Linking scales of flow variability to lotic ecosystem structure and function

Biggs, B. J. F., Nikora, V. I., & Snelder, T. H. (2005). Linking scales of flow variability to lotic ecosystem structure and function. River Research and Applications, 21(2-3), 283-298.

While biotic interactions have major influences on ecosystem, Biggs et al. argue that the abiotic environment constrains the biotic interactions playing a greater role in ecosystem. "An organism must be able to survive, grow and reproduce under a given set of abiotic conditions, before the habitat defined by those conditions can be considered viable for that species."  Abiotic conditions are the non-living chemical and physical factors in the environment as opposed to the biotic which is the living component of a community. Over evolutionary time species gradually adapt to specific habitats both abioticly and bioticly .  These abiotic environments act as evolutionary forces that drive the development of different sets of traits.  These forces are not static, and are extremely variable in both time and space. These forces can be climatic such as rain, wind, flooding, and flow variability.

Biggs et. al, punished work in River Research and Applications (River Res. Applic. 21: 283–298, 2005) linking flow variability to the lotic ecosystem structure and function.  Having a study area of New Zealand and focusing on rivers with a ranging difference in flow variability, they show that temporal variations in flow strongly influences the functional processes and structures of lotic ecosystems. They hypothesized that the lotic ecosystem is sensitive to flow variability at temporal scales, but also sensitive on scale of magnitude. They show that "infrequent, but high magnitude flow variations influence lotic ecosystem structure and function at high system levels (i.e. communities) through drag processes (resulting in ‘drag-disturbance’) whereas more frequent, but lower magnitude events influence ecosystem structure and function more through mass-transfer processes (controlling growth of individuals)."

Image via Wikipedia

While this reserached focuses on New Zealand, this concept of climatic senstivity in lotic ecosystems is critical in the age of climate change.  As with the Rivers in New Zealand, many rivers have variations in flow that is controlled by inter-annual variations in climate.  Year to year variations in New Zealand are driven by two Oscillations, the El Nino Southern Oscillation (ENSO) phenomenon superimposed by the Interdecadal Pacific Oscillation (IPO).  During El Nino there tends to be greater precipitation and higher more frequent flow events in the south and west of new Zealand. These inter-annual variations in flow regime have major implications river ecosystems due to the frequent flood disturbances in come years, and low flows in other years.  The figure below from the article shows the hydrograph of three rivers in New Zealand, where the inter-annual variation is apparent with the peaks in flow rates. The Bottom Chart is they hydrograph from the source of the two river above, while the source is relatively stable, down stream there is a strong variations related to runoff from storm events.

Biggs et. al. believes that ecological effects of horological variability follow a hierarchically principles, with effects of flow variation on communities by large scale events and event effects at lower levels with smaller scale flow variations.  They hypothesize that flow variability is the underlying reason for the temporal and spatial patterns of biological characteristic are different scales in the lotic ecosystem.

They conclude that "high energy flow events are generally catastrophic to lotic ecosystem structure and function for periods of time that vary depending on the resistance and resilience of the different populations."

Find it Online
Wiley Online Library - http://onlinelibrary.wiley.com/doi/10.1002/rra.847/abstract

Deforestation and Climate Variability effects on the Araguaia River, Brazil

Deforestation is impacting river systems like the Araguaia, which forms a natural border between the Brazilian states of Goias, Mato Grosso, Tocantins, and Pará.  The Araguaia River is a rare example of rapid geomorphologic response of a large alluvial river to land cover and land use change.  Deforestation alters the hydrological, geomorphological, and biochemical states of streams.  This occurs due to decrease evapotranspiration and increased runoff, river discharge, erosion and sediment fluxes from the land surface.  Over the past 4 decades, Brazil has experienced rapid regional development and land use change due to high demand of cattle feed, beef, and other agricultural commodities like sugar cane.  At the same time during the 1990s parts of Brazil has experienced increases in precipitation.  Determining how river systems respond to multiple changes require further study to link and quantify land use change and geomorphic responses.

