Morgan Ernest

[Martorell, C. & R.P. Freckleton. 2014. Testing the roles of
competition, facilitation and stochasticity on community structure in a
species-rich assemblage. Journal of Ecology
doi:10.1111/1365-2745.12173](http://onlinelibrary.wiley.com/doi/10.1111/1365-2745.12173/abstract)

At a given location in nature, why are some species present and others
absent? Why do some species thrive and have lots of individuals and
others are barely eeking out an existence? What determines how many
species can live together there? These questions have fascinated (some
might say obsessed) community ecologists for an almost embarrassing
number of decades. They have proven difficult questions to answer and
everyone has their favorite process they like to use to answer those
questions. Competition for limiting resources is perennially a favorite
process used to explain who gets into a community and who does well once
they're in it. But there are also a number of other processes that
clearly play important roles. Theory and data are showing that the
movement of species from location to location can alter what species
exist where and how many individuals they have at a site. The role of
facilitation (positive interactions among species) has increasingly been
getting play as well, especially in stressful environments. There can
also be a random component to the order that species arrive at a
particular location. Because it can be difficult for very similar
species to coexist, who is already at a location can influence who can
then get into that location (this is sometimes referred to as historical
or priority effects).  I'm sure I missed some processes and I'm equally
sure that someone out there right now is upset I didn't include theirs.
Others might (and by might I mean probably will) disagree with what I'm
about to say, but most of the time it seems to me that we spend most of
our time arguing about which process is most important. It's
competition! No it's dispersal limitation! Niches! No niches! I have
come to find this binary approach to studying communities wearisome. And
here's why. Does competition influence who exists at a particular
location? Yes. Does dispersal? Yes. Does facilitation? Yes. Do
stochastic processes? Yes. Do priority effects? Yes. We are at a point
in ecology where I think we can feel confident that these various
processes both exist and that they affect what we see in nature.
Instead, we need to figure out how these processes work together to
create the communities we observe. Does the role of a process stay
constant through time? Or does it change depending on whether a
community has been recently disturbed or is more established? Can we
weave together these processes to predict how a community will look
through time?

Right about now, you're wondering if I will ever actually mention the
Martorell & Freckleton paper. Here you go. Martorell & Freckleton (2014)
take data from a long-term study of plants in Mexico and analyze all the
pair-wise interactions among species in order to "document the intensity
and demographic importance of interactions and stochasticity in terms of
per capita effects, and to set them in a community context". In effect,
they used population models and the spatio-temporal data on plants to
assess for each species observed how its presence and population
growth/abundance was impacted by interactions with other species,
interactions with individuals of the same species, variability in the
environment, dispersal, and population stochasticity. If you want to
know how they did this, you'll need to read the paper. They found that
both competition and facilitation between species played an important
role in determining whether a new species could colonize a particular
site. Once established, competition and facilitation played less
important roles in explaining the abundance of species. Most of the
variation in abundance between species can be explained by interactions
with other members of the same species and by stochastic events
influencing dynamics at a location.\*

So why do I like this paper? Because it's a step towards that
integration of processes that I think we need to start doing. Their end
message isn't: process x affects 'thing I'm interested in' y. Their end
message is about how these processes are working together and when they
play a more (or less) important role for determining what species are
present and how well they are doing at a site. Their results suggest a
model of communities where interactions among species influences who
establishes at a particular location (i.e. the species composition in
community ecology lingo). However, stochastic events and interactions
among members of the same species become important for understanding
differences among species in abundances and population growth rates.
Only time will tell if this particular integration of processes holds
across different types of ecosystems. But right now it allows us to
start talking about more sophisticated models of how species come
together to create the diversity of species and abundances in a
community.

And what does this paper say about predicting the species in a community
and their abundances? My interpretation is that it says what I think a
growing number of us have suspected for a while. For a specific location
there is not a single expected configuration of a community. There are
many possible configurations. This means that precisely predicting the
species composition of a community will be difficult. But it also makes
me wonder whether it might be possible to predict the space of
possibilities and how probable those possibilities are. Given this
disturbance rate and this pool of possible species, there's a 60% chance
of this configuration of species, but only a 10% chance for this one. I
suspect many of my colleagues think that even this level of prediction
or forecasting is pure science fiction thinking on my part. But like
some of my other blogging colleagues ([hi,
Brian!](http://dynamicecology.wordpress.com/2012/11/27/ecologists-need-to-do-a-better-job-of-prediction-part-i-the-insidious-evils-of-anova/)
[hi,
Peter!](http://dynamicecology.wordpress.com/2012/12/10/ecological-forecasting-why-im-a-hypocrite-and-you-may-be-one-too/))
I believe that pushing our field from one focused on 'understanding' to
one focused on 'forecasting' or 'predicting' is one of the greatest
challenges our science faces\*\*. Figuring out how and when different
processes operate and what aspects of community structure they are
controlling is the first step towards forecasting. And that is exactly
why I like this article.

