Axel G. Rossberg | 3 Sep 14:00

PhD position: Community interaction webs based on functional groups

I am forwarding this message (hope that the PDF attachment makes it
through!).

Axel

[PS: As not all may be aware, everybody getting messages from this
list can also send messages to it.]

*******************************************
From: "Winfried Voigt" <winfried.voigt@...> 
To: "Friends and Colleagues" <winfried.voigt@...>
cc: PhD position Jena University

Dear friends and colleagues,

Please find enclosed the offer of a PhD position I would like to fill as 
soon 
as possible. I'd appreciate it very much if you could publish the 
advertisement in your institution or pass it directly to students you 
consider 
eligible for this position.

With thanks and kind regards,

Winnie

*******************************************

Dr Winfried Voigt
Community Ecology Group
(Continue reading)

Christian Mulder | 10 May 19:02
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soil C:N:P and allometric scaling


Dear All

We would like to inform you about two recent papers which may be of interest.


The first paper just appeared in Global Change Biology (Wiley/Blackwell):

ABSTRACT
The factors regulating the structure of food webs are a central focus of community and ecosystem ecology, as trophic interactions among species have important impacts on nutrient storage and cycling in many ecosystems. For soil invertebrates in grassland ecosystems in the Netherlands, the site-specific slopes of the faunal biomass to organism body mass relationships reflected basic biochemical and biogeochemical processes associated with soil acidity and soil C : N : P stoichiometry. That is, the higher the phosphorus availability in the soil, the higher, on average, the slope of the faunal biomass size spectrum (i.e., the higher the biomass of large-bodied invertebrates relative to the biomass of small invertebrates). While other factors may also be involved, these results are consistent with the growth rate hypothesis from biological stoichiometry that relates phosphorus demands to ribosomal RNA and protein production. Thus our data represent the first time that ecosystem phosphorus availability has been associated with allometry in soil food webs (supporting information available online). Our results have broad implications, as soil invertebrates of different size have different effects on soil processes.

This article is available from the journal's homepage or from F1000:
Welcome to F1000 Biology - the expert guide to the most important advances in biology



Recommended
F1000 Factor 3.0




Hypothesis
New Finding
Soil acidity, ecological stoichiometry and allometric scaling in grassland food webs.
Mulder C, Elser JJ
Glob Chang Biol 2009 Online early:- [full text]

Selected by | Robert Sterner
Evaluated 07 May 09



"Studies of allometric or scaling relationships in biology and ecology hold the promise of revealing general structuring forces; this interesting study explores how resource availability modulates those relationships. Across a range of soil conditions, where pH and phosphorus availability ranged widely, scaling slopes (plots of organism mass vs. abundance or biomass expressed in different ways) varied consistently. In general, richer soils (C:P was the strongest predictor) had slopes indicating greater representation of larger organisms. The natural conclusion, which should be tested further, is that high P conditions enhance trophic transfer efficiency, liberating higher trophic levels from "bottom up" control. This study very nicely integrates this resource-centric viewpoint with macroecological patterns to indicate some potentially general rules of community structure and ecosystem functioning."




The second paper, by C Mulder, HA Den Hollander, JA Vonk, AG Rossberg, GAJM Jagers op Akkerhuis & GW Yeates, will appear in Naturwissenschaften (Springer) next week.

ABSTRACT
The large range of body-mass values of soil organisms provides a tool to assess the ecological organization of soil communities. The goal of this paper is to identify graphical and quantitative indicators of soil community composition and ecosystem functioning, and to illustrate their application to real soil food webs. The relationships between log-transformed mass and abundance of soil organisms in 20 Dutch meadows and heathlands were investigated. Using principles of allometry, maximal use can be made of ecological theory to build and explain food webs. The aggregate contribution of small invertebrates such as nematodes to the entire community is high under low soil phosphorus content and causes shifts in the mass–abundance relationships and in the trophic structures. We show for the first time that the average of the trophic link lengths is a  reliable predictor for assessing soil fertility responses. Ordered trophic link pairs suggest a self-organizing structure of food webs according to resource availability and can predict environmental shifts in ecologically meaningful ways.

Revised proofs available upon request (please remember that this paper will be published Open Access as well, just like the previous one).
In that way, supplementary material contained in the Springer online version (doi:10.1007/s00114-009-0539-4) will be available to all users.


Many thanks, best regards

Christian Mulder


Disclaimer RIVM
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foodwebs@...
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Bearhop, Stuart | 8 May 12:28
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PhD oppertunity

Dear All

Please pass on to anyone you think might be interested.

