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

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

​​Research about the effects of climate change on ecological communities has been abundant in the last decades. In particular, studies about the effects of climate change on mountain ecosystems have been key for understanding and communicating the consequences of this global phenomenon. Alpine regions show higher increases in warming in comparison to low-altitude ecosystems and this trend is likely to continue. This warming has caused reduced snowfall and/or changes in the duration of snow cover. For example, Notarnicola (2020) reported that 78% of the world’s mountain areas have experienced a snow cover decline since 2000. In the same vein, snow cover has decreased by 10% compared with snow coverage in the late 1960s (Walther et al., 2002) and snow cover duration has decreased at a rate of 5 days/decade (Choi et al., 2010). These changes have impacted the dynamics of high-altitude plant and animal populations. Some impacts are changes in the hibernation of animals, the length of the growing season for plants and the soil microbial composition (Chávez et al. 2021).

Lenzi et al. (2023), give us an excellent study using long-term data on alpine amphibian populations. Authors show how climate change has impacted the reproductive phenology of Bufo bufo, especially the breeding season starts 30 days earlier than ~40 years ago. This earlier breeding is associated with the increasing temperatures and reduced snow cover in these alpine ecosystems. However, these changes did not occur in a linear trend but a marked acceleration was observed until mid-1990s with a later stabilization. Authors associated these nonlinear changes with complex interactions between the global trend of seasonal temperatures and site-specific conditions. 

Beyond the earlier breeding season, changes in phenology can have important impacts on the long-term viability of alpine populations. Complex interactions could involve positive and negative effects like harder environmental conditions for propagules, faster development of juveniles, or changes in predation pressure. This study opens new research opportunities and questions like the urgent assessment of the global impact of climate change on animal fitness. This study provides key information for the conservation of these populations.

References

Chávez RO, Briceño VF, Lastra JA, Harris-Pascal D, Estay SA (2021) Snow Cover and Snow Persistence Changes in the Mocho-Choshuenco Volcano (Southern Chile) Derived From 35 Years of Landsat Satellite Images. Frontiers in Ecology and Evolution, 9. https://doi.org/10.3389/fevo.2021.643850

Choi G, Robinson DA, Kang S (2010) Changing Northern Hemisphere Snow Seasons. Journal of Climate, 23, 5305–5310. https://doi.org/10.1175/2010JCLI3644.1

Lenzi O, Grossenbacher K, Zumbach S, Lüscher B, Althaus S, Schmocker D, Recher H, Thoma M, Ozgul A, Schmidt BR (2022) Four decades of phenology in an alpine amphibian: trends, stasis, and climatic drivers.bioRxiv, 2022.08.16.503739, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.08.16.503739

Notarnicola C (2020) Hotspots of snow cover changes in global mountain regions over 2000–2018. Remote Sensing of Environment, 243, 111781. https://doi.org/10.1016/j.rse.2020.111781

Scale is a big topic in ecology [1]. Environmental variation happens at particular scales. The typical scale at which organisms disperse is species-specific, but, as a first approximation, an ensemble of similar species, for instance, trees, could be considered to share a typical dispersal scale. Finally, characteristic spatial scales of species interactions are, in general, different from the typical scales of dispersal and environmental variation. Therefore, conceptually, we can distinguish these three characteristic spatial scales associated with three different processes: species selection for a given environment (E), dispersal (D), and species interactions (I), respectively.  

From the famous species-area relation to the spatial distribution of biomass and species richness, the different macro-ecological patterns we usually study emerge from an interplay between dispersal and local interactions in a physical environment that constrains species establishment and persistence in every location. To make things even more complicated, local environments are often modified by the species that thrive in them, which establishes feedback loops.  It is usually assumed that local interactions are short-range in comparison with species dispersal, and dispersal scales are typically smaller than the scales at which the environment varies (I < D < E, see [2]), but this should not always be the case. 

The authors of this paper [2] relax this typical assumption and develop a theoretical framework to study how diversity and ecosystem functioning are affected by different relations between the typical scales governing interactions, dispersal, and environmental variation. This is a huge challenge. First, diversity and ecosystem functioning across space and time have been empirically characterized through a wide variety of macro-ecological patterns. Second, accommodating local interactions, dispersal and environmental variation and species environmental preferences to model spatiotemporal dynamics of full ecological communities can be done also in a lot of different ways. One can ask if the particular approach suggested by the authors is the best choice in the sense of producing robust results, this is, results that would be predicted by alternative modeling approaches and mathematical analyses [3]. The recommendation here is to read through and judge by yourself.  