\*\*\*\*

\* Disclaimer: I've distilled the paper down to the core message of what
I found interesting and why. To understand what Martorell & Freckleton
did, all of their results, and what they thought made their results
interesting, you should really read the paper.

\*\*Acknowledgments: Sadly, I can't also link to the long and awesome
conversations that Ethan, [Allen
Hurlbert](http://labs.bio.unc.edu/Hurlbert/index.html) and I have been
having on this topic while on sabbatical. Trust me, they've been
revolutionary experiences that you wish you were there for.


Martorell, C. &amp; R.P. Freckleton. 2014. Testing the roles of competition, facilitation and stochasticity on community structure in a species-rich assemblage. Journal of Ecology doi:10.1111/1365-2745.12173  At a given location in nature, why are some species present and others absent? Why do some species thrive and have lots of individuals and others are barely eeking out an existence? What determines how many species can live together there?

Why I like this: Martorell and Freckleton (2014)

Ethan White

*This is a guest post by [Dan McGlinn](http://mcglinn.web.unc.edu/), a
[weecology](http://weecology.org) postdoc
([@DanMcGlinn](https://twitter.com/DanMcGlinn) on Twitter). It is a
Research Summary of: McGlinn, D.J., X. Xiao, and E.P. White. 2013. An
empirical evaluation of four variants of a universal species--area
relationship. PeerJ 1:e212 <http://dx.doi.org/10.7717/peerj.212>. These
posts are intended to help communicate our research to folks who might
not have the time, energy, expertise, or inclination to read the full
paper, but who are interested in a \<1000 general language summary.  
*

It is well established in ecology that if the area of a sample is
increased you will in general see an increase in the number species
observed.  There are a lot of different reasons why larger areas harbor
more species: larger areas contain more individuals, habitats, and
environmental variation, and they are likely to cross more barriers to
dispersal -- all things that promote more species to be able to exist
together in an area. We typically observe relatively smooth and simple
looking increases in species number with area. This observation has
mystified ecologists: How can a pattern that should be influenced by
many different and biologically idiosyncratic processes appear so
similar across scales, taxonomic groups, and ecological systems?

Recently a theory was proposed ([Harte et al.
2008](http://www.esajournals.org/doi/abs/10.1890/07-1369.1), [Harte et
al.
2009](http://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2009.01328.x/abstract))
which suggests that detailed knowledge of the complex processes that
influence the increase in species number may not be necessary to
accurately predict the pattern. The theory proposes that ecological
systems tend to simply be in their most likely configuration.
Specifically, the theory suggests that if we have information on the
total number of species and individuals in an area then we can predict
the number of species in smaller portions of that area.

Published work on this new theory suggests that it has potential for
accurately predicting how species number changes with area; however, it
has not been appreciated that there are actually four different ways
that the theory can be operationalized to make a prediction.  We were
interested to learn

1.  Can the theory accurately predict how species number changes with
    area across many different ecological systems, and
2.  Do the different versions of the theory consistently perform better
    than others

To answer these questions we needed data. We searched online and made
requests to our colleagues for datasets that documented the spatial
configuration of ecological communities.  We were able to pull together
a collection of 16 plant community datasets. The communities spanned a
wide range of systems including hyper-diverse, old-growth tropical
forests, a disturbance prone tropical forest, temperate oak-hickory and
pine forests, a Mediterranean mixed-evergreen forest, a low diversity
oak woodland, and a serpentine grassland.

![](https://lh4.googleusercontent.com/QpJ3-tZWDG2fT1Ipj-G_HxRHwMZGm3zjtBzhAnhjP66hOIEuw8mNafEvZgO6bNesZo_FKG60J-OQoCN5qwr3FI9oR0Zj8UqWXNyhkLjqqnANBzQnR30u1B7UMQ){width="624px;"
height="343px;"}

Fig 1. A) Results from one of the datasets, the open circles display the
observed data and the lines are the four different versions of the
theory we examined.  B) A comparison of the observed and predicted
number of species across all areas and communities we examined for one
of the versions of the theory.

