Guest Post by Willis Eschenbach
Driving home today, I heard about a new report from one of those Canadian “we work for the Government but we’re actually really truly independent, honest we are” kind of organizations. It’s called “PAYING THE PRICE: THE ECONOMIC IMPACTS OF CLIMATE CHANGE FOR CANADA.” It is chock full of the usual nonsense about how, in a country plagued by cold Arctic winds and suffering from a short growing season, a couple degrees of warming will be a multi-billion dollar national tragedy. It featured the usual huge numbers, warming will cost multiple tens of billions of dollars per year. (Curiously, there is no mention of any billions in supposed costs from the 20th century warming.)
I got to wondering about how they estimated these huge costs. I mean, were they based on scientific studies, or from actuarial data, or were they estimated from past damages, or were they just extracting the numbers from their fundamental orifices?
The answer, I found out, is “none of the above”. Once again, it’s models all the way down. In this case, it’s a whiz-bang model called Page09. Here’s their diagram of how it all works, from page 37 of the cited report.
Figure 1. Description from the climate report of the model used to estimate the damages from warming temperatures.
Damage functions? I like the sound of that, I never heard of a “damage function”, but then I was born yesterday. So I set out to understand the Page09 damage functions.
In my research I find this:
Within the PAGE09 Model, damage from climate change is modelled firstly as combination of specified damage functions for sea level rise, economic effects and non-economic effects.
In this reference they give the general form of the damage function. I have spread out the right side of the equation to show the two different parts.
Climate change economic and non-economic impacts before adaptation are captured as a proportion of GDP by the climate change damage function. As do all the other main IAMs with the exception of MERGE, damage is defined as a non-linear function (Bosello and Roson, 2007). Welfare impacts (WI) are expressed as a polynomial function of the difference between regional and tolerable temperature levels (RTT) as follows:
WI(t, d, r) = [RTT(t, d, r) / 2,5 ^POW ] * W(d, 0) *[WF(r)/100] * GDP(t, r)
where t corresponds to time, d identifies the damage type (economic, non-economic, sea level rise) and r the region; 2.5 are the °C corresponding to the tolerable increase in temperature due to global warming; POW is the power of the polynomial impact function; W(d, 0) is the impact in the focus region (i.e. EU) at 2.5 °C and WF(r) is the regional weight applied to EU impact to calculate the impact in other world regions. SOURCE
Let me give a stab at translating that into English. First, the left hand side in brackets says take the amount by which the region is warmer than the tolerable range RTT(t,d,r) . Divide that by 2.5, and take that to some power POW. That gives you the damage impact index.
Second, the right hand side just adjusts the damage index calculated on the left hand side, to convert the impact into a dollar value. The important thing to note is that for a given damage type and region, the right hand side is a constant, that is to say it does not vary with T. All the work is done by the left-hand side.
Another reference gives the exact same equation for the damage function, with different symbols:
1.3.2 Model adjustments
At the core of the damage function in PAGE09 is the Equation (5).14
d = alpha * (TACT/TCAL) ^ beta
where d is the damage, alpha is the damage at the calibration temperature, TCAL is the calibration temperature rise, and TACT is the actual temperature rise, beta is the damage exponent.
The calibration temperature is on average 3°C. Therefore, if the actual temperature rise is 3 °C, on average, the damage equals alpha. The damage exponent, beta, becomes more important as temperatures rise above TCAL. In the standard model, beta is entered as triangle (1.5, 2, 3). Therefore, on average, the exponent is 2.167 (slightly above a quadratic), meaning that at twice the calibration temperature (on average, TACT equals 6°C), the damage will be 4.5 times alpha. SOURCE
The damage function graphs out as shown in Figure 2, for various values of the power coefficient POW (also called “beta”) and RTT(t, d, r) (also called “TACT”).
Figure 2. The form of the damage function for the triangular number POW = {1.5, 2, 3}. Note that for a 5° rise the maximum curve (POW = 3) forecasts eight times the damage.
This shows that in all cases used in, damage rises faster than temperature.
