what brian reads

Biodiversity measurements

2009-06-15T09:27:00.003-06:00

Steinmann, Linder, and Zimmermann. 2009. Modelling plant species richness using functional groups. Ecological Modelling

In the ever-elusive goal of better plant richness modelling, these folk take on the challenge by using various higher order divisions in their models, to see what shakes out best for modelling plant species richness across Switzerland. They mainly attempted a middle-path sort of route- not a bottom-up, model the individual plant responses to environmental gradients and then overlay all those maps together (a common approach which completely disregards community interactions), and not a top-down, community model which doesn't model individual species responses (an obvious deficiency).

They found little benefit to their approach, which was sort of a let-down- but, in another way, refreshing. Non-results are rarely published, which is a shame. There was an interesting facet in that some functional groups were modeled far better than others, indicating some interesting differences (but, one of the best were trees, which usually model well because of their longevity and, therefore, sensitivity to environmental factors/relative immunity from stochastic events).

Rocchini, Chiarucci, and Loiselle. 2004. Testing the spectral variability hypothesis by using satellite multispectral imagery. Acta Oecologica

My interest in the spectral variability hypotheses (also described in an earlier post about Palmer, et al 2002) stems mainly from my dislike of classified imagery as such. It eliminates so much information from the image, and locks you into whatever errors are present at the time of the classification. The SVH is a way around it, but relatively unexplored. Rocchini and others seem to be the only group working on the idea, and they always use high spatial resolution stuff (they also have a kicking dataset, like Steinmann et al, which apparently they get mostly from other people. Lucky.). They've published a few more papers on the idea, but this 2004 is the first, so... start at the beginning.

They explain ~50% of the species richness at a 1 ha scale (over landscapes, of course), which is pretty impressive, since it's all done without looking at the individual spectral responses of the plants. The image is ground-truthed, of course, but only by count; i.e. anybody can do that, without any special tools. Plus, this is with Quickbird, so it's only four bands, and I'd bet good money you can improve on that 50% really easily with some higher spectral resolution stuff. At 30 m Landsat? That's a good question, and I'm sure it really depends on the scale of vegetiation present. People have used NDVI for this sort of thing via Landsat (Gould 2000), but I'm unaware of any attempts at full-on variability style methodologies.

VP free

2009-06-12T16:38:00.002-06:00

Variance partitioning
In an attempt to re-understand VP, I’m going to attempt to explain it to myself in word-form…

Variance, in regressions, is always present. R2 values are given to illustrate the amount of variance the model (regression) explains. Multiple regressions use several variables (x1, x2, etc) in an attempt to explain the response variable (y); each x contributes some “explanatory power” to the model. That’s stuff we know already…

How much does each x contribute to the explanatory power of the model? Well, first note that the order of insertion of independent variables into the model doesn’t change the final result (x1b + x2b + x3b…). Intermediate results will differ, but the final result is the same. Secondly, the contribution (in terms of increasing r2, if that’s our scorecard) of the second variable entered will change depending on what was entered first. Not only that, some variables which don't add anything to r2 might still be important, as they could mediate the effect of another variable in some important way. Overlapping disturbances would be a candidate.

Basically, it appears that you look at the change in r2 when each independent variable is added last, and then call that difference the “unique variance.”
Nothing super new so far, it’s the commonality analysis which seems like it’ll be useful- is it possible to look at the influence of A on B even if A adds nothing to an explanatory model of B, but mediates the effect of variable C on B?

Perhaps it works this way: A -> B <- C

Or this: C -> A -> B <- C

In the second case, A would appear, in a regression, to add nothing to a predictive model of B, but perhaps it’s mediating the effect of C in some way. Since they are correlated, it would be difficult (impossible?) to separate the two influences specifically, but perhaps it would be possible to get a measure of the importance of C via subtraction…

VARIATION PARTITIONING OF SPECIES DATA MATRICES: ESTIMATION AND COMPARISON OF FRACTIONS
Pedro R. Peres-Neto1, Pierre Legendre, Stéphane Dray, and Daniel Borcard
Ecology 87(10)

Haven't been posting, but have been reading...

