Ramon Margalef (1919-2004) was a pioneering scientist who introduced new concepts of ecology and evolution. For example, the Margalef Mandala (Margalef 1978Margalef R. 1978. Life-forms of phytoplankton. Oceanol. Acta 1: 493-509.) is a conceptual scheme that explains how variations in external energy can regulate the organismal succession within aquatic ecosystems (Terradas 2015Terradas J. 2015. El pensamiento evolutivo de Margalef. Ecosistemas 24: 104-109. https://doi.org/10.7818/re.2014.24-1.00 ). Similar in appearance to the spiritual symbol, the Margalef Mandala is a model of natural equilibrium describing the influences of physical (turbulence) and chemical (nutrients) forces on the development of ecological succession in aquatic ecosystems (Margalef 1978Margalef R. 1978. Life-forms of phytoplankton. Oceanol. Acta 1: 493-509., Margalef et al. 1979Margalef R., Estrada M., Blasco D. 1979. Functional morphology of organisms involved in red tides, as adapted to decaying turbulence. In: Taylor, D., Seliger, H. (eds), Toxic Dinoflagellate Blooms. Elsevier, New York pp. 89-94.). This idea laid the foundation for the trait-based approach in ecology and was recently corroborated with field data (Villamaña et al. 2019Villamaña M., Marañón E., Cermeño P., Estrada M., Fernández-Castro B., Figueiras F. G., Latasa M., Otero-Ferrer J. L., Reguera B., Mouriño-Carballido B. 2019. The role of mixing in controlling resource availability and phytoplankton community composition. Prog. Oceanogr. 178: 102181. https://doi.org/10.1016/j.pocean.2019.102181 ).
Margalef spent the early years of his career meticulously cataloguing plankton in streams and lakes around Spain. Later, he adopted methods from information theory to organize and understand these immense datasets (Margalef 1958Margalef R. 1958. Information theory in ecology. General Systems: Yearbook of the Society for General Systems Research 3: 36-71. http://hdl.handle.net/10261/165563 , 1968Margalef R. 1968. Perspectives in ecological theory. University of Chicago Press. 111 pp.). He used Shannon entropy (Shannon 1949Shannon C.E., Weaver W. 1949. The mathematical theory of communication. The University of Illinois Press, Urbana.) to express the information contained in the structure of a community (Margalef 1957Margalef R. 1957. La teoría de la información en Ecología. Mem. Real Acad. Cien. Art. Barcelona 32: 373-436. http://hdl.handle.net/10261/165554 , 1958Margalef R. 1958. Information theory in ecology. General Systems: Yearbook of the Society for General Systems Research 3: 36-71. http://hdl.handle.net/10261/165563 ). Consequently, he used information theory to relate the basic descriptors such as species abundance, distribution and diversity to energy and information flows in order to define population-in-environment as an irreducible unit of ecological study (Margalef 1968Margalef R. 1968. Perspectives in ecological theory. University of Chicago Press. 111 pp.).
Margalef realized that ecology should be studied by considering all variables and forces that are acting on organisms to gain a comprehensive knowledge of the ecosystem. This holistic approach initially contradicted those who focused on one specific parameter to understand ecological, physiological and evolutionary responses of organisms, an approach that was “easily reproducible and faster” in terms of data collection and scientific discussion than Margalef’s approach (Terradas 2015Terradas J. 2015. El pensamiento evolutivo de Margalef. Ecosistemas 24: 104-109. https://doi.org/10.7818/re.2014.24-1.00 ). However, it is now clear that all factors affecting the planet are acting together, and global processes must be considered as multi-stressor scenarios (Boyd et al. 2018Boyd P.W., Collins S., Dupont S., et al. 2018. Experimental strategies to assess the biological ramifications of multiple drivers of global ocean change-A review. Glob. Change Biol. 24: 2239-2261. https://doi.org/10.1111/gcb.14102 ). Margalef’s vision of humanity as an integral part of ecosystems should be considered in future models and theories to promote responsibility for the changes that are increasingly inflicted on nature. He integrated a multitude of concepts from other disciplines to explain ecology. He was a truly multidisciplinary scientist, borrowing from fields such as evolution, information theory and chemistry. In his last works, Margalef applied his ecological thinking to socio-ecological questions (Margalef 1997Margalef R. 1997. Our biosphere. In: O. Kinne (ed.), Excellence in Ecology, 10. Ecology Institute, Oldendrof/Luhe, 176 pp., 2000aMargalef R. 2000a. El marco ecológico para iluminar la sociedad actual. In: Naredo J.M. and Parra F. (eds), Economía, Ecología y Sostenibilidad en la sociedad actual. Siglo XXI, Madrid, pp. 51-66. ). For example, the inequalities in the availability and consumption of resources, the increase in energy consumption without a parallel increase in efficiency, and the accumulation of CO2 in the oceans. His ecological thinking led him to study cultural evolution, social change and financial powers (Margalef 2000bMargalef R. 2000b. Organització de la biosfera i reflexions sobre el present i el futur de la nostra espècie i de la ciència ecològica. Treb. Soc. Cat. Biol. 50: 47-59. Retrieved from. https://raco.cat/index.php/TreballsSCBiologia/article/view/15701 ).
The present review resulted from the discussions held during the workshop “2016 Ramon Margalef Summer Colloquia” under the title “Microbes in a changing world: diversity and biogeochemistry”. Inspired by Margalef’s holistic approach, we revisited four interrelated fields of aquatic microbial ecology: ecological theory, microbial diversity, biogeochemical cycles and global environmental changes (Fig. 1). We analysed and showed how several of Margalef’s ideas contributed to all of them and proposed an integrated approach for future research in aquatic microbial ecology. The present article is a subjective review that reflects the bias and perspectives of the authors.
