Together with collaborators of MIT, University of Washington and Old Dominion University, we have quantified timescales and length scales of decorrelation for a broad range of model phytoplankton species, functional traits, and body sizes. Our goal was to gain new insights about regional contributions of physical dispersal in shaping the phytoplankton community structure.
Spatial correlation scales of small phytoplankton (less or equal than 2 micrometers)
We used biomass anomalies from the long-term output of the MIT-gcm GUD, a complex plankton community model that replicates well global patterns of plankton diversity. We estimated decorrelation timescales from temporal autocorrelation functions and length scales from the correlations between each grid cell and adjacent waters at lag zero. In essence, we asked: 1. How long does it take for perturbations in biomass to disappear? and 2. Over what distance do populations vary in concert?
Biological nitrogen fixation refers to the conversion of dinitrogen gas via reduction to ammonium into bioavailable forms of nitrogen by a specialized group of microbes containing the nitrogenase enzyme complex. Various types of autotrophic microbes are capable of fixating nitrogen in the marine environment, including free-living cyanobacteria, diatom-cyanobacterial associations and colonial forming Trichodesmium spp. Most recently, studies demonstrate that marine nitrogen fixation can be carried out without light by nitrogen-fixing heterotrophic bacteria. However, direct measurements of nitrogen fixation in aphotic environments are relatively scarce. Heterotrophic, as well as unicellular and colonial photoautotrophic diazotrophs, are present in the oligotrophic Gulf of Aqaba (northern Red Sea). In this project, we evaluated the relative importance of these different diazotrophs to determine phosphate and nitrate variability at this location.
Results of two model simulations that replicate nitrate observations (black circles) in the Gulf of Aqaba: a model without nitrogen fixation (gray) and a model with autotrophic and heterotrophic nitrogen fixers (red).
We show that a model without N2 fixation can replicate the observed surface chlorophyll but fails to accurately simulate inorganic nutrient concentrations throughout the water column. Models with N2 fixation improve simulated deep nitrate by enriching sinking organic matter in nitrogen, suggesting that N2 fixation is necessary to explain the observations. The observed vertical structure of nutrient ratios and oxygen is reproduced best with a model that includes heterotrophic, colonial and unicellular autotrophic diazotrophs (Kuhn et al., 2018).
The phytoplankton spring bloom is a massive growth marine micro-algae that occurs annually during the spring season in mid and high latitudes. The spring bloom plays an important role in feeding the marine ecosystems and determining the amount of carbon exported to the deep ocean. The onset of this event has been explained from bottom-up and top-down perspectives, with different key expectations about how seasonal fluctuations of the mixed layer affect the plankton community.
Sensitivity of phytoplankton to small changes in model variables using a Taylor decomposition method. Changes in the mixed layer depth (C) reorganize phytoplankton in the water column, but the integrated effect is negligible (black line in F). Changes in light (A, and yellow lines in F) and zooplankton (E, and blue lines in F) both have significant effects on phytoplankton prior to the spring bloom (Kuhn et al., 2015)
This project assessed whether the assumptions inherent to two contrasting hypotheses are met on a typical simple Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) ecosystem model. The model was optimized and used in idealized experiments and sensitivity analyses that isolated the effects of mixed layer fluctuations.
Our results showed that the conceptual bases of both bottom-up and top-down approaches are required to explain the process of blooming; however, neither of their bloom initiation mechanisms fully applies in the experiments.
The ocean’s temperature has multiple direct and indirect effects on marine organisms. Metabolic rates and mortality rates usually correlate well with temperature. While this correlation doesn’t imply causation, understanding the relationship between temperature and the abundance of organisms is key to predict their response under a changing climate.
The western Galapagos Archipelago comprises two islands: Isabela and Fernandina. Two distinct shallow water biological communities have been identified in these islands: the Elizabeth region in the Bolivar Channel and the western region elsewhere (Edgar et al, 2004). These distinct communities have different responses to temperature variability (Kuhn, 2010).
Early in my career, I explored the influence of the upper water column temperature on sessile organisms, macroinvertebrates, non-commercial and commercial fish of the Galapagos Islands. In my Bachelor’s thesis, I used multivariate statistics, including principal components and cluster analysis, to elucidate these effects on non-commercial shallow water species of the western region of the islands. This region is characterized by strong topographic upwelling and is key for the survival of many endemic cold-water charismatic species, such as penguins and flightless cormorants. I found two distinct patterns of temperature dependence: 1) biological communities in a deep channel were strongly affected by vertical differences in temperature; and 2) communities close to the Equatorial Front were affected by seasonal variations in temperature (Kuhn, 2010).
Later, I collaborated on the analysis of the combined effects of fishing pressure and temperature variability on local fisheries. After accounting for the negative effects of fishing over the stocks of sea cucumber and spiny lobster, we found a positive lagged correlation between sea surface temperature and catch (Defeo et al., 2013). The spiny lobster series, for instance, can be replicated well as a bi-variate autoregressive process.
Correlations between mean annual in situ sea surface temperature and lagged catch of spiny lobster and sea cucumber in the Galapagos Islands, Ecuador (Defeo et al., 2013). Catch series from 1995 to 2011 were linearly detrended and the residuals added to the mean, to account for the effect of fishing. Encircled triangles in B and D indicate the positive effect of 1997/1998 El Niño over spiny lobster (2000) and sea cucumber (2002–2003) catches. El Niño and La Niña events were defined based on the Oceanic Niño Index (ONI) estimated by the National Oceanic and Atmospheric Administration (NOAA). **: P < 0.05; ***: P < 0.001. Catch and SST time series were provided by Galápagos National Park and Charles Darwin Foundation. Content reproduced Creative Commons Attribution-NonCommercial 4.0 International License
Defeo, O., Castrejón, M., Ortega, L., Kuhn, A., Gutiérrez, N., & Castilla, J. C. (2013). Impacts of Climate Variability on Latin American Small-scale Fisheries. Ecology and Society, 18(4). Edgar, G. J., Banks, S., Fariña, J. M., Calvopiña, M., & Martínez, C. (2004). Regional biogeography of shallow reef fish and macro‐invertebrate communities in the Galapagos archipelago. Journal of Biogeography, 31(7), 1107-1124. Kuhn, A.M. (2010). Influencia de la temperatura del mar sobre comunidades rocosas submareales de la Reserva Marina de Galapagos. Tesis para la obtencion del titulo de Licenciatura en Oceanografia. Escuela Politecnica del Litoral. Guayaquil – Ecuador.
Angela M. Kuhn 