2009-06-12T09:09:00.003-06:00

This morning-

Palmer, M., et al. 2002. Quantitative tools for perfecting species lists. Environmetrics. 13:121-137

Zimmermann, N., et al. 2007. Remote sensing based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah. Journal of Applied Ecology. 44:1057-1067

Ecosystem Values

2009-01-21T12:52:00.002-07:00

Social Goals and the Valuation of Ecosystem Services. Costanza 2000

A good read, although I disagreed with most things. There are a few interesting statements which I think are worth considering.

First, the paper makes the arguement that valuation of ecosystem services is inevitable, and all choices can be evaluated via projection of relative value (i.e. we choose x over y, therefore x is more valuable than y). I disagree. That is the dominant economic paradigm of our society (both now and historical). But it's not impossible to think of other thought paradigms where this inevitable tradeoff doesn't occur. It's not that choices are not made, but they are not seen in the same light. Therefore, the thought of "inevitable valuation" doesn't even occur. For example, if you don't care between two outcomes, than there's no assumption of value necessary. Or, if you are at state A and are choosing to either transform A to B or leave A alone, you could just consider it a transformation, not a tradeoff.

Building Lego's (should I build an airplane or a boat?) doesn't require a choice between the two based on value, because the inherent thing isn't changed, just altered. The assignment of value is a Western paradigm, and sure, it can be applied to every situation. But so could a paradigm based on choosing whatever option was mentioned first, or options whose title comes first in the alphabet. Those are silly, but they are still options.

I am annoyed with this "let's take this paradigm for granted," because once you start down the valuation path, ecosystems lose. Maybe not today, maybe not tomorrow, but soon... they lose. Today, wetlands purify our water cheaper then we can. But tomorrow, we invent a new technology which purifies water cheaper. All of a sudden, those wetlands have lost value. And putting astetic value (in terms of money) on ecosystems, or even moral value, will only fail in the long run- conservation is a luxury of the rich, as many have said, and people will always choose food over furry friends (and let's be honest, bringing the whole world to our level of luxury won't happen. even if it does, we'll want more, and the problem will begin all over again).

Later, the author says "valuation ultimately refers to the contribution of the item to meeting a specific goal or objective," and "one cannot state a value without stating the goal being served." So without a goal, something has no value? This is a very user-centered view of the world, which is what got us into this mess in the first place.

He argues "the decisions we make, as a society, about ecosystems imply valuations." Sure, according to the paradigm of "everything is a tradeoff between two values." But I think that thought process is what gets us into trouble in the first place. The philosophy of assigning values moves easily into saying "well, this place is nice, but I can make money building condos. I'll just donate to the Sierra club and conserve through them." Thinking in terms of valuation leads to only thinking in the present tense (and one time step ahead). It's all now- you choose between two options now.

Perhaps thinking in terms of place would work better. Thinking in terms of place doesn't assign value (although the valuation paradigm can be imposed on it, of course). Thinking in terms of place assigns consequences. It's not inherently a tradeoff between a human affected environment and a "pristine natural environment," it's just the environment and how it's changed. This leads to longer term thinking- if I do x, and want to do y later, is that possible? How should I structure x so that y is possible in 10 years?

I (being a good Western thinker in the tradition of the liberal arts) assign value unconsciously, as do most people around me. But our society has REALLY screwed up the planet we're supposed to steward- so perhaps that paradigm needs rethinking. I assign great moral value to "unspoiled lands," although even that term implies valuation. But somebody else sees unlimited development, or great beauty in a golf course. The vaguries of human perceptions of beauty are such that eventually, all land will be in control of somebody that thinks it will look better as a community rec center, and our development is far easier carried out then undone. If we rely on valuation to save landscapes, we're going to lose.

