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Where does facilitation fit in a framework for ecological theory?

Historically, ecological theory has been developed on the assumption that the most important processes structuring communities are overwhelmingly negative- namely competition, predation, and environmental stress. This week however, both papers we read argued that the role of positive species interactions has been severely underestimated. Facilitative interactions may play a key roll in increasing biodiversity and shaping communities.

The first paper explored the ways in which facilitation could be incorporated into the theoretical framework of modern ecology (Bruno, Stachowicz, & Bertness, 2003). We found their conclusion that facilitative interactions like habitat amelioration could result in a realized niche that is in fact larger than predicted by the fundamental niche to be particularly insightful. This is counter to the idea taught in most intro ecology courses that always depicts a shrunken realized niche relative to the fundamental niche. Our conversations led us to discuss the role of facilitative interactions in species invasions. Invasive species have been a growing source of concern for scientists and resource managers. Understanding how native species could facilitate invasives and contribute to the success of invaders could help us better predict invasion success.

These two papers complemented each other nicely. Where the first took a more theoretical approach, the second took a targeted approach to highlight how invaluable the role of facilitation may be in biodiversity experiments (Wright, Wardle, Callaway, & Gaxiola, 2017). They outlined three key mechanisms by which facilitative interactions could affect biodiversity and result in species specific overyielding. We focused our discussion on one of these mechanisms, the abiotic microclimate amelioration, which is the result of species reducing the effects of environmental stressors. These facilitative relationships are characteristic of many foundation species including mussels, corals and mangroves, that provide both structure and mitigate abiotic stressors (Jones, Lawton, & Shachak, 1994). Facilitations like these have been shown to be extremely important in harsh environments where heat stress, drought conditions or freezing temperatures may severely limit diversity. The implications of these facilitative interactions for diversity-productivity relationships suggest that incorporating facilitation into our framework could help us better predict outcomes for ecosystem stability.

Reading these papers this week feels like we’ve come full circle from where we started discussion biodiversity, niche theory, and competition. Developing new theories and frameworks that address the key role of facilitation will help advance ecological theory and generate valuable new ideas and understandings of the natural world. The real challenge is going to be changing how we teach the basics to reflect these changes to make sure that we move forward instead of getting stuck in the past.

  1. Bruno, J. F., Stachowicz, J. J., & Bertness, M. D. (2003). Inclusion of facilitation into ecological theory. Trends in Ecology and Evolution, 18(3), 119–125. https://doi.org/10.1016/S0169-5347(02)00045-9
  2. Jones, C. G., Lawton, J. H., & Shachak, M. (1994). Organisms as Ecosystem Engineers. Oikos. https://doi.org/10.2307/3545850
  3. Wright, A. J., Wardle, D. A., Callaway, R., & Gaxiola, A. (2017). The Overlooked Role of Facilitation in Biodiversity Experiments. Trends in Ecology and Evolution, 32(5), 383–390. https://doi.org/10.1016/j.tree.2017.02.011

Metrics to compare communities in space and time

To finish out the course, we selected two papers on the topic of diversity metrics. First was the 2005 paper by Chao et al., as well as the recent 2017 paper by Hillebrand et al. Both papers proposed improvements to more traditional diversity metrics like the Jaccard index through more comprehensive inclusion of either unseen species or species composition. I think strikingly, these two papers address very different audiences. Chao et al. published in Ecology Letters target ecologists who may adopt this new metric in their own scientific research. Hillebrand et al. rather utilize their new species diversity metric as a way to inform land and biological monitoring program managers on the nuances of stable local richness levels.

I think the adoption of the Chao’s statistical approach to beta diversity has largely been accepted (with >1000 citations). Yet by reading the paper, we began to understand the importance of choosing metrics that best test your questions. Especially with measures as contentious as beta diversity, being clear on the benefits and limitations of certain measures can lead to better selection of complementary metric choices (similar to model stacking). The primary goal of Chao et al. was to draw attention that almost all richness measures will be undersampled, comparisons between sites are rarely equal in sampling sizes, and species occurrence is uneven. The authors compare their revised metric (that incorporates both composition and abundance) to existing frameworks on empirical data and simulations of uneven and incomplete sampling. I think parasite systems fit nicely into datasets that the authors suggest for use of their updated metric.

