Estimating population parameters is critical for analysis and management of wildlife populations. Drawing inference at the population level requires a robust sampling scheme and information about the representativeness of the studied population (Williams et al. 2002). In their textbook, Williams et al. (see chapter 5, 2002) listed several sampling issues, including both temporal and spatial heterogeneity and especially imperfect detection. Several methods, either sampling-based or model-based can be used to circumvent these issues.

In their paper, Kissling et al. (2024) addressed the case of the Kittlitz’s murrelet (Brachyramphus brevirostris), a cryptic ice-associated seabird, combining spatial variation in its distribution, temporal variation in breeding propensity, imperfect detection and logistical challenges to access the breeding area. The Kittlitz’s murrelet is thus the perfect species to illustrate common issues and logistical difficulties to implement a standard sampling scheme. 

The authors proposed a modelling framework unifying several datasets from different surveys to extract information on each step of the detection process: the spatial match between the targeted population and the sampled population, the probability of presence in the sample area, the probability of availability given presence in the sample area and finally, the probability of detection given presence and availability. All these components were part of the framework to estimate abundance and trend for this species. 

They took advantage of a radiotracking survey during several years to inform spatial match and probability of presence. They performed a behavioural experiment to assess the probability of availability of murrelets given it was present in sampling area, and they used a conventional distance-sampling boat survey to estimate detection of individuals. This is worth noting that the most variable components were the probability of presence in the sample area, with a global mean of 0.50, and the probability of detection given presence and availability ranging from 0.49 to 0.77. The estimated trend for Kittlitz’s murrelet was negative and all the information gathered in this study will be useful for future conservation plan. 

Coupling a decomposition of the detection process with different data sources was the key to solve problems raised by such “difficult” species, and the paper of Kissling et al. (2024) is a good way to follow for other species, allowing to inform the detection components for the targeted species - and also for our global understanding of detection process, and to infer about the temporal trend of species of conservation concern. 

References

Williams, B. K., Nichols, J. D., and Conroy, M. J. (2002). Analysis and management of animal populations. Academic Press.

Michelle L. Kissling, Paul M. Lukacs, Kelly Nesvacil, Scott M. Gende, Grey W. Pendleton (2024) Using multiple datasets to account for misalignment between statistical and biological populations for abundance estimation. EcoEvoRxiv, ver.3 peer-reviewed and recommended by PCI Ecology https://doi.org/10.32942/X2W03T

Since Charles Darwin times, and probably earlier, naturalists have been eager to report the rarest pollinators being discovered, and this still happens even in recent times; e.g., increased evidence of lizards, cockroaches, crickets or earwigs as pollinators (Suetsugu 2018, Komamura et al. 2021, de Oliveira-Nogueira et al. 2023), shifts to invasive animals as pollinators, including passerine birds and rats (Pattemore & Wilcove 2012), new amazing cases of mimicry in pollination, such as “bleeding” flowers that mimic wounded insects (Heiduk et al., 2023) or even the possibility that a tree frog is reported for the first time as a pollinator (de Oliveira-Nogueira et al. 2023). This is in part due to a natural curiosity of humans about rarity, which pervades into scientific insight (Gaston 1994). Among pollinators, the apparent rarity of some interaction types is sometimes a symptom of a lack of enough inquiry. This seems to be the case of weevil pollination, given that these insects are widely recognized as herbivores, particularly those that use plant parts to nurse their breed and never were thought they could act also as mutualists, pollinating the species they infest. This is known as a case of brood site pollination mutualism (BSPM), which also involves an antagonistic counterpart (herbivory) to which plants should face. This is the focus of the manuscript (Haran et al. 2023) we are recommending here. There is wide treatment of this kind of pollination in textbooks, albeit focused on yucca-yucca moth and fig-fig wasp interactions due to their extreme specialization (Pellmyr 2003, Kjellberg et al. 2005), and more recently accompanied by Caryophyllaceae-moth relationship (Kephart et al. 2006). 

Here we find a detailed review that shows that the most diverse BSPM, in terms of number of plant and pollinator species involved, is that of weevils in the tropics. The mechanism of BSPM does not involve a unique morphological syndrome, as it is mostly functional and thus highly dependent on insect biology (Fenster & al. 2004), whereas the flower phenotypes are highly divergent among species. Probably, the inconspicuous nature of the interaction, and the overwhelming role of weevils as seed predators, even as pests, are among the causes of the neglection of weevils as pollinators, as it could be in part the case of ants as pollinators (de Vega et al. 2014). The paper by Haran et al (2023) comes to break this point.