Professor Edgardo Latrubesse was a Co-Principle Investigator (PI)  of an international project in Brazil named “Land use Impacts on the Water Resources of the Cerrado Biome” which was supported by NASA, Earth Science Enterprises and developed in collaboration  the Wood Hole Research Center, University of Goias Brazil,  and University of Brasilia.  Professor Latrubesse, with an international team of researchers, studied the river’s watershed, relating land use change to geomorphic response in the river system.  Their results are reported in the Journal of Biogeochemisty which shows that agricultural expansion has impacted the system. The team used modeling methods to simulate the watershed without land cover change, which suggested that about 1/3 of the observed discharge increase in the 1990s can be attributed to the observed increase in precipitation (Climate Variability). The simulation with land cover change compared to that without land cover change in the 1990s suggested that the remaining 2/3 of the observed discharge increase was most likely the result of some other factor such as a net decrease in evapotranspiration that occurred when native vegetation was replaced with more shallow rooted, less water-demanding pastures and crops.

Their paper can be found at:

Coe, M. T., E. M. Latrubesse, M. E. Ferreira, and M. L. Amsler (2011), The effects of deforestation and climate variability on the streamflow of the Araguaia River, Brazil, Biogeochemistry, 1–13.

The Power of Naming: The Toponymic Geographies of Commemorated African-Americans

Tretter, E. M. (2011). The Power of Naming: The Toponymic Geographies of Commemorated African-Americans. The Professional Geographer, 63(1), 34-54. doi:10.1080/00330124.2010.537936

(http://www.informaworld.com/openurl?genre=article&issn=0033-0124&volume=63&issue=1&spage=34)

The names that we give our streets, schools, parks, and other places in our landscape reflect our collective culture and history.  These place names can shape regional identities, give a neighborhood character, and recognize great people in our society.  Dr. Martin L. King Jr. is the most commemorated African-American in the United States, and in fact around the World.  Dr. King makes up nearly 2/3 of all African-American commemorations in the United States.  How does the other 1/3 of commemorative place-naming of notable African-Americans shape our American landscape?  

Image via WikipediaDr. Elliot Tretter has recently published a study on commemorative place-naming of notable African-Americans in the February 2011 issue of the Professional Geographer.  His study explores how there are regional characteristics associated with where African-Americans are commemorated, particularly pertaining to cities.   Dr. Tretter uses a variety of Internet-based mapping tools to collect a dataset on the regional variation of the commemoration of thirty famous African-Americans (fifteen men and fifteen women).

Dr. Tretter’s finding show that while Dr. King may have reached a universal symbol of African-Americans transcending limits, other African-Americans figure have not.  He found that African-American commemorations do follow a geographical pattern. In the fact, the patterns show that commemorations are in places associated with African-American.  These figures therefore are not recognized as universal members of a nation and remain symbols of a separate “black nation”.

Image via Wikipedia

The Black Nation

Related articles

• The 25 most influential African-American leaders in US history (thegrio.com)

Evaluation of Airborne Lidar Data to Predict Vegetation Presence/Absence

Article Citation: Monica Palaseanu-Lovejoy, Amar Nayegandhi, John Brock, Robert Woodman, C. Wayne Wright (2009) Evaluation of Airborne Lidar Data to Predict Vegetation Presence/Absence. Journal of Coastal Research: Fall 2009, Vol. , No. , pp. 83-97. 
http://www.jcronline.org.pinnacle.allenpress.com/doi/full/10.2112/SI53-010.1
One Line Summary

This study evaluates the capabilities of the Experimental Advanced Airborne Research LiDAR (EAARL) to predict the presence/absence of coastal vegetation communities in Barataria Preserve at Jean Lafitte National Park, Louisiana (JELA).
Short Summary
This study evaluates predictive vegetation models using LiDAR derived elevation (bare earth) and canopy height. Palaseany-Lovejoy et al.  compared two modeling methods, parametric and non-parametric. General linear models and generalized additive models using conventional methods are both evaluated for the study area.
This study aims to model and predict presence/absence of vegetation communities, and to assess the statistical significance of observed relationships with lidar metrics.  The objectives are to:

1. model and predict presence/absence of coastal vegetation communities using EAARL lidar metrics as predictor variables in an area with small topographic variability.
2. compare parametric and non-parametric methods of inference.
3. assess modeling and prediction accuracies using conventional evaluation methods and two new indexes, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). 