In many ways the Hillebrand paper seemed to reference key themes we had discussed with island biogeography, though now comparable or connected sites are the islands with various immigration and emmigration rates. While their adoption of species composition as a main reason for mismatches between global and local biodiversity trends, I did not find their results particularly compelling. Also, they fail to fully reach into how the species composition of  local sites with stable species richness values may influence the function of these communities. I think by using available datasets that certainly have trait data such as biomass this would have been a simple calculation that could have really hammered home their point. I do think this paper forced me to gain a deeper understanding of immigration credit and extinction debt, and perhaps how quasi-equilibriums from island biogeography may be misleading as to the equilibrium of certain sites. I did appreciate the conceptual diagram given in Figure 1 that shows how both richness and evenness may change in a system, and then the use of their metrics on already established datasets. I’m not sure how much the Dutch phytoplankton added to the analysis, and would have perhaps wanted a more diverse dataset to complement the Iowa phytoplankton or grasslands example.

I think these papers may be best referenced when researching a specific problem with a dataset we are using or when designing a diversity study. I appreciate the recognition of imperfect data but using statistics to overcome imperfect data in logical and repeatable ways. Whenever explaining species richness and its importance, walking through the sampling and analysis approach iteratively, as well as showing alternatives through validated datasets or simulations, strengthens the interpretations and importance of richness measures. 

Chao A, Chazdon RL, Colwell RK, Shen TJ. A new statistical approach for assessing similarity of species composition with incidence and abundance data. Ecology letters. 2005 Feb;8(2):148-59.

Hillebrand H, Blasius B, Borer ET, Chase JM, Downing JA, Eriksson BK, Filstrup CT, Harpole WS, Hodapp D, Larsen S, Lewandowska AM. Biodiversity change is uncoupled from species richness trends: Consequences for conservation and monitoring. Journal of Applied Ecology. 2018 Jan;55(1):169-84

The continuing development of the theory of island biogeography

Focusing on the theme of island biogeography, we read an experimental paper by Simberloff & Wilson as well as a synthesis paper from Patiño et al. that came out of working group discussions at the 2016 Island Biology Conference. Together, these two works span the wide breadth of topics foundational to island biogeography including dispersal dynamics, colonization patterns, and extinction rates. As my research may deal with thinking of patch dynamics between different habitats of various resources, clarification of island biogeography theory and its translatable application to non-island systems such as fragmented landscapes will be important.

Simberloff & Wilson’s goal is to test theory put forth by McArthur & Wilson’s Monograph in Population in Biology series. By fumigating mangrove islands off the coast of Florida, the authors are able to observe colonization and competition dynamics in action, until the islands reach equilibrium arthropod species richness levels. I was particularly impressed with the speed in which this equilibrium was reached, in less than a year. I think this may be in some ways do the methodology of the eradication, as resources and habitat were maintained unlike many natural experiments of island colonization after volcanic eruptions. However, this method may be appropriate for more targeted disturbances such as an invasive species or an epidemic that wipes out the arthropod community. With large scale manipulative projects like this, it seems inevitable that sampling and replication are issues. Across the six islands, the authors were not able to support that distance from the faunal source was indicative of time to equilibrium, despite clear distance patterns pre-defaunation on species compositions of islands. While species richness equilibriums were achieved, population abundances were not comparable to pre-defaunation. I think this exemplifies the more recent term of “immigration credit”, where colonizers can be counted for richness values before they are functionally fixed.

Patiño et al. ask 50 new questions from the context of island biogeography to drive future work. This genre of a “horizon scan” is an appealing synthesis piece that acts as a concrete product from conference discussions. To coordinate pre-conference surveys, during conference discussions, and post-conference editing certainly was a challenge, yet this paper exemplifies a model the type of planning necessary to optimize conference-based collaborations. I think in contrast to the methods used in the paper that spurred this reading group (Courchamp and Bradshaw 2018), this process seemed more iterative and with strategic inclusion of multiple perspectives. I also appreciated the ten questions that are heavily related to how island biogeography theory can inform conservation and management policies. This field seems to especially be influenced by cross-disciplines such as genetics, paleobiology, climatology and geology. I think similar to other areas of ecology, island biology studies will move to an increasingly ecosystem-level and function studies of multiple trophic level interactions, community dynamics, and global change.