Across the different communities we found that the theory was generally
quite accurate at predicting the number of species (Fig 1 above), and
that one of the versions of the theory was typically better than the
others in terms of the accuracy of its predictions and the quantity of
information it required to make predictions. There were a couple of
noteworthy exceptions in our results. The low diversity oak woodland and
the serpentine grassland both displayed unusual patterns of change in
richness. The species in the serpentine grassland were more spatially
clustered than was typically observed in the other communities and thus
better described by the versions of the theory that predicted stronger
clustering. Abundance in the oak woodland was primarily distributed
across two species whereas the other 5 species where only observed once
or twice. This unusual pattern of abundance resulted in a rather unique
S-shaped relationship between the number of species and area and
required inputting the observed species abundances to accurately model
the pattern.

The two key findings from our study were

1.  The theory provides a practical tool for accurately predicting the
    number of species in sub-samples of a given site using only
    information on the total number of species and individuals in that
    entire area.
2.  The different versions of the theory do make different predictions
    and one appears to be superior

Of course there are still a lot of interesting questions to address.
 One question we are interested in is whether or not we can predict the
inputs of the theory (total number of species and individuals for a
community) using a statistical model and then plug those predictions
into the theory to generate accurate fine-scaled predictions.  This kind
of application would be important for conservation applications because
it would allow scientists to estimate the spatial pattern of rarity and
diversity in the community without having to sample it directly. We are
also interested in future development of the theory that provides
predictions for the number of species at areas that are larger (rather
than smaller) than the reference point which may have greater
applicability to conservation work.

The accuracy of the theory also has the potential to help us understand
the role of specific biological processes in shaping the relationship
between species number and area.  Because the theory didn't include any
explicit biological processes, our findings suggest that specific
processes may only influence the observed relationship indirectly
through the total number of species and individuals. Our results do not
suggest that biological processes are not shaping the relationship but
only that their influence may be rather indirect.  This may be welcome
news to practitioners who rely on the relationship between species
number and area to devise reserve designs and predict the effects of
habitat loss on diversity.

If you want to learn more you can [read the full
paper](http://dx.doi.org/10.7717/peerj.212) (it's open access!) or check
out the [code underlying the
analysis](https://github.com/weecology/mete-spatial) (it's open source
and includes instructions for replicating the analysis!).

References:

Harte, J., A. B. Smith, and D. Storch. 2009. [Biodiversity scales from
plots to biomes with a universal species-area
curve](http://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2009.01328.x/abstract).
Ecology Letters 12:789--797.

Harte, J., T. Zillio, E. Conlisk, and A. B. Smith. 2008. [Maximum
entropy and the state-variable approach to
macroecology](http://www.esajournals.org/doi/abs/10.1890/07-1369.1).
Ecology 89:2700--2711.


This is a guest post by Dan McGlinn, a weecology postdoc (@DanMcGlinn on Twitter). It is a Research Summary of: McGlinn, D.J., X. Xiao, and E.P. White. 2013. An empirical evaluation of four variants of a universal species–area relationship.

Exploring MaxEnt based species-area relationship predictions [Research Summary]

*Communicating research more broadly is not only important for outreach
to the public, but with the rapidly expanding literature, we think it'll
also be important for communicating to other scientists. Back in 2012 we
started a post type called \[Research Summary\] which is based on the
idea that people might not have time to read a multi-page paper but
might be willing to read a \<1000 word post conveying the ideas in the
paper in a more casual format. Ethan [did one of
these](http://jabberwocky.weecology.org/2012/05/17/characterizing-the-species-abundance-distribution-with-only-information-on-richness-and-total-abundance-research-summary/)
for an Ecology paper his group published last year. Below, one of our
graduate students, Sarah Supp, has taken up the challenge to communicate
about her first-authored Ecology paper that just came out and has
written the guest post below.*

*Now, introducing, [Sarah
Supp](http://weecology.org/people/sarahsupp/Sarah_Supp/Welcome.html)
([@srsupp](https://twitter.com/srsupp) for those on twitter):*

\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*

*This is a research summary of: S. R. Supp, X. Xiao, S. K. M. Ernest,
and E. P. White. 2012. An experimental test of the response of
macroecological patterns to altered species interactions. Ecology 93:
2505-2511.*
[*doi:10.1890/12-0370.1*](http://www.esajournals.org/doi/pdf/10.1890/12-0370.1)

While many ecologists focus on why individuals, species, or ecological
habitats differ, macroecologists are often fascinated by *similarities*
among different groups or ecosystems. This focus on similarities emerges
because macroecologists treat individuals, populations and species as
ecological particles, and identify patterns in the structure of these
particles to understand ecological systems and organization.