It has been argued that truly general laws and rules, i.e. ones that are not contingent on organisms or environments, are lacking in ecology (Lawton 1999Lawton J. H. 1999. Are there general laws in ecology? Oikos 84: 177-192. https://doi.org/10.2307/3546712 ). Among the few exceptions are the species-area relationship as the positive power-law relationship between species richness and ecosystem area (Rosenzweig and Parry 1994Rosenzweig C., Parry M.L. 1994. Potential impact of climate change on world food supply. Nature 367: 133-138. https://doi.org/10.1038/367133a0 ) and the metabolic theory of ecology (Brown et al. 2004Brown J.H., Gillooly J.F., Allen A.P., et al. 2004. Toward a metabolic theory of ecology. Ecology 85: 1771-1789. https://doi.org/10.1890/03-9000 ) as the relationship between metabolic rate, body size and temperature. Margalef always tried to frame his work in a broad context, such as the laws of thermodynamics (Margalef 1975Margalef R. 1975. Diversity, stability and maturity in natural ecosystems. In: Unifying Concepts in Ecology. Springer, Netherlands, pp. 151-160. https://doi.org/10.1007/978-94-010-1954-5_12 ). His work not only included papers distinctly devoted to the microbial world (Margalef 1978Margalef R. 1978. Life-forms of phytoplankton. Oceanol. Acta 1: 493-509.), but he also crossed borders and refused to focus on theories that only apply to model systems (Margalef 1963Margalef R. 1963. On certain unifying principles in ecology. Amer. Nat. 97(897): 357-374. https://doi.org/10.1086/282286 ). Therefore, one of his main contributions to ecological theory in microbial ecology was his constant attempt to unify ecological understanding, which he considered a prerequisite for determining speculative explanations of observed patterns in nature. Although Margalef’s contributions to ecological theory went far beyond microbial ecology, some are especially important for the study of microorganisms.
Margalef adopted methods from information theory to organize and understand the immense datasets from his studies (Margalef 1958Margalef R. 1958. Information theory in ecology. General Systems: Yearbook of the Society for General Systems Research 3: 36-71. http://hdl.handle.net/10261/165563 ) and extracted insights applicable to many pressing themes in ecology, as was extensively reviewed recently (Sherwin and Prat 2019Sherwin W.B., Prat i Fornells N. 2019. The Introduction of Entropy and Information Methods to Ecology by Ramon Margalef. Entropy 21: 794. https://doi.org/10.3390/e21080794 ). Margalef used Shannon entropy (Shannon 1949Shannon C.E., Weaver W. 1949. The mathematical theory of communication. The University of Illinois Press, Urbana.) to describe the uncertainty that a randomly sampled individual belongs to a previously observed species, and thus the diversity within a community (Margalef 1957Margalef R. 1957. La teoría de la información en Ecología. Mem. Real Acad. Cien. Art. Barcelona 32: 373-436. http://hdl.handle.net/10261/165554 ). He used information theory to create quantitative descriptors and derive expectations for the species abundance distributions (Margalef 1978Margalef R. 1978. Life-forms of phytoplankton. Oceanol. Acta 1: 493-509.). After Margalef’s introduction, the use of information theory in ecology became more common (Pielou 1966Pielou, E. C. 1966. The measurement of diversity in different types of biological collections. J. Theor. Biol. 13: 131-144. https://doi.org/10.1016/0022-5193(66)90013-0 ). It provided the quantitative framework for modern biodiversity studies (Tuomisto 2010Tuomisto H. 2010. A diversity of beta diversities: Straightening up a concept gone awry. Part 2. Quantifying beta diversity and related phenomena. Ecography 33: 23-45. https://doi.org/10.1111/j.1600-0587.2009.06148.x ) and has been crucial for the development of microbial ecology as we understand it today. Indices based on information theory are essential to analyse the vast amount of sequence datasets in microbial ecology. However, in general, diversity indices should be used to test hypotheses and make predictions on the drivers of diversity rather than as results in themselves (Shade 2017Shade A. 2017. Diversity is the question, not the answer. ISME J. 11: 1-6. https://doi.org/10.1038/ismej.2016.118 ), as Margalef already realized (Margalef 1991Margalef R. 1991. Teoría de los sistemas ecológicos. Edicions Universitat Barcelona.). Just as Margalef moved from using information theory to describe communities to using it to provide expectations, the field of microbial ecology seems to be moving from an observational to a predictive discipline. Conjointly, the observed patterns provide expectations and general relationships that may apply to all organisms (Locey and Lennon 2016Locey K.J. Lennon J.T. 2016. Scaling laws predict global microbial diversity. Proc. Nat. Acad. Sci. USA 113: 5970-5975. https://doi.org/10.1073/pnas.1521291113 ).
Another of Margalef’s contributions was the focus on species traits as important integrative variables for advancing ecological theory. Traits represent a “common value” for studying the responses of disparate organisms to environmental gradients and ecosystem processes. Margalef’s Mandala represents an ecosystem as a bidimensional space described by two major factors affecting phytoplankton growth dynamics: nutrients and turbulence (Margalef 1978Margalef R. 1978. Life-forms of phytoplankton. Oceanol. Acta 1: 493-509., Margalef et al. 1979Margalef R., Estrada M., Blasco D. 1979. Functional morphology of organisms involved in red tides, as adapted to decaying turbulence. In: Taylor, D., Seliger, H. (eds), Toxic Dinoflagellate Blooms. Elsevier, New York pp. 89-94.). These external factors describe the preferred environmental conditions for functional groups of phytoplankton and how the pulses of energy can determine a new start of species succession. Although the Mandala was proposed in the context of phytoplankton succession and functional morphology, the rationale behind it involved a greater concept because both nutrients and turbulence are related to external energy supply (Margalef 1978Margalef R. 1978. Life-forms of phytoplankton. Oceanol. Acta 1: 493-509.). Later developments of this framework helped unify the four basic concepts of community ecology that bridge ecological and evolutionary scales in microbial communities: mutation, selection, dispersal and drift (Vellend 2016Vellend M. 2016. The theory of ecological communities. In: Monographs in population biology. Princeton University Press. https://www.jstor.org/stable/j.ctt1kt82jg ). The modern interpretations and extensions of the Margalef Mandala prove that his approach to ecological theory and community assembly processes remains valid (Wyatt 2014Wyatt T. 2014. Margalef’s mandala and phytoplankton bloom strategies. Deep-Sea Res. Pt. II 101: 32-49. https://doi.org/10.1016/j.dsr2.2012.12.006 ). Moreover, following the classical Margalef Mandala (based on phytoplankton succession), the prokaryote and protist successions could also be drawn using similar schemes with slight variations in the axes, moving from inorganic nutrients to organic matter (Pinhassi and Hagström 2000Pinhassi J., Hagström Å. 2000. Seasonal succession in marine bacterioplankton. Aquat. Microb. Ecol. 21: 245-256. https://doi.org/10.3354/ame021245 ).