Thus, the rarity of weevil pollination in former reports is not a consequence of an anecdotical nature of this interaction, even for the BSPM, according to the number of cases the authors are reporting, both in terms of plant and pollinator species involved. This review has a classical narrative format which involves a long text describing the natural history behind the cases. It is timely and fills the gap for this important pollination interaction for biodiversity and also for economic implications for fruit production of some crops. Former reviews have addressed related topics on BSPM but focused on other pollinators, such as those mentioned above. Besides, the review put much effort into the animal side of the interaction, which is not common in the pollination literature. Admittedly, the authors focus on the detailed description of some paradigmatic cases, and thereafter suggest that these can be more frequently reported in the future, based on varied evidence from morphology, natural history, ecology, and distribution of alleged partners. This procedure was common during the development of anthecology, an almost missing term for floral ecology (Baker 1983), relying on accumulative evidence based on detailed observations and experiments on flowers and pollinators. Currently, a quantitative approach based on the tools of macroecological/macroevolutionary analyses is more frequent in reviews. However, this approach requires a high amount of information on the natural history of the partnership, which allows for sound hypothesis testing. By accumulating this information, this approach allows the authors to pose specific questions and hypotheses which can be tested, particularly on the efficiency of the systems and their specialization degree for both the plants and the weevils, apparently higher for the latter. This will guarantee that this paper will be frequently cited by floral ecologists and evolutionary biologists and be included among the plethora of floral syndromes already described, currently based on more explicit functional grounds (Fenster et al. 2004). In part, this is one of the reasons why the sections focused on future prospects is so large in the review. 

I foresee that this mutualistic/antagonistic relationship will provide excellent study cases for the relative weight of these contrary interactions among the same partners and its relationship with pollination specialization-generalization and patterns of diversification in the plants and/or the weevils. As new studies are coming, it is possible that BSPM by weevils appears more common in non-tropical biogeographical regions. In fact, other BSPM are not so uncommon in other regions (Prieto-Benítez et al. 2017). In the future, it would be desirable an appropriate testing of the actual effect of phylogenetic niche conservatism, using well known and appropriately selected BSPM cases and robust phylogenies of both partners in the mutualism. Phylogenetic niche conservatism is a central assumption by the authors to report as many cases as possible in their review, and for that they used taxonomic relatedness. As sequence data and derived phylogenies for large numbers of vascular plant species are becoming more frequent (Jin & Quian 2022), I would recommend the authors to perform a comparative analysis using this phylogenetic information. At least, they have included information on phylogenetic relatedness of weevils involved in BSPM which allow some inferences on the multiple origins of this interaction. This is a good start to explore the drivers of these multiple origins through the lens of comparative biology.

References

Baker HG (1983) An Outline of the History of Anthecology, or Pollination Biology. In: L Real (ed). Pollination Biology. Academic Press.

de-Oliveira-Nogueira CH, Souza UF, Machado TM, Figueiredo-de-Andrade CA, Mónico AT, Sazima I, Sazima M, Toledo LF (2023). Between fruits, flowers and nectar: The extraordinary diet of the frog Xenohyla truncate. Food Webs 35: e00281. https://doi.org/10.1016/j.fooweb.2023.e00281

Fenster CB W, Armbruster S, Wilson P, Dudash MR, Thomson JD (2004). Pollination syndromes and floral specialization. Annu. Rev. Ecol. Evol. Syst. 35: 375–403. https://doi.org/10.1146/annurev.ecolsys.34.011802.132347

Gaston KJ (1994). What is rarity? In KJ Gaston (ed): Rarity. Population and Community Biology Series, vol 13. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-0701-3_1

Haran J, Kergoat GJ, Bruno, de Medeiros AS (2023) Most diverse, most neglected: weevils (Coleoptera: Curculionoidea) are ubiquitous specialized brood-site pollinators of tropical flora. hal. 03780127, version 2 peer-reviewed and recommended by Peer Community in Ecology. https://hal.inrae.fr/hal-03780127

Heiduk A, Brake I, Shuttleworth A, Johnson SD (2023) ‘Bleeding’ flowers of Ceropegia gerrardii (Apocynaceae-Asclepiadoideae) mimic wounded insects to attract kleptoparasitic fly pollinators. New Phytologist. https://doi.org/10.1111/nph.18888

Jin, Y., & Qian, H. (2022). V. PhyloMaker2: An updated and enlarged R package that can generate very large phylogenies for vascular plants. Plant Diversity, 44(4), 335-339. https://doi.org/10.1016/j.pld.2022.05.005

Kjellberg F, Jousselin E, Hossaert-Mckey M, Rasplus JY (2005). Biology, ecology, and evolution of fig-pollinating wasps (Chalcidoidea, Agaonidae). In: A. Raman et al (eds) Biology, ecology and evolution of gall-inducing arthropods 2, 539-572. Science Publishers, Enfield.