The main unusual assumption underlying the model suggested by the authors is non-local species interactions. They introduce interaction kernels to weigh the strength of the ecological interaction with distance, which gives rise to a system of coupled integro-differential equations. This kernel is the key component that allows for control and varies the scale of ecological interactions. Although this is not new in ecology [4], and certainly has a long tradition in physics ---think about the electric or the gravity field, this approach has been widely overlooked in the development of the set of theoretical frameworks we have been using over and over again in community ecology, such as the Lotka-Volterra equations or, more recently, the metacommunity concept [5].

In Physics, classic fields have been revised to account for the fact that information cannot travel faster than light. In an analogous way, a focal individual cannot feel the presence of distant neighbors instantaneously. Therefore, non-local interactions do not exist in ecological communities. As the authors of this paper point out, they emerge in an effective way as a result of non-random movements, for instance, when individuals go regularly back and forth between environments (see [6], for an application to infectious diseases), or even migrate between regions. And, on top of this type of movement, species also tend to disperse and colonize close (or far) environments. Individual mobility and dispersal are then two types of movements, characterized by different spatial-temporal scales in general. Species dispersal, on the one hand, and individual directed movements underlying species interactions, on the other, are themselves diverse across species, but it is clear that they exist and belong to two distinct categories. 

In spite of the long and rich exchange between the authors' team and the reviewers, it was not finally clear (at least, to me and to one of the reviewers) whether the model for the spatio-temporal dynamics of the ecological community (see Eq (1) in [2]) is only presented as a coupled system of integro-differential equations on a continuous landscape for pedagogical reasons, but then modeled on a discrete regular grid for computational convenience. In the latter case, the system represents a regular network of local communities,  becomes a system of coupled ODEs, and can be numerically integrated through the use of standard algorithms. By contrast,  in the former case, the system is meant to truly represent a community that develops on continuous time and space, as in reaction-diffusion systems. In that case, one should keep in mind that numerical instabilities can arise as an artifact when integrating both local and non-local spatio-temporal systems. Spatial patterns could be then transient or simply result from these instabilities. Therefore, when analyzing spatiotemporal integro-differential equations, special attention should be paid to the use of the right numerical algorithms. The authors share all their code at https://zenodo.org/record/5543191, and all this can be checked out. In any case, the whole discussion between the authors and the reviewers has inherent value in itself, because it touches on several limitations and/or strengths of the author's approach,  and I highly recommend checking it out and reading it through.

Beyond these methodological issues, extensive model explorations for the different parameter combinations are presented. Several results are reported, but, in practice, what is then the main conclusion we could highlight here among all of them?  The authors suggest that "it will be difficult to manage landscapes to preserve biodiversity and ecosystem functioning simultaneously, despite their causative relationship", because, first, "increasing dispersal and interaction scales had opposing
effects" on these two patterns, and, second, unexpectedly, "ecosystems attained the highest biomass in scenarios which also led to the lowest levels of biodiversity". If these results come to be fully robust, this is, they pass all checks by other research teams trying to reproduce them using alternative approaches, we will have to accept that we should preserve biodiversity on its own rights and not because it enhances ecosystem functioning or provides particular beneficial services to humans. 

References

[1] Levin, S. A. 1992. The problem of pattern and scale in ecology. Ecology 73:1943–1967. https://doi.org/10.2307/1941447

[2] Yuval R. Zelnik, Matthieu Barbier, David W. Shanafelt, Michel Loreau, Rachel M. Germain. 2023. Linking intrinsic scales of ecological processes to characteristic scales of biodiversity and functioning patterns. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology.  https://doi.org/10.1101/2021.10.11.463913

[3] Baron, J. W. and Galla, T. 2020. Dispersal-induced instability in complex ecosystems. Nature Communications  11, 6032. https://doi.org/10.1038/s41467-020-19824-4

[4] Cushing, J. M. 1977. Integrodifferential equations and delay models in population dynamics 
 Springer-Verlag, Berlin. https://doi.org/10.1007/978-3-642-93073-7

