Conservation biology is strongly rooted in the theory of island biogeography (TIB). In island systems where the ocean constitutes the inhospitable matrix, TIB predicts that species richness increases with island size as extinction rates decrease with island area (the species-area relationship, SAR), and species richness increases with connectivity as colonisation rates decrease with island isolation (the species-isolation relationship, SIR)[1]. In conservation biology, patches of habitat (habitat islands) are often regarded as analogous to islands within an unsuitable matrix [2], and SAR and SIR concepts have received much attention as habitat loss and habitat fragmentation are increasingly threatening biodiversity [3,4].
The existence of SAR in patch-matrix systems has been confirmed in several studies, while the relative importance of SIR remains debated [2,5] and empirical evidence is mixed. For example, Thiele et al. [6] showed that connectivity effects are trait specific and more important to explain species richness of short-distant dispersers and of specialist species for which the matrix is less permeable. Some authors have also cautioned that the relative support for or against the existence of SIR may depend on methodological decisions related to connectivity metrics, patch classification, scaling decisions and sample size [7].
In this preprint, Laroche and colleagues [8] argue that methodological limits should be fully understood before questioning the validity of SIR in patch-matrix systems. In consequence, they used a virtual ecologist approach [9] to qualify different methodological aspects and derive good practice guidelines related to patch delineation, patch connectivity indices, and scaling of indices with species dispersal distance.
Laroche et al. [8] simulated spatially-explicit neutral meta-communities with up to 100 species in artificial fractal (patch-matrix) landscapes. Each habitat cell could hold up to 100 individuals. In each time step, some individuals died and were replaced by an individual from the regional species pool depending on relative local and regional abundance as well as dispersal distance to the nearest source habitat cell. Different scenarios were run with varying degrees of spatial autocorrelation in the fractal landscape (determining the clumpiness of habitat cells), the proportion of suitable habitat, and the species dispersal distances (with all species showing the same dispersal distance). Laroche and colleagues then sampled species richness in the simulated meta-communities, computed different local connectivity indices for the simulated landscapes (Buffer index with different radii, dIICflux index and dF index, and, finally, related species richness to connectivity.
The complex simulations allowed Laroche and colleagues [8] to test how methodological choices and landscape features may affect SIR. Overall, they found that patch delineation is crucial and should be fine enough to exclude potential within-patch dispersal limitations, and the scaling of the connectivity indices (in simplified words, the window of analyses) should be tailored to the dispersal distance of the species group. Of course, tuning the scaling parameters will be more complicated when dispersal distances vary across species but overall these results corroborate empirical findings that SIR effects are trait specific [6]. Additionally, the results by Laroche and colleagues [8] indicated that indices based on Euclidian rather than topological distance are more performant and that evidence of SIR is more likely if Buffer indices are highly variable between sampled patches.
Although the study is very technical due to the complex simulation approach and the different methods tested, I hope it will not only help guiding methodological choices but also inspire ecologists to further test or even revisit SIR (and SAR) hypotheses for different systems. Also, Laroche and colleagues propose many interesting avenues that could still be explored in this context, for example determining the optimal grid resolution for the patch delineation in empirical studies.