Komamura R, Koyama K, Yamauchi T, Konno Y, Gu L (2021). Pollination contribution differs among insects visiting Cardiocrinum cordatum flowers. Forests 12: 452. https://doi.org/10.3390/f12040452

Pattemore DE, Wilcove DS (2012) Invasive rats and recent colonist birds partially compensate for the loss of endemic New Zealand pollinators. Proc. R. Soc. B 279: 1597–1605. https://doi.org/10.1098/rspb.2011.2036

Pellmyr O (2003) Yuccas, yucca moths, and coevolution: a review. Ann. Missouri Bot. Gard. 90: 35-55. https://doi.org/10.2307/3298524

Prieto-Benítez S, Yela JL, Giménez-Benavides L (2017) Ten years of progress in the study of Hadena-Caryophyllaceae nursery pollination. A review in light of new Mediterranean data. Flora, 232, 63-72. https://doi.org/10.1016/j.flora.2017.02.004

Suetsugu K (2019) Social wasps, crickets and cockroaches contribute to pollination of the holoparasitic plant Mitrastemon yamamotoi (Mitrastemonaceae) in southern Japan. Plant Biology 21 176–182. https://doi.org/10.1111/plb.12889

Rodents are well known as one of the main animal groups responsible for human-transmitted pathogens. As such, it seems logical to try and survey what kinds of pathogenic microbes might be harboured by wild rodents, in order to establish some baseline surveillance and prevent future zoonotic outbreaks (Bernstein et al., 2022). This is exactly what Abbate et al. (2023) endeavoured and their findings are intimidating. Based on quite a large sampling effort, they collected more than 700 rodents of seven species around two villages in northeastern France. They looked for molecular markers indicative of viral and bacterial infections and proceeded to analyze their pathogen communities using multivariate techniques.

Variation in the prevalence of the different pathogens was found among host species, with e.g. signs of CPXV more prevalent in Cricetidae while some Mycoplasma strains were more prevalent in Muridae. Co-circulation of pathogens was found in all species, with some evidencing signs of up to 12 different pathogen taxa. The diversity of co-circulating pathogens was markedly different between host species and higher in adult hosts, but not affected by sex. The dataset also evinced some slight differences between habitats, with meadows harbouring a little more diversity of rodent pathogens than forests. Less intuitively, some pathogen associations seemed quite repeatable, such as the positive association of Bartonella spp. with CPXV in the montane water vole. The study allowed the authors to test several associations already described in the literature, including associations between different hemotropic Mycoplasma species.

I strongly invite colleagues interested in zoonoses, emerging pandemics and more generally One Health to read the paper of Abbate et al. (2023) and try to replicate them across the world. To prevent the next sanitary crises, monitoring rodents, and more generally vertebrates, population demographics is a necessary and enlightening step (Johnson et al., 2020), but insufficient. Following the lead of colleagues working on rodent ectoparasites (Krasnov et al., 2014), we need more surveys like the one described by Abbate et al. (2023) to understand the importance of the dilution effect in the prevalence and transmission of microbial pathogens (Andreazzi et al., 2023) and the formation of epidemics. We also need other similar studies to assess the potential of different rodent species to carry pathogens more or less capable of infecting other mammalian species (Morand et al., 2015), in other places in the world.