Despite a long history of documenting macroecological patterns, an
understanding of *what* determines pattern behavior, *why* patterns are
so easily predicted by so many different models, and *how* we should go
about addressing real ecological problems using a macroecological
approach has still not been reached.

Three common macroecological patterns, and the focus for our study,
include: the species abundance distribution (SAD; distribution of
abundance across species), the species-area relationship (SAR;
accumulation of species across spatial scales), and the species-time
relationship (STR; accumulation of species through time). Since these
patterns exhibit regular behavior across taxonomic groups and ecological
habitats, they are increasingly being used to make inferences about
local-scale ecological processes and to inform management decisions.

<figure id="attachment_1169" class="wp-caption alignnone"
aria-describedby="caption-attachment-1169" style="width: 604px">
<a
href="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/macroecological-patterns.png"><img
src="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/macroecological-patterns.png?resize=604%2C223"
class="size-full wp-image-1169" loading="lazy" decoding="async"
data-attachment-id="1169"
data-permalink="https://jabberwocky.weecology.org/2013/01/16/do-macroecological-patterns-respond-to-altered-species-interactions-research-summary/macroecological-patterns/"
data-orig-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/macroecological-patterns.png?fit=851%2C315&amp;ssl=1"
data-orig-size="851,315" data-comments-opened="1"
data-image-meta="{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;}"
data-image-title="Macroecological patterns" data-image-description=""
data-image-caption="&lt;p&gt;Diagrams of three macroecological patterns and how they could potentially respond to changes in the removal of seed-eating rodents. Left: Species-Abundance distribution (SAD), Middle: Species-Area Relationship (SAR), Right: Species-Time Relationship (STR)&lt;/p&gt;
"
data-medium-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/macroecological-patterns.png?fit=300%2C111&amp;ssl=1"
data-large-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/macroecological-patterns.png?fit=851%2C315&amp;ssl=1"
data-recalc-dims="1" width="604" height="223"
alt="Diagrams of three macroecological patterns and how they could potentially respond to changes in the removal of seed-eating rodents. Left: Species-Abundance distribution (SAD), Middle: Species-Area Relationship (SAR), Right: Species-Time Relationship (STR)" /></a>
<figcaption>Diagrams of three macroecological patterns and how they
could potentially respond to changes in the removal of seed-eating
rodents. Left: Species-Abundance distribution (SAD), Middle:
Species-Area Relationship (SAR), Right: Species-Time Relationship
(STR)</figcaption>
</figure>

Recently, discussion on how to do ecology has sometimes presented a
dichotomy between two groups: "species identity matters" vs. "species
identity is unimportant".  A more useful way of discussing the problem
likely lies in asking more nuanced questions such as: How important are
species identities for my specific question? When does species identity
impact ecological organization? At what spatial/temporal scales? When
are species identities necessary for prediction? For example, recent
models suggest that the identity of species within a community or
ecosystem is unimportant for predicting the shape of macroecological
patterns. Instead, these models suggest that some macroecological
patterns may only be sensitive to changes in the species richness or
total abundance of the ecosystem being examined. This idea is pretty
radical (in our opinion), but untested.

We took an approach that we felt could address a few problems
simultaneously: **1)** Does species identity play a role in determining
the form of macroecological patterns, or are patterns only sensitive to
changes in species richness or total abundance?  **2)** Can we
effectively synthesize our detailed knowledge of a system with a
macroscopic approach in order to link pattern with process?

We used 15 years of data from the [Portal](http://portal.weecology.org)
[Project](http://portalproject.wordpress.com/2012/12/07/whats-going-on-outside-the-portal-site/#comments),
our lab's long-term research site in southeastern Arizona, to evaluate
the response of the summer and winter annual plant communities to
selective removal of rodent seed predators. It is not known if altered
species identity alone (changes in species composition caused by
manipulating an important interaction, seed predation \[above\]) can
lead to shifts in the form of these patterns, in the absence of other
changes (such as species richness and total abundance). At the Portal
site, interactions within and among rodent and plant communities are
well studied and we felt that this made our site an ideal experimental
venue for this project. Among experimental treatments (control, kangaroo
rat removal, and removal of all rodents), we compared changes in plant
species composition, species richness (S), total abundance (N), and the
form of each of the macroecological patterns (SAD, SAR, and STR).  Below
are examples of the data for each pattern from plot 22, a control plot,
and a photo of a plant sampling quadrat. In the photo, California poppy
(*Escholtzia mexicana*) and Stork's bill dominate (*Erodium
cicutarium*).