Simberloff DS, Wilson EO. (1969) Experimental zoogeography of islands: the colonization of empty islands. Ecology 50, 278–296.

Patiño J, Whittaker RJ, Borges PA, Fernández‐Palacios JM, Ah‐Peng C, Araújo MB, Ávila SP, Cardoso P, Cornuault J, de Boer EJ, de Nascimento L. (2017) A roadmap for island biology: 50 fundamental questions after 50 years of The Theory of Island Biogeography. Journal of Biogeography 44(5):963-83.

Food Webs: A relic of the past or a tool for the future?

The two papers we picked this week related to food web structuring and the ways we explore complex communities. We delved into our discussions of food web dynamics starting with the classic paper on food webs in Rocky intertidal systems (Paine, 1966). This paper is often credited with demonstrating the ideas of keystone predators, based on the removal experiment of Pisaster sea stars which led to a decline in species diversity.  Though this “classic” paper is often recommended reading for new ecologists, we found the concepts and ideas surprisingly underwhelming. Maybe it’s just knowledge we take for granted now that the field of ecology has progressed beyond describing who eats who.

We moved on to discuss a modern approach to mapping food web dynamics (Kéfi et al., 2015). This paper used an interaction network to assess trophic as well as non-trophic links in a food web. This type of network approach relies on a detailed understanding of all of the species interactions including competition and facilitation in addition to predation. Building this network requires in depth knowledge of the system but can highlight key areas of important interactions. For example, by including non-trophic interactions, Kefi et al demonstrated the importance of competition at basal trophic levels.

As a side note, while exploring some of the background on the Kefi et al. paper, we noticed that they went one step further by making an interactive online version of their network that can be found on the Chilean Ecological Network website (http://app.mappr.io/play/chile-marine-intertidal-network). This allows others to manipulate the web and visualize the different sets of interactions. I admit I probably spent 20 minutes just messing with the online app and getting a feel for the different species involved in different types of interactions. I found this online interactive web to be a great example of engaging and informative data visualization that supports their research.

While reading both of these papers, however, I was struck by the ways in which both were focused on direct species interactions through predation, competition, etc. and the distinct lack indirect interactions which may be just as important for structuring communities (Peacor & Werner, 2001).

Lastly, I’ve been reminded time and time again this semester that the major flaw with using food webs to understand a system is that they often exclude vital feedbacks with ecosystem processes. Food webs often ignore detrital pathways entirely and gloss over the vital role of decomposers in nutrient recycling.  To that end, I would argue that the contributions of the Paine and Kefi papers are valuable for understanding the basic species interaction structure but a broader approach to food web ecology that expands on non-trophic and indirect interactions and incorporates an ecosystem perspective is vital to progress in this field.

  1. Kéfi, S., Berlow, E. L., Wieters, E. A., Joppa, L. N., Wood, S. A., Brose, U., & Navarrete, S. A. (2015). Network structure beyond food webs : mapping non-trophic and trophic interactions on Chilean rocky shores. Ecology, 96(1), 291–303.
  2. Paine, R. T. (1966). Food Web Complexity and Species Diversity. The American Naturalist, 100(910), 65–75. https://doi.org/10.1086/282400
  3. Peacor, S. D., & Werner, E. E. (2001). The contribution of trait-mediated indirect effects to the net effects of a predator. Proceedings of the National Academy of Sciences, 98(7), 3904–3908. https://doi.org/10.1073/pnas.071061998

How to study incremental and pervasive human impacts

The two papers presented this week were a poor pairing to address the topic of anthropogenic change. We had selected this theme in the context of global change and the ‘age of the Anthropocene’ – a time of unique human impact from urbanization, deforestation, agricultural intensification, and increased carbon emissions. The papers we selected did not directly measure or experiment these human-driven changes, instead only reviewing human impact studied in a separate paper or touching on deforestation/pesticide use tangentially. Further, both views exhibited a static before and after of human impact, rather than a more appropriate incremental shift of anthropogenic drivers.