Many thanks

Stu

University of Exeter 
School of Biosciences 

PhD Studentships in Ecology

Project title:  Novel technologies for quantifying ecosystem function and biodiversity 

Three-year studentship: tuition fees (UK/EU rate) and annual stipend at current research council rate

Primary supervisor: Dr Stuart Bearhop
Secondary supervisor: Dr Frank Van Veen
Secondary supervisor: Dr Andrew Jackson (University College Dublin) 
The Food and Environment Research Agency supervisor: Dr Robbie McDonald

Deadline for applications: 23rd May 2009 (we plan to interview in Cornwall during early June)

Project summary: 
It is widely acknowledged that environmental change is the major threat to global biodiversity.
Environmental perturbations (invasive species, pollution, eutrophication etc) may impact
ecosystems in many ways and while effects such as species loss are often detectable, other deleterious
processes such alterations in the relationships among species (changing food web structure) are much
less obvious. Many of these measures of food web structure (e.g. foodweb complexity, food chain length,
total niche area, etc.) have been advocated as indicators of ecosystem function and thus understanding
such changes may be crucial to the preservation of biodiversity. Moreover being able to measure changes
in ecosystem function in a rapid fashion would have the potential to radically improve the evaluatio
 n of human impacts on ecosystems.
Until recently, proxies for ecosystem function have been largely unexplored perhaps because of the
difficulty in generating measures of ecosystem function using conventional approaches (such as
building foodwebs with stomach analyses). However recent developments in the field of stable isotopes
have the potential to enable ecosystem function metrics to be generated rapidly and could revolutionise
the way in which we monitor the environment and enhance our understanding of the key processes involved in
structuring communities.
The aim of this PhD is to use a series of experiments and "real world" situations to evaluate the use of stable
isotopes in generating measures of foodweb structure and in turn biodiversity AND ecosystem
assessment. It will also investigate some of the more fundamental questions about the processes driving
community structure. Building on the expanding collaborative research programme between the Food and
Environment Research Agency and the University of Exeter, the PhD project will combine both field and lab
approaches. The successful candidate will be based at the Centre for Ecology & Conservation (CEC) at the
University of Exeter's new multi-million pound campus in Cornwall. S/he will also spend periods at
Fera's laboratories in York and time in the field. This broad research prospectus
  will give opportunities for interacting with a range of researchers, field biologists and analysts. Open
to students from the European Union (although your spoken and written English should be of a high
standard), the successful candidate will have (or expect) a 1st class or high 2:1 class (or equivalent) in
biology or related subject, and excellent academic references. Applications from numerate students
are particularly welcome. 

For informal enquiries contact (Stuart Bearhop:
s.bearhop@...)  

Apply by CV and covering letter, providing contact details for two academic referees, to Stuart Bearhop: s.bearhop@...
Axel G. Rossberg | 7 Apr 13:55

Is all structure in food webs phylogenetic? Phylogenetic Correlations (III)

Dear List Members,

in a paper published last year, Williams and Martinez
[http://www.foodwebs.org/index_page/Williams2008JAE.pdf] put the
single "'niche dimension'" of their classical niche model
[http://www.foodwebs.org/index_page/Williams2000Nature.pdf] into
apostrophes, and explained that the model would actually "simulate
[...]  phylogenetic aspects" of food-web structure.  I agree (see
http://axel.rossberg.net/paper/Rossberg2006a.pdf).

The argument by which they arrive at this conclusion is as follows:
related species can have high trophic similarity, the niche model
produces species pairs with high trophic similarity, and therefore the
niche model simulates phylogenetic aspects.  Obviously, this argument
is stringent only when phylogenetic correlations are not only
contributing to, but the dominating cause for high trophic similarity
between species pairs (otherwise, high trophic similarity in the niche
model could reflect other structuring mechanisms).

This is the third part of a tutorial on phylogenetic correlations in
food-webs.  Here, I investigate how far this kind of reasoning can be
taken.  That is, I discuss the question how much of the structure we
see in food webs (all of it?) can be explained phylogenetically.

For parts I and II of the tutorial, please see

 http://permalink.gmane.org/gmane.science.biology.foodwebs/31


and

 http://permalink.gmane.org/gmane.science.biology.foodwebs/35


Enjoy part III.  Your comments on foodwebs <at> foodwebs.info are welcome.

Axel


** Part III: IS ALL STRUCTURE IN FOOD WEBS OF PHYLOGENETIC ORIGIN?

Most likely, the answer is no.  The trophic hierarchy underlying the
simple but powerful cascade model by Cohen & Newman (1985) is
generally understood as reflecting a size hierarchy: predators are
larger than their prey.  There are a few more structural features that
are probably unrelated to phylogenetic history, to which I will come
back later.  But the dominating structuring mechanism after the
trophic hierarchy seems to phylogeny.

The argument for this is not new, but, from the degree to which it is
taken up in the literature, I understand that it is largely unknown.


