5 Works

Data from: Shear-induced orientational dynamics and spatial heterogeneity in suspensions of motile phytoplankton

Michael T. Barry, Roberto Rusconi, Jeffrey S. Guasto & Roman Stocker
Fluid flow, ubiquitous in natural and man-made environments, has the potential to profoundly impact the transport of microorganisms, including phytoplankton in aquatic habitats and bioreactors. Yet, the effect of ambient flow on the swimming behavior of phytoplankton has remained poorly understood, largely due to the difficulty of observing cell-flow interactions at the microscale. Here, we present microfluidic experiments where we tracked individual cells for four species of motile phytoplankton exposed to a spatially non-uniform fluid...

Data from: Contrasting effects of spatial heterogeneity and environmental stochasticity on population dynamics of a perennial wildflower

Elizabeth E. Crone
Understanding how variation in growth, survival and reproduction affect population dynamics is a fundamental question in ecology. Although the effects of among-year variation (environmental stochasticity) are well understood, the effects of among-site variation (spatial heterogeneity) are less clearly defined. I evaluated the effects of spatial and temporal variation on the population dynamics of Pulsatilla patens, pasqueflower, a perennial prairie forb. I conducted a 10-year demographic monitoring study, and quantified vital rate variation among sites and...

Data from: Diet- and genetically-induced obesity differentially affect the fecal microbiome and metabolome in Apc1638N mice

Anna C. Pfalzer, Paula-Dene C. Nesbeth, Laurence D. Parnell, Lakshmanan K. Iyer, Zhenhua Liu, Anne V. Kane, C-Y. Oliver Chen, Albert K. Tai, Thomas A. Bowman, Martin S. Obin, Joel B. Mason, Andrew S. Greenberg, Sang-Woon Choi, Jacob Selhub, Ligi Paul & Jimmy W. Crott
Obesity is a risk factor for colorectal cancer (CRC), and alterations in the colonic microbiome and metabolome may be mechanistically involved in this relationship. The relative contribution of diet and obesity per se are unclear. We compared the effect of diet- and genetically-induced obesity on the intestinal microbiome and metabolome in a mouse model of CRC. Apc1638N mice were made obese by either high fat (HF) feeding or the presence of the Leprdb/db (DbDb) mutation....

Data from: Prioritizing management actions for invasive populations using cost, efficacy, demography, and expert opinion for 14 plant species worldwide

Natalie Z. Kerr, Peter W. J. Baxter, Roberto Salguero-Gomez, Glenda M. Wardle, Yvonne M. Buckley & Peter W.J. Baxter
Management of invasive populations is typically investigated case-by-case. Comparative approaches have been applied to single aspects of management, such as demography, with cost or efficacy rarely incorporated. We present an analysis of the ranks of management actions for 14 species in five countries that extends beyond the use of demography alone to include multiple metrics for ranking management actions, which integrate cost, efficacy and demography (cost-effectiveness) and managers’ expert opinion of ranks. We use content...

Data from: Learning to speciate: the biased learning of mate preferences promotes adaptive radiation

R. Tucker Gilman & Genevieve M. Kozak
Bursts of rapid repeated speciation called adaptive radiations have generated much of Earth’s biodiversity and fascinated biologists since Darwin, but we still do not know why some lineages radiate and others do not. Understanding what causes assortative mating to evolve rapidly and repeatedly in the same lineage is key to understanding adaptive radiation. Many species that have undergone adaptive radiations exhibit mate preference learning, where individuals acquire mate preferences by observing the phenotypes of other...

Registration Year

  • 2015

Resource Types

  • Dataset


  • Tufts University
  • Tufts Medical Center
  • University of Massachusetts Amherst
  • University of Queensland
  • Trinity College
  • Centre of Excellence for Environmental Decisions
  • University of Manchester
  • Max Planck Institute for Demographic Research
  • University of Sydney
  • Massachusetts Institute of Technology