[5] M. A. Leibold, M. Holyoak, N. Mouquet, P. Amarasekare, J. M. Chase, M. F. Hoopes, R. D. Holt, J. B. Shurin, R. Law, D. Tilman, M. Loreau, A. Gonzalez. 2004. The metacommunity concept: a framework for multi-scale community ecology. Ecology Letters, 7(7): 601-613. https://doi.org/10.1111/j.1461-0248.2004.00608.x

[6] M. Pardo-Araujo, D. García-García, D. Alonso, and F. Bartumeus. 2023. Epidemic thresholds and human mobility. Scientific reports 13 (1), 11409. https://doi.org/10.1038/s41598-023-38395-0

The preregistration "Investigating sex differences in genetic relatedness in great-tailed grackles in Tempe, Arizona to infer potential sex biases in dispersal" [1] presents the analysis plan that will be used to genetically and spatially investigate sex-biased dispersal in great-tailed grackles (Quiscalus mexicanus).
Several hypotheses implying mating systems, intrasexual competition or sex-related handicaps have been proposed to explain the diversity of dispersal patterns between or within species according to their ecological requirements, environmental factors such as seasonality [2], or individual characteristics such as age [3] or sex [4].
In birds, females are classically the dispersing sex, while males remain close to the place they were hatched [5], with potential benefits that males derive from knowing the local environment to establish territories [6].
In great-tailed grackles the males hold territories and the females choose which territory to place their nest in [7]. In this context, the main hypothesis is that females are the dispersing sex in this species. The authors of this preregistration plan to investigate this hypothesis and its 3 alternatives ((i) the males are the dispersing sex, (ii) both sexes disperse or (iii) neither of the two sexes disperse), investigating the spatial distribution of genetic relatives.
The authors plan to measure the genetic relatedness (using SNP markers) and geographic distances among all female dyads and among all male dyads in the fine geographic scale (Tempe campus, Arizona). If females disperse away from relatives, the females will be less likely to be found geographically close to genetic relatives.
This pre-registration shows that the authors are well aware of the possible limitations of their study, particularly in relation to their population of 57 individuals, on a small scale. But they will use methods that should be able to detect a signal. They were very good at incorporating the reviewers' comments and suggestions, which enabled them to produce a satisfactory and interesting version of the manuscript presenting their hypotheses, limitations and the methods they plan to use. Another point I would like to stress is that this pre-registration practice is a very good one that makes it possible to anticipate the challenges and the type of analyses to be carried out, in particular by setting out the working hypotheses and confronting them (as well as the methods envisaged) with peers from this stage. I therefore recommend this manuscript and thank all the contributors (authors and reviewers) for their work. I look forward to seeing the outcomes of this study.

References

[1] Sevchik A., Logan C. J., Folsom M., Bergeron L., Blackwell A., Rowney C., and Lukas D. (2019). Investigating sex differences in genetic relatedness in great-tailed grackles in Tempe, Arizona to infer potential sex biases in dispersal. In principle recommendation by Peer Community In Ecology. corinalogan.com/Preregistrations/gdispersal.html
[2] Fies, M. L., Puckett, K. M., and Larson-Brogdon, B. (2002). Breeding season movements and dispersal of Northern Bobwhites in fragmented habitats of Virginia. Vol. 5 , Article 35. Available at: trace.tennessee.edu/nqsp/vol5/iss1/35
[3] Marvá, M., and San Segundo, F. (2018). Age-structure density-dependent fertility and individuals dispersal in a population model. Mathematical biosciences, 300, 157-167. doi: 10.1016/j.mbs.2018.03.029
[4] Trochet, A., Courtois, E. A., Stevens, V. M., Baguette, M., Chaine, A., Schmeller, D. S., Clobert, J., and Wiens, J. J. (2016). Evolution of sex-biased dispersal. The Quarterly Review of Biology, 91(3), 297-320. doi: 10.1086/688097
[5] Greenwood, P. J., and Harvey, P. H. (1982). The natal and breeding dispersal of birds. Annual review of ecology and systematics, 13(1), 1-21. doi: 10.1146/annurev.es.13.110182.000245
[6] Greenwood, P. J. (1980). Mating systems, philopatry and dispersal in birds and mammals. Animal behaviour, 28(4), 1140-1162. doi: 10.1016/S0003-3472(80)80103-5
[7] Johnson, K., DuVal, E., Kielt, M., and Hughes, C. (2000). Male mating strategies and the mating system of great-tailed grackles. Behavioral Ecology, 11(2), 132-141. doi: 10.1093/beheco/11.2.132