Biotic interactions are often shaped by abiotic factors (Liu and Gaines 2022). Although this notion is not new in ecology and evolutionary biology, we are still far from a thorough understanding of how biotic interactions change along abiotic gradients in space and time. This is particularly challenging because abiotic factors can affect organisms and their interactions in multiple – direct or indirect – ways. For example, because abiotic conditions strongly determine how energy enters biological systems via producers, their effects can propagate through entire food webs, from the bottom to the top (O’Connor 2009, Gilbert et al 2019). Understanding how biological diversity - both within and across species - is shaped by the indirect effects of environmental conditions is a timely question as climate change and anthropogenic activities have been altering temperature and water availability across different ecosystems.

Motivated by the current water crisis and severe droughts predicted for the near future worldwide (du Plessis 2019), Migeon et al. (2023) investigated how water limitation on producers scales up to affect life-history patterns of a widespread crop pest, the spider mite Tetranychus urticae. The authors sampled spider mite populations (n = 12) along a striking gradient of climatic conditions (>16 degrees of latitude) in Europe. After letting mites acclimate to lab conditions for several generations, the authors performed a common garden experiment to quantify how the life-history traits of mite populations from different locations respond to drought stress in their host plants.

Curiously, the authors found that, when reared on drought-stressed plants, mites tended to develop faster, had higher fecundity and lower dispersion rates. This response was in line with some results obtained previously with Tetranychus species (e.g. Ximénez-Embun et al 2016). Importantly, despite some experimental caveats in the experimental design, which makes it difficult to completely disentangle the specific effects of location vs. environmental noise, results suggest the climate that populations originally experienced was also an important determinant of the plastic response in these herbivores. In fact, populations from wetter and colder regions showed a steeper change in drought response, while populations from arid climates showed a shallower response. This interesting result suggests the importance of intraspecific (between-populations) variation in the response to drought, which might be explained by the climatic heterogeneity in space throughout the evolutionary history of different populations. These results become even more important in our rapidly changing world, highlighting the importance of considering genetic variation (and conditions that generate it) when predicting plastic and evolutionary responses to stressful conditions.
 
REFERENCES

du Plessis, A. (2019). Current and Future Water Scarcity and Stress. In: Water as an Inescapable Risk. Springer Water. Springer, Cham. https://doi.org/10.1007/978-3-030-03186-2
 
Gibert, J.P. Temperature directly and indirectly influences food web structure. Sci Rep 9, 5312 (2019). https://doi.org/10.1038/s41598-019-41783-0
 
Liu, O. R., & Gaines, S. D. (2022). Environmental context dependency in species interactions. Proceedings of the National Academy of Sciences, 119(36), e2118539119. https://doi.org/10.1073/pnas.2118539119
 
Migeon A., Auger P., Fossati-Gaschignard O., Hufbauer R.A, Miranda M., Zriki G., Navajas M. (2023) The response to drought-stressed host plants varies among herbivorous mite populations from a climate gradient. bioRxiv, 2021.10.21.465244, ver. 4 peer-reviewed and recommended by Peer Community in Zoology. https://doi.org/10.1101/2021.10.21.465244
 
O'Connor, M.I. (2009), Warming strengthens an herbivore-plant interaction. Ecology, 90: 388-398. https://doi.org/10.1890/08-0034.1
 
Ximénez-Embún, M. G., Ortego, F., & Castañera, P. (2016). Drought-stressed tomato plants trigger bottom-up effects on the invasive Tetranychus evansi. PloS one, 11(1), e0145275. https://doi.org/10.1371/journal.pone.0145275

Molecular markers have drastically changed and improved our understanding of biological processes. In combination with PCR, markers revolutionized the study of all organisms, even tiny insects, and eukaryotic pathogens amongst others. Microsatellite markers were the most prominent and successful ones. Their success started in the early 1990s. They were used for population genetic studies, mapping of genes and genomes, and paternity testing and inference of relatedness. Their popularity is based on some of their characteristics as codominance, the high polymorphism information content, and their ease of isolation (Schlötterer 2004). Still, microsatellites are the marker of choice for a range of non-model organisms as next-generation sequencing technologies produce a huge amount of single nucleotide polymorphisms (SNPs), but often at expense of sample size and higher costs.
 