THE NESTED HIERARCHY MODEL

Cattin et al. (2004)
[http://www.unifr.ch/biol/ecology/bersier/publications/Nature_Cattin+_2004.pdf]

were perhaps the first to make the point by introducing their nested
hierarchy model.  The nested hierarchy model explains food-web
structure by (1) Cohen & Newman's trophic hierarchy, (2) a postulated
distribution of generality (i.e., # of prey), (3) a tendency of
related consumers to share resources.  The precise way networks are
built is strongly inspired by Sugihara's (1984) "niche-hierarchy
model, an assembly rule stating that species joining a community will
be successful only if they compete within single guilds" (Cattin et
al. 2004).  In his PhD thesis, Sugihara (1982) had shown that this
rule naturally leads to so called chordal niche-overlap graphs, which,
in turn, are closely related to the tendency of natural food webs to
be "interval".  Sugihara (1982) already speculated that phylogenetic
processes underlie this rule, with guilds corresponding to
phylogenetic clades.

While the nested-hierarchy model is frequently used in food-web
theory, the well-argued conclusions that Cattin et al. drew from their
work with the model have largely been ignored: "What we perceive to be
of higher importance than details of model construction are the
processes behind the nested-hierarchy model. We have shown how
phylogeny is intimately linked to trophic structure in natural
communities [...] body size is of secondary importance in explaining
food-web structure when compared with phylogeny."

One reason for the difficulties of this insight to penetrate the
literature may be that, when being scrutinized later, the differences
between nested hierarchy model webs and empirical data turned out to
be somewhat larger than for other food-web models which do not invoke
phylogenetic structure.  This weakness was later overcome by the
matching model.


THE MATCHING MODEL

Rather than just defining rules for constructing food webs, the
matching model (Rossberg et al. 2006
[http://axel.rossberg.net/paper/Rossberg2006bSup.pdf]) describes the
processes that lead to these structures.

The matching model combines (1) a stochastic model for the structure
of phylogenetic trees, (2) a model for the evolution of trophic traits
(one of which is body size) along these threes, (3) a model for the
determination of trophic link strengths from trophic traits, which
combines a trophic size hierarchy and a "matching" of foraging traits
with vulnerability traits, and (4) a model for the "measurement
process" by which binary food webs are constructed.  The model is put
together in such a way that any food-web pattern it generates must be
due to phylogenetic correlations of trophic traits or due to the size
hierarchy.  In particular, just as for the nested hierarchy model, no
assumption of low niche-space dimensionality is made.

Being more explicit about the details of food-web emergence naturally
adds complexity (and parameters) to the matching model when compared
to its predecessors.  But the added complexity pays off.  Using
standard methods of statistics that take differences in the number of
model parameters into account, it was shown (Rossberg et al. 2006)
that the matching model clearly outperformed the most accurate models
for food-web topology of this time, namely the niche model and the
nested hierarchy model, in reproducing empirical topologies.  Given
the data of 17 empirical food webs, the likelihood of the matching
model, based on Akaike weights, is about 10^125 times higher than that
of the niche model (10^338 for the nested hierarchy model).  And I am
unaware of any improvements over this result so far.

A playful way to see the differences between the abilities of niche
model and matching model to reproduce empirical data is to compare
visualizations of random adjacency matrices generated by the two
models with their empirical counterparts.  You may have done this
puzzle as a child: given a set of similar pictures, can you recognize
and characterize the one that is essentially different?  In our case,
that one displays empirical data rather than a simulation.  Sample
picture for 17 data sets you can find here:
[http://axel.rossberg.net/paper/Rossberg2006bSup.pdf] Give it a try!
For the adult in you, we put a red box around the empirical matrices.

If you, just as me, are unable to make out any visual differences
between empirical and model data in the case of the matching model,
this can be taken as evidence, complementing corresponding statistical
results (chi-square stats, Rossberg et al. 2006), that, in fact, the
topology of food webs originates from (a) a trophic size hierarchy,
(b) phylogenetic correlations, and (c) little else.  This conclusion
could be further hardened by similar statistical tests that take
account of the known phylogenies of the member species of empirical
food webs.  But such tests have not been done yet.


IMPLICATIONS

Given that phylogenetic correlations are strong at least in the sense
that they are statistically significant (see part II of the tutorial),
and are very likely one of the dominating structuring mechanisms of
food-web topology (see above), statistical analyses that seek to
identify structure of other origins in food-web data will definitely
have to work with phylogenetically structured null models or take
other precautions to avoid false positives due to phylogenetic
correlations.  Some interesting work of the past could have profited
from more attention to this point.


OUTLOOK

In the two following messages of the tutorial I am planning to discuss
HOW the processes described by the matching lead to the observed
structures in food webs.


ADDITIONAL RESOURCES

Those seeking to use the matching model as a null model for their
analysis, to develop it further, or to challenge it by their own
theory might find the following two postings useful:

Tons of matching model sample outputs:

 http://axel.rossberg.net/datatable/datatable.html


An algorithm to sample random matching model webs without having to
simulate it:

 http://axel.rossberg.net/paper/Rossberg2007a.pdf

 http://permalink.gmane.org/gmane.science.biology.foodwebs/22



LITERATURE

Cohen, J.E., Newman, C.M., 1985. A stochastic theory of community food
webs. Models and aggregated data. Proc. R. Soc. Lond. B 224, 421-448.

