in the study of biodiversity from global databases to consider the points raised by the authors, as it is quite likely that other databases might suffer from the same ailments as well. Reading this paper is also educating and humbling in its own way, since the publication of the original papers based on InsectChange seems to have proceeded without red flags from reviewers or editors. The need for publishing fast results that will make the next buzz, thus obeying the natural selection of bad science (Smaldino and McElreath, 2016), might be the systemic culprit. However, this might also be the opportunity ecology needs to consider the reviewing and curation of data as a crucial step of science quality assessment. To make final assessments, let us proceed with less haste.

References

Augustine, S. P., Bailey-Marren, I., Charton, K. T., Kiel, N. G. & Peyton, M. S. (2024) Improper data practices erode the quality of global ecological databases and impede the progress of ecological research. Global Change Biology, 30, e17116. https://doi.org/10.1111/gcb.17116

Cardinale, B. J., Gonzalez, A., Allington, G. R. H. & Loreau, M. (2018) Is local biodiversity declining or not? A summary of the debate over analysis of species richness time trends. Biological Conservation, 219, 175-183. https://doi.org/10.1016/j.biocon.2017.12.021

Desquilbet, M., Gaume, L., Grippa, M., Céréghino, R., Humbert, J.-F., Bonmatin, J.-M., Cornillon, P.-A., Maes, D., Van Dyck, H. & Goulson, D. (2020) Comment on “Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances”. Science, 370, eabd8947. https://doi.org/10.1126/science.abd8947

Duchenne, F., Porcher, E., Mihoub, J.-B., Loïs, G. & Fontaine, C. (2022) Controversy over the decline of arthropods: a matter of temporal baseline? Peer Community Journal, 2. https://doi.org/10.24072/pcjournal.131

Duputié, A., Zimmermann, N. E. & Chuine, I. (2014) Where are the wild things? Why we need better data on species distribution. Global Ecology and Biogeography, 23, 457-467. https://doi.org/10.1111/geb.12118

Gaume, L. & Desquilbet, M. (2024) InsectChange: Comment. biorXiv, ver.4 peer-reviewed and recommended by PCI Ecology https://doi.org/10.1101/2023.06.17.545310

Hallmann, C. A., Sorg, M., Jongejans, E., Siepel, H., Hofland, N., Schwan, H., Stenmans, W., Müller, A., Sumser, H., Hörren, T., Goulson, D. & de Kroon, H. (2017) More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLOS ONE, 12, e0185809. https://doi.org/10.1371/journal.pone.0185809

Jähnig, S. C., Baranov, V., Altermatt, F., Cranston, P., Friedrichs-Manthey, M., Geist, J., He, F., Heino, J., Hering, D., Hölker, F., Jourdan, J., Kalinkat, G., Kiesel, J., Leese, F., Maasri, A., Monaghan, M. T., Schäfer, R. B., Tockner, K., Tonkin, J. D. & Domisch, S. (2021) Revisiting global trends in freshwater insect biodiversity. WIREs Water, 8, e1506. https://doi.org/10.1002/wat2.1506

Maldonado, C., Molina, C. I., Zizka, A., Persson, C., Taylor, C. M., Albán, J., Chilquillo, E., Rønsted, N. & Antonelli, A. (2015) Estimating species diversity and distribution in the era of Big Data: to what extent can we trust public databases? Global Ecology and Biogeography, 24, 973-984. https://doi.org/10.1111/geb.12326

Rocchini, D., Hortal, J., Lengyel, S., Lobo, J. M., Jiménez-Valverde, A., Ricotta, C., Bacaro, G. & Chiarucci, A. (2011) Accounting for uncertainty when mapping species distributions: The need for maps of ignorance. Progress in Physical Geography, 35, 211-226. https://doi.org/10.1177/0309133311399491

Smaldino, P. E. & McElreath, R. (2016) The natural selection of bad science. Royal Society Open Science, 3. https://doi.org/10.1098/rsos.160384

Tessarolo, G., Ladle, R. J., Lobo, J. M., Rangel, T. F. & Hortal, J. (2021) Using maps of biogeographical ignorance to reveal the uncertainty in distributional data hidden in species distribution models. Ecography, 44, 1743-1755. https://doi.org/10.1111/ecog.05793

van Klink, R., Bowler, D. E., Comay, O., Driessen, M. M., Ernest, S. K. M., Gentile, A., Gilbert, F., Gongalsky, K. B., Owen, J., Pe'er, G., Pe'er, I., Resh, V. H., Rochlin, I., Schuch, S., Swengel, A. B., Swengel, S. R., Valone, T. J., Vermeulen, R., Wepprich, T., Wiedmann, J. L. & Chase, J. M. (2021) InsectChange: a global database of temporal changes in insect and arachnid assemblages. Ecology, 102, e03354. https://doi.org/10.1002/ecy.3354

van Klink, R., Bowler, D. E., Gongalsky, K. B., Swengel, A. B., Gentile, A. & Chase, J. M. (2020) Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science, 368, 417-420. https://doi.org/10.1126/science.aax9931

Most, if not all, predators consume carrion in some circumstances (Sebastián-Gonzalez et al. 2023). Consequently, significant fluctuations in carrion availability can impact predator-prey dynamics by altering the ratio of carrion to live prey in the predators' diet (Roth 2003). Changes in carrion availability may lead to reduced predation when carrion is more abundant (hypo-predation) and intensified predation if predator populations surge in response to carrion influxes but subsequently face scarcity (hyper-predation), (Moleón et al. 2014, Mellard et al. 2021). However, this relationship between predation and scavenging is often challenging because of the lack of empirical data.
 
