Have you ever wondered why some species breed seasonally while others do not? You might think it is all down to lattitude and the harshness of winters but it turns out it is quite a bit more complicated than that. A consequence of this is that climate change may result in the evolution of the degree of seasonal reproduction, with some species perhaps becoming less seasonal and others more so even in the same habitat. 

Burtschell et al. (2023) investigated how various factors influence seasonal breeding by building an individual-based model of a baboon population from which they calculated the degree of seasonality for the fittest reproductive strategy. They then altered key aspects of their model to examine how these changes impacted the degree of seasonality in the reproductive strategy. What they found is fascinating. 

The degree of seasonality in reproductive strategy is expected to increase with increased seasonality in the environment, decreased food availability, increased energy expenditure, and how predictable resource availability is. Interestingly, neither female cycle length nor extrinsic infant mortality influenced the degree of seasonality in reproduction.

What this means in reality for seasonal species is more challenging to understand. Some environments appear to be becoming more seasonal yet less predictable, and some species appear to be altering their daily energy budgets in response to changing climate in quite complex ways. As with pretty much everything in biology, Burtschell et al.'s work reveals much nuance and complexity, and that predicting how species might alter their reproductive timing is fraught with challenges.

The paper is very well written. With a simpler model it may have proven possible to achieve analytical solutions, but this is a very minor gripe. The reviewers were positive about the paper, and I have little doubt it will be well-cited. 

REFERENCES

Burtschell L, Dezeure J, Huchard E, Godelle B (2023) Evolutionary determinants of reproductive seasonality: a theoretical approach. bioRxiv, 2022.08.22.504761, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.08.22.504761

Local adaptation shall occur whenever selective pressures vary across space and overwhelm the effects of gene flow and local extinctions (Kawecki and Ebert 2004). Because the intimate interaction that characterizes their relationship exerts a strong selective pressure on both partners, host-parasite systems represent a classical example in which local adaptation is expected from rapidly evolving parasites adapting to more evolutionary constrained hosts (Kaltz and Shykoff 1998). Such systems indeed represent a large proportion of the study-cases in local adaptation research (Runquist et al. 2020). Biotic interactions intervene in many environment-related societal challenges, so that understanding when and how local adaptation arises is important not only for understanding evolutionary dynamics but also for more applied questions such as the control of agricultural pests, biological invasions, or pathogens (Parker and Gilbert 2004).

The exact conditions under which local adaptation does occur and can be detected is however still the focus of many theoretical, methodological and empirical studies (Blanquart et al. 2013, Hargreaves et al. 2020, Hoeksema and Forde 2008, Nuismer and Gandon 2008, Richardson et al. 2014). A recent review that evaluates investigations that examined the combined influence of biotic and abiotic factors on local adaptation reaches partial conclusions about their relative importance in different contexts and underlines the many traps that one has to avoid in such studies (Runquist et al. 2020). The authors of this review emphasize that one should evaluate local adaptation using wild-collected strains or populations and over multiple generations, on environmental gradients that span natural ranges of variation for both biotic and abiotic factors, in a theory-based hypothetico-deductive framework that helps interpret the outcome of experiments. These multiple targets are not easy to reach in each local adaptation experiment given the diversity of systems in which local adaptation may occur. Improving research practices may also help better understand when and where local adaptation does occur by adding controls over p-hacking, HARKing or publication bias, which is best achieved when hypotheses, date collection and analytical procedures are known before the research begins (Chambers et al. 2014). In this regard, the route taken by Olvera-Vazquez et al. (2021) is interesting. They propose to investigate whether the rosy aphid (Dysaphis plantaginea) recently adapted to its cultivated host, the apple tree (Malus domestica), and chose to pre-register their hypotheses and planned experiments on PCI Ecology (Peer Community In 2020). Though not fulfilling all criteria mentioned by Runquist et al. (2020), they clearly state five hypotheses that all relate to the local adaptation of this agricultural pest to an economically important fruit tree, and describe in details a powerful, randomized experiment, including how data will be collected and analyzed. The experimental set-up includes comparisons between three sites located along a temperature transect that also differ in local edaphic and biotic factors, and contrasts wild and domesticated apple trees that originate from the three sites and were both planted in the local, sympatric site, and transplanted to allopatric sites. Beyond enhancing our knowledge on local adaptation, this experiment will also test the general hypothesis that the rosy aphid recently adapted to Malus sp. after its domestication, a question that population genetic analyses was not able to answer (Olvera-Vazquez et al. 2020).