Sugihara, G., 1982. Niche Hierarchy: Structure, Organization and
Assembly In Natural Communities. PhD Thesis, Princeton University.

Sugihara, G. in Population Biology. Proceedings of Symposia in Applied
Mathematics (ed. Levin, S. A.)  83–101 (American Mathematical Society,
Providence, Rhode Island, 1984).
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foodwebs <at> foodwebs.info
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Axel G. Rossberg | 24 Feb 13:51

Re: Phylogenetic Correlations (II)

From: Christian Mulder <Christian.Mulder@...>
Subject: Re: [Foodwebs] Phylogenetic Correlations (II)
Date: Mon, 23 Feb 2009 12:29:26 +0100
Message-ID: <OFD89213ED.78545398-ONC1257566.00393E58-C1257566.003F1ED2@...>


> > Hi Axel, interesting discussion. I am only wondering on the kind of taxonomic > resolution of some cited references, like "Sand Beach, California" > (J.W.Nybakken 1982 as Cohen's web #50). > It is biologically hard to model, or even to imagine, trophic links between > (1) debris, (2) plankton, (3) amphipods, (4) Blepharipoda, (5) Emerita > analoga, (6) Tivela stultorum, (7) Donax, (8) Olivella, (9) Thoracophelia, > (10) Nepthys, (11) Policines, (12) sea otter, (13) birds, and (14) fishes. > Member species of each of these taxa have not trophic roles sufficiently > similar to warrant grouping them together, but crucial nodes of such a food > web are missing (echinoderms, for instance).
Hi Christian, thank you for the comments. You are right that, if you look at each of the taxa more closely, we will find differences between member species. But this would not preclude that species are trophically more similar within taxa such as those listed above (i.e. mostly genera) than across them. The results of Cattin et al. (2004) and Bersier & Kerli (2007) would suggest this is so. However, since the question here is slightly different from theirs, the answer might be different. If one could show that it was, this could be an interesting result. Intuition might somewhat be against the idea that species within taxa are trophically very similar, if we see species mostly in their roles as consumers. As mentioned before, trophic similarity seems to be stronger for the species' roles as resources. And the roles of species as resources might also have been the major motivation for their grouping in many historical food webs, if we imagine these webs as being constructed by starting with some higher predators ("sinks"), and then repeatably asking the question "so what do these guys eat?" until the sources are reached. Regarding the missing nodes, I assume you are right about these, too. Your example "echinoderms" would support the idea that lumping species taxonomically is a good idea, wouldn't it? Best, Axel PS: Looking at the web cited above again, it appears there were some spelling errors in the original sources: Nepthys -> Nephtys, Policines -> Polinices (a theorist's blind guesses)
Axel G. Rossberg | 17 Feb 13:59

Phylogenetic Correlations (II)

Dear Foodwebs List Members

this is the second part of a tutorial on phylogenetic correlations in
food-webs.  The first part discussed the question what phylogenetic
correlations are, and can be found here:

 http://www.mail-archive.com/foodwebs-meEmJjl1h1Ek+I/owrrOrA <at> public.gmane.org/msg00024.html

Here, I discuss the question how strong these correlations are.

Enjoy,

Axel

** Part II: HOW STRONG ARE PHYLOGENETIC CORRELATIONS IN FOOD-WEB TOPOLOGIES? 

PHYLOGENETIC CORRELATIONS IN HISTORICAL FOOD-WEB DATA

It is well known, and easily understood, that phylogenetic
correlations in data sets become the clearer the finer the taxonomic
resolution of the data sets is:  If there are more pairs of closely
related species, the similarities of these species become more
obvious.  For food webs, a theoretical analysis of this effect can be
found here http://axel.rossberg.net/paper/Rossberg2007a.pdf.

Historical food-web data sets, such as that compiled in Joel Cohen's
book "Community Food Webs" from 1990, are rather small and often have
comparatively low taxonomic resolution. This may explain why
phylogenetic correlations historically received little attention in
the field.

Rather than in the adjacency matrices, indications for phylogenetic
correlations can be found in the node descriptions of old food webs.
Cohen's web #50 ("Sand Beach, California" from J.W.Nybakken 1982), for
example, describes trophic links between (1) debris, (2) plankton, (3)
amphipods, (4) Blepharipoda, (5) Emerita analoga, (6) Tivela
stultorum, (7) Donax, (8) Olivella, (9) Thoracophelia, (10) Nepthys,
(11) Policines, (12) sea otter, (13) birds, and (14) fishes.  Thus, of
the 14 nodes, 9 refer to taxonomic units higher than species,
apparently because the member species of each of these taxa have
trophic roles sufficiently similar to warrant grouping them together.
The pattern is not always this clear.  In other webs one find nodes
defined by trophic role or body size.  Yet, of the 113 webs Cohen's
1990 collection, there are, by my count, at most 13 that do not
contain nodes referring to higher taxa.  The other 100 do.