There are some odd parts of using this form of a damage function.
First, the one that rises the fastest with increasing warming (POW = 3, green line) starts out the slowest. What would be the physical reason for that?
Second, it assumes that human beings don’t learn. Sure, if there is one year of warmer weather, some farmers will lose money from planting the wrong thing, or at the wrong time. But if the warmer weather continues, the farmers will plant earlier and rejoice that the growing season is longer.
There is also another problem with this kind of analysis. In addition to assuming that farmers are stupid and that damage goes up geometrically as temperatures rise, there is no provision for the benefits of the warming. They pay lip service to the idea of benefits in the report, but I see no serious understanding of the difference between the costs and the benefits of warming for Canada. One difference is that the costs are often short-term (adjustment costs), while the benefits of the warmer climate are often longer lasting.
Again, farming is a good example. The costs to farming of a warming are short-lived. For a few years the farmers would plant something that might not be optimum for the new, warmer climate. But after that, the longer growing season is a benefit forever … how can they not include things like that?
Around the latitude of Canada, the change in average temperature as one goes north is on the order of 2.5° (where damage = 1) for every couple hundred miles. So if you took a Canadian farm and moved it two hundred miles south, do you seriously think that the farmers would suffer huge problems?
The same thing is true of the forests. They claim there will be huge damage to the forests from a few degrees temperature rise … but for many forests in Canada, the same forest exists two hundred miles to the south of a given point … and two hundred miles to the north of that point. That’s a change of FIVE DEGREES, OMG, THE SOUTHERN TREES MUST BE BURNING UP, THEY ARE FIVE DEGREES WARMER THAN THE NORTHERN TREES, COULD BE EIGHT TIMES THE DAMAGE …
I fear I can’t appropriately express my contempt for this kind of grade-school level of thinking about damage impact. If that’s the best a bunch of “damage analysts” can come up with, I’d fire them on the spot.
Always learning, I find out that this family of models are called “IAMS”, for Impact Assessment Models. The most trenchant comment I have found about them comes from the first source cited above, which says (emphasis mine):
An interesting challenge to the methodology of IAMs comes from a series of papers from Weitzman (2009a, 2009b, 2009c). In these papers, he puts forward a number of critiques of the current cost-benefit analysis of climate change, especially the approach embodied in IAMs.
Weitzman’s observations go even further with the elaboration of what is referred to as the ‘dismal theorem’. The idea is basically that under certain conditions, the expected loss from high-consequence, low-probability events can be infinite. In such a situation, standard cost-benefit analysis is therefore no longer an appropriate tool. Weitzman argues that, given the extent of our current understanding, these conditions apply to climate change.
Taking this idea to its limit would suggest that IAMs have little relevance for policy, as the response ought always to be to choose policies that do everything possible to avoid an infinite loss, even if there is only a small probability of such an outcome.
This “dismal theorem” is an extremely important conclusion, and is applicable to a host of the modeling exercises involved with thermal doomsday scenarios.
So Canadians, when they throw this high-cost, low-value modeling exercise in your face, you can just say “Sorry, go hawk your model results somewhere else. IAMS have little relevance for policy”.
Finally, as a businessman, I’ve done a host of cost-benefit studies. I have no problem with a proper historically based cost-benefit analysis of some possible future occurrence or action. However, the “PAYING THE PRICE …” report is nothing of the sort.
My condolences to my northern neighbors, who have their own Kyoto crosses to bear …
w.
PS — The climate models say that the maximum effect of the putative warming will be seen in the extra-tropical winter nights. Is this a problem? I mean, I don’t hear a lot of Canadians saying “Dang, it’s getting way too warm after midnight in February” …
PPS — my favorite argument is that the problem is not the absolute temperature change, it is the speed of the temperature change that is claimed will cause the problems. Yeah, at the much-hyped theoretical future rate of 0.03 degrees of warming per year, watch out when you step on board. If you’re not ready for it, the G forces from suddenly taking on that magnitude of high-speed warming can cause whiplash …
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
It seems a certain story, along with reader’s comments, has been scrubbed.