The high level of polymorphism of microsatellite markers, which consist of one to six base-pair nucleotide motifs replicated up to 10 or 20 times, results from slippage events during DNA replication. Short hairpin loops might shorten the template strand or extend the new strand. However, such slippage events might occur during PCR amplification resulting in additional bands or peaks. Such stutter alleles often appear to differ by one repeat unit and might be hard to interpret but definitively reduce automated scoring of microsatellite results.
 
A standalone software package available to handle stuttering is Microchecker (van Oosterhout et al., 2004, which nowadays faces incompatibilities with updated versions of different operating systems. Thus, de Meeûs and Noûs (2022), in their manuscript, tackled the stuttering issue by developing an OS-independent analysis pipeline based on standard spreadsheet software such as Microsoft Office (Excel) or Apache Open Office (Calc). The authors use simulated populations differing in the mating system (pangamic, selfing (30%), clonal) and a different number of subpopulations and individuals per subpopulation to test for differences among the null model (no stuttering), a test population with 2 out of 20 loci (10%) with stuttering, and the latter with stuttering cured. Further to this, the authors also re-analyse data from previous studies utilising organisms differing in the mating system to understand whether control of stuttering changes major parameter estimates and conclusions of those studies.
 
Stuttering of microsatellite loci might result in increased heterozygote deficits. The authors utilise the FIS (inbreeding coefficient) as a tool to compare the different treatments of the simulated populations. Their method detected stuttering in pangamic and selfing populations, while the detection of stuttering in clonal organisms is more difficult. The cure for stuttering resulted in FIS values similar to those populations lacking stuttering. The re-analysis of four previously published studies indicated that the new method presented here is more accurate than Microchecker (van Oosterhout et al., 2004) in a direct comparison. For the Lyme disease-transmitting tick Ixodes scapularis (De Meeûs et al., 2021), three loci showed stuttering and curing these resulted in data that are in good agreement with pangamic reproduction. In the tsetse fly Glossina palpalis palpalis (Berté et al., 2019), two out of seven loci were detected as stuttering. Curing them resulted in decreased FIS for one locus, while the other showed an increased FIS, an indication of other problems such as the occurrence of null alleles. Overall, in dioecious pangamic populations, the method works well, and the cure of stuttering improves population genetic parameter estimates, although FST and FIS might be slightly overestimated. In monoecious selfers, the detection and cure work well, if other factors such as null alleles do not interfere. In clonal organisms, only loci with extremely high FIS might need a cure to improve parameter estimates.
 
This spreadsheet-based method helps to automate microsatellite analysis at very low costs and thus improves the accuracy of parameter estimates. This might certainly be very useful for a range of non-model organisms, parasites, and their vectors, for which microsatellites are still the marker of choice. 
 
References

Berté D, De Meeus T, Kaba D, Séré M, Djohan V, Courtin F, N'Djetchi KM, Koffi M, Jamonneau V, Ta BTD, Solano P, N’Goran EK, Ravel S (2019) Population genetics of Glossina palpalis palpalis in sleeping sickness foci of Côte d'Ivoire before and after vector control. Infection Genetics and Evolution 75, 103963. https://doi.org/0.1016/j.meegid.2019.103963

de Meeûs T, Chan CT, Ludwig JM, Tsao JI, Patel J, Bhagatwala J, Beati L (2021) Deceptive combined effects of short allele dominance and stuttering: an example with Ixodes scapularis, the main vector of Lyme disease in the U.S.A. Peer Community Journal 1, e40. https://doi.org/10.24072/pcjournal.34

de Meeûs T, Noûs C (2022) A simple procedure to detect, test for the presence of stuttering, and cure stuttered data with spreadsheet programs. Zenodo, v5, peer-reviewed and recommended by PCI Zoology. https://doi.org/10.5281/zenodo.7029324