<figure id="attachment_1170" class="wp-caption alignnone"
aria-describedby="caption-attachment-1170" style="width: 604px">
<a
href="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/plants.jpg"><img
src="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/plants.jpg?resize=604%2C453"
class="size-full wp-image-1170" loading="lazy" decoding="async"
data-attachment-id="1170"
data-permalink="https://jabberwocky.weecology.org/2013/01/16/do-macroecological-patterns-respond-to-altered-species-interactions-research-summary/plants/"
data-orig-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/plants.jpg?fit=720%2C540&amp;ssl=1"
data-orig-size="720,540" data-comments-opened="1"
data-image-meta="{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;}"
data-image-title="Plants" data-image-description=""
data-image-caption="&lt;p&gt;Example of sampling quadrat and observed empirical patterns from a specific experimental plot in 2008.&lt;/p&gt;
"
data-medium-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/plants.jpg?fit=300%2C225&amp;ssl=1"
data-large-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/plants.jpg?fit=720%2C540&amp;ssl=1"
data-recalc-dims="1" width="604" height="453"
alt="Example of sampling quadrat and observed empirical patterns from a specific experimental plot in 2008." /></a>
<figcaption>Example of sampling quadrat and observed empirical patterns
from a specific experimental plot in 2008.</figcaption>
</figure>

We found that plant species composition was *always* influenced by the
removal of kangaroo rats and by removal of all rodent seed predators.
Interestingly, we also found that removing kangaroo rats (keystone
species) *did not* influence plant species richness or total abundance.
This suggests that compensatory dynamics are at work. Finally, when we
compared the macroecological patterns among the experimental treatments,
we found differences in the macro-patterns *only* occurred when plant
species richness or total abundance was altered, and *not* by
compositional changes alone. (Below: Where the parameters *do not* cross
the dotted line, there were significant differences among the paired
manipulations \[R-C: total rodent removals vs. controls; K-C: kangaroo
rat removals vs. controls\]. Note that the only place this occurs is in
the winter annual community when species richness \[S\] and total
abundance \[N\] are affected by the removal of *all* rodent seed
predators. The rodent pictured is Merriam's Kangaroo Rat, *Dipodomys
merriami.*)

<figure id="attachment_1171" class="wp-caption alignnone"
aria-describedby="caption-attachment-1171" style="width: 604px">
<a
href="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/results.jpg"><img
src="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/results.jpg?resize=604%2C453"
class="size-full wp-image-1171" loading="lazy" decoding="async"
data-attachment-id="1171"
data-permalink="https://jabberwocky.weecology.org/2013/01/16/do-macroecological-patterns-respond-to-altered-species-interactions-research-summary/results/"
data-orig-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/results.jpg?fit=720%2C540&amp;ssl=1"
data-orig-size="720,540" data-comments-opened="1"
data-image-meta="{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;}"
data-image-title="Results" data-image-description=""
data-image-caption="&lt;p&gt;Does removing seed-eating rodents influence the shapes of macroecological patterns in plant communities? Depends on whether removing rodents influences species richness and/or total abundance of plants in the community. (Dashed line represents no difference between treatments)&lt;/p&gt;
"
data-medium-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/results.jpg?fit=300%2C225&amp;ssl=1"
data-large-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2013/01/results.jpg?fit=720%2C540&amp;ssl=1"
data-recalc-dims="1" width="604" height="453"
alt="Does removing seed-eating rodents influence the shapes of macroecological patterns in plant communities? Depends on whether removing rodents influences species richness and/or total abundance of plants in the community. (Dashed line represents no difference between treatments)" /></a>
<figcaption>Does removing seed-eating rodents influence the shapes of
macroecological patterns in plant communities? Depends on whether
removing rodents influences species richness and/or total abundance of
plants in the community. (Dashed line represents no difference between
treatments)</figcaption>
</figure>

So what does this mean? Let's revisit our initial questions:

**1)   ** **Does species identity plan a role in determining the form of
macroecological patterns, or are patterns only sensitive to changes in
species richness or total abundance? ** Our research suggests that the
key to interpreting and predicting patterns lies in our ability to make
realistic predictions of community level variables, such as species
richness or total abundance. Although changes in species richness or
total abundance were most the important predictors for change in our
macroecological patterns, we are not suggesting that changes in species
identity are inconsequential. In fact, we believe that our findings
suggest an important, but indirect role, for the role of species
interactions in determining macroecological patterns. Species
interactions may facilitate or hinder compensation dynamics, which in
turn may lead to shifts in the number of species or the total number of
individuals in response to manipulation. [In a recent
paper](http://130.111.193.18/unified.pdf), Brian McGill suggests that
what drives S and N is a central unanswered question in ecology.

**2)   ** **Can we effectively synthesize our detailed knowledge of a
system with a macroscopic approach in order to link pattern with
process?** We feel that our approach of using small-scale experimental
field data with macroecology (which has largely relied on large-scale
observational data) provides a potentially powerful framework for
improving our understanding of the linkages between pattern and process.
Studies using a similar approach may help bridge important gaps between
pattern and process, between local and regional scale ecology and
between basic and applied science.


<em>
 Communicating research more broadly is not only important for outreach to the public, but with the rapidly expanding literature, we think it’ll also be important for communicating to other scientists.
</em>

Do macroecological patterns respond to altered species interactions? [Research Summary]

*This is the first of a new category of posts here at Jabberwocky
Ecology called Research Summaries. We like the idea of communicating our
research more broadly than to the small number of folks who have the
time, energy, and interest to read through entire papers. So, for every
paper that we publish we will (hopefully) also do a blog post
communicating the basic idea in a manner targeted towards a more general
audience. As a result these posts will intentionally skip over a lot of
detail (technical and otherwise), and will intentionally use language
that is less precise, in order to communicate more broadly. We suspect
that it will take us quite a while to figure out how to do this well.
Feedback is certainly welcome.*

This is a Research Summary of: White, E.P., K.M. Thibault, and X. Xiao.
2012. Characterizing species-abundance distributions across taxa and
ecosystems using a simple maximum entropy model. Ecology.
<http://dx.doi.org/10.1890/11-2177.1>\*

The species-abundance distribution describes the number of species with
different numbers of individuals. It is well known that within an
ecological community most species are relatively rare and only a few
species are common, and understanding the detailed form of this
distribution of individuals among species has been of interest in
ecology for decades. This distribution is considered interesting both
because it is a complete characterization of the commonness and rarity
of species and because the distribution can be used to test and
parameterize ecological models.

Numerous mathematical descriptions of this distribution have been
proposed and much of the research into this pattern has focused on
trying to figure out which of these descriptions is "the best" for a
particular group of species at a small number of sites. We took an
alternative approach to this pattern and asked: Can we explain broad
scale, cross-taxonomic patterns in the general shape of the abundance
distribution using a simple model that requires only knowledge of the
species richness and total abundance (summed across all species) at a
site?

To do this we used a model that basically describes the most likely form
of the distribution if the average number of individuals in a species is
fixed (which turns out to be a slightly modified version of the classic
log-series distribution; see the paper or [John Harte's new
book]{target="http://www.amazon.com/Maximum-Entropy-Ecology-Distribution-Energetics/dp/0199593426/ref=sr_1_1?ie=UTF8&qid=1337197559&sr=8-1"}
for details). As a result this model involves no detailed biological
processes and if we know richness and total abundance we can predicted
the abundance of each species in the community (i.e., the abundance of
the most common species, second most common species... rarest species).

Since we wanted to know how well this works in general (not how well it
works for birds in Utah or trees in Panama) we put together a a dataset
of more than 15,000 communities. We did this by combining 6 major
datasets that are either citizen science, big government efforts, or
compilations from the literature. This compilation includes data on
birds, trees, mammals, and butterflies. So, while we're missing the
microbes and aquatic species, I think that we can be pretty confident
that we have an idea of the general pattern.

In general, we can do an excellent job of predicting the abundance of
each rank of species (most abundant, second most abundant...) at each
site using only information on the species richness and total abundance
at the site. Here is a plot of the observed number of individuals in a
given rank at a given site against the number predicted. The plot is for
[Breeding Bird Survey](http://www.pwrc.usgs.gov/BBS/) data, but the rest
of the datasets produce similar results.