Succession, as ecological maturity, was a life-long concern for Margalef. He defined it as “the transformation of an excess of available energy into a future increase in biomass” (Margalef 1963Margalef R. 1963. On certain unifying principles in ecology. Amer. Nat. 97(897): 357-374. https://doi.org/10.1086/282286 ). More mature ecosystems are the most stable ones, allowing an increase in information via structures or behaviour and a decrease in the energy needed to maintain them. The definition of succession based on thermodynamics (less mature systems are characterized by a higher ratio of primary production to biomass) also generates solid expectations on directional flows of energy and information across systems of unequal maturity: a net transfer of energy in the form of biomass occurs from the less mature to the more mature systems. Furthermore, based on these general principles, Margalef predicted the consequences of human exploitation and rising temperatures on ecosystems in terms of reduced diversity and stability (Margalef 1963Margalef R. 1963. On certain unifying principles in ecology. Amer. Nat. 97(897): 357-374. https://doi.org/10.1086/282286 ), which is of a shocking topicality. These insights can be applied to microbial ecology and coincide with current studies of succession in microbial communities (Ortiz-Álvarez et al. 2018Ortiz-Álvarez R., Fierer N., De Los Ríos A., Casamayor E.O., Barberán A. 2018. Consistent changes in the taxonomic structure and functional attributes of bacterial communities during primary succession. ISME J. 12: 1658-1667. https://doi.org/10.1038/s41396-018-0076-2 ).
Microbial communities are critical components of important global processes. Species composition is important, among other things, for the stability and proper functioning of ecosystems and their services (Goswami et al. 2017Goswami M., Bhattacharyya P., Mukherjee I., Tribedi P. 2017. Functional diversity: an important measure of ecosystem functioning. Adv. Microbiol. 7: 82-93. https://doi.org/10.4236/aim.2017.71007 ), and one of the main challenges in microbial ecology has been the estimation of species diversity (Vitorino and Bessa 2018Vitorino L.C., Bessa L.A. 2018. Microbial diversity: the gap between the estimated and the known. Diversity 10: 46. https://doi.org/10.3390/d10020046 ). Today, we strive to understand the patterns of community structure and its dynamics in terms of ecosystem health and function (Shade 2017Shade A. 2017. Diversity is the question, not the answer. ISME J. 11: 1-6. https://doi.org/10.1038/ismej.2016.118 ). Microbial ecologists have worked persistently to increase the sampling effort, making advancements in molecular techniques and developing mathematical measurements of diversity known as “diversity indices” (Fuhrman and Hagström 2008Fuhrman J.A., Hagstrom K. 2008. Bacterial and Archaeal Community Structure and its Patterns. In: Microbial Ecology of the Oceans (pp. 45-90). Hoboken, NJ, USA: John Wiley and Sons, Inc. https://doi.org/10.1002/9780470281840.ch3 ). Diversity indices use either incidence (presence/absence) or relative abundance of species when comparing diversity in two or more communities (Schroeder and Jenkins 2018Schroeder P.J., Jenkins D.G. 2018. How robust are popular beta diversity indices to sampling error? Ecosphere 9: e02100. https://doi.org/10.1002/ecs2.2100 ). Quantitative approaches to functional and taxonomic diversity such as the Rao coefficient and the Simpson index have been applied (Botta-Dukát 2005Botta-Dukát Z. 2005. Rao’s quadratic entropy as a measure of functional diversity based on multiple traits. J. Veg. Sci. 16: 533-540. https://doi.org/10.1111/j.1654-1103.2005.tb02393.x ). Other strategies measure functional diversity by functional richness and evenness (Goswami et al. 2017Goswami M., Bhattacharyya P., Mukherjee I., Tribedi P. 2017. Functional diversity: an important measure of ecosystem functioning. Adv. Microbiol. 7: 82-93. https://doi.org/10.4236/aim.2017.71007 ). Margalef actively contributed to the development of novel diversity indices: the Margalef index (d) includes abundance in the determination of diversity (Margalef 1951Margalef R. 1951. Diversidad de especies en les communidades naturales. Publ. Inst. Biol. Apl. Barcelona 6: 59-72.), while the Shannon index (H′) accounts for evenness plus richness (Margalef 1957Margalef R. 1957. La teoría de la información en Ecología. Mem. Real Acad. Cien. Art. Barcelona 32: 373-436. http://hdl.handle.net/10261/165554 , Moseman et al. 2009 Moseman S.M., Zhang R., Qian P.Y., Levin L.A. 2009. Diversity and functional responses of nitrogen-fixing microbes to three wetland invasions. Biol. Invasions 11: 225-239. https://doi.org/10.1007/s10530-008-9227-0 ; Table 1).
