Paper 28 - By Kaitlyn Sullivan

Paper 28

Pielou, E.C. 1977.  The latitudinal spans of seaweed species and their patterns of overlap.  Journal of Biogeography 4:299-311.

Blog by Kaitlyn Sullivan                                  

Paper Author: Evelyn C. Pielou

(Commentary by Christy M. McCain)

Christy M. McCain

·       Ph.D. from University of Kansas

·       Associate Professor and Curator of Vertebrates Dept. of Ecology & Evolutionary Biology and University of Colorado Boulder Natural History Museum

Research interests:

“I am interested in the mechanisms producing and maintaining patterns of species distribution, abundance, and diversity. To address these processes, I consider three levels of ecological organization to be equally important: species-level autecology, population-level dynamics, and community-level processes and interactions. My research so far has highlighted small mammal range dynamics, abundance patterns across altitudinal ranges, and species richness patterns along latitudinal and elevational gradients. I particularly exploit mountain systems as natural experiments to look at how evolutionary history, ecological processes, and future climate change influence species populations. My overarching goal is to strive for quantitative, general theories applicable to both the advancement of ecology and the improvement of our conservation strategies. I use multiple tools at various spatial scales to address research questions, including field studies, synthesis of collection and historical data, comparative analyses, null models, GIS, and simulation modeling.”

Christy M McCain. (n.d.). Retrieved January 30, 2017, from http://www.colorado.edu/ebio/christy-m-mccain

Evelyn C. Pielou                

·       Ph.D. from University of London

·       Professor of Biology at the Queen's University, Kingston (1968-71)

·       Professor at Dalhousie University in Halifax, Nova Scotia (1974-81)

·       Oil Sands Environmental Research professor at the University of Lethbridge, Alberta (1981-86)

·       Died July 16, 2016

Research Interests:

E.C. Pielou was a Canadian-born, British-trained Evolution and Ecology Biologist who significantly contributed “to the development of mathematical ecology, the mathematical modeling of natural systems.”  Mostly self-taught, she began her career in 1963 as a research scientist for the Canadian Department of Forestry, then transferred into the Department of Agriculture in 1964.  Starting in 1968, Pielou spent the rest of her career as a research professor at three distinguished universities.  During that time, she wrote and published 10 books and over 60 articles, of which earned her a Ph.D. from the University of London.  Throughout her lifetime, Pielou was the recipient of many awards including :

·       Fellow, Royal Society of Arts

·       George Lawson Medal (Canadian Botanical Association), 1984

·       Eminent Ecologist Award (Ecological Society of America), 1986

·       Distinguished Statistical Ecologist Award (International Congress of Ecology), 1990

·       Several honorary degrees and memberships

She recently passed away in her home town of Comox, British Columbia, Canada.

Evelyn C. Pielou Evolution and Ecology. (n.d.). Retrieved January 30, 2017, from http://www.science.ca/scientists/scientistprofile.php?pID=208

Paper- Summary/Main points:

The purpose of this paper is to describe a method of analyzing species’ ranges by depicting each species as a line on a map.  When all species are included in the map, the ranges are shown as a sheaf of lines.  “Each line relates to a single species: the location and length of the line show the position and the extent of that species’ range.  The sheaf as a whole shows the wat in which the several species’ ranges overlap.”

·       “Species range limits and size”

·       “Patterns of overlap among closely and distantly related species”

·       “The latitudinal gradient in species richness”

·       Testing two conflicting hypotheses of overlap

(1)  “The range limits of congeneric species are independently located”

·       Species that are closely related should overlap due to shared ancestry.

·       The unconditioned hypothesis – “locations of the northern and southern limits of the s spans are entirely at random.”

·       Lengths of span are undefined

(2)  “The ranges themselves, assumed to have their observed lengths, are independently located.”

·       There will be minimal overlapping due to competitive exclusion among closely related species.

·       The conditioned hypothesis – “takes into account the lengths of the s spans and the availability of shoreline length where they must be located.”

·       Lengths of spans are based off actual, observed lengths which are assumed to be independently and randomly located within the given space.

Methods

·       Data was based off literature with previously recorded northern and southern limits of algae occurrence.

·       684 species of benthic marine algae.

o   395 species of Rhodophyta

o   174 species of Chlorophyta 

o   115 species of Phaeophyta

·       It was assumed that the span of each species was defined by its northern and southern (latitudinal) limits.

Results/Conclusions

·       “It was concluded that competition between related algal species has no effect on the locations of their spans, and hence on their geographical zonation patterns.  [However,] the local, as opposed to geographical, pattern of seaweed distribution, in contrast, appears to be strongly affected by competition.”  In other words, overlap in range limits is much more prevalent among congeneric species than was previously predicted by competitive exclusion.  Also, across the latitudinal gradient, species ranges were distributed independently.

·       She observed that while completion highly influences the distribution of local algae, the same is untrue of geographical distribution.

·       “She attributed her results to allopatric speciation followed by rampant marine dispersal.”

·       Results follow two commonly accepted macroecological patterns

o   “Most common range sizes are the smallest”

o   “Latitudinal patterns in diversity are unimodal”

Questions

·       What are mid-domain effects and how did Pielou’s set of analyses influence it?