Climate change and range shifts

2009-01-21T12:32:00.003-07:00

Predicting climate-induced range shifts: Model differences and model reliability. Lawler et al, 2006

Modeling! Modeling in R, which is more impressive. This is a great paper- not in terms of being particularly interesting, or revolutionary, but in terms of usefulness. There needs to be more papers like this, a straightforward comparison between modeling approaches using the same data, so relative errors, types of errors, etc can all be directly seen. The researchers take 100 different mammal species present in and around Brazil, and model their current distribution based on nine climate variables and one land cover variable- basically the inputs for most climate change scenarios. Then, they compare the results to actual distributions. Fun.

There are some interesting results. Random forest models were far and away the best. Genetic algorithms were second place, although they had problems with errors of commisson. Other models, like classification trees, GAMs, etc did relatively worse. I'd hypothesize that random forests did better specifically because they sampled from the 10 inputs with replacement, meaning they randomlly added weights to the various factors, so there was an added feature that neural networks and the other machine learning algorithms didn't have.

But, like all models, they have their problems, which follow.....

Prediction of plant species distributions across six millenia. Pearman et al, 2008.

This is a more applied study, where Pearman and friends attempt to model tree species in Europe. For a twist, they model from 6000 BP to now, 6000 BP only, and now only, in an attempt validate future predictions (using past climate records and pollen finds). Their main finding was that some species are modeled quite well, and others not so well- the ones which came out winners are dominant competitors for light. This makes perfect sense, and highlights the main limitation of this study, Lawler's, and most other species distribution models I've seen (and they readily admit to this limitation as well). Light competition is the only way in which most plants experience biotic constraints on their distribution. Most plants don't interact directly, especially these trees, beyond the race for good spots in the canopy. Thus, species which are competitively dominant won't really experience biotic controls on their distribution, because wherever they live, they win. Species which are not competitively dominant will experience this biotic limit to their range, and therefore models which don't take biotic factors into account won't be as accurate.

A second limition is both assume that species are at current equilibria with respect to their distribution. But the Johnstone article (reviewed earlier) indicates that some species are still expanding their range, invalidating this assumption.

Pearman also mentionsthe possibility of rapid niche shifts, which I don't know much about, but which would also invalidate predictions into the future.

RS and N (no weeds)

2009-01-15T15:18:00.003-07:00

Canopy nitrogen, carbon assimilation, and albedo in
temperate and boreal forests: Functional relations
and potential climate feedbacks
S. V. Ollinger, et al.

Another remote sensing paper, and it continues on with my recent readings in foliar nitrogen. The researchers use AVIRIS (and a little Hyperion, where necessary) to estimate foliar nitrogen levels over a few landscapes in temperate/boreal forests scattered over Canada. I received this paper after emailing S. Ollinger himself about some AVIRIS work he's doing, and he graciously sent me this along with a few thoughts... but back to the paper. They found a strong relationship between measured foliar N and reflectance across most of the NIR spectrum- cool, because that means you can get foliar N estimates from other (read: free) sensors. To quote directly:

"Collectively, these results suggest that we already have a basis
for detecting variation in %N and CAmax of forest canopies at
continental scales by using scaled relationships with albedo
and/or simple measures of NIR reflectance obtained during the
peak period of the growing season."

Then, they tie the N measurements to carbon fixation, using flux towers (through BOREAS sites I assume; I believe that's where the imagery is). All well and good.