|Rao coefficient||HD (p)||Quadratic entropy||Rao (1982)Rao C.R. 1982. Diversity and dissimilarity coefficients: a unified approach. Theor. Pop. Biol. 21: 24-43. https://doi.org/10.1016/0040-5809(82)90004-1|
|Simpson index||D||Species diversity||Simpson (1949)Simpson E.H. 1949. Measurement of diversity. Nature 163: 688. https://doi.org/10.1038/163688a0|
|Evenness index||J’||Species evenness||Pielou (1966)Pielou, E. C. 1966. The measurement of diversity in different types of biological collections. J. Theor. Biol. 13: 131-144. https://doi.org/10.1016/0022-5193(66)90013-0|
|Shannon index||H’||Species entropy||Shannon and Weaver (1949)Shannon C.E., Weaver W. 1949. The mathematical theory of communication. The University of Illinois Press, Urbana.|
|Margalef index||d||Species richness||Margalef (1951)Margalef R. 1951. Diversidad de especies en les communidades naturales. Publ. Inst. Biol. Apl. Barcelona 6: 59-72.|
Each method that analyses diversity has limitations and biases. Several analysis pipelines are available for a set of high throughput sequencing data (used to easily calculate diversity; Pylro et al. 2014Pylro V.S., Roesch L.F.W., Morais D.K., et al. 2014. Data analysis for 16S microbial profiling from different benchtop sequencing platforms. J. Microbiol. Meth. 107: 30-37. https://doi.org/10.1016/j.mimet.2014.08.018 ). However, the limitations and biases start from the very beginning, including sampling (agreement on sampling protocols between laboratories must be reached; Prosser 2010Prosser J.I. 2010.Replicate or lie. Env. Microbiol. 12: 1806-1810. https://doi.org/10.1111/j.1462-2920.2010.02201.x ) DNA/RNA extraction, PCR/primer bias, sequencing artefacts of cutoff for defining operational taxonomic units, development of consistent reference databases, and choice of including or excluding singletons/doubletons (operational taxonomic units that occur only once or twice, respectively, in each dataset). (Goodrich et al. 2014Goodrich J.K., Waters J.L., Poole A.C., et al. 2014. Human genetics shape the gut microbiome. Cell 159: 789-799. https://doi.org/10.1016/j.cell.2014.09.053 ). Furthermore, many studies have focused on a single sampling point, leaving out spatio-temporal variability. Transects, temporal series and diversity patterns at different scales should become the norm (Jones et al. 2012Jones S.J., Southward A.J., Wethey D.S. 2012. Climate change and historical biogeography of the barnacle. Global Ecol. Biogeogr. 21: 716-724. https://doi.org/10.1111/j.1466-8238.2011.00721.x ). As the technique applied to analyse samples depends strongly on the question posed by the microbial ecologist, there is a need for good working protocols regarding the wide ranges of techniques to determine microbial diversity (PCR-based 16S/8S studies, metagenomics, etc.), accompanied by data analysis and publication of the raw data. A common bioinformatics pipeline is also needed to compare results from multiple studies because pipelines have an inherent bias, and using distinct pipelines delivers different results (Logares et al. 2012Logares R., Haverkamp T.H.A., Kumar S., et al. 2012. Environmental microbiology through the lens of high-throughput DNA sequencing: Synopsis of current platforms and bioinformatics approaches. J. Microbiol. Met. 91: 106-113. https://doi.org/10.1016/j.mimet.2012.07.017 ). As computers provide a completely controlled environment, implementing a common pipeline with low biases should be easier than implementing a universal molecular laboratory protocol. Although biases and limitations cannot be eliminated, a strong effort to take them into account and thus analyse datasets carefully is essential. The correct choice of diversity index is an important issue. Many indices have been proposed to estimate biodiversity (Goswami et al. 2017Goswami M., Bhattacharyya P., Mukherjee I., Tribedi P. 2017. Functional diversity: an important measure of ecosystem functioning. Adv. Microbiol. 7: 82-93. https://doi.org/10.4236/aim.2017.71007 ), but there is no consensus on which is most appropriate and informative in each context (Morris et al. 2014Morris E.K., Caruso T., Buscot F., et al. 2014. Choosing and using diversity indices: Insights for ecological applications from the German Biodiversity Exploratories. Ecol. Evol. 4: 3514-3524. https://doi.org/10.1002/ece3.1155 ). Margalef’s attitude and legacy can help solve this conundrum: by constantly investigating links between different scientific disciplines, he suggested that only a careful mathematical interpretation of a given formula assures a correct ecological interpretation. From this perspective, an index should be chosen based on what it truly measures (e.g. for testing specific hypotheses), acknowledging the different facets of biodiversity (and that most indices are not simply interchangeable).
The microbial community composition plays a crucial role in the health (functionality) of an ecosystem (Astudillo-García et al. 2019Astudillo-García C., Hermans S.M., Stevenson B., Buckley H.L., Lear G. 2019. Microbial assemblages and bioindicators as proxies for ecosystem health status: potential and limitations. Appl. Microbiol. Biot. 103: 6407-6421. https://doi.org/10.1007/s00253-019-09963-0 ). A decrease in species richness (the number of species inhabiting a particular niche) and evenness (how evenly the species are distributed) might have a negative impact on the ecosystem’s productivity and stability, resulting in overall decreased functionality (Goswami et al. 2017Goswami M., Bhattacharyya P., Mukherjee I., Tribedi P. 2017. Functional diversity: an important measure of ecosystem functioning. Adv. Microbiol. 7: 82-93. https://doi.org/10.4236/aim.2017.71007 ). Therefore, assessing the phylogenetic and functional diversity of microbial communities allows a more precise and efficient way of describing an ecosystem. The recognition of functional groups of species helps to understand functional diversity. Also, community diversity can be explained hierarchically, by describing the diversity of functional groups using methods such as cluster analysis for functional traits (Lepš 2005Lepš J. 2005. Diversity and ecosystem function. Veg. Ecol. 199-237. https://doi.org/10.1023/A:1008867931773 ). The significant effects of functional diversity on the productivity and functioning of an ecosystem can be quantitatively explained by the sampling effect model and the niche differentiation model (Goswami et al. 2017Goswami M., Bhattacharyya P., Mukherjee I., Tribedi P. 2017. Functional diversity: an important measure of ecosystem functioning. Adv. Microbiol. 7: 82-93. https://doi.org/10.4236/aim.2017.71007 ). A sampling effect suggests that the increase in diversity of an ecosystem increases the probability that it harbours competitive species, thus making it more productive “by change”. By contrast, the niche differentiation model assumes that habitats are spatiotemporally heterogeneous and occupied by species with different traits that allow them to compete for resources, be productive and thrive in the prevailing conditions. Likewise, niche complementarity and species redundancy can be explained using functional traits, which underlie the mechanisms by which diversity affects ecosystem functioning (Goswami et al. 2017Goswami M., Bhattacharyya P., Mukherjee I., Tribedi P. 2017. Functional diversity: an important measure of ecosystem functioning. Adv. Microbiol. 7: 82-93. https://doi.org/10.4236/aim.2017.71007 ). The rivets and idiosyncratic models relate functional diversity and species richness to ecosystem functioning. The rivet model suggests that the ecological function of different species sharing the same niche space overlaps (Ehrlich and Ehrlich. 1981Ehrlich P.R., Ehrlich A.H. 1981. Extinction: the causes and consequences of the disappearance of species. New York: Random House.), while the idiosyncratic model suggests that the ecological function of a particular niche varies proportionately with an increase in species richness (Lawton 1994Lawton J. H. 1994. What do species do in ecosystems? Oikos 71: 367. https://doi.org/10.2307/3545824 ).
