Research

(For a very non-technical, jargon-free description of my research, look over here!)

IMG_9159As a scientist, I am fascinated by understanding how environmental variation affects the ecology, physiology, and evolution of different organisms. Environmental change is everywhere: as fundamental as the rising and setting of the sun and the turning of seasons. Variation in light, temperature, precipitation, and the abundance of food, predators, mutualists and parasites, create complex challenges for living organisms. I study how patterns of variation influence the physiological and behavioral adaptations of different species, which represent their ‘solutions’ to these challenges. Different suites of adaptations alter the competition and success of different species, ultimately influencing the diversity of communities and the function of ecosystems across a wide range of scales.

Most of my current projects involve phytoplankton, tiny photosynthetic organisms inhabiting lakes and oceans. I care deeply about advancing a strong, quantitative, and conceptually driven understanding of ecology: much of what I do focuses on developing and testing theories using a combination of large data sets, diverse statistical tools, mathematics, and targeted experiments. Finally, we humans have profound effects on the variability of the world we inhabit (both planned and unintentionally). A major component of my research right now involves studying the effects of anthropogenic climate change on plankton communities and marine ecosystems.

More specific summaries of my major projects follow:

  1. Effects of climate change on the ecology & evolution of plankton: linking physiology to global ecosystem function using Earth Systems Models.
  2. Local adaptation, trait-environment relationships, and the thermal biology of phytoplankton.
  3. Competition, coexistence, and evolution in fluctuating environments.
  4. Matters of size: cell size as a master trait in phytoplankton.
  5. Resource competition and N2-fixing cyanobacteria blooms.

 


 

1. Effects of climate change on the ecology & evolution of plankton: linking physiology to global ecosystem function using Earth Systems Models.

Over most of the world’s oceans, climate change is driving increases in ocean temperatures which will likely continue to rise over the coming century. Temperature has a critical effect on the growth rate of ecotherms, including phytoplankton and zooplankton.  Rising water temperatures may exceed the upper limits that resident plankton species can tolerate. In temperate and polar regions, other species adapted to warmer environments can replace these resident species. In tropical regions, however, there may be no extant species adapted to higher temperatures. Here, responses to climate change will be dictated by evolution, but critically, the form and rate of adaptation is largely unknown.

Working with Charles Stock, and my post-doc advisors David Vasseur and Jorge Sarmiento, I am using a marine ecosystem model (embedded within an Earth Systems Model that resolves ocean circulation, physics, and chemistry) to study the response of planktonic communities to climate change, given different evolutionary scenarios. Evolutionary rates often depend on body size and population abundance, properties that differ between trophic groups. As part of this work, we’re investigating what might happen if zooplankton and phytoplankton experience different levels of evolutionary constraint. These models allow us to connect the physiology of plankton (their thermal biology), with processes happening at the population level (evolution), to explore the fate of communities and critical marine ecosystems at a global scale.

novel envirs 31C

Over the next ~100 years, regions of the worlds oceans exceeding 31 C will increase (RCP 8.5 Scenario). These are regions where the functioning of current plankton populations may decline, without a rapid evolutionary response.

 

2. Local adaptation, trait-environment relationships, and the thermal biology of phytoplankton.

Diversity change

As a result of rising temperatures, species distributions will shift pole-wards, leading to altered patterns of diversity across the world’s oceans (Thomas et al. 2012).

Each phytoplankton species has an optimum temperature, where it can grow most quickly, and a range of temperatures over which it can grow at all (a temperature niche). In collaboration with Mridul Thomas, we have shown that the temperature traits of marine phytoplankton species are strongly related to the temperature environments where they were collected, from pole to pole. Additionally, using an eco-evolutionary model as a predictive tool, I found that these trait-environment relationships are consistent with patterns we would expect if species are locally adapted to their environment. Building on these conclusions, we showed how changing ocean temperatures will shift the fundamental distributions of these species, changing patterns of diversity globally.

In related work, we’ve found that these trait-environment patterns also occur in freshwater phytoplankton species, across similar global gradients. Interestingly, when viewed separately, major functional groups of phytoplankton (including cyanobacteria, diatoms, dinoflagellates, and green algae) have distinct trait-environment relationships, likely reflecting differences in their ecology and evolutionary constraints.

For more, see: Thomas et al. 2012, Thomas et al. 2015, Kremer et al. in prep.

 

3. Competition, coexistence, and evolution in fluctuating environments.

Fig8 copy

When evolution is slow, divergent selection leads to two coexisting species with different trait attractors (A, B); but rapid evolution leads to trait convergence, supporting only on species (Kremer & Klausmeier 2013).

Organisms inhabiting fluctuating environments face several challenges. Traits that make a species well suited to one set of conditions usually reduces its growth when conditions change. Evolution through selection can counteract these effects, allowing species to shift their traits (or strategies) for dealing with fluctuations in response to environmental change. Exploring the conditions leading to coexistence (given different kinds of fluctuations), I showed that rapid evolution can prevent multiple species from coexisting. The traits of coexisting species depend on the kind of fluctuations employed and details of tradeoffs in species’ abilities,

See: Kremer & Klausmeier 2013, or BEACON blog post.

 

4. Matters of size: cell size as a master trait in phytoplankton.

cell size distrib

Cyanobacteria have much smaller cells than other phytoplankton, but the colonies that they form can be just as large as single diatom or dinoflagellate cells!

Size definitely matters if you’re a phytoplankton cell. Size and shape together determine how successfully cells can compete for nutrients, how easily they sink, and how likely they are to get eaten. I am studying patterns of variation in cell size, both within and across species. I’m interested in answering questions such as: Are closely related species similar in size? Are there fundamental differences between major functional groups of phytoplankton? How does cell size relate to other important traits? Do species with small cells compensate by forming colonies?

For more, see: Kremer et al. 2014.

 

5. Resource competition and N2-fixing cyanobacteria blooms.

epa map

Back in the 1970s, the EPA conducted an amazing survey of lakes across the USA (red dots). With this data, we can tackle a lot of big questions about  the factors that influence the diversity and function of phytoplankton communities.

Under some conditions, Cyanobacteria can reach really high abundances in lakes, forming unsightly, smelly, and sometimes toxic blooms. One hypothesis explaining why and when blooms occur focuses on a unique ability some Cyanobacteria have: they can convert atmospheric Nitrogen into a biologically useful form. This might make them really good competitors in lakes when available nitrogen levels are very low, inhibiting the growth of other kinds of phytoplankton. I’m using a large observational data set of lakes from across the USA to test this hypothesis. I want to understand what conditions favor blooms of Cyanobacteria (N-fixing and non-fixing species). This work has required developing statistical methods to deal with zero-inflated and proportional data.

 

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