References

Blanquart F, Kaltz O, Nuismer SL, Gandon S (2013) A practical guide to measuring local adaptation. Ecology Letters, 16, 1195–1205. https://doi.org/10.1111/ele.12150

Briscoe Runquist RD, Gorton AJ, Yoder JB, Deacon NJ, Grossman JJ, Kothari S, Lyons MP, Sheth SN, Tiffin P, Moeller DA (2019) Context Dependence of Local Adaptation to Abiotic and Biotic Environments: A Quantitative and Qualitative Synthesis. The American Naturalist, 195, 412–431. https://doi.org/10.1086/707322

Chambers CD, Feredoes E, Muthukumaraswamy SD, Etchells PJ, Chambers CD, Feredoes E, Muthukumaraswamy SD, Etchells PJ (2014) Instead of “playing the game” it is time to change the rules: Registered Reports at <em>AIMS Neuroscience</em> and beyond. AIMS Neuroscience, 1, 4–17. https://doi.org/10.3934/Neuroscience.2014.1.4

Hargreaves AL, Germain RM, Bontrager M, Persi J, Angert AL (2019) Local Adaptation to Biotic Interactions: A Meta-analysis across Latitudes. The American Naturalist, 195, 395–411. https://doi.org/10.1086/707323

Hoeksema JD, Forde SE (2008) A Meta‐Analysis of Factors Affecting Local Adaptation between Interacting Species. The American Naturalist, 171, 275–290. https://doi.org/10.1086/527496

Kaltz O, Shykoff JA (1998) Local adaptation in host–parasite systems. Heredity, 81, 361–370. https://doi.org/10.1046/j.1365-2540.1998.00435.x

Kawecki TJ, Ebert D (2004) Conceptual issues in local adaptation. Ecology Letters, 7, 1225–1241. https://doi.org/10.1111/j.1461-0248.2004.00684.x

Nuismer SL, Gandon S (2008) Moving beyond Common‐Garden and Transplant Designs: Insight into the Causes of Local Adaptation in Species Interactions. The American Naturalist, 171, 658–668. https://doi.org/10.1086/587077

Olvera-Vazquez SG, Remoué C, Venon A, Rousselet A, Grandcolas O, Azrine M, Momont L, Galan M, Benoit L, David G, Alhmedi A, Beliën T, Alins G, Franck P, Haddioui A, Jacobsen SK, Andreev R, Simon S, Sigsgaard L, Guibert E, Tournant L, Gazel F, Mody K, Khachtib Y, Roman A, Ursu TM, Zakharov IA, Belcram H, Harry M, Roth M, Simon JC, Oram S, Ricard JM, Agnello A, Beers EH, Engelman J, Balti I, Salhi-Hannachi A, Zhang H, Tu H, Mottet C, Barrès B, Degrave A, Razmjou J, Giraud T, Falque M, Dapena E, Miñarro M, Jardillier L, Deschamps P, Jousselin E, Cornille A (2020) Large-scale geographic survey provides insights into the colonization history of a major aphid pest on its cultivated apple host in Europe, North America and North Africa. bioRxiv, 2020.12.11.421644. https://doi.org/10.1101/2020.12.11.421644

Olvera-Vazquez S.G., Alhmedi A., Miñarro M., Shykoff J. A., Marchadier E., Rousselet A., Remoué C., Gardet R., Degrave A. , Robert P. , Chen X., Porcher J., Giraud T., Vander-Mijnsbrugge K., Raffoux X., Falque M., Alins, G., Didelot F., Beliën T., Dapena E., Lemarquand A. and Cornille A. (2021) Experimental test for local adaptation of the rosy apple aphid (Dysaphis plantaginea) to its host (Malus domestica) and to its climate in Europe. In principle recommendation by Peer Community In Ecology. https://forgemia.inra.fr/amandine.cornille/local_adaptation_dp, ver. 4.