Margalef suggested that microbial diversity is expansive and dynamic. He proposed that “the real structure of an ecosystem is a property that remains out of reach.” (Margalef 1963Margalef R. 1963. On certain unifying principles in ecology. Amer. Nat. 97(897): 357-374. https://doi.org/10.1086/282286 ). In other words, diversity is not a question that can be addressed by a single observation. According to Margalef, continuous monitoring is needed to understand the diversity of dynamic and complex microbial ecosystems, which is indeed the way microbial ecologists are operating nowadays (Mestre et al. 2020Mestre M., Höfer J., Sala M.M., Gasol J.M. 2020. Seasonal variation of bacterial diversity along the marine particulate matter continuum. Front. Microbiol. 11: 1590. https://doi.org/10.3389/fmicb.2020.01590 ). For example, remote sensing has been proposed as a promising technology for the continuous and high-frequency monitoring of biodiversity and ecosystem functions at large spatial scales (Pettorelli et al. 2018Pettorelli N., Schulte to Bühne H., Tulloch A., et al. 2018. Satellite remote sensing of ecosystem functions: opportunities, challenges and way forward. Remote Sens. Ecol. Cons. 4: 71-93. https://doi.org/10.1002/rse2.59 ). Also, automated and continuous monitoring of phytoplankton communities through in situ scanning-flow cytometry increases our ability to predict future changes in biodiversity and the functions it sustains (Thomas et al. 2018Thomas M.K., Fontana S., Reyes M., Kehoe M., Pomati F. 2018. The predictability of a lake phytoplankton community, over time-scales of hours to years. Ecol. Lett. 21: 619-628. https://doi.org/10.1111/ele.12927 ).
Until the last decade, methodological constraints such as the inadequacies of conventional microscopy and cultivation-dependent techniques limited progress in the field (Jing et al. 2013Jing H., Xia X., Suzuki K., Liu H. 2013.Vertical profiles of bacteria in the tropical and subarctic oceans revealed by pyrosequencing. PLoS ONE 8: e79423. https://doi.org/10.1371/journal.pone.0079423 ). However, the advent of molecular techniques, particularly ‘next-generation sequencing’, has increased our understanding of microbial communities (Heidelberg et al. 2010Heidelberg K.B., O’Neil K.L., Bythell J.C., Sebens K.P. 2010. Vertical distribution and diel patterns of zooplankton abundance and biomass at Conch Reef, Florida Keys (USA). J. Plankton Res. 32(1): 75-91. https://doi.org/10.1093/plankt/fbp101 ; Sánchez-Quinto and Falcon 2019Sánchez-Quinto A., Falcón L.I. 2019. Metagenome of Acropora palmata coral rubble: Potential metabolic pathways and diversity in the reef ecosystem. PLoS ONE 14: e0220117. https://doi.org/10.1371/journal.pone.0220117 ), with current estimates of microbial diversity being at least 100 times greater than previously thought (Vitorino and Bessa 2018Vitorino L.C., Bessa L.A. 2018. Microbial diversity: the gap between the estimated and the known. Diversity 10: 46. https://doi.org/10.3390/d10020046 ). Nevertheless, in line with Margalef’s intuition, microbial ecologists report that, even with modern tools and techniques, it is not easy to identify true microbial diversity and mapping of variations in community structure in space and time in the complex and highly dynamic marine environment (Biller et al. 2018Biller S.J., Berube P.M., Dooley K., et al. 2018. Data descriptor: Marine microbial metagenomes sampled across space and time. Sci. Data 5: 180176. https://doi.org/10.1038/sdata.2018.176 ). Some investigations indicate that the extent-and therefore the functional potential-of marine microbial biodiversity are limitless and seem to grow greater as new techniques emerge to measure them (Heidelberg et al. 2010Heidelberg K.B., O’Neil K.L., Bythell J.C., Sebens K.P. 2010. Vertical distribution and diel patterns of zooplankton abundance and biomass at Conch Reef, Florida Keys (USA). J. Plankton Res. 32(1): 75-91. https://doi.org/10.1093/plankt/fbp101 ).
Margalef’s efforts to integrate micro- and macroscopic visions of ecosystems inspire how biogeochemistry should be studied in the era of discoveries in the microbial world. Margalef strived to integrate different fields of ecology (matter-energy-biodiversity) with a common quantitative currency, which is why he applied information theory and thermodynamics to ecology (Margalef 1957Margalef R. 1957. La teoría de la información en Ecología. Mem. Real Acad. Cien. Art. Barcelona 32: 373-436. http://hdl.handle.net/10261/165554 , 2000aMargalef R. 2000a. El marco ecológico para iluminar la sociedad actual. In: Naredo J.M. and Parra F. (eds), Economía, Ecología y Sostenibilidad en la sociedad actual. Siglo XXI, Madrid, pp. 51-66. ). Although he focused on the study of primary production─limiting nutrients rather than on biogeochemistry itself, Margalef honoured the holistic nature of the Vernadskian biosphere as an innovative planetary vision of life in which biogeochemistry plays a key connective role (Margalef 1992Margalef R. 1992. Oblik Biosfer (A View of the Biosphere). Moscow: Russian Academy of Sciences, Institute of Oceanology.). Therefore, it is highly likely that the possibility of linking microbial community structure with quantification of its contribution to biogeochemical cycling rates would have been of concern to Margalef, should he have had access to current microbial ecology discoveries and toolboxes.