Alessa & Chapin is an Update article in TREE that is basically a positive response to a conceptual review published in Frontiers in the same year by Ellis and Ramankutty, a paper now with over 1000 citations. Not only were we dissatisfied with this brief overview, but we found the land classifications incomplete due to the omission of marine systems. With global classification systems, as in Figure 1, I struggle to discern what is most important as a viewer and reader of the paper, rather than a user of spatial data. Certainly, the fine scale detail is necessary when inputting this layer into a future model to select sites, project a species’ habitat, or estimate nutrient cycling. As a figure in a paper, however, I argue that the authors would do better to focus on certain important regions of human impact, or to dilute their classification system to a smaller amount of bins (<= 7 to abide by color theory). We were unclear on the function of this type of work, though hypothesized that one or both of the authors had acted as a peer reviewer for the Ellis and Ramankutty paper.

Our historical paper, Likens et al. 1970  is a monumental study on how removing a component from an ecosystem can have consequences on nutrient flow. Their experiment, however, was not modeled after a standing logging practice. Instead, this study was an ecosystem science study rather than an explicit look at anthropogenic change. They provide an extensive look at all the ecosystem processes that can change due to a component in the nutrient cycle being disrupted, from specific elemental levels to hydrological function.

Recognizing these two papers did not complement each other nor excite us while reading, I think the best use of this blog post is to recommend a new pairing of papers that could be used in a future semester. For a current paper, I think Borer et al. 2017 in Nature Ecology & Evolution provides a cumulative approach to studying human impacts, specifically increased nutrient inputs, through comparative, observational, and experimental work. Not only is this paper does this work showcase the global, coordinated work of Nutrient Net, but it’s lead author, Elizabeth Borer, is a leading female ecologist in current ecosystems and disease ecology research.  For a classic work on ecological consequences of human impacts, I suggest Michael Soulé’s paper from 1985, “What Is Conservation Biology?”. In complement to the Borer et al., this work proposes a synthetic, multidisciplinary framework to study conservation biology and sets the stage for work documenting the “Anthropocene”.

References:

Alessa L, Chapin III FS. (2008). Anthropogenic biomes: a key contribution to earth-system science. Trends in Ecology & Evolution 23(10):529-31.

Borer ET, Grace JB, Harpole WS, MacDougall AS, & Seabloom EW. (2017). A decade of insights into grassland ecosystem responses to global environmental change. Nature Ecology & Evolution, 1(5), 0118.

Ellis EC, Ramankutty N. (2008), Putting people in the map: anthropogenic biomes of the world. Frontiers in Ecology and the Environment 6:439-447.

Likens GE, Bormann FR, Johnson NM, Fisher DW, Pierce RS. (1970). Effects of forest cutting and herbicide treatment on nutrient budgets in the Hubbard Brook watershed- ecosystem. Ecological Monographs 40, 23–47.

Soulé, M. E. (1985). What is conservation biology?. BioScience, 35(11), 727-734.

The dual axes of host-parasite systems

This week we read two disease ecology papers both in Nature: the classic Anderson & May (1979) paper that introduces the compartmental model foundational to most parasite population theory and a review from Keesing et al. (2010) on the multiple impacts biodiversity can have on infectious diseases, a continually debated topic in the study of emerging infectious diseases. Comparing the two papers was difficult. These works are different styles of articles (though both listed as reviews), written about two different scales, with different directionality of effects between hosts and parasites. Anderson & May focus on parasite trait affects on a single host species population through a modeling approach, while Keesing synthesized some case studies on host community traits that affect parasite populations. Inevitably disease ecology studies involve multiple species, which adds complexity to their dynamics. Taking perspectives from both reviews will allow us to apply to address the multiple different axes at play in host-parasite systems.