Parker IM, Gilbert GS (2004) The Evolutionary Ecology of Novel Plant-Pathogen Interactions. Annual Review of Ecology, Evolution, and Systematics, 35, 675–700. https://doi.org/10.1146/annurev.ecolsys.34.011802.132339

Peer Community In. (2020, January 15). Submit your preregistration to Peer Community In for peer review. https://peercommunityin.org/2020/01/15/submit-your-preregistration-to-peer-community-in-for-peer-review/

Richardson JL, Urban MC, Bolnick DI, Skelly DK (2014) Microgeographic adaptation and the spatial scale of evolution. Trends in Ecology & Evolution, 29, 165–176. https://doi.org/10.1016/j.tree.2014.01.002

The slippersnail (Crepidula fornicata), originally from the eastern coast of North America, has invaded European coastlines from Norway to the Mediterranean Sea [1]. This species is capable of achieving incredibly high densities (up to several thousand individuals per square meter) and likely has major impacts on a variety of community- and ecosystem-level processes, including alteration of carbon and nitrogen fluxes and competition with native suspension feeders [2].

Given this potential for competition, it is important to understand the diet of C. fornicata and its potential overlap with native species. However, previous research on the diet of C. fornicata and related species suggests that the types of food consumed may change with age [3, 4]. This species has an unusual reproductive strategy. It is a sequential hermaphrodite, which begins life as a somewhat mobile male but eventually slows down to become sessile. Sessile individuals form stacks of up to 10 or more individuals, with larger individuals on the bottom of the stack, and decreasingly smaller individuals piled on top. Snails at the bottom of the stack are female, whereas snails at the top of the stack are male; when the females die, the largest males become female [5]. Thus, understanding these potential ontogenetic dietary shifts has implications for both intraspecific (juvenile vs. male vs. female) and interspecific competition associated with an abundant, invasive species.

To this end, Androuin and colleagues evaluated the stable-isotope (d13C and d15N) and fatty-acid profiles of food sources and different life-history stages of C. fornicata [6]. Based on previous work highlighting the potential for life-history changes in the diet of this species [3,4], they hypothesized that C. fornicata would shift its diet as it aged and predicted that this shift would be reflected in changes in its stable-isotope and fatty-acid profiles. The authors found that potential food sources (biofilm, suspended particulate organic matter, and superficial sedimentary organic matter) differed substantially in both stable-isotope and fatty-acid signatures. However, whereas fatty-acid profiles changed substantially with age, there was no shift in the stable-isotope signatures. Because stable-isotope differences between food sources were not reflected in differences between life-history stages, the authors conservatively concluded that there was insufficient evidence for a diet shift with age. The ontogenetic shifts in fatty-acid profiles were intriguing, but the authors suggested that these reflected age-related physiological changes rather than changes in diet.

The authors’ work highlights the need to consider potential changes in the roles of invasive species with age, especially when evaluating interactions with native species. In this case, C. fornicata consumed a variety of food sources, including both benthic and particulate organic matter, regardless of age. The carbon stable-isotope signature of C. fornicata overlaps with those of several native suspension- and deposit-feeding species in the region [7], suggesting the possibility of resource competition, especially given the high abundances of this invader. This contribution demonstrates the potential difficulty of characterizing the impacts of an abundant invasive species with a complex life-history strategy. Like many invasive species, C. fornicata appears to be a dietary generalist, which likely contributes to its success in establishing and thriving in a variety of locations [8].

References

[1] Blanchard M (1997) Spread of the slipper limpet Crepidula fornicata (L. 1758) in Europe. Current state dans consequences. Scientia Marina, 61, 109–118. Open Access version : https://archimer.ifremer.fr/doc/00423/53398/54271.pdf

[2] Martin S, Thouzeau G, Chauvaud L, Jean F, Guérin L, Clavier J (2006) Respiration, calcification, and excretion of the invasive slipper limpet, Crepidula fornicata L.: Implications for carbon, carbonate, and nitrogen fluxes in affected areas. Limnology and Oceanography, 51, 1996–2007. https://doi.org/10.4319/lo.2006.51.5.1996

[3] Navarro JM, Chaparro OR (2002) Grazing–filtration as feeding mechanisms in motile specimens of Crepidula fecunda (Gastropoda: Calyptraeidae). Journal of Experimental Marine Biology and Ecology, 270, 111–122. https://doi.org/10.1016/S0022-0981(02)00013-8

[4] Yee AK, Padilla DK (2015) Allometric Scaling of the Radula in the Atlantic Slippersnail Crepidula fornicata. Journal of Shellfish Research, 34, 903–907. https://doi.org/10.2983/035.034.0320