Schlötterer C (2004) The evolution of molecular markers - just a matter of fashion? Nature Reviews Genetics 5, 63-69. https://doi.org/10.1038/nrg1249

van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes 4, 535-538. https://doi.org/10.1111/j.1471-8286.2004.00684.x

Ticks are notorious vectors of diseases in humans and other vertebrates. Much effort has been expended to understand tick diversity and ecology with the aim of managing their populations to alleviate the misery they bring. Further, the fundamental question of whether ticks are usually host generalists or host specialists has been debated at length and is important both for understanding the mechanisms of their diversification as well as for focusing control of ticks [1].

One elegant resolution of this question is to consider most tick species to be global generalists but local specialists [1]. This is well illustrated in a series of studies of the seabird tick, Ixodes uriae, which is comprised of host-specific races that show genetic [2], morphological [3] and host performance [4] differences associated with the seabirds they feed on. Such a pattern has clear ramifications for sympatric speciation; however, the factors that potentially act to drive these differences have remained elusive.

Dupraz et al. [5] have now made intriguing and important steps toward bridging the gap between demonstrating local patterns of tick host association and understanding the physiological mechanisms that may facilitate such divergences. They collected I. uriae ticks from the nests of two seabirds – Atlantic puffins and common guillemots – on the north side of Iceland. Four populations of ticks were sampled, with one island providing both puffin ticks and guillemot ticks, to give two tick populations from each of the two seabird host species. They then washed the ticks in solvent and analyzed the dissolved cuticular hydrocarbons (CHCs) using GC mass spectrometry, revealing 22 different hydrocarbon compounds common to most of these samples. CHCs are known to be important across arthropods for a variety of functions ranging from reducing water loss to facilitating communication and recognition between individuals with species.

Dupraz et al. [5] found three hydrocarbons that distinguished puffin ticks most consistently from guillemot ticks. A cross-validation test for host type also assigned 75% of the tick pools to the seabird host of origin. However, with these limited sample sizes, statistical analysis revealed no significant difference in CHC profiles between the host types, although a tendency was evident. Nonetheless, this study revealed a number of potentially diagnostic CHCs for tick host type, as well as some that may be more diagnostic of locations. This provides a fascinating and actionable foundation for further work using additional sites and host types, as well as an entry point into discerning the mechanisms at play in producing the diversity, complexity and adaptability that make ticks such medical menaces.

References

[1]  McCoy, K.D., Léger, E., Dietrich, M., 2013. Host specialization in ticks and transmission of tick-borne diseases: a review. Front. Cell. Infect. Microbiol. 3. https://doi.org/10.3389/fcimb.2013.00057

[2]  McCoy, K.D., Chapuis, E., Tirard, C., Boulinier, T., Michalakis, Y., Bohec, C.L., Maho, Y.L., Gauthier-Clerc, M., 2005. Recurrent evolution of host-specialized races in a globally distributed parasite. Proc. R. Soc. B Biol. Sci. 272, 2389–2395. https://doi.org/10.1098/rspb.2005.3230

[3]  Dietrich, M., Beati, L., Elguero, E., Boulinier, T., McCoy, K.D., 2013. Body size and shape evolution in host races of the tick Ixodes uriae. Biol. J. Linn. Soc. 108, 323–334. https://doi.org/10.1111/j.1095-8312.2012.02021.x

[4]  Dietrich, M., Lobato, E., Boulinier, T., McCoy, K.D., 2014. An experimental test of host specialization in a ubiquitous polar ectoparasite: a role for adaptation? J. Anim. Ecol. 83, 576–587. https://doi.org/10.1111/1365-2656.12170

[5] Dupraz, M., Leroy, C., Thórarinsson, T. L., d’Ettorre, P. and McCoy, K. D. (2022) Within and among population differences in cuticular hydrocarbons in the seabird tick Ixodes uriae. bioRxiv, 2022.01.21.477272, ver. 5 peer-reviewed and recommended by Peer Community in Zoology. https://doi.org/10.1101/2022.01.21.477272