Reading Notes
Maps of vegetation communities and their spatial distribution are a primary tools in conservation, land management application, and decision support systems.
Several large scale efforts to map vegetation have used environmental gradients, in some cases combined with remote sensing data, to model and predict the presence/absence or percentage coverage of vegetation. (Bio, Alkemade, and Barendregt, 1998; Dobrowski et al., 2006; Frescino, Edwards, and Moisen, 2001; Moisen and Edwards, 1999; Moisen et al., 2006; Yee and Mitchell, 1991).
Relevant environmental gradients include elevation, slope, aspect, soil properties, water availability and subsurface depth, temperature, isolation, and latitude and longitude.
Remote sensing-based modeling and predictions are divided into two main groups: Parametric and non-parametric methods.
Parametric methods:  
Positives: Have the benefits of ease to use. Easy to interpret, straightforward statistical properties, and use explicit regression equations.
Negatives: Based on the assumption of normal distribution.
Non-parametric methods
Positives: Do not require normal distribution, and can accommodate different distributions. These are data driven methods rather then model driven methods.

Lidar EAARL Vegetation Metrics

Definition of the EAARL Composite Footprint

The EAARL is a temporal waveform-resolving, green-wavelength (532 nm), small-footprint airborne lidar instrument.  The EAARL green-wavelength laser can map bathymetry (to a limit), topography, and vegetation simultaneously. Because this is a small footprint LiDAR system, it is able to map canopy heights of individual trees as opposed to forest segments.
Four distinct metrics are derived from the continuous EAARL waveforms: bare earth (BE), canopy height (CH), canopy reflection ratio (CRR), and the height of median energy (HOME).
All four EAARL lidar-derived metrics were calculated in this study: bare earth, canopy height, canopy reflection ratio, and height of median energy.
Bare Earth - Represents the last return value.
Canopy height - is the distance from the composite-footprint first-return to the ground.
Canopy reflection ratio - is the sum of the waveform returns reflected off the canopy divided by the sum of all returns.
Height of Median Energy -  is the median height of the entire composite waveform.

Evaluation Criteria
Models can be evaluated qualitatively or quantitatively in order to measure the degree of data fitting, or to assess the predictive power for real data or events (Myers, 1997).


Sensitivity is a measure of the proportion of true presence predicted by the model when the species actually occurred at that location and specificity is the proportion of absence predicted when true non-events or absence occurred (Cumming, 2000; Fielding and Bell, 1997).
Important Sources
Examples of generalized additive model (GAM) applications in modeling for plant ecology, mapping and prediction, forestry and ecological analyses have been presented by Austin (2002), Austin (2007), Austin et al. (2006), Frescino, Edwards, and Moisen (2001), Guisan, Edwards, and Hastie (2002), Leathwick, Elith, and Hastie (2006), Lehmann, Overton, and Leathwick (2002), Moisen et al. (2006), Wood and Augustin (2002), Yee and Mackenzie (2002), and Yee and Mitchell (1991).

Bio, A. M. F. , R. Alkemade , and A. Barendregt . 1998. Determining alternative models for vegetation response analysis: a non-parametric approach. Journal of Vegetation Science 9 (1):5–16.

Dobrowski, S. Z. , J. A. Greenberg , C. M. Ramirez , and S. L. Ustin . 2006. Improving image derived vegetation maps with regression based distribution modeling. Ecological Modelling 192 (1–2):126–142.

Frescino, T. S. , T. C. Edwards Jr , and G. G. Moisen . 2001. Modeling spatially explicit forest structural attributes using generalized additive models. Journal of Vegetation Science 12 (1):15–26. Moisen, G. G. and T. C. Edwards Jr . 1999. Use of generalized linear models and digital data in forest inventory of northern Utah. Journal of Agricultural, Biological and Environmental Statistics 4 (4):372–390.  Moisen, G. G. , E. A. Freeman , J. A. Blackard , T. S. Frescino , N. E. Zimmermann , and T. C. Edwards Jr . 2006. Predicting tree species presence and basal area in Utah: a comparison of stochastic gradient boosting, generalized additive models, and tree-based methods. Ecological Modelling 199 (2):176–187. Myers, J. C. 1997. Geostatistical Error Management: Quantifying uncertainty for environmental sampling and mapping. New York Van Nostrand Reinhold. 571. p.   Yee, T. W. and N. D. Mitchell . 1991. Generalized additive models in plant ecology. Journal of Vegetation Science 2 (5):587–602.

