There is quite a lot to respond to here. I used to be of the same mindset on limits. I followed the The Oil Drum while it was still running and attend a few limits to growth conferences (the ones where attendees called themselves “Doomers”). After engaging with that material, I don’t think the projections are accurate and think the catastrophizing is unwarranted. In particular, I don’t think resource limits are likely to be a significant issue to humanity in the 21st century. Peak oil concern just isn’t a reality; resource economics just doesn’t work like that, and demand is elastic. The Oil Drum shut down partly in recognition that Peak Oil wasn’t a useful concept anymore, and academics had long since departed from it.
Some more specific points:
Factor 1 - Land Grabbing
Can you provide citations and sources for the % of population this is happening to?
Factor 3 - Climate
“As a consequence, the Sahara will expand well over a hundred kilometres south, a process called desertification.”
Increasing desterification is a concern, but 100 kilometers advancement across such a large continent isn’t going to make a difference.
“vast parts of land will become unsuitable for agriculture and hence will force hundreds of people to leave their homes.”
I would not call hundreds of people a humanitarian crisis.
It’s not clear that the issues you cite are enough to trigger the catastrophic famine and migrations you prophesize. People respond to droughts and other agricultural challenges in different ways—switching crops, using different water sources, relying on more imports, and finding other income.
EA fund a lot of efforts that help this part of the world, malaria eradication and deworming in particular, which yield significant economic gains and life improvement. Development and increasing incomes improves resiliency. You are suggesting that despite these efforts, the factors you describe will overwhelm all of the health and development work being done. You present limited information, and will need more data, models, and economic models to justify the level of concern you are raising.
On Limits To Growth (LTG).
Statements along the lines of “The LTG collapse scenario has been fairly accurate to date” imply that there are real world metrics mapped to LTG variables, and that the they expect the underlying model dynamics to remain roughly accurate. I’ve been able to find one published piece of work where someone explicitly details the variables they use to match to LTG. That report was by Graham Turner, the author of the Guardian Piece you cite. The report is not peer-reviewed, and was published by the institute where Graham is a senior fellow. It is based on a 2008 paper that was peer-reviewed. The author picked per capita electricity consumption and literacy rates to represent global “services per capita”. This is misleading. One can pick almost any available variable remotely tied to represent “services per capita” that matches the shape of the LTG model, scale it, and claim that the “LTG standard run is close to reality”. There are so many spurious correlations out there. Even then, the majority of trends are 20%, 50%, 100%+ off from the “LTG standard run”. The report does not include statistical fit or calibration statistics.
How can one meaningful track global pollution? Or non-renewable resources remaining? It was never the intent of the work to be a predictive forecasting tool. The variables are lumped together proxies to represent categories of real world things, and the authors were explicit when they made the report that these did not represent real world variables; they were to just trying to show the dynamics of their theoretical model. Subsequent updates to the LTG model haven’t been able to resolve which collection of real world variables get weighted together to match to which LTG variables. It’s easy to cherry pick data to match the trend, especially if you aren’t precommitting what constitutes a fit. And even if there is a good match to trends, that doesn’t mean that a specific model is the correct representation of reality; there may be many models with wildly different assumptions of the dynamics that produce the same result.
Vaclav Smil’s review of the LTG is a longer deconstruction of the LTG modeling exercise and worth a read.
More importantly, Dennis and Jorgen (living original authors who I’ve met) repeatedly say these forecasts are not to be taken literally. Jorgen Randers has a new (2014) forecast which looks very different from the “resource crisis” scenario in the 1972 LTG model. Jorgen now claims the climate crisis is the key concern and the driving force in the model. Even then, he still assumes the same overall model dynamics, but doesn’t detail the mechanisms for how the variables will actually influence each-other. For example, in using carbon emissions as his pollution variable, he assumes climate change will greatly increase overall death rates, overwhelming all factors that reduce death rates. There are many models out there (30+) that make assumptions on how climate change impacts human society in the future of which Jorgen’s new work is just one. None assume overall death rate increases as Jorgen does, especially in the near term. Be wary of projections from a single model/source. The point is, it is misguided to get doomy about older model forecasts from one model that the authors say are no longer reflective of reality, especially when there is a much wider variety of more complex, robust forecasting models in existence today that have different scenarios.
Thanks for the feedback and the food for thought it gave me to you as well.
On LTG: Now I´ve read the papers by Turner and the one by Smith.