References

Abbate, J. L., Galan, M., Razzauti, M., Sironen, T., Voutilainen, L., Henttonen, H., Gasqui, P., Cosson, J.-F. & Charbonnel, N. (2023) Pathogen community composition and co-infection patterns in a wild community of rodents. BioRxiv, ver.4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2020.02.09.940494 

Andreazzi, C. S., Martinez-Vaquero, L. A., Winck, G. R., Cardoso, T. S., Teixeira, B. R., Xavier, S. C. C., Gentile, R., Jansen, A. M. & D'Andrea, P. S. (2023) Vegetation cover and biodiversity reduce parasite infection in wild hosts across ecological levels and scales. Ecography, 2023, e06579.
https://doi.org/10.1111/ecog.06579
 
Bernstein, A. S., Ando, A. W., Loch-Temzelides, T., Vale, M. M., Li, B. V., Li, H., Busch, J., Chapman, C. A., Kinnaird, M., Nowak, K., Castro, M. C., Zambrana-Torrelio, C., Ahumada, J. A., Xiao, L., Roehrdanz, P., Kaufman, L., Hannah, L., Daszak, P., Pimm, S. L. & Dobson, A. P. (2022) The costs and benefits of primary prevention of zoonotic pandemics. Science Advances, 8, eabl4183.
https://doi.org/10.1126/sciadv.abl4183
 
Johnson, C. K., Hitchens, P. L., Pandit, P. S., Rushmore, J., Evans, T. S., Young, C. C. W. & Doyle, M. M. (2020) Global shifts in mammalian population trends reveal key predictors of virus spillover risk. Proceedings of the Royal Society B: Biological Sciences, 287, 20192736.
https://doi.org/10.1098/rspb.2019.2736
 
Krasnov, B. R., Pilosof, S., Stanko, M., Morand, S., Korallo-Vinarskaya, N. P., Vinarski, M. V. & Poulin, R. (2014) Co-occurrence and phylogenetic distance in communities of mammalian ectoparasites: limiting similarity versus environmental filtering. Oikos, 123, 63-70.
https://doi.org/10.1111/j.1600-0706.2013.00646.x
 
Morand, S., Bordes, F., Chen, H.-W., Claude, J., Cosson, J.-F., Galan, M., Czirjak, G. Á., Greenwood, A. D., Latinne, A., Michaux, J. & Ribas, A. (2015) Global parasite and Rattus rodent invasions: The consequences for rodent-borne diseases. Integrative Zoology, 10, 409-423.
https://doi.org/10.1111/1749-4877.12143

Although monitoring the prevalence of pathogens in wildlife is crucial, there are logistical constraints that make this difficult, costly, and unpractical. This problem is often compounded when attempting to measure the temporal dynamics of prevalence. To improve the detection rate, a commonly used technique is pooling samples, where multiple individuals are analyzed at once. Yet, this introduces further potential biases: low-prevalence samples are effectively diluted through pooling, creating a false negative risk; negative samples are masked by the inclusion of positive samples, possibly artificially inflating the estimate of prevalence (and masking the inter-sample variability).

In their contribution, Borremans et al. (2024) come up with a modelling technique to provide accurate predictions of prevalence dynamics using a mix of pooled and individual samples. Because this model represents the pooling of individual samples as a complete mixing process, it can accurately estimate the prevalence dynamics from pooled samples only.

It is particularly noteworthy that the model provides an estimation of the false negative rate of the test. When there are false negatives (or more accurately, when the true rate at which false negatives happens), the value of the effect coefficients for individual-level covariates are likely to be off, potentially by a substantial amount. But besides more accurate coefficient estimation, the actual false negative rate is important information about the overall performance of the infection test.

The model described in this article also allows for a numerical calculation of the probability density function of infection. It is worth spending some time on how this is achieved, as I found the approach relying on combinatorics to be particularly interesting. When pooling, both the number of individuals that are mixed is known, and so is the measurement made on the pooled samples. The question is to figure out the number of individuals that because they are infectious, contribute to this score. The approach used by the authors is to draw (with replacement) possible positive and negative test outcomes assuming a number of positive individuals, and from this to estimate a pathogen concentration in the positive samples. This pathogen concentration can be transformed into its test outcome, and this value taken over all possible combinations is a conditional estimate of the test outcome, knowing the number of pooled individuals, and estimating the number of positive ones.

This approach is where the use of individual samples informs the model: by providing additional corrections for the relative volume of sample each individual provides, and by informing the transformation of test values into virus concentrations.

The authors make a strong case that their model can provide robust estimates of prevalence even in the presence of common field epidemiology pitfalls, and notably incomplete individual-level information. More importantly, because the model can work from pooled samples only, it gives additional value to samples that would otherwise have been discarded because they did not allow for prevalence estimates.