<figure id="attachment_970" class="wp-caption aligncenter"
aria-describedby="caption-attachment-970" style="width: 604px">
<a
href="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2012/05/white_etal_2012_bbs_fig.png"><img
src="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2012/05/white_etal_2012_bbs_fig.png?resize=604%2C455"
title="white_etal_2012_bbs_fig" class="size-full wp-image-970"
loading="lazy" decoding="async" data-attachment-id="970"
data-permalink="https://jabberwocky.weecology.org/2012/05/17/characterizing-the-species-abundance-distribution-with-only-information-on-richness-and-total-abundance-research-summary/white_etal_2012_bbs_fig/"
data-orig-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2012/05/white_etal_2012_bbs_fig.png?fit=812%2C612&amp;ssl=1"
data-orig-size="812,612" data-comments-opened="1"
data-image-meta="{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;}"
data-image-title="white_etal_2012_bbs_fig" data-image-description=""
data-image-caption="&lt;p&gt;Observed-predicted plot for ~3000 breeding bird survey communities. Since there are over 100,000 points on this plot we’ve color coded them by the number of points in the vicinity of the focal point, so red areas have lots of points nearby and blue areas have very few points. The black line is the 1:1 line.&lt;/p&gt;
"
data-medium-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2012/05/white_etal_2012_bbs_fig.png?fit=300%2C226&amp;ssl=1"
data-large-file="https://i0.wp.com/jabberwocky.weecology.org/wp-content/uploads/2012/05/white_etal_2012_bbs_fig.png?fit=812%2C612&amp;ssl=1"
data-recalc-dims="1" width="604" height="455"
alt="Observed-predicted plot for Breeding Bird Survey data showing a good ability of the model to predict the observed data." /></a>
<figcaption>Observed-predicted plot for nearly 3000 <a
href="http://www.pwrc.usgs.gov/BBS/">Breeding Bird Survey</a>
communities. Since there are over 100,000 points on this plot we’ve
color coded them by the number of points in the vicinity of the focal
point, so red areas have lots of points nearby and blue areas have very
few points. The black line is the 1:1 line.</figcaption>
</figure>

The model isn't perfect of course (they never are and we highlight some
of its failures in the paper), but it means that if we know the richness
and total abundance of a site then we can capture over 90% of the
variation in the form of the species-abundance distribution across
ecosystems and taxonomic groups.

This result is interesting for two reasons:

First, it suggests that the species-abundance distribution, on its own,
doesn't tell us much about the detailed biological processes structuring
a community. Ecologists have know that it wasn't fully sufficient for
distinguishing between different models for a while (though we didn't
always act like it), but our results suggest that in fact there is very
little additional information in the distribution beyond knowing the
species richness and total abundance. As such, any model that yields
reasonable richness and total abundance values will probably produce a
reasonable species-abundance distribution.

Second, this means that we can potentially predict the full distribution
of commonness and rarity even at locations we have never visited. This
is possible because richness and total abundance can, at least
sometimes, be well predicted using remotely sensed data. These
predictions could then be combined with this model of the
species-abundance distribution to make predictions for things like the
number of rare species at a site. In general, we're interested in
figuring out how much ecological pattern and process can be effectively
characterized and predicted at large spatial scales, and this research
helps expand that ability.

So, that's the end of our first Research Summary. I hope it's a useful
thing that folks get something out of. In addition to the science in
this paper, I'm also really excited about the process that we used to
accomplish this research and to make it as reproducible as possible. So,
stay tuned for some follow up posts on big data in ecology,
collaborative code development, and making ecological research more
reproducible.

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------  
\**The paper will be Open Access once it is officially published but
,for reasons that don't make a lot of sense to me, it is behind a
paywall until it comes out in print.*


<em>
 This is the first of a new category of posts here at Jabberwocky Ecology called Research Summaries. We like the idea of communicating our research more broadly than to the small number of folks who have the time, energy, and interest to read through entire papers. So, for every paper that we publish we will (hopefully) also do a blog post communicating the basic idea in a manner targeted towards a more general audience.
</em>

Publicaciones de Rogue Scholar

Why I like this: Martorell and Freckleton (2014)

Exploring MaxEnt based species-area relationship predictions [Research Summary]

Do macroecological patterns respond to altered species interactions? [Research Summary]

Characterizing the species-abundance distribution with only information on richness and total abundance [Research Summary]