My thoughts, to tie into the previous post, are about using this foliar N to potentially address biodiversity levels, potential for invasion, and perhaps even invasion monitoring (I don't know a lot of biogeochemistry, so hopefully I don't say something dumb at this point, but I'll try anyway). Would higher biodiversity sites (in the understory: say vascular plants, or invertebrates, or whatever) also have higher foliar N in the overstory? I would imagine so, given simple things like nutrient availability, more potential niches, etc. Would invasive species be reflected in the overstory N (either via nitrogen fixation themselves, like Scotch broom or sea buckthorn, or by exclusion of other nitrogen fixing plants, see previous post)? To speculate further (what fun!), what would the edge of higher nitrogen zones look like? If you look at the map in the paper, there's a lot of heterogeneity in the foliar nitrogen levels across forests- so... could any sort of meta-population/meta-community dynamics be happening across that edge?

Remote Sensing and Weeds

2009-01-15T14:58:00.003-07:00

Remote analysis of biological invasion and biogeochemical change

Gregory P. Asner and Peter M. Vitousek

More weeds, this time over to Hawaii for my favorite tree, Myrica faya (I believe it was recently renamed, because I learned it as M. faya and then was told there was a new name, but can't remember it). One of my favorites because the wood isn't super dense, and it's hackable with a machete when doing invasive species control.

Regardless, it's a nitrogen fixing invasive, and the Asner/Vitousek study looks at using foliar N as measured via AVIRIS to detect M. faya prior to it's domination of the canopy. It works, quite well. And for another note, they also found they could detect another invasive, a ginger (and not a fun thing to attempt to control), via water content measurements from AVIRIS- and it's an understory plant. This is a slight vindication for me, since I heard that something like this was possible from Greg in Hawaii, but when taking remote sensing back in Washington later, was told that sensing anything below the canopy wasn't possible. Awsome, it's in print.

This has me thinking: Scotch broom is another invasive species, nitrogen fixing, present in the west and up into BC and Alaska. While I don't think it makes it to the canopy, I wonder if you can detect it's presence via overstory N levels, especially since foliar N seems to be pretty low in most of our forests. The next review has a paper which also inspires that thought....

Fire! Weeds!

2009-01-15T14:49:00.002-07:00

Fire and invasive species within the temperate and boreal Coniferous forest of western North America
RJ Harrod, S Reichard - Proceedings of the Invasive Species Workshop, 2000 - jfsp.nifc.gov

Ah, fire. The ubiquitous disturbance that northern forests deal with on a regular basis, and one of the few bringers-of-heterogenity which can be relied on to make things interesting, especially where invasive species are concerned. This paper gives a general overview of the ways that weeds exploit fire for spread, through several potential life strategies. Not a bad review. Of interest are some reviews of fire regimes to kill of invasive species (3 years of early fires to kill yellow starthistle, for instance (although they also mention that early fires are thought to kill Canadian thistle, which in my experience is invincible)).

The later parts of the paper lapse into a discussion of potential influences on the fire regime itself by invasives- namely Bromus tectorums increase of the fire cycle (well evidenced) and spotted knapweeds decrease of the fire cycle (is there evidence for that?).

On another note, I think it might be useful to not think of invasive species as "special," since they invade a post-fire environment just like any other species- it's just that they nearly always win the colonization race, and then (potentially) control the site in perpetuity. Perhaps they are playing with a stacked deck, since they might have gotten some enemy-release help, but the mechanics are often the same.

Long overdue!

2009-01-12T09:23:00.002-07:00

It's been a month! Ridiculous. But I've read quite a bit over the break, since Audrey and I stayed in Boulder and most other people didn't- it's been nice and relaxing. I'll just list a bunch of the highlights....

Books: Alaska's Changing Boreal Forest (an LTER book). Stuart Chapin, et al.
Great resource. Balances hard science with good writing, which doesn't seem to be very common in books. Very interesting, especially the parts related to forest and permafrost dynamics. They have quite a bit on successional communities, but nothing on any multiple disturbance sites. Also has some interesting info on fire patterns in Alaska. Quite well cited, no real complaints.

Canada's Boreal Forest, J. D. Henry, Smithsonian Press.
A lighter read, more literary, but still cited and grounded. I read through it expecting a little more ecology, but the strength of the book really lies in the cultural issues associated with resource extraction and climate change. Light enough to read for a break from the LTER book, so it was a nice complement. Not a resource for research, however.