References

[1] MacArthur, R.H. and Wilson, E.O. (1967) The theory of island biogeography. Princeton University Press, Princeton.
[2] Fahrig, L. (2013) Rethinking patch size and isolation effects: the habitat amount hypothesis. Journal of Biogeography, 40(9), 1649-1663. doi: 10.1111/jbi.12130
[3] Hanski, I., Zurita, G.A., Bellocq, M.I. and Rybicki J (2013) Species–fragmented area relationship. Proceedings of the National Academy of Sciences U.S.A., 110(31), 12715-12720. doi: 10.1073/pnas.1311491110
[4] Giladi, I., May, F., Ristow, M., Jeltsch, F. and Ziv, Y. (2014) Scale‐dependent species–area and species–isolation relationships: a review and a test study from a fragmented semi‐arid agro‐ecosystem. Journal of Biogeography, 41(6), 1055-1069. doi: 10.1111/jbi.12299
[5] Hodgson, J.A., Moilanen, A., Wintle, B.A. and Thomas, C.D. (2011) Habitat area, quality and connectivity: striking the balance for efficient conservation. Journal of Applied Ecology, 48(1), 148-152. doi: 10.1111/j.1365-2664.2010.01919.x
[6] Thiele, J., Kellner, S., Buchholz, S., and Schirmel, J. (2018) Connectivity or area: what drives plant species richness in habitat corridors? Landscape Ecology, 33, 173-181. doi: 10.1007/s10980-017-0606-8
[7] Vieira, M.V., Almeida-Gomes, M., Delciellos, A.C., Cerqueira, R. and Crouzeilles, R. (2018) Fair tests of the habitat amount hypothesis require appropriate metrics of patch isolation: An example with small mammals in the Brazilian Atlantic Forest. Biological Conservation, 226, 264-270. doi: 10.1016/j.biocon.2018.08.008
[8] Laroche, F., Balbi, M., Grébert, T., Jabot, F. and Archaux, F. (2020) Three points of consideration before testing the effect of patch connectivity on local species richness: patch delineation, scaling and variability of metrics. bioRxiv, 640995, ver. 5 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/640995
[9] Zurell, D., Berger, U., Cabral, J.S., Jeltsch, F., Meynard, C.N., Münkemüller, T., Nehrbass, N., Pagel, J., Reineking, B., Schröder, B. and Grimm, V. (2010) The virtual ecologist approach: simulating data and observers. Oikos, 119(4), 622-635. doi: 10.1111/j.1600-0706.2009.18284.x

Citizen science is becoming an important piece for the acquisition of scientific knowledge in the fields of natural sciences, and particularly in the inventory and monitoring of biodiversity (McKinley et al. 2017). The information generated with the collaboration of citizens has an evident importance in conservation, by providing information on the state of populations and habitats, helping in mitigation and restoration actions, and very importantly contributing to involve society in conservation (Brown and Williams 2019). An obvious advantage of these initiatives is the ability to mobilize human resources on a large territorial scale and in the medium term, which would otherwise be difficult to finance. The resulting increasing information then can be processed with advanced computational techniques (Hochachka et al 2012; Kelling et al. 2015), thus improving our interpretation of the distribution of species. Specifically, the ability to obtain information on a large territorial scale can be integrated into studies based on Species Distribution Models SDMs. One of the common problems with SDMs is that they often work from species occurrences that have been opportunistically recorded, either by professionals or amateurs. A great challenge for data obtained from non-professional citizens, however, remains to ensure its standardization and quality (Kosmala et al. 2016). This requires a clear and effective design, solid volunteer training, and a high level of coordination that turns out to be complex (Brown and Williams 2019). Finally, it is essential to perform a quality validation following scientifically recognized standards, since they are often conditioned by errors and biases in obtaining information (Bird et al. 2014). There are two basic approaches to obtain the necessary data for this validation: getting it from an external source (external validation), or allocating a part of the database itself (internal validation or cross-validation) to this function.
Matutini et al. (2020) in his work 'How citizen science could improve Species Distribution Models and their independent assessment' shows a novel application of the data generated by a citizen science initiative ('Un Dragon dans mon Jardin') by providing an external source for the validation of SDMs, as a tool to construct habitat suitability maps for nine species of amphibians in western France. Importantly, 'Un Dragon dans mon Jardin' contains standardized presence-absence data, the approximation recognized as the most robust (Guisan, et al. 2017). The SDMs to be validated, in turn, were based on opportunistic information obtained by citizens and professionals. The result shows the usefulness of this external data source by minimizing the overestimation of model accuracy that is obtained with cross-validation with the internal evaluation dataset. It also shows the importance of properly filtering the information obtained by citizens by determining the threshold of sampling effort.
The destiny of citizen science is to be integrated into the complex world of science. Supported by the increasing level of the formation of society, it is becoming a fundamental piece in the scientific system dedicated to the study of biodiversity and its conservation. After funding for scientists specialized in the recognition of biodiversity has been cut back, we are seeing a transformation of the activity of these scientists towards the design, coordination, training and verification of programs for the acquisition of field information obtained by citizens. A main goal is that a substantial part of this information will eventually get integrated into the scientific system, and rigorous verification process a fundamental element for such purpose, as shown by Matutini et al. (2020) work.