The thing is, while I do genuinely concur with much of the critique by Smith; disputes about data accuracy, methods of aggregate analysis and the question whether their delicate interlinkages are representative of real-world complexities is the kind of debate that is bound to diffuse every time when you do things like QCA (Qualitative Comparative Analysis), systemic design, surveys or future predictions. Future research and macro-models are oversimplifications by necessity and therefore generate controversial, messy debates by nature. In that sense, it is logical and fruitful that we are having this discussion, which leads to the healthy challenging to existing pre-conception that one always loves to assert as something splendidly hermetically sealed.
That being said, next to the anecdotal parts, the legitimate critique raised by Smil and others about the methods of the first WW3 modelling I have read so far, it indeed shakes up the statements made but provides no concise line of argumentation that would actually invalidate them in any way. The way Smil likes to conclude from the methods being imperfect (which they certainly were especially when this mode of computer-based analysis was in its infancy at the time) to any conclusions thereby being equally invalid seems to constitute a similarly flawed process of proving one’s point.
With what I wrote here, then, I did not assert to have delivered irrefutable arguments, but much rather fair approximations as to what, supported by the data, could happen in the future and that even the possibility of these scenarios being feasible should lead EA to investigate them more thoroughly.
So while even current models lack any kind of satisfactory representation of real world-complexities, they meanwhile give us a fair approximation for a rough but feasible future outlook. Now, I´ve also had the privilege of meeting Randers, Bardi and Maxton last year, and they by no means claim any perfection but point out that the data, by applying common sense, points in a clear direction that is consistent with their models outlook: When we have already exceeded planetary boundaries by 2.5 times (again an arbitrary aggregate thing, fair enough), human population has grown to 7.5 billion and will grow further, when energy demand due to population growth and rising living standards increases further, when we can assume with relative safety that in 20 years we can only extract half the oil relative to now and that the current pace of global energy transition would need to be multiple times faster to rectify the shortges thereby created; that we need CO2 emmissions to peak in the next two years and completely stop them by 2050 in order to have a chance meet the 2 degrees goal to prevent catastrophic chain reactions, but actually CO2 emmission are continuing to climb as no country is yet determined to fulfill its climate commiments and when the tipping points is soon to be reached that even absruptly stoppin any emmissions could stop climate change anymore—THEN we do not need highly sophisticated models to be able to conclude that these trends will create multiple sorts of catastrophies with grave humanitarian implications.
Now on Scenario 1: First of all, you pointed me to a mistake in the article: The effects of climate change could displace hundreds of millions of people rather than hundreds.
It is difficult to find good data on land grabbing, try the “Land Matrix” data bank which registers the areas affected, the actors and miscellaneous data.
What we know is that the development community is saying that the dimensions are growing significantly right now and that millions of people have already been displaced. There´s little research on this (https://www.brot-fuer-die-welt.de/themen/fluchtursachen/fluchtursache-landraub/), exact percentages are therefore hard to come by: In Sudan, 23% of land is in the hands of foreign investors, in Sierra Leone 40%, in Gabon 85% (UNHCR), but a region-wide assessment has not yet been conducted to my knwoledge.
So for further analysis, we would need more data which is hard to come by as any deeper investigation of this phenomenon is usually prevented by the very governments that facilitate it, which makes it easier for them to justify that by land grabbing the local population benefits due to modern agricultural equipment when in fact all those fields are being used to cultivate cash crops that are being exported as evident in the import/export data.
So you are entirely right that I require more data to substantiate the extent of my claim!
“You are suggesting that despite these efforts, the factors you describe will overwhelm all of the health and development work being done.”
-In essence, yes. Development doesn´t necessarily enhance resilience, it may also create dependencies on aid and foreign imports, the international rural development budget currently sits at a measly 15%, hence climate adaptation is vastly underfunded to this very day. Conflicts in the region continue to sweep away decades of advancements in development in some cases. For real resilience, empowerment, rural development, environmental education, partially localising supply chains as well as other measures would need to be undertaken but continue to be severely neglected, which tied into a different debate about development effectiveness.
In a World Bank report form 2013, I found this though:
“In Sub-Saharan Africa, by the 2030s droughts and heat will leave 40 percent of the land now growing maize unable to support that crop, while rising temperatures could cause major loss of savanna grasslands threatening pastoral livelihoods. By the 2050s, depending on the sub-region, the proportion of the population undernourished is projected to increase by 25-90 percent compared to the present.” (http://www.worldbank.org/en/topic/climatechange/publication/turn-down-the-heat)
And that mostly confirms that in some form or another, this Malthusian disaster ot at the very least more seroius famines are ought to happen.