Some papers:
Development of a large area biodiversity monitoring system driven by remote sensing. Duro et al. 2007. Progress in Physical Geography
-More of a project proposal, these folks are trying to get a system set up for monitoring northern Canada (and Alaska, basically) for changes in biodiversity, disturbance patterns, etc. It's not entirely a clear proposal, and it seems more like an idea-sheet than an actual plan at this point. I'm going to reread it and see what else I can get out of it after the first read.

Non-equilibrium succession dynamics indicate continued northern migration of lodgepole pine. Johnstone and Chapin, 2003. Global Change Biology.
-An interesting proposal. They argue that lodgepole pines are still moving north post-glacial period. There's a couple interesting thoughts about this- anthropogenic climate change isn't the driving force behind lodgepole's movements north, and most models are based on static assumptions (the pines live where the pines can live), but if the distribution is moving north and that movement is not tied to a changing climate, then those assumptions are incorrect. (They also assume that plant species migrate individualistically, which I disagree with. Plants migrate according to their local and distributional environment- they move to where they can live. But a plants potential habitat is not just the abiotic factors like temperature and climate, which this paper and most other models assume, a plant's potential habitat must also take into account the biotic factors too. In other words, plants may TRY and migrate individualistically, but their success is tied to a community migrating (or a suitable, but different, community existing elsewhere)). Another issue with their conclusion is the potential for some source-sink population effects going on- there's not any evidence presented which shows that these new stands of lodgepole springing up after disturbance in spruce forests are going to survive, reproduce, and spread the species north- could be a sink population, or a less viable population anyway, leading to a more ragged edge to lodgepole distribution but not necessarily a moving-north distribution.

Extending community ecology to landscapes. Urban, et al. 2002. Ecoscience.
-Decent paper which explores sampling problems related to doing community ecology on a landscape level. All in all, they look into some interesting ways to calculate sample sites and sample number, including randomized ideal with planned sites to match that ideal on a logistically possible level.

Biogeography and landscape ecology. M. Kent. 2007. Progress in Physical Geography.
Landscape ecology: What is the state of the state. M. Turner. 2005. Ann. Rev. Ecol. Evol. Sys.

There were/are many more, but I'll leave those for now.

Any recommendations?

Metacommunties and RS

2008-12-03T11:23:00.003-07:00

Haven't posted in a while, Thanksgiving saw a lot of friends in town. But another reason is this book, which I've been reading for a while (along with several articles, of course). Books quite interesting, and according to a few folk, this is the current authority on metacommunities. It seems to me that metacommunity theory is a bridge between non-spatial population/community ecology and the spatial landscape ecology- exactly what I'm interested in. Currently I'm reading about pitcher plant/invertibrate metacommunities, which offer an intersting system of spatially seperate habitat which is temporally variable, requiring dispersal between the patches- similar to clear cuts, disturbances, etc in forests. Good stuff. It's a well written book so far.

Other things recently read:
Lucas 2008. Hyperspectral remote sensing to assess vascular plant specices richness. Remote Sensing of the Environment
-Pretty good, but they didn't find any good predictors without first defining habitat class. Not necessarily a problem, but an additional step. I wonder if they would have had more predictive power with some unmixing.

Gillespie 2008 Assessing biodiversity from space. Progress in Physical Geography
-Great review. Still reading through the references, but the stuff on assessing alpha and beta diversity via remote sensing is extremely interesting, especially considering that models of invasive species typically only focus on abiotic environments, but should (according to several people) include info on biotic interactions- one aspect of which is indicated by the general biodiversity in the area. Plus, rapid identification of biodiversity hotspots- even on the local scale- would be extremely useful for conservation.