(are my contractions correct? “hopefully” they are)
http://www.theglobeandmail.com/news/national/canadian-arctic-nearly-loses-entire-ice-shelf-from-global-warming/article2185500/comments/?plckFindCommentKey=CommentKey:6098eb7e-dfa7-4f30-9a31-f87206f8d977
Willis
“Here’s my problem. Seems like at the end of that process, what we have is a fast, computationally simple way to calculate the wrong answer …”
did you watch all the way to the end and get the import of the work they were doing on reconstructions?
In this line of work there are not “wrong” answers.
Your simple functions cannot reconstruct the field, you only reconstructed 1 dimension as I recall. Nevertheless, what they found out about the S/N was interesting.. There will be some interesting paleo that uses this approach.. with a GCM recon as a prior
Thanks Fred. And Fred and you other Canucks, maybe you should pass this drivel on to some of your PC MP’s and see if they can do anything about the funding for the “Round Table”. I am waiting for my weather to warm here in central Alberta. I just split 6 cords of wood. Maybe that is why it is warming up cause all my neighbours are also stockpiling wood like crazy – carbon credits? Oh yeah, that’s right, we get carbon credits for using zero tillage on our fields. Gotta go fill out my application …. (CTV also carried this silly story along with CBC.)
Wayne Delbeke in Faraway, Alberta, Canada … and yes it is a real place.
Models and projections about the outcome of the federal election on May 2 did not see the rise of the New Democratic Party into the official opposition. Anybody who tries to use a model to predict the course of the economy are no better than those idiot pollsters who haven’t yet discovered the biases that led them to completely miss the orange wave of the NDP.
Willis and all other skeptics who visit here, rest assured that most Canadians have tuned out of the climate alarmist hysteria, especially when you consider that the current government has deftly mouthed the words “fighting climate change” while avoiding actions that would ruin our economy and the results of the last election were thus:
Conservative Party of Canada 166 seats (a majority win that assures power for 5 years)
New Democratic Party 103 seats (greenies and socialists)
Liberal Party of Canada 34 seats (talked of a Carbon tax two elections ago)
Bloc Québecois 4 seats
Green Party of Canada 1 seat
The battle for Canada has been won by the skeptics, but I pity the province of Ontario because it looks like the result of their upcoming provincial election will be another few years of good taxpayer money shredded by wind turbines in a coalition of parties enamoured by the alarmist agenda.
Because of this article, I went to the ICSC home page. I found this: Environment Canada invites public feedback on carbon dioxide reduction plan. Geez. I thought it was safe to vote for Stephen Harper. Yes, I live in Ontario and it looks like McGuinty will be elected again, although with a minority. I would call him an econut but he doesn’t care about the environment.
I have a few problems with your extensive analysis Willis. Firstly, as a Canadian I am pleased that risk assessments are being conducted and I will be even more pleased if our government actually uses this advice in a constructive manner. Prudent policy making must follow this kind of analysis.
You mock the model approach used in this work, but neglect to mention that the PAGE09 model is one of the first models to take into account both mitigation and adaption. The Canadian Prairie region (for example) is expected to get warmer and drier, conditions which have occurred several times in the past. Is it not wise now, to develop drought resistant seeds and other mitigative farming practices, in the chance that these droughts will be prolonged. Being prepared for both expected and unexpected conditions is usually considered good management, and governments, together with private business, must engage in these prudent practices. If the analysis is wrong, nothing is lost. But if the assessments prove correct, we have a chance to continue growing crops and feeding the increasing global populations.
By the way Ellis, you should be aware that warming is already having a devastating impact in Western Canada and Alaska. Because our winters are not cold enough, critters like the Pine beetle and the Spruce Bud Worm now survive, and multiply and they are devastating our forests. Wildfires now become massive quickly leading to loss of lives, timber, and property. Our government agencies struggle to contain these conflagrations, and costs are rising commensurately. This is not a trivial matter, Willis.