In sum: Yes, the data that is currently available does not entirely verify the level of concern raised by me, but at the same time makes it very possible by what is known, and that even the rest of the data is vastly “better” than expected, we still can safely expect larger famines and hence large-scale loss of life to occur within the next decades. Hence it is not a question if larger famines are going to happen, but in what dimensions. And that very circumstance could dictate a heavy shift in priorities for Effective Altruism as a whole.
A) peak oil → energy scarcity → humanitarian crisis from ?
If not A), then:
B) emissions → climate change → agricultural loss → humanitarian crisis from famine
(with land grabbing exacerbating the crisis)
Let’s jump to the crux of Rander’s update to the LTG model, since that is the most recent work most closely attached to the concept. The fundamental collapse prediction comes from the pollution—death rate linkage that I mention in the previous comment. What basis is there to assume the overall death rate will increase? And how does the model explain the decreasing death rates in that part of the world?
Is it based on a presumed energy scarcity? “when we can assume with relative safety that in 20 years we can only extract half the oil relative to now and that the current pace of global energy transition would need to be multiple times faster to rectify the shortages thereby created”
Where do you derive the assumption that oil production will be cut in half in 20 years for reasons of scarcity? U.S. EIA forecasts relatively flat curves. And how do you distinguish good substitutions from shortages?
Concerns about peak oil presume a fixed consumption per person, meaning no fuel substitution or demand elasticity. I think this is incorrect. Oil consumption is responsive to price, and even in the least elastic sector where it is used (transportation), there is still a tradeoff in size vs. efficiency for cars people buy. You can go on Gapminder and see how the trend in oil consumption per person can vary quite a bit over several years. Electricity consumption per person (what Turner used as his proxy for “services per person”) has actually been decreasing in the U.S. because of large-scale efficiency. I expect we’ll see more of that in other sectors including transportation, with lower energy use but greater energy services overall.
Given the substitution and efficiency arguments, and how none of the climate-economic models in IPCC’s modeling exercises show an energy scarcity or pollution induced collapse, I don’t think causal chain A you propose is a reality we can expect.
So that leaves causal chain B. The World Bank report is for a 4-degree temperature rise, and is by no means a fait accompli. I think what we do now looks a lot like what EAs are currently funding in the region—improving health and encouraging inclusive development. When people have greater incomes and are less dependent on agriculture, climate change effects are less severe. This is the assessment of a follow-up report the World Bank did to the 4-degree report which is worth reading: Shock Waves Managing the Impacts of Climate Change on Poverty.
There is quite a lot to respond to here. I used to be of the same mindset on limits. I followed the The Oil Drum while it was still running and attend a few limits to growth conferences (the ones where attendees called themselves “Doomers”). After engaging with that material, I don’t think the projections are accurate and think the catastrophizing is unwarranted. In particular, I don’t think resource limits are likely to be a significant issue to humanity in the 21st century. Peak oil concern just isn’t a reality; resource economics just doesn’t work like that, and demand is elastic. The Oil Drum shut down partly in recognition that Peak Oil wasn’t a useful concept anymore, and academics had long since departed from it.
Some more specific points: Factor 1 - Land Grabbing Can you provide citations and sources for the % of population this is happening to?
Factor 3 - Climate “As a consequence, the Sahara will expand well over a hundred kilometres south, a process called desertification.” Increasing desterification is a concern, but 100 kilometers advancement across such a large continent isn’t going to make a difference. “vast parts of land will become unsuitable for agriculture and hence will force hundreds of people to leave their homes.” I would not call hundreds of people a humanitarian crisis. It’s not clear that the issues you cite are enough to trigger the catastrophic famine and migrations you prophesize. People respond to droughts and other agricultural challenges in different ways—switching crops, using different water sources, relying on more imports, and finding other income. EA fund a lot of efforts that help this part of the world, malaria eradication and deworming in particular, which yield significant economic gains and life improvement. Development and increasing incomes improves resiliency. You are suggesting that despite these efforts, the factors you describe will overwhelm all of the health and development work being done. You present limited information, and will need more data, models, and economic models to justify the level of concern you are raising.
On Limits To Growth (LTG). Statements along the lines of “The LTG collapse scenario has been fairly accurate to date” imply that there are real world metrics mapped to LTG variables, and that the they expect the underlying model dynamics to remain roughly accurate. I’ve been able to find one published piece of work where someone explicitly details the variables they use to match to LTG. That report was by Graham Turner, the author of the Guardian Piece you cite. The report is not peer-reviewed, and was published by the institute where Graham is a senior fellow. It is based on a 2008 paper that was peer-reviewed. The author picked per capita electricity consumption and literacy rates to represent global “services per capita”. This is misleading. One can pick almost any available variable remotely tied to represent “services per capita” that matches the shape of the LTG model, scale it, and claim that the “LTG standard run is close to reality”. There are so many spurious correlations out there. Even then, the majority of trends are 20%, 50%, 100%+ off from the “LTG standard run”. The report does not include statistical fit or calibration statistics. How can one meaningful track global pollution? Or non-renewable resources remaining?