Tang 2007 Improving urban classification through fuzzy SMA.
-Not bad. They take mixed pixels, and instead of just doing traditional linear unmixing, they also use the mixed means and covariances in determining endmembers, sort of a "fuzzy endmember" (which is reminiscent of endmember bundles, Asner/Wessman/etc. (in fact, I'm not sure as to the actual difference at this point)). The paper didn't describe methods that well, so I'm not sure as to the mechanics, but the concept makes sense. It was unmixed based on only a few classes determined from hyperspatial info. I wonder if you could use neighboring pixel stuff in conjunction with fuzzy endmembers to improve classification.

Invasions!

2008-11-13T11:11:00.002-07:00

Exotic taxa less related to native species are more invasive. Strauss, et al. PNAS 2006

Species invasions and extinction: The future of biodiversity on islands. Sax amd Gaines. PNAS 2008

So, it's been a while since I posted! I've been reading quite a bit, just keep forgetting to post on it. Which is unfortunate, I think this'll be a good resource later, when I remember reading something but don't remember where....

First off, the species invasions and extinctions paper was a fun read, although a little dissatisfying in terms of their conclusions. Also, it contradicts the work I did in Hawaii. They claim that, so far, native plant species richness has not really declined on islands, whereas vertebrate richness has. Vertebrate richness decline is pretty well known, I think they would have been better served just focusing on plants. In Hawaii, however, many plants are being driven to extinction by invasives. Their inclusion of New Zealand might have potentially skewed their results- NZ is so large, from a plant’s perspective, that it would provide numerous refugia and sub-optimal habitat in which, potentially, a plant species could persist. Most other islands, however, are much smaller, not providing such respite from the invasion. I realize it was a large scaled study, and so included lots of variation, but the predictions would be different for smaller islands with less topographical variation (and less area in general). At least in Hawaii, competition with invaders is a major cause of native species going extinct. But, perhaps it’s a special case- I doubt it, I think it’s more related to island size. I also believe their case would have been strengthened had they included functionally extinct species in the “extinct” column (and they imply that they think so too), but they only included actual extinctions. The other paper was quite cool, and directly addressed one of my questions earlier in the semester. Basically, the more unrelated an introduced species is to the native flora, the more likely it is to be a pest species, supporting the enemy release hypothesis and Darwin’s naturalization hypothesis (in that species more closely related often succeed, but don’t become pests because of in-common predators). It makes me wonder a few things- would a dramatic change in disturbance regimes cause native species to become pests, or would natural controls ramp up fast enough? Are globally distributed pest species (like the verbena family) more phylogenetically isolated as a whole? Is there also a phylogenetic relationship with the most impacted species from an invasion (seems less likely, in that the most impacted species is probably more a function of morphological traits and life histories)?

Neutral theory tested by birds, Ostling 2006 and Coexistence of Neutral and Niche Perspectives, Liebold 2006

2008-10-23T09:58:00.001-06:00

Ostling presents a case study on birds testing neutral theory over the whole of South America, and finds it lacking. No real surprise there, on a regional scale differences in habitat and niches should predominate in determining species communities. But on a smaller scale, neutral theory isn't ruled out either, as Liebold makes the point of noting (of course, niche theory isn't excluded either). Both papers seem to make the point that a blend of the two views is appropriate (usually), and the degree of blending depends on the community in question, the scale of investigation, and the evolutionary history of the species. I'm wondering if it's fair to say that if within species phenotypic variation (averaged over all ecologically important traits) is greater than between species variation in a given ecological setting then neutral interactions will predominate, and if between species variation is greater then niche differentiation will predominate. Neither excludes the other completely, of course. I also found this prediction by Liebold pretty interesting- equivalent species should be more prevalent in areas more recently subjected to ecological upheavals. If that's the case, we should have a lot of evidence around us from the recent glaciation of N America. Second, I wonder if species previously considered "recently speciated" or "on their way to divergence" might actually be endpoints (i.e. ecological selection forces are no longer actively driving the two species apart), different species maintained by neutral interactions, rather then simply species on their way to more dramatic speciation. This neutral theory stuff is intersting to me- I don't have a lot of background in it. Apparently it was popularized after I finished my undergrad. I always thought of it more as a foil, a null model like the Hardy-Weinburg, to test more robust theories against. Cool to read about it's actual application, and even if it turns out to be just a null model in the end, it's still certainly generated a lot of good thought.