References

[1] Bird TJ et al. (2014) Statistical solutions for error and bias in global citizen science datasets. Biological Conservation 173: 144-154. doi: 10.1016/j.biocon.2013.07.037
[2] Brown ED and Williams BK (2019) The potential for citizen science to produce reliable and useful information in ecology. Conservation Biology 33: 561-569. doi: 10.1111/cobi.13223
[3] Guisan A, Thuiller W and Zimmermann N E (2017) Habitat Suitability and Distribution Models: With Applications in R. The University of Chicago Press. doi: 10.1017/9781139028271
[4] Hochachka WM, Fink D, Hutchinson RA, Sheldon D, Wong WK and Kelling S (2012) Data-intensive science applied to broad-scale citizen science. Trens Ecol Evol 27: 130-137. doi: 10.1016/j.tree.2011.11.006
[5] Kelling S, Fink D, La Sorte FA, Johnston A, Bruns NE and Hochachka WM (2015) Taking a ‘Big Data’ approach to data quality in a citizen science project. Ambio 44(Supple. 4):S601-S611. doi: 10.1007/s13280-015-0710-4
[6] Kosmala M, Wiggins A, Swanson A and Simmons B (2016) Assessing data quality in citizen science. Front Ecol Environ 14: 551–560. doi: 10.1002/fee.1436
[7] Matutini F, Baudry J, Pain G, Sineau M and Pithon J (2020) How citizen science could improve Species Distribution Models and their independent assessment. bioRxiv, 2020.06.02.129536, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/2020.06.02.129536
[8] McKinley DC et al. (2017) Citizen science can improve conservation science, natural resource management, and environmental protection. Biological Conservation 208:15-28. doi: 10.1016/j.biocon.2016.05.015

The processes that trigger community assembly are still in the centre of ecological interest. While prior work mostly focused on spatial patterns of co-occurrence within a meta-community framework [reviewed in 1, 2] recent studies also include temporal patterns of community composition [e.g. 3, 4, 5, 6]. In this preprint [7], Franck Jabot and co-workers extend they prior approaches to quasi neutral community assembly [8, 9, 10] and develop an analytical framework of spatial and temporal diversity turnover. A simple and heuristic path model for beta diversity and an extended ecological drift model serve as starting points. The model can be seen as a counterpart to Ulrich et al. [5]. These authors implemented competitive hierarchies into their neutral meta-community model while the present paper focuses on environmental filtering. Most important, the model and parameterization of four empirical data sets on aquatic plant and animal meta-communities used by Jabot et al. returned a consistent high influence of environmental stochasticity on species turnover. Of course, this major result does not come to a surprise. As typical for this kind of models it depends also to a good deal on the initial model settings. It nevertheless makes a strong conceptual point for the importance of environmental variability over dispersal and richness effects. One interesting side effect regards the impact of richness differences (ΔS). Jabot et al. interpret this as a ‘nuisance variable’ as they do not have a stringent explanation. Of course, it might be a pure statistical bias introduced by the Soerensen metric of turnover that is normalized by richness. However, I suspect that there is more behind the ΔS effect. Richness differences are generally associated with respective differences in total abundances and introduce source – sink dynamics that inevitably shape subsequent colonization – extinction processes. It would be interesting to see whether ΔS alone is able to trigger observed patterns of community assembly and community composition. Such an analysis would require partitioning of species turnover into richness and nestedness effects [11]. I encourage Jabot et al. to undertake such an effort.
The present paper is also another call to include temporal population variability into metapopulation models for a better understanding of the dynamics and triggering of community assembly. In a next step, competitive interactions should be included into the model to infer the relative importance of both factors.