It was never the intent of the work to be a predictive forecasting tool. The variables are lumped together proxies to represent categories of real world things, and the authors were explicit when they made the report that these did not represent real world variables; they were to just trying to show the dynamics of their theoretical model. Subsequent updates to the LTG model haven’t been able to resolve which collection of real world variables get weighted together to match to which LTG variables. It’s easy to cherry pick data to match the trend, especially if you aren’t precommitting what constitutes a fit. And even if there is a good match to trends, that doesn’t mean that a specific model is the correct representation of reality; there may be many models with wildly different assumptions of the dynamics that produce the same result. Vaclav Smil’s review of the LTG is a longer deconstruction of the LTG modeling exercise and worth a read.
More importantly, Dennis and Jorgen (living original authors who I’ve met) repeatedly say these forecasts are not to be taken literally. Jorgen Randers has a new (2014) forecast which looks very different from the “resource crisis” scenario in the 1972 LTG model. Jorgen now claims the climate crisis is the key concern and the driving force in the model. Even then, he still assumes the same overall model dynamics, but doesn’t detail the mechanisms for how the variables will actually influence each-other. For example, in using carbon emissions as his pollution variable, he assumes climate change will greatly increase overall death rates, overwhelming all factors that reduce death rates. There are many models out there (30+) that make assumptions on how climate change impacts human society in the future of which Jorgen’s new work is just one. None assume overall death rate increases as Jorgen does, especially in the near term. Be wary of projections from a single model/source. The point is, it is misguided to get doomy about older model forecasts from one model that the authors say are no longer reflective of reality, especially when there is a much wider variety of more complex, robust forecasting models in existence today that have different scenarios.
Thanks for the feedback and the food for thought it gave me to you as well. On LTG: Now I´ve read the papers by Turner and the one by Smith. The thing is, while I do genuinely concur with much of the critique by Smith; disputes about data accuracy, methods of aggregate analysis and the question whether their delicate interlinkages are representative of real-world complexities is the kind of debate that is bound to diffuse every time when you do things like QCA (Qualitative Comparative Analysis), systemic design, surveys or future predictions. Future research and macro-models are oversimplifications by necessity and therefore generate controversial, messy debates by nature. In that sense, it is logical and fruitful that we are having this discussion, which leads to the healthy challenging to existing pre-conception that one always loves to assert as something splendidly hermetically sealed.
That being said, next to the anecdotal parts, the legitimate critique raised by Smil and others about the methods of the first WW3 modelling I have read so far, it indeed shakes up the statements made but provides no concise line of argumentation that would actually invalidate them in any way. The way Smil likes to conclude from the methods being imperfect (which they certainly were especially when this mode of computer-based analysis was in its infancy at the time) to any conclusions thereby being equally invalid seems to constitute a similarly flawed process of proving one’s point.
With what I wrote here, then, I did not assert to have delivered irrefutable arguments, but much rather fair approximations as to what, supported by the data, could happen in the future and that even the possibility of these scenarios being feasible should lead EA to investigate them more thoroughly. So while even current models lack any kind of satisfactory representation of real world-complexities, they meanwhile give us a fair approximation for a rough but feasible future outlook. Now, I´ve also had the privilege of meeting Randers, Bardi and Maxton last year, and they by no means claim any perfection but point out that the data, by applying common sense, points in a clear direction that is consistent with their models outlook: When we have already exceeded planetary boundaries by 2.5 times (again an arbitrary aggregate thing, fair enough), human population has grown to 7.5 billion and will grow further, when energy demand due to population growth and rising living standards increases further, when we can assume with relative safety that in 20 years we can only extract half the oil relative to now and that the current pace of global energy transition would need to be multiple times faster to rectify the shortges thereby created; that we need CO2 emmissions to peak in the next two years and completely stop them by 2050 in order to have a chance meet the 2 degrees goal to prevent catastrophic chain reactions, but actually CO2 emmission are continuing to climb as no country is yet determined to fulfill its climate commiments and when the tipping points is soon to be reached that even absruptly stoppin any emmissions could stop climate change anymore—THEN we do not need highly sophisticated models to be able to conclude that these trends will create multiple sorts of catastrophies with grave humanitarian implications.