Today, modern molecular techniques, namely omics, have clarified the role of microbes in some biogeochemical processes. The findings range from gene discovery to stoichio-genomics, including gene evolution over geological time and the mapping of genes, transcripts and proteins in the environment (Young et al. 2012Young J.N., Rickaby R.E.M., Kapralov M., Filatov D.A. 2012. Adaptive signals in algal Rubisco reveal a history of ancient atmospheric carbon dioxide. Philos. Trans. R. Soc. B 367: 483-492. https://doi.org/10.1098/rstb.2011.0145 ). Nevertheless, the inference of biogeochemical rates from omics/molecular datasets remains a challenge. Simultaneous measurements and correlations between functional gene expression and biogeochemical rates have offered unconnected results suggesting that different regulation mechanisms operate at protein and cell levels (Hultman et al. 2015Hultman J., Waldrop M.P., Mackelprang R., et al. 2015. Multi-omics of permafrost, active layer, and thermokarst bog soil microbiomes. Nature. 521: 208-212. https://doi.org/10.1038/nature14238 ). Consequently, it is crucial to pay attention to single-cell processes. These are one of the missing links between the three steps of the central dogma of molecular biology, namely replication, transcription and translation (from DNA to RNA to protein), assessed by omics, and the actual effect of microbes on biogeochemical rates.
In this context, the phosphorus (P) cycle is one of the most important and probably deserves as much attention in the ocean as it has been paid in freshwaters (Margalef 1998Margalef R. 1998. Elements limitants, explotabilitat i diversitat. Homenatge a Bolòs i al fòsfor. Acta Bot. Barcino. 45: 633-643. Retrieved from. https://raco.cat/index.php/ActaBotanica/article/view/59590 , Letscher and Moore 2015Letscher R.T., Moore J.K. 2015. Preferential remineralization of dissolved organic phosphorus and non-Redfield DOM dynamics in the global ocean: Impacts on marine productivity, nitrogen fixation, and carbon export. Global Biogeochem. Cy. 29: 325-340. https://doi.org/10.1002/2014GB004904 ). The crucial steps of this cycle include interactions with chemical species (e.g. aluminium) and with living beings, in which phosphatases play a key role in the utilization of dissolved organic phosphorus and polyphosphate. Margalef’s foundational experiments and assumptions about the role of microorganisms (i.e. plankters) in the regeneration of phosphate by phosphatases (Margalef 1950Margalef R. 1950. Rôle des entomostracés dans la régéneration des phosphates, internationale vereinigung für theoretische und angewandte. Limnologie: Verhandlungen. 11: 246-247. https://doi.org/10.1080/03680770.1950.11895232 ) have been confirmed, expanded and detailed over time (see Boavida 2012Boavida M.J. 2012. It all started with Margalef’s paper of 1951. Limnetica 31: 187-192.). In the framework of microbial enzymatic activities (i.e. phosphatases) contributing to phosphorus cycling, recent advances include (i) the discovery of diverse pH-dependent metallo-phosphatase isoenzymes in prokaryotic and micro-eukaryotic plankton genomes (Sebastian and Ammerman 2009Sebastian M., Ammerman J.W. 2009. The alkaline phosphatase PhoX is more widely distributed in marine bacteria than the classical PhoA. ISME J. 3: 563-572. https://doi.org/10.1038/ismej.2009.10 ), (ii) the development and use of single-cell fluorescent substrates in environmental plankton samples (Polaske et al. 2016Polaske N.W., Kelly B.D., Ashworth-Sharpe J., Bieniarz C. 2016. Quinone methide signal amplification: covalent reporter labeling of cancer epitopes using alkaline phosphatase substrates. Bioconjug. Chem. 27: 660-666. https://doi.org/10.1021/acs.bioconjchem.5b00652 ), (iii) new strategies of analytical determination that address a large diversity of P-substrates in the environment, and (iv) the development of mathematical models for phosphatase activity in microalgae (Ghyoot et al. 2015Ghyoot C., Gypens N., Flynn K.J., Lancelot C. 2015. Modelling alkaline phosphatase activity in microalgae under orthophosphate limitation: the case of Phaeocystis globosa. J. Plankton Res. 37: 869-855. https://doi.org/10.1093/plankt/fbv062 ). This multifaceted approach has helped understand why the results of enzymatic activity (i.e. ecological function) can be poorly correlated with any of the omics approaches (gene presence, gene expression and protein presence). The reason is that fine modulation of the enzyme activity is due, for example, to isoenzyme gene diversity, the dependence of different isoenzymes on temperature, substrate concentration (i.e. kinetic properties) and metallic cofactors, microbe-specific metabolic responses (such as lipid remodelling), and the physiological status of different individuals in a population (Valdespino-Castillo et al. 2014Valdespino-Castillo P.M., Alcántara-Hernández R.J., Alcocer J., et al. 2014. Alkaline phosphatases in microbialites and bacterioplankton from Alchichica soda lake, Mexico. FEMS Microbiol. Ecol. 90: 504-519. https://doi.org/10.1111/1574-6941.12411 ). Furthermore, phosphatase research is paving the path to understanding other microbial enzyme classes that play a role in the phosphorus cycle (phosphonate esterases, phosphodiesterases and phytases, e.g. Dyhrman et al. 2007Dyhrman S.T., Ammerman J.W., Van Mooy B.A.S. 2007. Microbes and the marine phosphorus cycle. Oceanography 20: 110-116. https://doi.org/10.5670/oceanog.2007.54 ) and, by extension, to all the important cycles (e.g. carbon, nitrogen and silicon). Experimental designs on microfluidic platforms and analytical tools for assessing the intracellular chemical composition (atomic force microscopy, chemical imaging, etc.) might also help parameterize the mathematical models. Like the Margalef Mandala, therefore, a multifaceted approach is required to investigate the role of microbes in linking the biogeochemical cycles through the study of omics.