References

[1] Götzenberger, L. et al. (2012). Ecological assembly rules in plant communities—approaches, patterns and prospects. Biological reviews, 87(1), 111-127. doi: 10.1111/j.1469-185X.2011.00187.x
[2] Ulrich, W., & Gotelli, N. J. (2013). Pattern detection in null model analysis. Oikos, 122(1), 2-18. doi: 10.1111/j.1600-0706.2012.20325.x
[3] Grilli, J., Barabás, G., Michalska-Smith, M. J., & Allesina, S. (2017). Higher-order interactions stabilize dynamics in competitive network models. Nature, 548(7666), 210. doi: 10.1038/nature23273
[4] Nuvoloni, F. M., Feres, R. J. F., & Gilbert, B. (2016). Species turnover through time: colonization and extinction dynamics across metacommunities. The American Naturalist, 187(6), 786-796. doi: 10.1086/686150
[5] Ulrich, W., Jabot, F., & Gotelli, N. J. (2017). Competitive interactions change the pattern of species co‐occurrences under neutral dispersal. Oikos, 126(1), 91-100. doi: 10.1111/oik.03392
[6] Dobramysl, U., Mobilia, M., Pleimling, M., & Täuber, U. C. (2018). Stochastic population dynamics in spatially extended predator–prey systems. Journal of Physics A: Mathematical and Theoretical, 51(6), 063001. doi: 10.1088/1751-8121/aa95c7
[7] Jabot, F., Laroche, F., Massol, F., Arthaud, F., Crabot, J., Dubart, M., Blanchet, S., Munoz, F., David, P., and Datry, T. (2019). Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition. bioRxiv, 480335, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/480335
[8] Jabot, F., & Chave, J. (2011). Analyzing tropical forest tree species abundance distributions using a nonneutral model and through approximate Bayesian inference. The American Naturalist, 178(2), E37-E47. doi: 10.1086/660829
[9] Jabot, F., & Lohier, T. (2016). Non‐random correlation of species dynamics in tropical tree communities. Oikos, 125(12), 1733-1742. doi: 10.1111/oik.03103
[10] Datry, T., Bonada, N., & Heino, J. (2016). Towards understanding the organisation of metacommunities in highly dynamic ecological systems. Oikos, 125(2), 149-159. doi: 10.1111/oik.02922
[11] Baselga, A. (2010). Partitioning the turnover and nestedness components of beta diversity. Global ecology and biogeography, 19(1), 134-143. doi: 10.1111/j.1466-8238.2009.00490.x

Mammals show a very low level of variation in vertebral count, both among and within species, in comparison to other vertebrates [1]. Jordan’s rule for fishes states that the vertebral number among species increases with latitude, due to ambient temperatures during development [2]. Temperature has also been shown to influence vertebral count within species in fish [3], amphibians [4], and birds [5]. However, in mammals the count appears to be constrained, on the one hand, by a possible relationship between the development of the skeleton and the proliferations of cell lines with associated costs (neural malformations, cancer etc., [6]), and on the other by the cervical origin of the diaphragm [7].
Knight et al. [8] investigate the effect of intrauterine temperature variation on skeletal morphology during development, and focus on a particular mammal, Dasypus novemcinctus, or nine-banded armadillo. Armadillos (Xenarthra) and are characterized by relatively low body temperatures and low basal rates of metabolism. Dasypus novemcinctus is the only xenarthran mammal to have naturally expanded its range into the middle latitudes of the U.S., and one of the few mammals that invaded North America from South America. It is one of few placentals that withstand considerable decrease of body temperature without torpor. It presents a resting body temperature that is low and variable for a placental mammal of its size [9] and is the only vertebrate that gives birth to monozygotic quadruplets. Among 42 monotreme, marsupial and placental genera, Dasypus novemcinctus shows the highest variation of thoracolumbar vertebral count [10].
The particularities of Dasypus novemcinctus regarding vertebral count variation and ability to withstand variable temperature qualify it as a target organism for study of the relationship between skeleton morphology and temperature in mammals.
Knight et al. [8] explored variability in vertebral count within Dasypus novemcinctus to understand whether temperature during development determines skeleton morphology. To this end they experimented with 22 armadillos (19 with data) and litters from 12 pregnant females, in two environments, for three years — an impressive effort and experimental setup. Moreover, they used a wide variety of advanced experimental and analytical techniques. For example, they implanted intra-abdominal, long-term temperature recorders, which recorded data every 6 to 120 minutes for up to several months. They analysed body temperature periodicity by approximation of the recordings with Fourier series, and they CT-scanned fetuses.
All 19 individuals (from which data could be gathered) exhibited substantial daily variation in body temperature. Several intriguing results emerged such as the counter-intuitive finding that the mammals’ body temperature fluctuates more indoors than outdoors. Furthermore, three females (out of 12) were found to have offspring with atypical skeletons, and two of these mothers presented an extremely low internal temperature early in pregnancy. Additionally, genetically identical quadruplets differed skeletally among themselves within two litters.
Results are not yet definitive about the relationship of temperature during development and vertebral count in Dasypus novemcinctus. However, Knight et al. [8] demonstrated that nine-banded armadillos survive with high daily internal temperature fluctuations and successfully bring to term offspring which vary in skeletal morphology among and within genetically identical litters despite major temperature extremes.