[5] Collin R (1995) Sex, Size, and Position: A Test of Models Predicting Size at Sex Change in the Protandrous Gastropod Crepidula fornicata. The American Naturalist, 146, 815–831. https://doi.org/10.1086/285826

[6] Androuin T, Dubois SF, Hubas C, Lefebvre G, Grand FL, Schaal G, Carlier A (2021) Trophic niche of the invasive gregarious species Crepidula fornicata, in relation to ontogenic changes. bioRxiv, 2020.07.30.229021, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2020.07.30.229021

[7] Dauby P, Khomsi A, Bouquegneau J-M (1998) Trophic Relationships within Intertidal Communities of the Brittany Coasts: A Stable Carbon Isotope Analysis. Journal of Coastal Research, 14, 1202–1212. Retrieved May 4, 2021, from http://www.jstor.org/stable/4298880

[8] Machovsky-Capuska GE, Senior AM, Simpson SJ, Raubenheimer D (2016) The Multidimensional Nutritional Niche. Trends in Ecology & Evolution, 31, 355–365. https://doi.org/10.1016/j.tree.2016.02.009

"Good and evil are so close as to be chained together in the soul"
Robert Louis Stevenson, Dr. Jekyll and Mr. Hyde

Maternally inherited symbionts—microorganisms that pass from a female host to her progeny—have two main ways of increasing their own fitness. First, they can increase the fecundity or viability of infected females. This “positive fitness effects” strategy is the one commonly used by mutualistic symbionts, such as Buchnera aphidicola—the bacterial endosymbiont of the pea aphid, Acyrthosiphon pisum [4]. Second, maternally inherited symbionts can manipulate the reproduction of infected females in a way that enhances symbiont transmission at the expense of host fitness. A famous example of this “reproductive parasitism” strategy is the cytoplasmic incompatibility (CI) [3] induced by bacteria of the genus Wolbachia in their arthropod and nematode hosts. CI works as a toxin-antidote system, whereby the sperm of infected males is modified in a lethal way (toxin) that can only be reverted if the egg is also infected (antidote) [1]. As a result, CI imposes a kind of conditional sterility on their hosts: while infected females are compatible with both infected and uninfected males, uninfected females experience high offspring mortality if (and only if) they mate with infected males [7].

These two symbiont strategies (positive fitness effects versus reproductive parasitism) have been traditionally studied separately, both empirically and theoretically. However, it has become clear that the two strategies are not mutually exclusive, and that a reproductive parasite can simultaneously act as a mutualist—an infection type that has been dubbed “Jekyll and Hyde” [6], after the famous novella by Robert Louis Stevenson about kind scientist Dr. Jekyll and his evil alter ego, Mr. Hyde. In important previous work, Zug and Hammerstein [7] analyzed the consequences of positive fitness effects on the dynamics of different kind of infections, including “Jekyll and Hyde” infections characterized by CI and other reproductive parasitism strategies. Building on this and related modeling framework, Karisto et al. [2] re-investigate and expand on the interplay between positive fitness effects and reproductive parasitism in Wolbachia infections by focusing on CI in both diplodiploid and haplodiploid populations, and by paying particular attention to the mathematical assumption structure underlying their results.

Karisto et al. begin by reviewing classic models of Wolbachia infections in diplodiploid populations that assume a “negative fitness effect” (modeled as a fertility penalty on infected females), characteristic of a pure strategy of reproductive parasitism. Together with the positive frequency-dependent effects due to CI (whereby the fitness benefits to symbionts infecting females increase with the proportion of infected males in the population) this results in population dynamics characterized by two stable equilibria (the Wolbachia-free state and an interior equilibrium with a high frequency of Wolbachia-carrying hosts) separated by an unstable interior equilibrium. Wolbachia can then spread once the initial frequency is above a threshold or an invasion barrier, but is prevented from fixing by a proportion of infections failing to be passed on to offspring. Karisto et al. show that, given the assumption of negative fitness effects, the stable interior equilibrium can never feature a Wolbachia prevalence below one-half. Moreover, they convincingly argue that a prevalence greater than but close to one-half is difficult to maintain in the presence of stochastic fluctuations, as in these cases the high-prevalence stable equilibrium would be too close to the unstable equilibrium signposting the invasion barrier.