References

Benny Borremans, Caylee A. Falvo, Daniel E. Crowley, Andrew Hoegh, James O. Lloyd-Smith, Alison J. Peel, Olivier Restif, Manuel Ruiz-Aravena, Raina K. Plowright (2024) Reconstructing prevalence dynamics of wildlife pathogens from pooled and individual samples. bioRxiv, ver.3 peer-reviewed and recommended by PCI Ecology https://doi.org/10.1101/2023.11.02.565200

Which biological traits modulate species distribution has historically been and still is one of the core questions of the macroecology and biogeography agenda [1, 2]. As most of the Earth surface has been modified by human activities [3] understanding the strategies that allow species to inhabit human-dominated landscapes will be key to explain species geographic distribution in the Anthropocene. In this vein, Logan et al. [4] are working on a long-term and integrative project aimed to investigate how great-tailed grackles rapidly expanded their geographic range into North America [4]. Particularly, they want to determine which is the role of behavioral flexibility, i.e. an individual’s ability to modify its behavior when circumstances change based on learning from previous experience [5], in rapid geographic range expansions. The authors are already working in a set of complementary questions described in pre-registrations that have already been recommended at PCI Ecology: (1) Do individuals with greater behavioral flexibility rely more on causal cognition [6]? (2) Which are the mechanisms that lead to behavioral flexibility [7]? (3) Does the manipulation of behavioral flexibility affect exploration, but not boldness, persistence, or motor diversity [8]? (4) Can context changes improve behavioral flexibility [9]?
In this new pre-registration, they aim to determine whether the more behaviorally flexible individuals have more flexible foraging behaviors (i.e. use a wider variety of foraging techniques in the wild and eat a larger number of different foods), habitat use (i.e. higher microhabitat richness) and social relationships (i.e., are more likely to have a greater number of bonds or stronger bonds with other individuals; [4]). The project is ambitious, combining both the experimental characterization of individuals’ behavioral flexibility and the field characterization of the foraging and social behavior of those individuals and of wild ones.
The current great-tailed grackles project will be highly relevant to understand rapid geographic range expansions in a changing world. In this vein, this pre-registration will particularly help to go one step further in our understanding of behavioral flexibility as a determinant of species geographic distribution. Logan et al. [4] pre-registration is very well designed, main and alternative hypotheses have been thought and written and methods are presented in a very detailed way, which includes the R codes that authors will use in their analyses. Authors have answered in a very detailed way each comment that reviewers have pointed out and modified the pre-registration accordingly, which we consider highly improved the quality of this work. That is why we strongly recommend this pre-registration and look forward to see the results.

References

[1] Gaston K. J. (2003) The structure and dynamics of geographic ranges. Oxford series in Ecology and Evolution. Oxford University Press, New York.
[2] Castro-Insua, A., Gómez‐Rodríguez, C., Svenning, J.C., and Baselga, A. (2018) A new macroecological pattern: The latitudinal gradient in species range shape. Global ecology and biogeography, 27(3), 357-367. doi: 10.1111/geb.12702
[3] Newbold, T., Hudson, L. N., Hill, S. L. L., Contu, S., Lysenko, I., Senior, R. A., et al. (2015). Global effects of land use on local terrestrial biodiversity. Nature, 520(7545), 45–50. doi: 10.1038/nature14324
[4] Logan CJ, McCune K, Bergeron L, Folsom M, Lukas D. (2019). Is behavioral flexibility related to foraging and social behavior in a rapidly expanding species? In principle recommendation by Peer Community In Ecology. http://corinalogan.com/Preregistrations/g_flexforaging.html
[5] Mikhalevich, I., Powell, R., and Logan, C. (2017). Is Behavioural Flexibility Evidence of Cognitive Complexity? How Evolution Can Inform Comparative Cognition. Interface Focus 7: 20160121. doi: 10.1098/rsfs.2016.0121.
[6] Fronhofer, E. (2019) From cognition to range dynamics: advancing our understanding of macroecological patterns. Peer Community in Ecology, 100014. doi: 10.24072/pci.ecology.100014
[7] Vogel, E. (2019) Adapting to a changing environment: advancing our understanding of the mechanisms that lead to behavioral flexibility. Peer Community in Ecology, 100016. doi: 10.24072/pci.ecology.100016
[8] Van Cleve, J. (2019) Probing behaviors correlated with behavioral flexibility. Peer Community in Ecology, 100020. doi: 10.24072/pci.ecology.100020
[9] Coulon, A. (2019) Can context changes improve behavioral flexibility? Towards a better understanding of species adaptability to environmental changes. Peer Community in Ecology, 100019. doi: 10.24072/pci.ecology.100019