After working on disease ecology projects and in the midst of ECOL6150 Population Biology of Infectious Diseases, reading through Anderson & May’s work was particularly exciting. Most intriguing was their original use of standard variables, XYZ, (see Figure 3) rather than the now ubiquitous S-I-R compartmental model. I think Anderson & May allow simple adjustments to build to more complicated mathematical models, providing an interpretable framework to approach any population dynamics question. I appreciate that they isolate one variable, the number of hosts, and address this as dynamic in the context of parasite transmission factors. This trend has extended into other variables of focus in my labs, for instance, how the degree of provisioning or animal movement can also be dynamically scaled. Further, Anderson & May provided convincing evidence through their multipronged use of experimental, modeling, and comparative analysis. Lastly, I thought it was particularly intriguing to think about their point of modern vs. non-industrialized societies, in which infectious agents that are more epidemic wouldn’t survive due to low influx of susceptibles. Typically I think of infectious pathogens as more of undeveloped world issue, yet this view may emphasize intermediate levels of developement where there are large populations but poor public health access, as opposed to undeveloped and isolated communities. 

Unique to Keesing et al. is the authors’ motivation to influence policy, as evidenced by a current events-based opener rather than a scientific thesis. The authors elaborate on known issues regarding linkages between biodiversity and ecosystem services to include currently unknown consequences on the emergence and transmission of infectious diseases. While we agreed with the authors on many points, much of our discussion focused on the inadequate figures to argue the author’s points. In particular, Figure 1 and 2 suffer from poor data visualization techniques: awkward scaling, using non-interpretable colors and pie graphs. We discussed how the small sliver of green/yellow contrast on Fig. 1 did not hit home the main goal of this case study: that host behavior drives host competence. We thought that this could have been better addressed through bar graphs comparing hosts in a more straight forward way. Similarly, Fig. 2 was also disappointing in that there was too much information. I wish they had further synthesized trends based on continent or GDP of country, as on a map many of the pie charts were lost. I do think this paper set the stage for the classic disease systems used in biodiversity case studies: lyme and hantavirus. We did appreciate that they broke down the underlying mechanisms on how biodiversity loss can increase transmission through either changes in host/vector abundance or behavior. Despite these issues in figures, I think the overarching goal of the article to shed light on the urgency to study biodiversity’s role on infectious disease was effective in motivating science in the 2010s. 

References:

Anderson RM, May RM. (1979) Population biology of infectious diseases: part I. Nature 280: 361–367.

Keesing F, Belden LK, Daszak P, Dobson A, Harvell CD, Holt RD, Hudson P, Jolles A, Jones KE, Mitchell CE, Myers SS. (2010) Impacts of biodiversity on the emergence and transmission of infectious diseases. Nature 468(7324): 647.

Niche Theory and the Empty Niche

This week we turned our discussion to the topic of ecological niches. That is, we discussed the variety of ways that a species’ ecological niche could be defined from its environmental tolerances, to the species interactions, to an n-dimensional hypervolume. We also discussed the concept of an “empty niche” and its role in speciation and invasion.

For our classic paper we read “Concluding Remarks” by G.E. Hutchinson,1 which he wrote to summarize the new ideas and thoughts from a recent Symposium on populations and demography. Hutchinson describes his quantitative approach to understanding niche theory, as pulling out the metaphorical vacuum cleaner to synthesize the “irrelevant litter” that has accumulated around niche theory. He starts by arguing that the applicability (or lack of) to human demography is not a reflection of a flaw in the theory, but instead demonstrates that we are not considering it on the right time scale or asking the right questions. He then uses an example of amphipods that don’t exist in seemingly suitable habitat to argue that the “suitable habitat” is based on our understanding and perception of the environment, which differs considerably from that of an amphipod species.  Our discussion of this long-winded paper ultimately led us to consider how variation in space/time can contribute significantly to the maintenance of species diversity.