Warming also leads to increased evaporation, and in my region, there is already a loss of ground water as a result. Neither is this a trivial matter Willis. There are real costs involved in mitigating the impacts which are presently being experienced and it is reasonable to expect that these costs will increase. Every farmer I know is now acting as though there will be tougher times ahead here in Western Canada, and I’m sure that farmers in Kansas and Texas are acting similarly. This too is called good management practice Willis.
The federal government (or The Stephen Harper Government as the MSM like to use) has not changed the Fixed Election Dates Act:
The Fixed Election Dates Act establishes fixed election dates for Canadian federal elections every four years, except when a government loses a vote on a non-confidence motion, in which case an election would be held immediately.
So its only 4 years, not 5.
Many regions of B.C. saw their coldest spring in their history this year. The snowpack was well above normal this year as well. The fire season was well below normal for the number of fires and area burnt.
Last year Forests and Range Minister Pat Bell said he has had scientists in the forests for the past 8 years and they tell him that the forests are getting drier due to Global Warming. This is Cherry Picking from an El Nino year that saw some record snowfalls, and I found it rather dubious to use 8 years of weather to make Climate Change proclamations.
This year the way the fire service does its accounting has changed to add in costs of training and other costs which greatly increases the apparent cost of fighting forest fires. If we hadn’t had such a low number of fires this year in which earlier this year the costs where much greater than the same time last year while the number of fires was much smaller, you can be sure that this accounting trick would not have been exposed and the high costs of fire fighting would have been touted as proof of Catastrophic Climate Change. As it was, B.C. Made a lot of money having our fire fighters shipped off to fight fires in other places.
I once believed in this Pine Beetle epidemic being a result of Global Warming, but it doesn’t add up. It isn’t really plausible that a global rise in temperatures of 0.7 K over a 150 year time frame, a rise of only 0.3 % could explain this Beetle outbreak. It is far more likely to be a naturally occurring cycle exasperated by the forest practices over the last few decades, of fire suppression and logging practices.
The Idea of the warmer temperatures is really about how fast the cold weather comes, before the beetles’ have built up ther natural glycol defences to combat the cold.
What do the temperature statistics say, I have never seen them, and I bet this is because it would completely render Global Warming as the cause of this outbreak to the junk science bin.
Make that a La Nina above. I’m fairly new at this Climate Science research, 1.5 years so far.
Hugh Pepper says:
October 3, 2011 at 12:19 am
Thanks, Hugh. I am not fond of “risk assessments”. I much prefer cost/benefit analyses.
In either case, I certainly hope that you do not see the “PAYING THE PRICE” document as a serious or balanced or thorough analysis of any type. It is nothing of the sort, for the reasons I mentioned, plus others.
Somehow, you have the idea that a computer model in this case can outperform an actual analysis. The idea that you can pick numbers for some “damage function” and draw out meaningful results beggars belief. The only way to do this type of analysis is for actual humans to look at and investigate and carefully ponder every bit of evidence from previous warmings and from previous coolings. For example, Canada warmed over the 20th century. Where is the careful, scientific analysis of what that warming cost Canada, and what that warming brought to Canada? How can you think that a computer can estimate that with a bozo-simple power function?
You say that there are costs from changing climate. Hugh, climate has always been and always will be changing. About half the time it has been warming, and about half the time it has been cooling, for at least the last half billion years or so.
And yes, each time it has done so, there have been “real costs involved in mitigating the impacts” for man, beast, and plant, whether the climate has been cooling or it has been warming.
But what you ignore is that there have also been benefits, whether the climate has been cooling or warming. And you know what? Especially in the sub-Arctic regions, the benefits of slight warming generally outweigh the costs. Read the contemporaneous accounts of the Little Ice Age, cold is much harder on plants, animals, and humans than is heat.