Now on Scenario 1: First of all, you pointed me to a mistake in the article: The effects of climate change could displace hundreds of millions of people rather than hundreds. It is difficult to find good data on land grabbing, try the “Land Matrix” data bank which registers the areas affected, the actors and miscellaneous data. What we know is that the development community is saying that the dimensions are growing significantly right now and that millions of people have already been displaced. There´s little research on this (https://www.brot-fuer-die-welt.de/themen/fluchtursachen/fluchtursache-landraub/), exact percentages are therefore hard to come by: In Sudan, 23% of land is in the hands of foreign investors, in Sierra Leone 40%, in Gabon 85% (UNHCR), but a region-wide assessment has not yet been conducted to my knwoledge. So for further analysis, we would need more data which is hard to come by as any deeper investigation of this phenomenon is usually prevented by the very governments that facilitate it, which makes it easier for them to justify that by land grabbing the local population benefits due to modern agricultural equipment when in fact all those fields are being used to cultivate cash crops that are being exported as evident in the import/export data. So you are entirely right that I require more data to substantiate the extent of my claim!
“You are suggesting that despite these efforts, the factors you describe will overwhelm all of the health and development work being done.” -In essence, yes. Development doesn´t necessarily enhance resilience, it may also create dependencies on aid and foreign imports, the international rural development budget currently sits at a measly 15%, hence climate adaptation is vastly underfunded to this very day. Conflicts in the region continue to sweep away decades of advancements in development in some cases. For real resilience, empowerment, rural development, environmental education, partially localising supply chains as well as other measures would need to be undertaken but continue to be severely neglected, which tied into a different debate about development effectiveness.
In a World Bank report form 2013, I found this though: “In Sub-Saharan Africa, by the 2030s droughts and heat will leave 40 percent of the land now growing maize unable to support that crop, while rising temperatures could cause major loss of savanna grasslands threatening pastoral livelihoods. By the 2050s, depending on the sub-region, the proportion of the population undernourished is projected to increase by 25-90 percent compared to the present.” (http://www.worldbank.org/en/topic/climatechange/publication/turn-down-the-heat) And that mostly confirms that in some form or another, this Malthusian disaster ot at the very least more seroius famines are ought to happen.
In sum: Yes, the data that is currently available does not entirely verify the level of concern raised by me, but at the same time makes it very possible by what is known, and that even the rest of the data is vastly “better” than expected, we still can safely expect larger famines and hence large-scale loss of life to occur within the next decades. Hence it is not a question if larger famines are going to happen, but in what dimensions. And that very circumstance could dictate a heavy shift in priorities for Effective Altruism as a whole.
The causal chain you propose is:
A) peak oil → energy scarcity → humanitarian crisis from ?
If not A), then:
B) emissions → climate change → agricultural loss → humanitarian crisis from famine (with land grabbing exacerbating the crisis)
Let’s jump to the crux of Rander’s update to the LTG model, since that is the most recent work most closely attached to the concept. The fundamental collapse prediction comes from the pollution—death rate linkage that I mention in the previous comment. What basis is there to assume the overall death rate will increase? And how does the model explain the decreasing death rates in that part of the world? Is it based on a presumed energy scarcity? “when we can assume with relative safety that in 20 years we can only extract half the oil relative to now and that the current pace of global energy transition would need to be multiple times faster to rectify the shortages thereby created” Where do you derive the assumption that oil production will be cut in half in 20 years for reasons of scarcity? U.S. EIA forecasts relatively flat curves. And how do you distinguish good substitutions from shortages? Concerns about peak oil presume a fixed consumption per person, meaning no fuel substitution or demand elasticity. I think this is incorrect. Oil consumption is responsive to price, and even in the least elastic sector where it is used (transportation), there is still a tradeoff in size vs. efficiency for cars people buy. You can go on Gapminder and see how the trend in oil consumption per person can vary quite a bit over several years. Electricity consumption per person (what Turner used as his proxy for “services per person”) has actually been decreasing in the U.S. because of large-scale efficiency. I expect we’ll see more of that in other sectors including transportation, with lower energy use but greater energy services overall.
Given the substitution and efficiency arguments, and how none of the climate-economic models in IPCC’s modeling exercises show an energy scarcity or pollution induced collapse, I don’t think causal chain A you propose is a reality we can expect.
So that leaves causal chain B. The World Bank report is for a 4-degree temperature rise, and is by no means a fait accompli. I think what we do now looks a lot like what EAs are currently funding in the region—improving health and encouraging inclusive development. When people have greater incomes and are less dependent on agriculture, climate change effects are less severe. This is the assessment of a follow-up report the World Bank did to the 4-degree report which is worth reading: Shock Waves Managing the Impacts of Climate Change on Poverty.