Intermediate Disturbance Hypothesis, Fractal landscapes, and heterogeneity

2008-10-22T08:00:00.005-06:00

A pretentious title of sorts, but... I was reading through "the effect of landscape structure on community self-organization and critical biodiversity" (With 2004), which is quite interesting, and noticed a connection between her landscape structure creations and disturbance maps. Her fractal landscapes (ranging from random to highly ordered) look just like different disturbance maps, corresponding to small, frequent disturbances to rare, large disturbances. The connection wasn't made in her paper, but it's still kind of cool. Then, thinking about how landscape biodiversity is usually a simple function of the amount of habitat available, I put together a graph combining those two ideas, mostly for myself to try and clarify the relationship. Hopefully it makes sense. The boxes on the left show the types of habitat in the different setups, I didn't indicate edge on the two lower ones, but they are there. It requires not thinking about edges as "effected interior habitat," but rather considering them unique habitat in their own right, which is a fair statement, I imagine. Second, all of those boxes on the left are supposed to have the same amount of black and white (before edges are taken into account) so there's no change in the amount of habitat before edges from highly clumped (top) to highly fragmented (bottom). This would also place Kendi's invasibility work right in the middle too.

Note that landscape heterogeneity peaks in the middle. Forgot to put that line in.

Now that I post that, I think it's probably a pretty trivial and obvious relationship. But... it's there now, and I need to go vote, so it's staying up. Cheers.

On the importance of landscape history for assessing extinction risk, Schrott (2005), Ecological Applications

2008-10-17T11:20:00.004-06:00

Pretty interesting paper detailing the risk of extinction in various landscape situations over time, and showing the potential for lagged responses in population size. If there's a lagged response, then any population viability assessment could be quite erroneous if based on only the current situtation, and not looking at the past history. Makes sense. It's pretty theoretical, so there are several arbitrary deliniations for a viable population, threshold values, etc, but that's fine. Of course, there is a caveat that extinction thresholds are so different for individual species that a cookbook approach (i.e. how much habitat is "enough") is to be avoided- but then the whole paper is "strategic," in that it's meant to be applicable broadly... So when calculating suitable and unsuitable habitat, aren't you more or less calculating what is "enough?" Perhaps splitting hairs and being unfair to a theoretical argument, I suppose.

One problem is the way they calculate spread. Both the persistence and the "invasion" calculations are the same, i.e. the species has the same chance at persistence in suitable habitat as it does spread into neighboring suitable habitat. Work by Kendi has shown that in many cases, it's more difficult to spread then persist, and some sort of favorable conditions need to exist before a species spreads into neighboring habitats, even if that habitat would be perfectly suitable once the species arrives (like an activation energy barrier from chemistry or something), mainly due to competition, low initial population sizes, stochastic issues, etc.

While this is based entirely from the conservation viewpoint, there's no reason the same ideas wouldn't be directly applicable to invasions... for an invader to invade, it's got to avoid going extinct when colonizing. Makes sense for the bark beetle too- they are effectivly destroying their own habitat as they go along, changing the landscape structure and therefore altering the environment in which the next generation has to make a living. Finally, how do you do this assessment on a species intitially? If you haven't made repeated population and landscape assessments over the last 20 years, then this analysis doesn't seem to help, unless we can find some clever way to circumvent that problem...

2008-10-15T15:25:00.000-06:00

Invasion in a heterogeneous world: resistance, coexistence or hostile takeover?
Melbourne, et al. Ecology Letters (2007) 10:77-94