QUANTIFYING THE STRENGTH OF PHYLOGENETIC CORRELATIONS IN FOOD WEBS

I will, in the following, nevertheless, concentrate on explicitly
reported food-web topologies, and ask if and how the strength of
phylogenetic correlations can be measured.  

This question poses itself more vigorously here than in other parts of
ecology, where it is sufficient to understand how to eliminate the
statistical effect of correlations from the data.  For the complex
statistics that we use to characterize food webs, this approach to
identify structure beyond phylogeny might be difficult to carry out.
Rather, one would try to build null models that explicitly exhibit
phylogenetic correlations, and would compare these with the data.  But
for this the strength of the correlations needs to be known.

Some care must be taken when asking how strong phylogenetic
correlations are, because the answer may depend on the taxonomic
resolution of the data set (s.a.), its taxonomic scope (a broader
scope shift weights to more distantly related species pairs), and its
spacial scope (over larger distances spacial correlations may
dominate).  Let me distinguish the following three kinds of measures:
"local" measures, for the degree by which correlation decay in time
after two species shared their last common ancestor, "global" measures
for the overall degree of correlations in a food web, and measures
comparing the strengths of different effects, where at least one
relates to phylogenetic correlations.

Cattin et al. 2004:
(http://www.unifr.ch/biol/ecology/bersier/publications/Nature_Cattin+_2004.pdf)

I sketched the method of Cattin in Part I already.  Regressions
between the taxonomic distance and the trophic similarity for all
species pairs in a data set were computed.  The slopes of these
regressions could serve as measures of the "local" kind.  But,
unfortunately, these slopes were not reported, since the point to be
made at this time was just to establish that phylogenetic correlations
are measurable at all.  And this was quite clear: "There was a strong
relationship (all P-values < 0.001) [...]"  So clear, perhaps, that
this important fact ultimately did not receive enough attention.  In a
sense, this result can be seen as a "global" characterization of
phylogenetic correlations in food webs.

Rossberg et al. 2006:
(http://axel.rossberg.net/paper/Rossberg2006b.pdf) 

We fitted a model for purely phylogenetically structured food webs (to
be described in Part III) to empirical data.  This produced, among
others, estimates for two model parameters p_v and p_f that
characterize the heredity of trophic traits on the time scale
separating speciations.  The model distinguishes between the heredity
(1-2 p_v) of traits characterising vulnerability to predation, and the
heredity (1-2 p_f) of traits determining foraging strategies and
capabilities.  These parameters could again serve as "local" measures
for the strength of correlations.  But care has to be taken, because a
"speciation" here is a separation of two "species" at the level of
taxonomic resolution of the fitted food-web data set (which varies
greatly even within data sets).  The numbers are therefore not
directly comparable between data sets.  Yet, the values of p_v and p_f
from the same fitted data set can be compared, and this comparison
yields an interesting result: usually, p_v << p_f, that is, evolution
of foraging traits is much faster than of vulnerability traits.  The
median of the ratio p_v/p_f over all fitted data sets was 0.039, and
0.0179 when excluding sets with many parasites and pathogens.  This
suggests that vulnerability traits evolve by a factor 25 to 60 slower
than foraging traits.


>From the fitted model, it might also be possible to derive a "global"
measure for the strength of phylogenetic correlations in a community, such as the average degree of phylogenetic correlation between two species selected randomly from the community (with replacement). To my understanding, such a measure would not depend on taxonomic resolution, but only on the taxonomic and spacial scope. But a technical complication of the model (the phylogenetic tree is not fully represented), so far prevented us from doing this. Bersier & Kerli, 2007: (http://dx.doi.org/10.1016/j.ecocom.2007.06.013) These authors performed an analysis similar to that by Cattin et al. discussed above, but now distinguishing between trophic similarities with respect to foraging and with respect to vulnerability. To some degree, the analysis confirmed that correlations between vulnerability traits (or consumer sets) are stronger than between foraging traits (or resource sets), but some uncertainty remained. Here, too, the slopes of the regression lines (and their measurement error) unfortunately remained unreported. It might be interesting to extend this work by determining the specific functional relationship between taxonomic distance and phylogenetic correlation. Rossberg, this tutorial: Since still no satisfactory measure for the "local" degree of phylogenetic correlation seems to exist, I made here yet another attempt: From diet tables of 25 fish species from the Bering Sea (http://doc.nprb.org/web/03_prjs/), I extracted all pairs of distinct diet items of the same consumer that (1) are resolved to species level and (2) belong to the same genus. For each pair, let f_1 and f_2 denote the proportions of biomass that the two species contribute to the consumer's stomach content. I took the logarithms of these values, l_1=log_10(f_1), l_2=log_10(f_2), and plotted the points (l_1,l_2) and (l_2,l_1) into a graph. The result you can see here http://axel.rossberg.net/paper/genus_pairs.pdf. Apparently, the log diet contributions of resource pairs from the same genus typically differ by less then one: the RMS difference is 0.86, corresponding to a spread by a factor 10^.86=7.2 in intake. (Similar results are obtained when deleting all points in the lower left 2x2 square of the graph to avoid selection biases.) Much of this difference may be attributable to differences in prey abundance. The actual differences in trophic link strengths to related resources may be smaller. Repeating this analysis with corrections for prey abundance may be worthwhile. OUTLOOK In the next message, I will have a closer look at our phylogenetically structured food-web model mentioned above.
Axel G. Rossberg | 5 Feb 19:01

NEXT SIZEMIC WORKSHOP: Sweden, June 1-6, 2009. Information on How to Apply

Julia Blanchard asked me to post the following.