We turned next to discuss the Sahney et al.2 and the concept of the empty niche contributing to the explosion of biodiversity with the expansion of species to terrestrial environments. Sahney used body size, diet and habitat to explore the potential modes of life that species could fill. The modes of life in some ways are similar to Hutchinson’s n-dimensional cube with 3 specific dimensions. In this case, Sahney argued that when species moved from sea to land there were countless niches waiting to be filled, which contributed to the rapid speciation and expansion of tetrapods. They also suggested that 64% of the terrestrial “modes of life” have yet to be filled and that tetrapod diversity may continue to increase as those modes are filled. While this suggestion will ultimately be difficult to verify, it seems plausible that empty niches may still play a vital role in understanding biodiversity.

Understanding the role of empty niche space can also help us better understand the vulnerability of systems to invasion. Recent anthropogenic disturbances to environments have led to major disruptions to ecosystems through both the extirpation of existing species and the introduction of novel players. These disruptions can lead to unexpected consequences like invader meltdown and community collapse. For that reason taking into account the amount of empty niche space in a habitat may help inform management decisions.

References:

  1. Hutchinson, G. E. Concluding Remarks. 117, 1937–1938 (1975).
  2. Sahney, S., Benton, M. J. & Ferry, P. A. Links between global taxonomic diversity , ecological diversity and the expansion of vertebrates on land. Biol. Lett. 6, 544–547 (2010).

Sessility: a model trait to study species interactions

For our week on competitive theory, we read two papers on the interactions between sessile (i.e. stationary, immobile) organisms. Almost 50 years apart, both Connell (1961) and Wulff (2008) utilize experimental manipulation in natural systems to assess species interactions. Competitive theory centers on similar species due to their diet, phylogenetic closeness or function fighting to utilize the same resource and can often lead to the exclusion of the less competitive species. Each of this week’s studies builds upon a profound amount of natural history to then test theory on which resource or phenomena may be lead sessile organisms to organize in space.

Connell explores the stark spatial segregation of two barnacle species, an upper resident Chthamalus stellatus and a lower resident Balanus balanoides along Scotland’s rocky intertidal shore. First, Connell removed barnacles to look at each single species along the full intertidal gradient. He found that  Chthamalus was able to survive in a much broader environmental area than observed (fundamental niche > realized niche). Balanus, the faster growing better crowd competitor, could not exist in upper bands of the zone due to environmental pressures (heat that led to desiccation). Interestingly, with the introduction of a predator or a parasite, these competitive interactions appeared to decrease.

Wulf’s study, however, observes collaborative interactions between sponges focusing on a poor competitor, Lissodendoryx colombiensis. Sponges uniquely form diverse assemblages that grow on top of each other, and seem to defy standard competitive theory. Wulf showed that crowding of sponges on and around Lissodendoryx deterred predation pressure from the starfish, Oreatus reticulatus.

A fascinating similarity between these two papers is they are both single-authored. Are there perceptions of a single-author? Does this show more initiative and independence of the scientist? Or does singularity in authorship show a lack of collaborative spirit, often necessary to link natural history and ecological mechanisms? Certainly both these projects took an immense amount of work beyond the author in data collection, processing and organization, and write-up. Yet, perhaps these tasks don’t seem to warrant authorship. I think this brings up a unique point about coordination vs. collaboration, and how lead authors may work with many, and yet be the sole driver of their research.

I was particularly struck, that not only is the Wulff paper single-authored, but the ten self-cited papers are single-authored as well. Standards of authorship operate differently among labs. For instance, dissertation work may be single-authored completely or be required to include the graduate advisors. In Dr. Wullf’s case, it seems to be the former, as her graduate students also produce single-authored work. I think this single-authorship, and perhaps the attitude behind it, maybe a component in how Dr. Wulff is so successful (R1 professor, Smithsonian fellow, and prolific publishing), despite the notorious leaky pipeline for women in her field.

References:

Connell, JH (1961). The influence of interspecific competition and other factors on the distribution of the barnacle Chthamalus stellatus. Ecology 42, 710–743 .

Wulff, JL (2008). Collaboration among sponge species increases sponge diversity and abundance in a seagrass meadow. Marine Ecology, 29(2):193-204.