Is the climate changing? Assuredly and constantly. Is the globe warming? Generally yes, in fits and starts, since the Little Ice Age. Is the warming of the late 20th century anomalous? No, it is statistically indistinguishable from earlier warming. Are there changes, in Canada and elsewhere, from those three centuries of warming? Sure. From 1890 to 1940 Southern Canada, the agricultural zone, warmed by almost two degrees.Where are the fabled billions of dollars of losses from that warming? Then southern Canada cooled by about a degree until 1970. Were there savings or gains during that time? The vaunted “damage function” would say so … do you agree?
Then southern Canada warmed, like the rest of the planet, to a peak in 1998, and it has been basically stable since then … point me out the costs from that warming, and show me how, per the “damage function”, those costs have continued even though the warming stopped in 1998.
I’m sure you see the problems. Climates do change. But the costs are not as great as alarmists would have it, and the benefits are much larger than the alarmists would have it.
Bottom line? Climate is always either warming or cooling. For a cold country like Canada, if you had to make a choice (we can’t, but it’s a fun game) … which one would you pick, warming or cooling? Which one is worse overall?
w.
If the climate guy hocks like a snake oil salesman, looks like a snake oil seller, and leaves you breathless with the claims of a snake oil product, then buy if you believe you are that stupid. Why am I so willing to let the gullible fall into a batch of snake oil? You can’t fix stupid.
If I may comment on those inputs:
The first is “emissions trajectories” which are referred to as if the were independent of inputs 4 and 5. which is, in point of fact, absurd, since the levels of socioeconomic development and economic “baseline” are in part functions of energy consumption, energy consumption being the chief driver for emissions. Thus it is fallacious to treat these as “separate” inputs. This will be true almost regardless of the model they use to determine future emissions. Now, putting aside for the moment the issue of whether “modeling” the economy is a feasible or reasonable thing to do, as if it were a physical system (it is not reasonable, but it’s not important for now). The problem is that one needs more than just future emissions to determine future concentrations, one needs a full blown carbon cycle model. No where do they indicate what model is use to determine concentrations from emissions, but the model almost certainly requires arbitrary terms to keep too much rise from happening in the twentieth century, and then ceases allow the “missing sink” to grow, as it has been for a century, thereby eliminating the mysterious, but very real, buffer between our emissions and the concentration in the atmosphere, guaranteeing that the concentrations will grow rapidly, almost certainly more so than in reality. So input one almost certainly results in an overestimate of “damages.”
The second input, “sensitivity” is probably an overestimated value. This could be talked to death, but in fact as we shall see, the other inputs are sufficiently murky as to make whether they get this right irrelevant! Nevertheless, there is a good chance this overestimates “damages” making us two for two.
The third input doesn’t appear to have obvious consequences for their estimates of damages, except that for whatever reason the appear to be modeling damages as functions of the size temperature change, without regard to what that represents a change from. Well, naturally when they get models saying the higher latitudes warm more, their model says the further North you are, the more screw you will be. If you think about it, this defies all common sense: it would suggest that, essentially, if an are in the far North comes to have almost the same temperature as an area to it’s south, the Northern area will suffer horrendously because it’s temperature level is exactly the same as a relatively well off area to it’s South. In fact, the opposite is arguably true. So a again, overestimate, we are three for three.
As for the “economic baseline” this is presumably referring to economic conditions as the stand today. One wonders if the damage analysts noticed that the vast majority of Canada’s economic activity takes place huddled along the southern border. Well, anyway, we finally have something they should be able to screw up, at least not in any particular direction with regard to “damages” although they probably underestimate the level of economic activity due to “underground” activity. We now stand at 3 for 4 overestimating impacts.
With respect to the fifth input, I have to shake my head, because I know this input is derived from economic “models” that were wrong before their equations were even conceived of. One cannot mathematically model human behavior, which fundamentally constitutes the “economy” and determines the path of socioeconomic development. Their predictions with respect to future development can only be correct by pure luck, which is quite a long shot. But let us be generous, and say that just because economic modeling is utter nonsense, doesn’t mean this results in over or underestimating impacts one way or another. However, it is worth asking, whether the modelers realize that the future development that drives their emissions scenarios, apart from being a neglected implied negative feedback (since socioeconomic development is supposed to be slowed by these “impacts” but the unimpaired development drives the emissions, despite supposedly not happening) is not feasible without those emissions: that the size of the damages should pale in comparison to the size of future socioeconomic development so that we will all still be better off. But let’s ignore that feedback thing since it probably doesn’t really exist and call them 3 for 5 overestimating.