Global changes in the natural environments were not new to Margalef. The biosphere as a whole entity was discussed by Margalef in his book Our Biosphere (1997Margalef R. 1997. Our biosphere. In: O. Kinne (ed.), Excellence in Ecology, 10. Ecology Institute, Oldendrof/Luhe, 176 pp.), in which he introduced new theoretical concepts of organization of ecosystems, ranging from stratification of marine plankton to global regulation, that were extraordinarily advanced for the ecology of the time. Indeed, the idea contained in the Margalef Mandala of relating the composition of phytoplankton to specific parameters of the water column could help us to predict future changes in marine microbial community composition, especially regarding recent global changes in ocean biogeochemistry, such as warming, acidification, deoxygenation and bio-invasions.
Currently, the oceans are experiencing rapid and unprecedented shifts in biogeochemical parameters as a result of global change. Anthropogenic activities are having impacts on atmospheric and oceanic carbon dioxide (CO2), nutrient pollution and the introduction of non-native organisms, which are critical issues for world oceans and ecosystems in general. For instance, atmospheric CO2 is rising to unprecedented levels (+415 ppm in 2020; Dlugokencky and Tans 2020Dlugokencky E., Tans P. 2020. Global Monitoring Laboratory-Carbon Cycle Greenhouse Gases. Retrieved July 6, 2020, from www.esrl.noaa.gov/gmd/ccgg/trends.), leading to direct and indirect effects on marine organisms (Borrero-Santiago et al. 2016aBorrero-Santiago A.R., DelValls T.A., Riba I. 2016. Carbon Capture and Storage (CCS): Risk assessment focused on marine bacteria. Ecotoxicol. Environ. Saf. 131: 157-163. https://doi.org/10.1016/j.ecoenv.2016.04.020 ) that may modify succession and evolution. One of the consequences of the rising CO2 levels is the warming of marine waters, which favours stratification, reduces oxygen solubility and enhances respiration rates of marine organisms (Gruber 2011Gruber N. 2011. Warming up, turning sour, losing breath: ocean biogeochemistry under global change. Philos. Trans. R. Soc. A 369: 1980-1996. https://doi.org/10.1098/rsta.2011.0003 ). Increased levels of CO2 dissolved in seawater lead to a reduction of carbonate availability and a lowering of pH, causing acidification stress (Gattuso et al. 2011Gattuso J.P., Hansson L. 2011. Ocean acidification: background and history. In: Ocean Acidification, Oxford Univ. Press, Inc. USA. https://doi.org/10.1093/oso/9780199591091.003.0006 ). Together with changing oceanic circulation, these factors might be responsible for the recent and future decreases in the ocean’s oxygen content and in the formation of oxygen minimum zones (OMZs), which are defined as water masses with dissolved oxygen concentrations declining by 0.09 to 0.34 µmol kg−1 y−1 (Levin 2018). The microbial degradation of organic matter, and subsequently the oceanic carbon pump, might be altered in OMZs, leading to a fall in N2 production by the microbial community and modifying chemical and biological gradients in the water column (Bertagnolli and Steward 2018Bertagnolli A.D., Stewart F.J. 2018. Microbial niches in marine oxygen minimum zones. Nat. Rev. Microbiol. 16: 723-729.https://doi.org/10.1038/s41579-018-0087-z ).
Human influence is not only related to changes driven by increasing CO2 in the atmosphere. The introduction of non-native organisms is currently a challenge in many parts of the oceans. These introductions or invasions may be accelerated by global environmental changes but are also being enhanced by direct anthropogenic drivers such as the transfer of ballast water and aquaculture (González-Ortegón and Moreno-Andrés 2021González-Ortegón E.; Moreno-Andrés J. 2021. Anthropogenic Modifications to Estuaries Facilitate the Invasion of Non-Native Species. Processes 9: 740. https://doi.org/10.3390/pr9050740 ). For these invasions to occur, microbes need to be transported from a source to a foreign environment, but invasions are also determined by competitive interactions. Specific examples of microbial transfer that have been reported include evidence of bacilli endospores dispersed over long distances by ocean currents and the spreading of toxic cyanobacteria (Fastner et al. 2007Fastner J., Rucker J., Stuken A., et al. 2007.Occurrence of the cyanobacterial toxin cylindrospermopsin in northeast Germany. Environ. Toxicol. 22: 26-32. https://doi.org/10.1002/tox.20230 ) as well as invasive protists (Wyatt and Carlton 2002Wyatt T., Carlton J.T. 2002. Phytoplankton introductions in European coastal waters: why are so few invasions reported? In: Briand F. (ed), Alien Marine Organisms Introduced by Ships in the Mediterranean and Black Seas - Commission Internationale pour l’Exploration Scientifique de la Mer Mediterranee. 20: 41-46.). Microbial invasions can be divided into four steps: (i) introduction, (ii) establishment, (iii) growth and spread, and (iv) impact (Levine et al. 2004Levine J.M., Adler P.B., Yelenik S.G. 2004. A meta-analysis of biotic resistance to exotic plant invasions. Ecol. Lett. 7: 975-989. https://doi.org/10.1111/j.1461-0248.2004.00657.x ). The ecological rules that drive microbial interactions within the community are decisive (Locey and Lennon 2016Locey K.J. Lennon J.T. 2016. Scaling laws predict global microbial diversity. Proc. Nat. Acad. Sci. USA 113: 5970-5975. https://doi.org/10.1073/pnas.1521291113 ). Additionally, anthropogenic perturbations induce instability in the ecosystem and may thus alter the potential for invasion (González-Ortegón and Moreno-Andrés 2021González-Ortegón E.; Moreno-Andrés J. 2021. Anthropogenic Modifications to Estuaries Facilitate the Invasion of Non-Native Species. Processes 9: 740. https://doi.org/10.3390/pr9050740 ). These aspects were mentioned by Margalef (Margalef 1963Margalef R. 1963. On certain unifying principles in ecology. Amer. Nat. 97(897): 357-374. https://doi.org/10.1086/282286 , 1975Margalef R. 1975. Diversity, stability and maturity in natural ecosystems. In: Unifying Concepts in Ecology. Springer, Netherlands, pp. 151-160. https://doi.org/10.1007/978-94-010-1954-5_12 ), who predicted the consequences of the use of natural resources by humans and highlighted its impacts.