Ecological Neutral Theory: From Concept to Tool

My first year of grad school has been a roller coaster. Developing my questions, taking classes, doing fieldwork, and so much reading. It has been a whirlwind learning about and discussing countless ecological theories, so I was really excited this week to read about one that admittedly has always confused me. Neutral theory is one of those “classic” theories that is taught in modern ecology classes and has always rubbed me the wrong way. The idea that there are no ecological differences between organisms or species seems like a non-starter, why would different species exist if all species were equal and the survival of a species was simply the result of stochastic processes?

To try to understand it, I went back and read some of Hubbell’s early papers on the topic including his work in Costa Rica and Tree Dispersal1 to try to understand why the concept of neutral theory seemed so at odds with my understanding of species interactions.  Of all of Hubbell’s papers, why was this one included on the penultimate list by Courchamp and Bradshaw? It was there in the very last paragraph that things started to make sense again.  Hubbell spends most of the paper discussing tree abundance and seed dispersal and how the tree community can be explained in simple terms by a stochastic model, but what caught my attention was the statement right at the end, so small I nearly missed it.

“Obviously this model is an oversimplified representation of the dynamics of natural communities, but it does provide a number of important lessons….”

There it was. Proof that even the author of the paper thinks neutral theory isn’t the full story. I turned next to a 2012 paper by Rosindell et al. that I hoped would hold all the answers. In The case for Ecological Neutral Theory2 the authors discuss some of the contentious debates surrounding neutral theory. They make a case that the concept of ‘neutral theory’ is not to treat all organisms as equal but to be used as a null model for comparison when species are not.  They point out that at some scales neutral theory may be the simplest explanation for the data, and it’s the job of the scientist to prove otherwise. Finally, a clear explanation for why Neutral theory is still relevant to modern ecology.

Perhaps, I missed the boat in my other ecology courses, but I can’t imagine presenting neutral theory in any other way but as a tool to be used. I’m left with more questions than answers about other “classic” theories and how they are taught in ecology courses, but at least on this topic I feel relatively satisfied.

The concluding thoughts of the Rosindell paper are a reminder to us all, that theories change and evolve, and we must recognize the limitations of our understanding.

References:

  1. Hubbell, S. P. Tree Dispersion, Abundance, and Diversity in a Tropical Dry Forest. Science (80-. ). 203, 1299–1309 (1979).
  2. Rosindell, J., Hubbell, S. P., He, F., Harmon, L. J. & Etienne, R. S. The case for ecological neutral theory. Trends Ecol. Evol. 27, 203–208 (2012).

Why is the World Green? Community Structuring from Species Interactions

The World is Green hypothesis, which stems from the classic work of Hairston, Smith and Slobodkin (1960), suggests that since herbivores are not limited by their food, they must instead be limited by their predators.  While this is often considered an oversimplification of the drivers of community structuring, this idea has served as a foundation of ecological research and theory for many years. The authors proposed that trophic levels alternate between bottom-up and top-down control, such that plants and carnivores are both limited by resources while herbivores are limited by carnivores. This idea suggests that species interactions play a vital role in determining not only which species will be found but also how many of each species a community can support.

In the years following the HSS hypothesis, many ecologists used targeted experiments to begin teasing apart the relative influence of biotic and abiotic variables in determining community structure. One such example is Lubchenco and Menge (1978) that sought to disentangle the relative importance of disturbance and predation in coastal rocky intertidal systems. Their research suggests that while environmental factors and disturbance can set a baseline for the community composition, species interactions, like predation and competition, also play a vital role in shaping community structure.

Recent research has supported the idea that species interactions are vital drivers of community structuring. A 2015 article (Lima-Mendez et al) took a modern approach to exploring community structuring. Using global data from the Tara Oceans project, they argued that species distributions could not be predicted from environmental factors alone and that biotic interactions play a large role in structuring communities. They constructed interaction networks for plankton species and used experimental methods to validate predicted interactions. Utilizing techniques from microbiology and systematics, the authors were able to demonstrate that the organization of ocean food webs can be predicted from patterns of species co-occurrence.

These three papers took three very different approaches to understanding community structuring (theory, experiments, survey and synthesis), but I found it compelling that all three argued for more than environmental conditions shaping communities and highlighted the primacy of species interactions.