In the study conducted by Sidous et al. (2024), they used a large database on the abundance of spotted hyenas and their prey in Zimbabwe and Multivariate Autoregressive State-Space Models to calculate hyena and prey population densities and trends over a 60-year span. The researchers took advantage of abrupt fluctuations in elephant carcass availability that produced alternating periods of high and low carrion availability related to changing management strategies (i.e., elephant culling and water supply).
 
Interestingly, their analyses reveal a coupling of predator and prey densities over time, but they do not detect an effect of carcass availability on predator and prey dynamics. However, the density of prey and hyena was partially driven by the different temporal periods, suggesting some subtle effects of carrion availability on population trends. While it is acknowledged that other variables likely impact the population dynamics of hyenas and their prey, this is the first attempt to understand the influence of carrion pulses on predator-prey interactions across an extensive temporal scale. I hope this helps to establish a new research line on the effect of large carrion pulses, as this is currently largely understudied, even though the occurrence of carrion pulses, such as mass mortality events, is expected to increase over time (Fey et al. 2015).
 
References
 
Courchamp, F. et al. 2000. Rabbits killing birds: modelling the hyperpredation process. J. Anim. Ecol. 69: 154-164.
https://doi.org/10.1046/j.1365-2656.2000.00383.x

Fey, S. B. et al. 2015. Recent shifts in the occurrence, cause, and magnitude of animal mass mortality events. PNAS 112: 1083-1088.
https://doi.org/10.1073/pnas.1414894112
 
Mellard, J. P. et al. 2021. Effect of scavenging on predation in a food web. Ecol. Evol. 11: 6742- 6765.
https://doi.org/10.1002/ece3.7525

Moleón, M. et al. 2014. Inter-specific interactions linking predation and scavenging in terrestrial vertebrate assemblages. Biol. Rev. Camb. Philos. Soc. 89: 1042-1054.
https://doi.org/10.1111/brv.12097
 
Roth, J. 2003. Variability in marine resources affects arctic fox population dynamics. J. Anim. Ecol. 72: 668-676.
https://doi.org/10.1046/j.1365-2656.2003.00739.x
 
Sebastián-González, E. et al. 2023. The underestimated role of carrion in diet studies. Global Ecol. Biogeogr. 32: 1302-1310.
https://doi.org/10.1111/geb.13707
 
Sidous, M. et al. 2024. Insights on the effect of mega-carcass abundance on 1 the population dynamics of a facultative scavenger predator and its prey. bioRxiv, ver. 2 peer-reviewed and recommended by PCI Ecology.
https://doi.org/10.1101/2023.11.08.566247

Urban areas are expanding worldwide, and have become a dominant part of the landscape for many species. Urbanization can fragment pre-existing populations of vulnerable species leading to population declines and the loss of connectivity. On the other hand, expansion of urban areas can also facilitate the spread of human commensals including pests. Knowledge of the features of cityscapes that facilitate gene flow and maintain diversity of pests is thus key to their management and eradication.
Cities are complex mosaics of natural and manmade surfaces, and habitat quality is not only influenced by physical aspects of the cityscape but also by socioeconomic factors and human behaviour. Constant development means that cities also change rapidly in time; contemporary urban life reflects only a snapshot of the environmental conditions faced by populations. It thus remains a challenge to identify the features that actually drive ecology and evolution of populations in cities [1]. While several studies have highlighted strong urban clines in genetic structure and adaption [2], few have considered the influence of factors beyond physical aspects of the cityscape or historical processes.
In this paper, Stragier et al. [3] sought to identify the current and past features of the cityscape and socioeconomic factors that shape genetic structure and diversity of the house mouse (Mus musculus domesticus) in Dakar, Senegal. The authors painstakingly digitized historical maps of Dakar from the time of European settlement in 1862 to present. The authors found that the main spatial genetic cline was best explained by historical cityscape features, with higher apparent gene flow and genetic diversity in areas that were connected earlier to initial European settlements. Beyond the main trend of spatial genetic structure, they found further evidence that current features of the cityscape were important. Specifically, areas with low vegetation and poor housing conditions were found to support large, genetically diverse populations. The authors demonstrate that their results are reproducible using several statistical approaches, including modeling that explicitly accounts for spatial autocorrelation.
The work of Stragier et al. [3] thus highlights that populations of city-dwelling species are the product of both past and present cityscapes. Going forward, urban evolutionary ecologists should consider that despite the potential for rapid evolution in urban landscapes, the signal of a species’ colonization can remain for generations.

References

[1] Rivkin, L. R., Santangelo, J. S., Alberti, M. et al. (2019). A roadmap for urban evolutionary ecology. Evolutionary Applications, 12(3), 384-398. doi: 10.1111/eva.12734
[2] Miles, L. S., Rivkin, L. R., Johnson, M. T., Munshi‐South, J. and Verrelli, B. C. (2019). Gene flow and genetic drift in urban environments. Molecular ecology, 28(18), 4138-4151. doi: 10.1111/mec.15221
[3] Stragier, C., Piry, S., Loiseau, A., Kane, M., Sow, A., Niang, Y., Diallo, M., Ndiaye, A., Gauthier, P., Borderon, M., Granjon, L., Brouat, C. and Berthier, K. (2020). Interplay between historical and current features of the cityscape in shaping the genetic structure of the house mouse (Mus musculus domesticus) in Dakar (Senegal, West Africa). bioRxiv, 557066, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/557066