The final “input” are their “damage functions”, and we have already discussed several problems with them. I will just like to mention one thing, since problems with there functional form, insistence on positive sign for “damages” and faulty assumptions have already been noted: These damage functions are almost certainly based on changes to weather patterns which simply aren’t, and probably will never, happen. I have look for evidence all over for weather getting worse: there is none. Therefore, the vast majority of the “damage function” coefficients should be equal to zero. Since they are not, the are overestimating again, leaving them 4 for 6.
Now that’s just the inputs! But clearly they are overestimating future “damages” by quite a lot. Which means that, with just that, their primary conclusions are thrown out.
@Gary Young: If it’s 4 years it may as well be 8. I doubt any of the opposition parties can muster the discipline to convince us that they could be trusted with government in time for the next election.
My first reaction was “OI – they have copied my idea!”
Well the damage function at least!
http://manicbeancounter.wordpress.com/2011/02/11/climate-change-policy-in-perspective-%E2%80%93-part-1-of-4/
Actually, this can be found by the claims of the Stern Review or AR4. Try looking at the table in AR4 of “Examples of impacts associated with global average temperature change” and you will get the idea.
More seriously Willis, this is worse than you thought. The paper makes the claim that unlikely but high impact events should be considered. The argument is that the likelihood and impacts of potential catastrophes are both higher than previously thought. The paper then states
“Various tipping points can be envisaged (Lenton et al., 2008; Kriegler et al., 2009), which would lead to severe sudden damages. Furthermore, the consequent political or community responses could be even more serious.”
Both of these papers are available online at PNAS.org.
The Lenton paper consisted of a group of academics specialising in catastrophic tipping points getting together for a retreat in Berlin. They concluded that these tipping points needed to include “political time horizons”, “ethical time horizons”, and where a “A significant number of people care about the fate of (a)
component”. That is, there is a host of non-scientific reasons for exaggerating the extent and the likelihood of potential events.
The Krieger paper says “We have elicited subjective probability intervals for the occurrence of such major changes under global warming from 43 scientists.” Is anybody willing to assess if the subjective probability intervals might deviate from objective probability intervals, and in which direction?
So the “Climate Change damage impacts” paper takes two embellished tipping points papers and adds “…the consequent political or community responses could be even more serious.”
There is something else you need to add into the probability equation. The paper assumes the central estimate of temperature rise from a doubling of CO2 levels is 2.8 degrees centigrade. This is only as a result of strong positive feedbacks. Many will have seen the recent discussions at Climateaudit and wattsupwiththat about the Spencer & Bracewell, Lindzen and Choi and Dessler papers. Even if Dessler is given the benefit of the doubt on this, the evidence for strong positive feedbacks is very weak indeed.
In conclusion, the most charitable view is that this paper takes an exaggerated view (both magnitude and likelihood) of a couple of papers with exaggerated views (both magnitude and likelihood), all subject to the occurrence of a temperature rise for which there is no robust empirical evidence.
Please note my recent comment was based on a source document for the Canadian paper. It is still a story that gets embellished with every re-telling.
Hugh Pepper says:
October 3, 2011 at 12:19 am
I have friends and relatives in the forestry industry including tree planters and biologists doing beetle counts. In their unanimous opinion, the biggest problem has little to do with climate (temperature, rainfall, snowfall, sunshine hours etc) but everything to do with forest management. Pines stands used to self regulate, but when you plant hundreds of acres of closely spaced pine trees of the same age, same species with similar genetics, you are creating a disaster in waiting a lo and behold …
Nature will take care of it, but it will take some time.
By the way Hugh, it is not temperature alone that kills the pests, it also has to do with timing, duration, moisture and a host of other variables.. A good Chinook a few years ago had a 90% kill rate in the foothills west of Calgary. If you know how the pine beetle works, you will know why.