·       If allopatric speciation does not account for speciation among benthic algae, have other mechanisms been determined to cause sympatric speciation in this class of plants?

·       In recent years, have improvements to Pielou’s methodology been made in an effort to generate data with greater biogeographic significance?

Paper 43

Conner, E.F. and E.D. McCoy. 1979. The statistics and biology of the species-area relationship. American Naturalist 113:791-833.

Blog by Rebbeca Kiat

Paper Authors: Edward F. Connor, Earl D. McCoy

(Commentary by Brian A. Maurer)

Brian A. Maurer

·      Ph.D. from  University of Arizona

·      Associate Professor at Michigan State University

“Ecology is understood to be the study of phenomena that occur on a wide range of spatial and temporal scales. My interest focuses on the largest spatial and longest temporal scales studied by ecologists.  To understand the importance of processes at geographical scales, it is important to understand how they connect to local scale processes.  Thus, I am interested in modeling population and community dynamics in a geographical context.  I am working with a variety of vertebrate organisms to model how population dynamics and abundance vary from one place to the next within their geographical ranges.  These focal questions, however, give rise to a number of different ancillary questions regarding such things as the ecological and evolutionary importance of body size, geographic patterns of species diversity, and resource use behavior.  Modeling ecological systems in space and time is a major tool that I use to answer questions about geographic scale ecological processes.  To this end, my lab uses a variety of quantitative and computational technologies. We intensively use geographical information systems (GIS) to analyze and model spatial processes.  Spatial statistics and related techniques from geostatistics provide the analytical framework for many of our statistical analyses.  Finally, use of nonlinear and spatially explicit mathematical modeling techniques allows us to develop theoretical approaches to large scale ecological systems.”

Edward F. Connor

·      Ph.D. from  Florida State University

·      Professor at San Francisco State University

“I am broadly interested in population and community ecology, statistical ecology, biogeography, insect-plant interactions, and sampling and monitoring design in ecology and conservation. My field research employs insects communities and insect-host plant systems to answer basic questions about the population dynamics of pest insects and the structure of insect communities. My interests in statistical ecology and biogeography lie in developing probabilitistic statistical procedures for the analysis of biogeographic data and in developing a rigorous framework for hypothesis testing and staitsical inference using both experimental and non-experimental  evidence in ecology. My work on sampling design focuses on questions concerning the optimal design and allocation of effort in monitoring plant, bird, and bee populations and communities.

My recent research has focused on trying to determine the mechanism by which insects induce pall galls (tumors) and its evolution, developing hierarchical models for abundance data, and automating avian population monitoring.”

Earl D. McCoy

·      Ph.D. from  Florida State University

·      Professor and Associate Chair at University of South Florida

“My students and I study a broad range of ecological and biogeographical problems. Many of our projects relate in some way to conservation biology, either in theory or in practice. Most of our current research deals with conservation and restoration of severely threatened upland habitats, particularly sandhill and scrub, in Florida. Within this framework, my students have focused their projects on a variety of topics: structure of gopher tortoise populations, demography and autecology of sand skinks, restoration of Florida mouse populations on lands mined for phosphate, and comparative biology of common and rare frogs, for example. Other students have focused their projects on topics such as methods of ecological analysis and the composition of species' assemblages. My own research encompasses additional topics in the areas of disturbance ecology, particularly fire ecology; biogeographical theory; and the philosophical basis of ecology.

Virtually all of the research being conducted by my students is aimed at solving particular problems and, therefore, probably would be labeled "applied research" by many persons.”

Paper - Summary/Main points:

·      Concerned with use and interpretation of species-area curves.

·      Power function model vs. alternative models – is it the best model? Theoretically unique in explaining observations?

·      Biological explanations for these models?

(1) “Does the equilibrium model provide a unique theoretical basis for the species-area relationship?”

·      Habitat diversity hypothesis - with increased area, more variety of habitats?

·      Area-per se hypothesis - equilibrium theory of island biogeography?

·      Sampling hypothesis – passive sampling; increased sampling for larger areas?

(2) “Is the power function model (log/log), derived from equilibrium theory, the best model of the species-area relationship?”

·      Is there a model that statistically fits the data the best?

·      Danger in applying a model without comparison to other models/ignoring important assumption made when applying a model.

·      Analysis of 100 data sets of species-area curves from literature and re-analyzing using various models – found no best-fit model.

·      Note: did not look at curvilinear models?

·      The power function and the untransformed models provide good fits most frequently.

(3) “Can the parameters of the power function or other species-area models be interpreted biologically?”

·      Closer look at parameter values for models (e.g. z , k, log k)

·      Slope parameters – predictions and limitations and what this means

·      Published predictions and interpretations at the time were not supported by available evidence – needed more data/due to the nature of the claim could not be tested

Questions:

·      In this paper, the authors also discuss Arrhenius’s 1920 & 1921 papers and the equations from them (note previous reading). Were there limitations to these equations or were there underlying assumptions?

·      Do we have new evidence that might better explain some of these models now, biologically?

·      Why did the authors not look not look at curvilinear models? Is this relevant?