Axel 
****************************************************************************

        Dear Colleagues, 

        The 2nd International SIZEMIC workshop:"Body size and
        ecosystem dynamics: Implications for conservation and
        management of natural resources" lead by Andrea Belgrano
        (Swedish Board of Fisheries) will take place on June 1-6,
        2009, at the Sven Lovén Centre for Marine Sciences, Strömstad,
        Sweden (http://www.tmbl.gu.se/).

        Please see the attached documents for information about this
        exciting workshop and instructions on how to apply. This
        information can also be downloaded from www.sizemic.org.

        All applications should be sent to
        andrea.belgrano@... before the close of Sunday,
        March 15th.

        Could you please forward this announcement to anyone who may be
        interested in attending.

        Thank you very much...and hope to see you in Sweden!

        Best wishes, 
        Julia

        http://www.sizemic.org/Documents/Sizemic_workshop_2009.pdf
        http://www.sizemic.org/Documents/Sizemic_Sweden_Application_2009.doc    


> ________________________________________________ > Julia L. Blanchard > Environment & Ecosystems > Centre for Environment, Fisheries and Aquaculture Science (Cefas) > Pakefield Road, Lowestoft > NR33 0HT > United Kingdom > tel +44 (0)1502 527701 > email: julia.blanchard@... > www.sizemic <at> org > > >
Axel G. Rossberg | 23 Jan 19:43

Food Web Theory - Postdoc

Dear List Members,

Gregg Hartvigsen from the ESA Theory Section kindly sent me this
posting.

Axel

************************************************************

Postdoctoral Positions in Food Web Theory
University of Toronto and University of Guelph

One or two postdoctoral positions are available now to work on
analyzing the dynamics of models of distinct foodwebs that are linked
by movements of one or more of the component species.  The position
will be supervised by Kevin McCann at the University of Guelph and
Peter Abrams at the University of Toronto, and the position may be
based in either institution.  The work is part of a larger project
examining the impacts of climate change on lake ecosystems involving a
multi-disciplinary team of academic and government scientists (Peter
Abrams, Don Jackson, Kevin McCann, Nigel Lester, Ken Minns, Brian
Shuter, Jake Vander Zanden). We are looking for candidates with a
strong background in modeling.  Salary is $42,500 (Canadian) per year,
and funding is available for 2 years.  If you are interested, please
send your c.v., pdfs of two publications, and the name and contact
information for three referees to peter.abrams@...
<mailto:peter.abrams@...>, and ksmccann@...
<mailto:ksmccann@...>
Jennifer Dunne | 23 Jan 19:54
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Computational Ecological & Environmental Sciences Group (Microsoft) Postdoc opportunities

 

 

Dear List Members,

 

Rich Williams has post-doc opportunities available in his research group, as detailed below.  Feel free to disseminate.

 

---------------------------------------

 

Computational Ecological & Environmental Sciences Group Microsoft Research Cambridge, UK.

Postdoctoral Scientists

http://research.microsoft.com/ecology

 

The Computational Ecology & Environmental Science group at Microsoft Research, based in Cambridge, England, has openings for postdoctoral research scientists in the following areas: ecological networks, plant ecology, behavioural ecology, biodiversity and biogeography.

 

The CEES group undertakes research to deepen our understanding of critical fundamental and applied problems in ecology and the environmental sciences, and develops novel computational methods for addressing these problems. The group has a strong scientific publication record, is very well resourced, has a sister group in computational biology, and benefits from links to a software and tools team with whom we aim to develop useable, freely available software for use by the scientific community. All members of the CEES group pursue personal research agendas, as well as working closely with a wide range of external partners including senior academics, co-supervised PhD students, and NGOs. CEES postdocs are expected to carry out novel scientific research, and to publish this research in international peer-reviewed scientific journals; as well as engaging with the mission of the group more widely.

 

A demonstrated interest and background in quantitative ecology / environmental science; interest in research at the interface of ecology, biology, computer science and other related disciplines; and an interest in developing and disseminating novel computational methods; are required.  Interested candidates are welcome to contact any member of the CEES for informal discussions prior to applying. Applications should include a statement of research interests and curriculum vita. Review of applications will begin March 1st and continue until the positions are filled.

 

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Axel G. Rossberg | 13 Jan 10:39

Phylogenetic Correlations (I)

Dear Foodwebs List Members

****************************************************************
******* First of all a happy year 2009 for all of you! *********
****************************************************************

With this message I would like to initiate a small tutorial on

     Phylogenetic correlations in food-web topology.  