The popularity of iNaturalist and other online biodiversity databases to which the general public and specialists alike contribute observations has skyrocketed in recent years (Dance 2022). The AI-based algorithms (computer vision) which provide the first identification of a given organism on an uploaded photograph have become very sophisticated, suggesting initial identifications often down to species level with a surprisingly high degree of accuracy. The initial identifications are then confirmed or improved by feedback from the community, which works particularly well for organismal groups to which many active community members contribute, such as the birds. Hence, providing initial observations and identifying observations of others, as well as browsing the recorded biodiversity for given locales or the range of occurrences of individual taxa has become a meaningful and satisfying experience for the interested naturalist. Furthermore, several research studies have now been published relying on observations uploaded to iNaturalist (Szentivanyi and Vincze 2022). However, using the enormous amount of natural history data available on iNaturalist in a systematic way has remained challenging, since this requires not only retrieving numerous observations from the database (in the hundreds or even thousands), but also some level of transparent quality control.

Billotte (2022) provides a protocol and R scripts for the quality assessment of downloaded observations from iNaturalist, allowing an efficient and reproducible stepwise approach to prepare a high-quality data set for further analysis. First, observations with their associated metadata are downloaded from iNaturalist, along with the corresponding entries from the Global Biodiversity Information Facility (GBIF). In addition, a taxonomic reference list is obtained (these are available online for many taxa), which is used to assess the taxonomic consistency in the dataset. Second, the geo-tagging is assessed by comparing the iNaturalist and GBIF metadata. Lastly, the image quality is assessed using pyBRISQUE. The approach is illustrated using spiders (Araneae) as an example. Spiders are a very diverse taxon and an excellent taxonomic reference list is available (World Spider Catalogue 2022). However, spiders are not well known to most non-specialists, and it is not easy to take good pictures of spiders without using professional equipment. Therefore, the ability of iNaturalist’s computer vision to provide identifications is limited to this date and the community of specialists active on iNaturalist is comparatively small. Hence, spiders are a good taxon to demonstrate how the pipeline results in a quality-controlled dataset based on crowed-sourced data. Importantly, the software employed is free to use, although inevitably, the initial learning curve to use R scripts can be steep, depending on prior expertise with R/RStudio. Furthermore, the approach is employable with databases other than iNaturalist.

In summary, Billotte's (2022) pipeline allows researchers to use the wealth of observations on iNaturalist and other databases to produce large metadata and image datasets of high-quality in a reproducible way. This should pave the way for more studies, which could include, for example, the assessment of range expansions of invasive species or the evaluation of the presence of endangered species, potentially supporting conservation efforts.

References

Billotte J (2022) A pipeline for assessing the quality of images and metadata from crowd-sourced databases. BiorXiv, 2022.04.29.490112, ver 5 peer reviewed and recommended by Peer Community In Zoology. https://doi.org/10.1101/2022.04.29.490112

Dance A (2022) Community science draws on the power of the crowd. Nature, 609, 641–643. https://doi.org/10.1038/d41586-022-02921-3

Szentivanyi T, Vincze O (2022) Tracking wildlife diseases using community science: an example through toad myiasis. European Journal of Wildlife Research, 68, 74. https://doi.org/10.1007/s10344-022-01623-5

World Spider Catalog (2022). World Spider Catalog. Version 23.5. Natural History Museum Bern, online at http://wsc.nmbe.ch. https://doi.org/10.24436/2

The sorting of organisms along a fast-slow continuum through correlations between life history traits is a long-standing framework (Stearns 1983) and corresponds to the pace-of-life axis. This axis represents the variation in a continuum of life-history strategies, from fast-reproducing short-lived species to slow-reproducing long-lived species. The pace-of-life axis has been the focus of much research largely in mammals, birds, reptiles and plants but less so in invertebrates (Salguero-Gómez et al. 2016; Araya-Ajoy et al. 2018; Healy et al. 2019; Bakewell et al. 2020). Outcomes from this research have highlighted variation across taxa on this axis and mixed support for, and against, patterns expected of the pace-of-life continuum. Given this, a greater understanding of the variation of the pace-of-life across-, and within, taxa are needed. Indeed, Guicharnard et al. (2023) highlight several points regarding our broader understanding of pace-of-life. In general, invertebrates are poorly represented, the variation of pace-of-life across taxonomic scales is less well understood and the relationship between pace-of-life and dispersal, a key life history, requires more attention. Here, Guicharnard et al. (2023) provide a first attempt at addressing the relationship between dispersal and pace-of-life at different scales.