Karisto et al. then relax the assumption of negative fitness effects and allow for positive fitness effects (modeled as a fertility premium on infected females) in a diplodiploid population. They show that positive fitness effects may result in situations where the original invasion threshold is now absent, the bistable coexistence dynamics are transformed into purely co-existence dynamics, and Wolbachia symbionts can now invade when rare. Karisto et al. conclude that positive fitness effects provide a plausible and potentially testable explanation for the low frequencies of symbiont-carrying hosts that are sometimes observed in nature, which are difficult to reconcile with the assumption of negative fitness effects. 

Finally, Karisto et al. extend their analysis to haplodiploid host populations (where all fertilized eggs develop as females). Here, they investigate two types of cytoplasmic incompatibility: a female-killing effect, similar to the CI effect studied in diplodiploid populations (the “Leptopilina type” of Vavre et al. [5]) and a masculinization effect, where CI leads to the loss of paternal chromosomes and to the development of the offspring as a male (the “Nasonia type” of Vavre et al. [5]). The models are now two-sex, which precludes a complete analytical treatment, in particular regarding the stability of fixed points. Karisto et al. compensate by conducting large numerical analyses that support their claims. Importantly, all main conclusions regarding the interplay between positive fitness effects and reproductive parasitism continue to hold under haplodiploidy. 

All in all, the analysis and results by Karisto et al. suggest that it is not necessary to resort to classical (but depending on the situation, unlikely) mechanisms, such as ongoing invasion or source-sink dynamics, to explain arthropod populations featuring low-prevalent Wolbachia infections. Instead, low-frequency equilibria might be simply due to reproductive parasites conferring beneficial fitness effects, or Wolbachia symbionts playing Dr. Jekyll (positive fitness effects) and Mr. Hyde (cytoplasmatic incompatibility). 

References

[1] Beckmann JF, Bonneau M, Chen H, Hochstrasser M, Poinsot D, Merçot H, Weill M, Sicard M, Charlat S (2019) The Toxin–Antidote Model of Cytoplasmic Incompatibility: Genetics and Evolutionary Implications. Trends in Genetics, 35, 175–185. https://doi.org/10.1016/j.tig.2018.12.004

[2] Karisto P, Duplouy A, Vries C de, Kokko H (2022) Positive fitness effects help explain the broad range of Wolbachia prevalences in natural populations. bioRxiv, 2022.04.11.487824, ver. 5 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.04.11.487824

[3] Laven H (1956) Cytoplasmic Inheritance in Culex. Nature, 177, 141–142. https://doi.org/10.1038/177141a0

[4] Perreau J, Zhang B, Maeda GP, Kirkpatrick M, Moran NA (2021) Strong within-host selection in a maternally inherited obligate symbiont: Buchnera and aphids. Proceedings of the National Academy of Sciences, 118, e2102467118. https://doi.org/10.1073/pnas.2102467118

[5] Vavre F, Fleury F, Varaldi J, Fouillet P, Bouletreau M (2000) Evidence for Female Mortality in Wolbachia-Mediated Cytoplasmic Incompatibility in Haplodiploid Insects: Epidemiologic and Evolutionary Consequences. Evolution, 54, 191–200. https://doi.org/10.1111/j.0014-3820.2000.tb00019.x

[6] Zug R, Hammerstein P (2015) Bad guys turned nice? A critical assessment of Wolbachia mutualisms in arthropod hosts. Biological Reviews, 90, 89–111. https://doi.org/10.1111/brv.12098

[7] Zug R, Hammerstein P (2018) Evolution of reproductive parasites with direct fitness benefits. Heredity, 120, 266–281. https://doi.org/10.1038/s41437-017-0022-5