Cheers,
Axel

** PREFACE

While it has long been recognized that phylogenetic correlations can
induce structure in ecological data in general, the role of
phylogenetic correlations for food webs topology is often
underestimated.  Some of you might not even be sure what "phylogenetic
correlation" in this context means.  The purpose of this first message
is to clarify this question.  Later messages, following in loose
sequence, will address other issues, e.g., empirical evidence for
phylogenetic correlations and typical patterns characteristic for
phylogenetically structured food webs.

I am writing this tutorial because, in my view, unawareness of the
explanatory power of phylogenetic correlations has become a major
obstacle for progress in food-web science.  Progress which is critical
if food-web science is to contribute to the mitigation of biodiversity
loss, either by informing management or by contributing to a better
founded valuation of biodiversity, morally or monetarily.  For those
of us, including myself, who have put efforts into the investigation
of phylogenetic correlations in food webs already, this is of course
also an opportunity to showcase our work.  But I hope to convince you
that the subject is too important to be left alone, independent of
whether you have worked on it before or not.

A mailing list seems to be the ideal medium for such a tutorial,
especially because of its strongly interactive nature.  If you are
following the tutorial and you find points that are unclear (which is
then entirely my fault) or you can offer additional or alternative
perspectives on a topic, I strongly encourage you to share your
questions and views on the list (simply by replying to
<foodwebs@...>) or otherwise to write me directly
(<axel@...>).  Hopefully, many of you will find these
messages interesting.  To the others I would like to extend my
apologies already now, in case that messages become too frequent or
too long.

** Part I: WHAT ARE PHYLOGENETIC CORRELATIONS IN FOOD-WEB TOPOLOGY? 

PHYLOGENETIC CORRELATIONS

Related species (or individuals) have similar ecological (or
biological) characters.  More precisely: When ecological characters
are described by quantitative measures, these measures are
statistically more correlated in ensembles of species pairs with close
phylogenetic (evolutionary) relationships than for ensembles of
distantly related species pairs.  This phenomenon is a keystone of
Darwin's theory.  It is known under various names, such as
"phylogenetic constraints", "phylogenetic signal", or "phylogenetic
correlation".

Phylogenetic correlations can lead to a violation of the hypothesis of
statistical independence of data points that underlies most standard
methods of statistical data analyses.  Much work has therefore been
devoted to the question how the effect of phylogenetic correlations
can be taken into account in order to isolate those correlations
attributable to causal relationships alone.  A common approach is the
use of "phylogenetically independent contrasts".  Another option is to
generate the distributions of test statistics under the null
hypotheses in question in Monte Carlo simulation that mimic evolution,
and thus naturally produce phylogenetic correlations.  For an
extensive discussion, see Garland et al.'s introductory review
http://findarticles.com/p/articles/mi_qa3746/is_199904/ai_n8829021.

PHYLOGENETIC CORRELATIONS IN FOOD WEB TOPOLOGY

How does the similarity of related species affect food-web topology?
Intuitively, we expect that similar species have similar consumers and
resources.  Apart from subtleties discussed below, this implies that
related species tend to share consumers and resources.  As a simple
example, a bird eating one kind of seed is likely to eat other kinds
of seeds but perhaps no insects, and a bird eating one kind of insect
will eat other insects but perhaps no seeds.  

In order to make this idea precise, consider food-web topologies
represented by adjacency matrices a_ij (with the indices i,j running
over all species in the web), where a_ij=1 when i is eaten by j and
otherwise a_ij=0.  The intuition that related species share consumers
can be formalized by the statement that a_ik and a_jk are, for fixed
k, more correlated for ensembles of pairs of closely related resources
(i,j) than for ensembles of distantly related resource pairs.  The
corresponding statement for similarity of resources refers to
correlations between a_ki and a_kj.  Yes, correlations can be computed
for binary variables such as the matrix elements a_ij.  But of course
one expects the same kind of correlation structure also if, instead of
a_ij, a suitable quantitative measure of link strength l_ij is used.In
short, trophic similarities of related species would directly be
reflected in phylogenetic correlations of trophic links or link
strengths.

To improve statistical power, practical analyses will often consider
correlations computed over links to all consumers and/or all resources
k at the same time.  One can expect that high values of
corr(a_ik,a_jk) and/or corr(a_ki,a_kj) computed for fixed (i,j) over
all k can directly be associated with the phylogenetic distance
between i and j.  This is how Cattin et al. did the first statistical
demonstration of phylogenetic correlations in food webs
(http://www.unifr.ch/biol/ecology/bersier/publications/Nature_Cattin+_2004.pdf).
Analyses making more direct use of the established statistical
techniques have, to my knowledge, so far remained preliminary (see
Ives and Godfray,
http://ora.ouls.ox.ac.uk/objects/uuid:e57495e5-9d2e-4858-8e24-8fc7b7445615/datastreams/ATTACHMENT01).