Environmental microbiology and microbiome science have progressively implemented these conceptual developments, and several reports in the last few decades have explored microbial system diversity in relation to community, environmental or climatic stability to understand species invasions. Microbiome studies of species invasions provide a new dimension for understanding the mechanisms underlying these invasions. In addition to competition and synergistic relationships, which are hot topics of microbiome research, at least two other emergent properties of microbial systems seem to be important players with respect to microbial invasions: immediate or delayed responses of horizontal gene transfer (Emamalipour et al. 2020Emamalipour M., Seidi K., Vahed S. Z., et al. 2020. Horizontal gene transfer: from evolutionary flexibility to disease progression. Front. Cell Develop. Biol. 8. https://doi.org/10.3389/fcell.2020.00229 ) as a short-term exchange of genetic information; and pulse-coordinated responses, such as quorum sensing, as a regulation of gene expression according to microbial population. The latter has been found to be an important challenge in aquaculture (Fuente et al. 2015Fuente, M.d.L., Miranda, C.D., Jopia, P., et al. 2015. Growth inhibition of bacterial fish pathogens and quorum-sensing blocking by bacteria recovered from Chilean salmonid farms. J. Aquat. Anim. Health 27: 112-122. https://doi.org/10.1080/08997659.2014.1001534 ). Finally, the speed of ecosystem change is unquestionably another relevant element in the instability and adaptive responses of biological systems.
In addition to warming, acidification, deoxygenation and bio-invasions, the accumulation of plastic in the ocean is a major concern today. Plastic is currently the most common form of marine debris, and negative impacts of plastic pollution on the marine environment are documented at every level of biological organization, from molecules to ecosystems (Guo and Wang 2019Guo X., Wang J. 2019. The chemical behaviors of microplastics in marine environment: A review. Mar. Poll. Bull. 142: 1-14. https://doi.org/10.1016/j.marpolbul.2019.03.019 ). The microbial inhabitants of plastic marine debris termed “the plastisphere” (Amaral-Zettler et al. 2020Amaral-Zettler L.A., Zettler E.R., Mincer T.J. 2020. Ecology of the plastisphere. Nat. Rev. Microbiol.18: 139-151. https://doi.org/10.1038/s41579-019-0308-0 ) are an emerging source of genetic and metabolic diversity that may profoundly change our views of global marine matter and energy budgets.
Following Margalef’s approach to humanity as a part of natural ecosystems, we should include the changes brought about by anthropogenic impacts into the natural fluctuation of marine microorganisms. The generated matrix will help to predict changes in microbial distribution and functionality.
Ramon Margalef introduced innovative ideas in the study of ecology, particularly in microbial ecology, as discussed in this review. He considered that unifying ecological understanding was a prerequisite for going beyond speculative explanations of observed patterns in nature, and that quantifying differences in biological and ecosystem structures is fundamental to the understanding of the mechanisms underlying ecological processes.
It may seem surprising that concepts and ideas developed decades ago can improve the way we study microbial ecology today. Margalef did not have access to many of the techniques and data that are now available, but his thinking is instrumental in avoiding the risk of data dredging. There is an ongoing debate about the way science should be defined and conducted (e.g. “Defining the scientific method” 2009Defining the scientific method. 2009. Nat. Methods 6: 237. https://doi.org/10.1038/nmeth0409-237 ), with some researchers more inclined towards data-driven research and others towards hypothesis-driven research. Without pretending to resolve this debate, we argue that Margalef is a prime example of how a combination of both approaches, namely predicting patterns and inferring mechanisms, can be extremely effective in revealing ecological laws and rules (see also e.g. Fontana et al. 2021Fontana S., Rasmann S., de Bello F., et al. 2021. Reconciling trait-based perspectives along a trait-integration continuum. Ecology 102(10): e03472. https://doi.org/10.1002/ecy.3472 ).
Taking inspiration from Margalef’s teaching, we propose an integrated conceptual approach for microbial ecology (Fig. 1), which includes ecological theory, microbial diversity, biogeochemical cycles and global change. This new representation visualizes the interdisciplinary nature of microbial ecology as an intersection of related research fields. As an example, ecosystem structures are fundamental to the integration of information theory and diversity-related concepts into ecology (Margalef 1957Margalef R. 1957. La teoría de la información en Ecología. Mem. Real Acad. Cien. Art. Barcelona 32: 373-436. http://hdl.handle.net/10261/165554 , 1985Margalef R. 1985. Ecosystems: diversity and connectivity as measurable components of their complication. In: The Science & Praxis of Complexity. United Nations University (UNU), Tokyo, GLDB-2/UNUP-560.). As we have explained at length in this review, we believe improvements should be made particularly in three areas of ecological studies: sampling strategy, data analysis and ecological interpretation.
Considering Margalef’s view, microbial ecologists must have a clear perspective that improving a multidisciplinary approach between biologists, bioinformaticians, statisticians and oceanographers will be key to understanding microbial ecology as a whole. All variables and factors are directly and indirectly intercorrelated. They cannot be fully understood without considering all the others. Today, the scientific community needs to develop new concepts and an integrated vision of all disciplines in microbial ecology. To move forward, it might be necessary to look back: it is back to the future with Ramon Margalef!