The authors, under controlled conditions, investigated how life-history traits and effective dispersal covary for 28 lines from five species of endoparasitoid wasps from the genus Trichogramma. At the species level negative correlations were found between development time and fecundity, matching pace-of-life axis predictions. Although this correlation was not found to be significant among lines, within species, a similar pattern of a negative correlation was observed. This outcome matches previous findings that consistent pace-of-life axes become more difficult to find at lower taxonomic levels. Unlike the other life-history traits measured, effective dispersal showed no evidence of differences between species or between lines. The authors also found no correlation between effective dispersal and other-life history traits which suggests no dispersal/life-history syndromes in the species investigated. One aspect that was not assessed was the impact of density dependence on pace-of-life and effective dispersal, largely as this was a first step in assessing relationship of dispersal with pace-of-life at different scales. However, the authors do acknowledge the importance of future studies incorporating density dependence and that such studies could potentially lead to more generalizable understanding of pace-of-life and dispersal within Trichogramma.

A pleasant addition was the link to potential implications for biocontrol. This addition showed an awareness by the authors of how insights into pace-of-life can have an applied component. The results of the study highlighted that selecting for specific lines of a species, to maximise a trait of interest at the cost of another, may not be as effective as selecting different species when implementing biocontrol. This is especially important as often single, established species used in biocontrol are favoured without consideration of the potential of other species which can lead to more efficient biocontrol.    

REFERENCES

Araya-Ajoy, Y.G., Bolstad, G.H., Brommer, J., Careau, V., Dingemanse, N.J. & Wright, J. (2018). Demographic measures of an individual's "pace of life": fecundity rate, lifespan, generation time, or a composite variable? Behavioral Ecology and Sociobiology, 72, 75.
https://doi.org/10.1007/s00265-018-2477-7
 
Bakewell, A.T., Davis, K.E., Freckleton, R.P., Isaac, N.J.B. & Mayhew, P.J. (2020). Comparing Life Histories across Taxonomic Groups in Multiple Dimensions: How Mammal-Like Are Insects? The American Naturalist, 195, 70-81.
https://doi.org/10.1086/706195
 
Guicharnaud, C., Groussier, G., Beranger, E., Lamy, L., Vercken, E. & Dahirel, M. (2023). Life-history traits, pace of life and dispersal among and within five species of Trichogramma wasps: a comparative analysis. bioRxiv, 2023.01.24.525360, ver. 3 peer-reviewed and recommended by Peer Community in Zoology.
https://doi.org/10.1101/2023.01.24.525360
 
Healy, K., Ezard, T.H.G., Jones, O.R., Salguero-Gómez, R. & Buckley, Y.M. (2019). Animal life history is shaped by the pace of life and the distribution of age-specific mortality and reproduction. Nature Ecology & Evolution, 3, 1217-1224.
https://doi.org/10.1038/s41559-019-0938-7
 
Salguero-Gómez, R., Jones, O.R., Jongejans, E., Blomberg, S.P., Hodgson, D.J., Mbeau-Ache, C., et al. (2016). Fast-slow continuum and reproductive strategies structure plant life-history variation worldwide. Proceedings of the National Academy of Sciences, 113, 230-235.
https://doi.org/10.1073/pnas.1506215112
 
Stearns, S.C. (1983). The Influence of Size and Phylogeny on Patterns of Covariation among Life-History Traits in the Mammals. Oikos, 41, 173-187.
https://doi.org/10.2307/3544261