How do you estimate the biodiversity of a whole community, or the distribution of abundances and ranges of its species, from presence/absence data in scattered samples?
It all starts with the collector's dilemma: if you double the number of samples, you will not get double the number of species, since you will find many of the same common species, and only a few new rare ones.
This non-additivity has prompted many ecologists to study the Species-Area Relationship. A common theoretical approach has been to connect this spatial pattern to the overall distribution of how common or rare a species can be. At least since Fisher's celebrated log-series [1], ecologists have been trying to, first, infer the shape of the Species Abundance Distribution, and then, use it to predict how many species should be found in a given area or a given number of samples. This has found many applications, from microbial communities to tropical forests, from estimating the number of yet-unknown species to predicting how much biodiversity may be lost if a fraction of the habitat is removed.
In this elegant work, Tovo et al. [2] propose a method that starts only from presence/absence data over a number of samples, and provides the community's diversity, as well as its abundance and range size distributions. This method is simple, analytically explicit, and accurate: the authors test it on the classic Pasoh and Barro Colorado Island tropical forest datasets, and on simulated data. They make a very laudable effort in both explaining its theoretical underpinnings, and proposing a straightforward step-by-step guide to applying it to data.
The core of Tovo et al's method is a simple property: the scale invariance of the Negative Binomial (NB) distribution. Subsampling from a NB gives another NB, where a single parameter has changed. Therefore, if the Species Abundance Distribution is close enough to some NB (which is flexible enough to accommodate all the data here), we can estimate how this parameter changes when going from (1) a single sample to (2) all the available samples, and from there, extrapolate to (3) the entire community.
This principle was first applied by the authors in a previous study [3] that required abundance data in the samples, rather than just presence/absence. Given that binary occurrence data is far more available in a variety of empirical settings, this extension is worthwhile (including its new predictions on range size distributions), and it deserves to be widely known and tested.

ADDITIONAL COMMENTS

1) To explain the novelty of the authors' contribution, it is useful to look at competing techniques.
Some ""parametric"" approaches try to infer the whole-community Species Abundance Distribution (SAD) by guessing its functional form (Gaussian, power-law, log-series...) and fitting its parameters from sampled data. The issue is that this distribution shape may not remain in the same family as we increase the sampling effort or area, so the regression problem may not be well-defined. This is where the Negative Binomial's scale invariance is useful.
Other ""non-parametric"" approaches have renounced guessing the whole SAD: they simply try to approximate of its tail of rare species, by looking at how many species are found in only one (or a few) samples. From this, they derive an estimate of biodiversity that is agnostic to the rest of the SAD. Tovo et al. [2] show the issue with these approaches: they extrapolate from the properties of individual samples to the whole community, but do not properly account for the bias introduced by the amount of sampling (the intermediate scale (2) in the summary above).

2) The main condition for all such approaches to work is well-mixedness: each sample should be sufficiently like a lot drawn from the same skewed lottery. As long as that condition applies, finding the best approach is a theoretical matter of probabilities and combinatorics that may, in time, be given a definite answer.
The authors also show that ""well-mixed"" is not as restrictive as it sounds: the method works both on real data (which is never perfectly mixed) and on simulations where species are even more spatially clustered than the empirical data. In addition, the Negative Binomial's scale invariance entails that, if it works well enough at some spatial scale, it will also work at all higher scales (until one reaches the edges of the sufficiently-well-mixed community)

3) One may ask: why the Negative Binomial as a Species Abundance Distribution?
If one wishes for some dynamical explanation, the Negative Binomial can be derived from neutral birth and death process with immigration, as shown by the authors in [3]. But to be applied to data, it should only be able to approximate the empirical distribution well enough (at all relevant scales). Depending on one's taste, this type of probabilistic approaches can be interpreted as:
- purely phenomenological, describing only the observational process of sampling from an existing state of affairs, not the ecological processes that gave rise to that state.
- a null model, from which everything in practice is expected to deviate to some extent.
- or a way to capture the statistical forces that tend to induce stable relationships between different patterns (as long as no ecological process opposes them strongly enough).

References

[1] Fisher, R. A., Corbet, A. S., & Williams, C. B. (1943). The relation between the number of species and the number of individuals in a random sample of an animal population. The Journal of Animal Ecology, 42-58. doi: 10.2307/1411
[2] Tovo, A., Formentin, M., Suweis, S., Stivanello, S., Azaele, S., & Maritan, A. (2019). Inferring macro-ecological patterns from local species' occurrences. bioRxiv, 387456, ver. 2 peer-reviewed and recommended by PCI Ecol. doi: 10.1101/387456
[3] Tovo, A., Suweis, S., Formentin, M., Favretti, M., Volkov, I., Banavar, J. R., Azaele, S., & Maritan, A. (2017). Upscaling species richness and abundances in tropical forests. Science Advances, 3(10), e1701438. doi: 10.1126/sciadv.1701438