Related articles

• Researchers Create Global Map of Tree Height (usnews.com)
• First-of-its-kind map details the height of the globe's forests (eurekalert.org)

Spatial Autocorrelation: Trouble or New Paradigm?

Author(s): Pierre Legendre
Source: Ecology, Vol. 74, No. 6 (Sep., 1993), pp. 1659-1673
Published by: Ecological Society of America
Stable URL: http://www.jstor.org/stable/1939924

Legendre defines spatial autocorrelation as a property of random variable at a pair of locations that if are more similar then expected by random correlation,  are positively autocorrelated, and if less similar are negatively autocorrelated.  Spatial autocorrelation is general property of ecological variables.

Notes on Writing Papers and Theses - Ken Lertzman

Notes on Writing Papers and Theses
Ken Lertzman
Bulletin of the Ecological Society of America, Vol. 76, No. 2 (Jun., 1995), pp. 86-90
Published by: Ecological Society of America
Stable URL: http://www.jstor.org/stable/20167913

Dr. Lertzman outlines common problems that he has found in scientific writing from his students. These problems give you insight into what someone who has reviewed many these, papers, and articles has found as common problems.  He offers 21 notes to keep in mind when writing.

1) Know your audience - You must adopt a style and level of writing appropriate for your audience.

• Scientific writing is not "general purpose" and should not be tailored to be understood by everyone.
• For class papers your audience is your professor.  I would extend it to the other people in your graduate seminar.
• For Journals it will be the people who read the journal. (ie Geomorphology would be read by geomorphologists.)

2) Your professor is not there to teach you basic grammer and spelling.

Think about it, you want them to use your time together to make progress with you in your research. Use someone else to fix grammer and spelling.

3) Don't turn in your first draft

I was surprised that he even had this in here. However he did say one thing that stuck with me: "Good writing is rewriting."  So I understood this section is that you need to rework your writing over and over.  That is how excellent writing emerges.

4) Get and use style books

5) Avoid passive constructions when possible.

Avoid passive voice. It is unclear. It is better to use a personal pronoun then to use the passive.

6) Avoid abusing word forms

The Columbian Encounter and the Little Ice Age: Abrupt Land Use Change, Fire, and Greenhouse Forcing

Image via WikipediaThe Little Ice Age, a period of global cooling that occurred between 1500 and 1750, has been the subject of much scientific debate about what roles do people play in global climate change, and if natural variation has been the source of past warming and cooling periods.  The Little Ice Age has been previously attributed exclusively to natural variations through mechanisms like decrease in solar irradiance (the amount of sunlight which reaches the Earth), increase in global volcanic activity, and changes in ocean circulations.  The current article "The Columbian Encounter and the Little Ice Age: Abrupt Land Use Change, Fire, and Greenhouse Forcing" by Robert Dull and other leading researchers argue that anthropogenic causes played a larger role then once anticipated.  They conclude that the rapid population crash of indigenous people of the new world after the Columbian Encounter lead to a reforestation of the Neotropics creating a terrestrial biospheric carbon sequestration in the order of 2 to 5 billion tons.  A carbon sequestration event of this magnitude would be a significant forcing mechanism for global cooling during the Little Ice Age period.  Dull et al. reviewed fire history and reported high-resolution charcoal records to support the idea that the Neotropical lowlands went from being a net source of carbon dioxide to a net sink in the centuries following the Columbian encounters.   This article furthers the concept of anthropogenic forcing of climate before the Industral Revolution, and shows that people have a longer history on global climate change.

The Columbian Encounter and the Little Ice Age:Abrupt Land Use Change, Fire, and Greenhouse Forcing is avilable in the Annuals of the Assocation of American Geographers Special Issue on Climate Change October 2010


Dull, Robert A. , Nevle, Richard J. , Woods, William I. , Bird, Dennis K. , Avnery, Shiri and Denevan, William M.(2010) 'The Columbian Encounter and the Little Ice Age: Abrupt Land Use Change, Fire, and Greenhouse Forcing', Annals of the Association of American Geographers,, First published on: 01 September 2010 (iFirst)

http://dx.doi.org/10.1080/00045608.2010.502432

Robert A. Dull's UT Faculty Profile