“canadian-contretemps”
Shortly after I linked to WUWT and JoNova in the comments section at G&M, the pertinent article, along with the comments disappeared.
http://s22.photobucket.com/albums/b331/kevster1346/?action=view¤t=iceshelves.jpg
Someone at the G&M got cold feet?
Wayne Delbeke says:
October 3, 2011 at 2:26 pm
“Pines stands used to self regulate, but when you plant hundreds of acres of closely spaced pine trees of the same age, same species with similar genetics, you are creating a disaster in waiting a lo and behold …”
You’re missing the key point here Wayne, for lodgepole pines (the main mt pine beetle host in Canada).
The lp pine is fire dependent on the long time scale. Their cones only release their seeds after they are burned. So when fire happens they naturally “plant hundreds of acres of closely spaced pine trees of the same age, same species with similar genetics” and thereby they “are creating a disaster in waiting.” But it is not a ‘disaster’ for them, in the long run. It sets up the cycle, to be burned again (most typical) or to get mature enough to support mt pine beetles which turn these stands into fire prone kindling and then burn. Without fire, shade tolerant species like spruce (typically) will take over the areas. Spruce can start growing in the shade of the pines but not vice versa.
Thus even-aged stands are the natural norm for lodgepole pines, not some new invention. The modern problem is fire suppression which stopped this fire cycle and allowed so much lp pine to mature into beetle habitat.
Again, no habitat, no mt pine beetle epidemics, no matter how warm winters are.
Now, if they are dumb enough to replant these pine forests as you describe, or just let them burn which will do the same thing, then we will have learned nothing. The trick now is to recreate diversity in tree species and lp pine age classes.
(The beetle is ALWAYS there in low numbers, attacking older trees, but if they are still healthy they can resist those low beetle numbers.)
P.S. I first worked on this problem back in the 1970s when the mt pine beetle hit the border region between Glacier Nat Park and Waterton Nat Park. So much for unprecedented.
Seems I buggered the link to image upthread.
http://i22.photobucket.com/albums/b331/kevster1346/iceshelves.jpg
I really like the turtles quote spin, “We can’t measure any warming.” “Very clever young man, but the warming is in the models, it’s models- all the way down!”
clipe says:
October 3, 2011 at 4:19 pm
Seems to still be there:
http://www.theglobeandmail.com/report-on-business/economy/economic-costs-of-climate-change-will-be-high-panel-warns/article2183729/
Al Gored says:
October 3, 2011 at 4:44 pm
Wayne Delbeke says:
October 3, 2011 at 2:26 pm
“Pines stands used to self regulate, but when you plant hundreds of acres of closely spaced pine trees of the same age, same species with similar genetics, you are creating a disaster in waiting a lo and behold …”
You’re missing the key point here Wayne, for lodgepole pines (the main mt pine beetle host in Canada).
—————————————————
Pine forests were replanted with the trees only a step or two apart for years, under the assumption they would thin naturally through disease and adjacent trees competing for space. After 20 years, different methods of planting are being experimented with, varied spacing, varied species. In the mean time, different methods of thinning are also being tried, including clear cutting juvenile trees and replanting parts of the forest and simple multiple thinnings of trees in an effort to recover the wood in a commercial manner while encouraging the remaining trees to grow to a decent merchantable timber size instead of becoming wood chips. And this helps to deal with parasites and disease. We learn, but we learn slowly but considering the life of mature farmed tree is 80 to 100 years, it is going to take a while. But we are getting there. I see large trees being harvested in areas some of our young tree huggers think are virgin forest. But they are worrying about areas that were actually cut in the first half of the 20th century. They now appear as beautiful large stands of future building studs. We are learning. I love waking into the forest and showing the folks worrying about the cutting of these “old growth” forests and showing them the stumps of trees that were cut down 80 years ago BS more.
While forest management has a way to go, it is doing fairly well in many regions from what I can see.
Wayne