PHYLOGENETIC CORRELATIONS OF TRAITS DETERMINING TROPIC LINKS

Trophic interactions between species are not immediately hereditary
traits of either consumers or resources.  For example, we expect two
sympatric, closely related species to interact similarly with an
invading alien species, even though such interactions have never
occurred before.  This expectation is based on the intuition that
trophic interactions are determined by traits of consumers and
resources, and phylogenetic correlations in these traits lead to
correlated interaction strengths.

The subtlety mentioned above now occurs when consumers are highly
specialized to particular resources, and consumers and resources
co-evolve (e.g., in the case of parasites).  This can lead to
situations where species A eats B but not B', and A' eats B' but not
B, that is, there is no overlap in resources or consumer sets, and
yet, from the resource set of A and the close phylogenetic
relationships between A and A' as consumers and B and B' as resources,
one may guess that A' eats B'.  This is an example of a manifestation
of phylogenetic correlations in food webs which is not reducible to
phylogenetic correlations of link presences/absences.  It has to be
explained in terms of correlations in traits determining links.

The relationship between traits and trophic link strength (or
presence/absence of links) is, however, not well understood.  To
illustrate, nevertheless, how phylogenetic correlations of traits can
affect correlations of link strength, consider a simple example where
the link strength l_ik for consumption of different resource species i
by some fixed consumer k is determined additively by contributions
from three traits of the resource species.  Link strength can then be
decomposed as

  l_ik = (some constant) + u_ik + v_ik + w_ik,

with the value of each addend determined by one trait.  One can also
consider multiplicative contributions of the three traits to link
strength.  In this case l_ik as given above is interpreted as the
logarithm of link strength.

Now, assume that the contributions of the three components are
uncorrelated (a change of trait variables to the principal components
contributing to l_ik might achieve this).  Then

  cov(l_ik,l_jk) = cov(u_ik,u_jk) + cov(v_ik,v_jk) + cov(w_ik,w_jk) 

and hence

  var(l_ik) = var(u_ik) + var(v_ik) + var(w_ik) 

giving the correlation

  corr(l_ik,l_jk) = cov(l_ik,l_jk)/var(l_ik).

In the simple case that the variances of all components are equal, that
is, if var(u_ik) = var(v_ik) = var(w_ik), the correlation of link
strength is easily seen to reduce to

  corr(l_ik,l_jk) = [corr(u_ik,u_jk) + corr(v_ik,v_jk) + corr(w_ik,w_jk)]/3,

that is, the size of phylogenetic correlation of links strength is
simply the mean over all traits of the of phylogenetic correlations of
their contributions to l_ik.  When the variances of the contributions
differ, one obtains a corresponding weighted mean with the weights
equal to the variances.

To estimate the phylogenetic correlations of the component
contributions to link strength, it may often be justified to assume
these contributions to depend linearly on the trait values in a first
approximation.  In such a case, the phylogenetic correlations of the
contributions to link strength equal the phylogenetic correlations of
the corresponding trait values.

This simple calculation suggests that the order of magnitude of
phylogenetic correlations of link strength (1) is given by the
magnitude of the phylogenetic correlations of the main traits
determining link strength, and (2) is independent of the number of
traits determining link strength.

OUTLOOK

In the next message, I will discuss the question how strong
phylogenetic correlations in food webs typically are.
Lyne Morissette | 16 Dec 16:48
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Announcement of a conference: Ecopath 25 years

*"Ecopath 25 years"*

Conference: August 30 - September 1, 2009
Introductory Workshop: August 26-28
Specialized workshops: September 2-3, 2009
In Vancouver, Canada

‘Ecopath: 25 years’ Congress is being planned to be held at Fisheries  
Centre, University of British Columbia in September 2009. The meeting  
is intended to be an international scientific reunion on ecosystem  
modelling using the software Ecopath and Ecosim (EwE). It is also  
meant to celebrate the 25 years of the first applications of Ecopath  
approach; originally developed by Jeff Polovina from NOAA in the early  
1980s and since chiefly been expanded and significantly improved upon  
by scientists at the Fisheries Centre, UBC.

*Conference*
A global overview of the advancement of Ecopath with Ecosim modelling  
approach in the fields of fisheries management, ecosystem comparisons,  
spatial analyses, climate impacts, and ecosystem-based management.  
Limited to 120 participants.

*Introductory workshop*
An introduction to Ecopath with Ecosim uses working in the new version  
of the software (EwE6). Limited to 30 participants.

*Specialized Workshops*
Applications of the EwE 6 software, tentatively focusing on: Ecoseed  
(spatial optimizations), economic modeling, interoperability and plug- 
ins, and gaming. Suggestions on additional topics of interest can be  
submitted till January 15, 2009. Limited to 120 participants.

For details regarding pricing, please view the attached flyer or the  
URL "conference.ecopath.org".

Regards,
Ecopath Conference Committee

Gmane