References

[1] Hautier L, Weisbecker V, Sánchez-Villagra MR, Goswami A, Asher RJ (2010) Skeletal development in sloths and the evolution of mammalian vertebral patterning. Proceedings of the National Academy of Sciences, 107, 18903–18908. doi: 10.1073/pnas.1010335107
[2] Jordan, D.S. (1892) Relations of temperature to vertebrae among fishes. Proceedings of the United States National Museum, 1891, 107-120. doi: 10.5479/si.00963801.14-845.107
[3] Tibblin P, Berggren H, Nordahl O, Larsson P, Forsman A (2016) Causes and consequences of intra-specific variation in vertebral number. Scientific Reports, 6, 1–12. doi: 10.1038/srep26372
[4] Peabody RB, Brodie ED (1975) Effect of temperature, salinity and photoperiod on the number of trunk vertebrae in Ambystoma maculatum. Copeia, 1975, 741–746. doi: 10.2307/1443326
[5] Lindsey CC, Moodie GEE (1967) The effect of incubation temperature on vertebral count in the chicken. Canadian Journal of Zoology, 45, 891–892. doi: 10.1139/z67-099
[6] Galis F, Dooren TJMV, Feuth JD, Metz JAJ, Witkam A, Ruinard S, Steigenga MJ, Wunaendts LCD (2006) Extreme selection in humans against homeotic transformations of cervical vertebrae. Evolution, 60, 2643–2654. doi: 10.1111/j.0014-3820.2006.tb01896.x
[7] Buchholtz EA, Stepien CC (2009) Anatomical transformation in mammals: developmental origin of aberrant cervical anatomy in tree sloths. Evolution and Development, 11, 69–79. doi: 10.1111/j.1525-142X.2008.00303.x
[8] Knight F, Connor C, Venkataramanan R, Asher RJ. (2020). Body temperatures, life history, and skeletal morphology in the nine-banded armadillo (Dasypus novemcinctus). PCI-Ecology. doi: 10.17863/CAM.50971
[9] McNab BK (1980) Energetics and the limits to a temperate distribution in armadillos. Journal of Mammalogy, 61, 606–627. doi: 10.2307/1380307
[10] Asher RJ, Lin KH, Kardjilov N, Hautier L (2011) Variability and constraint in the mammalian vertebral column. Journal of Evolutionary Biology, 24, 1080–1090. doi: 10.1111/j.1420-9101.2011.02240.x

Consistent individual differences in habitat use are found across species and can play a role in who an individual mates with, their risk of predation, and their ability to compete with others (Stuber et al. 2022). However, the data informing such hypotheses come primarily from temperate regions (Stroud & Thompson 2019, Titley et al. 2017). This calls into question the generalizability of the conclusions from this research until further investigations can be conducted in tropical regions.

Giacomini and colleagues (2023) tackled this task in an investigation of consistent individual differences in habitat use in the Central American tropics. They explored whether Spix’s disc-winged bats form positional hierarchies in roosts, which is an excellent start to learning more about the social behavior of this species - a species that is difficult to directly observe. They found that individual bats use their roosting habitat in predictable ways by positioning themselves consistently either in the bottom, middle, or top of the roost leaf. Individuals chose the same positions across time and across different roost sites. They also found that age and sex play a role in which sections individuals are positioned in.

Their research shows that consistent individual differences in habitat use are present in a tropical system, and sets the stage for further investigations into social behavior in this species, particularly whether there is a dominance hierarchy among individuals and whether some positions in the roost are more protective and sought after than others.

References

Giacomini G, Chaves-Ramirez S, Hernandez-Pinson A, Barrantes JP, Chaverri G. (2023). Consistent individual positions within roosts in Spix's disc-winged bats. bioRxiv, https://doi.org/10.1101/2022.11.04.515223 

Stroud, J. T., & Thompson, M. E. (2019). Looking to the past to understand the future of tropical conservation: The importance of collecting basic data. Biotropica, 51(3), 293-299. https://doi.org/10.1111/btp.12665

Stuber, E. F., Carlson, B. S., & Jesmer, B. R. (2022). Spatial personalities: a meta-analysis of consistent individual differences in spatial behavior. Behavioral Ecology, 33(3), 477-486. https://doi.org/10.1093/beheco/arab147 

Titley, M. A., Snaddon, J. L., & Turner, E. C. (2017). Scientific research on animal biodiversity is systematically biased towards vertebrates and temperate regions. PloS one, 12(12), e0189577. https://doi.org/10.1371/journal.pone.0189577