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# 90% Of The World Population Will Be Food Stressed By 2100

## Abstract

Climate change can alter conditions that sustain food production and availability, with cascading consequences for food security and global economies. Here, we evaluate the vulnerability of societies to the simultaneous impacts of climate change on agriculture and marine fisheries at a global scale. Under a “business-as-usual” emission scenario, ~90% of the world’s population—most of whom live in the most sensitive and least developed countries—are projected to be exposed to losses of food production in both sectors, while less than 3% would live in regions experiencing simultaneous productivity gains by 2100. Under a strong mitigation scenario comparable to achieving the Paris Agreement, most countries—including the most vulnerable and many of the largest CO2 producers—would experience concomitant net gains in agriculture and fisheries production. Reducing societies’ vulnerability to future climate impacts requires prompt mitigation actions led by major CO2 emitters coupled with strategic adaptation within and across sectors.

## INTRODUCTION

The impact of climate change on the world’s ecosystems and the cascading consequences for human societies is one of the grand challenges of our time (13). Agriculture and marine fisheries are key food production sectors that sustain global food security, human health, economic growth, and employment worldwide (46), but are substantially and heterogeneously affected by climatic change (7, 8), with these impacts being projected to accelerate as greenhouse gas emissions rise (912). Policy decisions on mitigation and adaptation strategies require understanding, anticipating, and synthesizing these climate change impacts. Central to these decisions are assessments of (i) the extent to which impacts in different food production sectors can be compensated, (ii) the consequences for human societies, and (iii) the potential benefits of mitigation actions. In that regard, global vulnerability assessments that consider countries’ exposure of food production sectors to climate-induced changes in productivity, their socioeconomic sensitivity to affected productivity, as well as their adaptive capacity are certainly useful to define the opportunity space for climate policy, provided that food production sectors are analyzed together. Building on previous multisector assessments of exposure (13, 14) and vulnerability (11), our purpose is to move toward a global-scale analysis of human vulnerability to climate change on two major food sectors: agriculture and marine fisheries.

We draw from the vulnerability framework developed in the Intergovernmental Panel on Climate Change (IPCC) (Fig. 1) to assess human vulnerability to climate change impacts on agriculture and marine fisheries for, respectively, 240 and 194 countries, states, or territories (hereafter “countries”). We evaluated exposure by projecting changes in productivity of agriculture (maize, rice, soy, and wheat) and marine fisheries to the end of the century relative to contemporary values under two contrasting greenhouse gas emission scenarios (exposure): a “business-as-usual” scenario [Representative Concentration Pathway 8.5 (RCP8.5)] and a strong mitigation scenario (RCP2.6). To generate a comprehensive index of vulnerability for agriculture and marine fisheries, we then integrated these models with socioeconomic data on countries’ dependency on each sector for food, economy, and employment (sensitivity) and the capacity to respond to climate impacts by mobilizing future assets (adaptive capacity) (Fig. 1 and table S1).

In contrast to previous global studies on vulnerability that are focused on a single sector, our approach seeks to uncover how the different vulnerability dimensions (exposure, sensitivity, and adaptive capacity) of agriculture and marine fisheries interact and co-occur under future climate scenarios to derive priority areas for policy interventions and identify potential synergies or trade-offs. We examine the impacts of climate change on two global food production sectors that are key for livelihoods and food security globally (15, 16) and for which data were available with an acceptable degree of confidence. The likely impacts on other food sectors (aquaculture, freshwater fisheries, and livestock production), for which global climate change projections are less developed, are discussed only qualitatively but will be an important future research priority as climate projections on these sectors become more refined.

## RESULTS AND DISCUSSION

### A “perfect storm” in the tropics

Spatial heterogeneity of predicted climate change impacts on agriculture and fisheries, coupled with varying degrees of human sensitivity and adaptive capacity on these sectors, suggest that for multisector countries (i.e., countries engaged in both sectors, as opposed to landlocked countries with no or negligible marine fisheries), climate change may induce situations of “win-win” (i.e., both sectors are favored by climate change), “win-lose” (i.e., losses in one sector and gains in the other), or “lose-lose” i.e., both sectors are negatively affected. Under future climate projections, tropical areas, particularly in Latin America, Central and Southern Africa, and Southeast Asia, would disproportionately face lose-lose situations with exposure to lower agriculture productivity and lower maximum fisheries catch potential by 2100 (Fig. 2, A and B, and fig. S1). These areas are generally highly dependent on agriculture and fisheries for employment, food security, or revenue (Fig. 2, C and D).

Conversely, countries situated at high latitudes (e.g., Europe and North America)—where food, jobs, and revenue dependences on domestic agriculture and seafood production are generally lower—will experience losses of lower magnitude or even gains in some cases (e.g., Canada or Russia) under future climate conditions (Fig. 2A). This latitudinal pattern of exposure is consistent across both climate change scenarios (fig. S1) and is mostly due to the combined effects of increased temperature, rainfall changes, water demand, and CO2 effects on photosynthesis and transpiration (agriculture), as well as temperature-induced shifts in species’ distribution ranges due to changes in suitable habitat and primary production (marine fisheries), as reported in other studies (10, 12, 1719).

The different dimensions of vulnerability generally merge to create a “perfect tropical storm” where the most vulnerable countries to climate change impacts on agriculture are also the most vulnerable to climate impacts on their fisheries (ρ = 0.67, P < 0.001 under RCP8.5 and ρ = 0.68, P < 0.001 under RCP2.6; Fig. 3 and fig. S2). For agriculture and, to a lesser extent, fisheries, sensitivity is negatively correlated with adaptive capacity (ρ = −0.79, P < 0.001 for agriculture and ρ = −0.12, P = 0.07 for fisheries; fig. S2), indicating that countries that are most dependent on food production sectors generally have the lowest adaptive capacity (Fig. 2). The potential impacts (i.e., the combination of exposure and sensitivity) of climate change on agriculture or fisheries will be exacerbated in the tropics, where most developing countries with lower capacity to respond to and recover from climate change impacts are located. Overall, vulnerability remains consistent across scenarios, with countries most vulnerable under RCP8.5 also ranking high under RCP2.6 for both sectors, and vice versa (ρ = 0.98, P < 0.001 and ρ = 0.96, P < 0.001 for agriculture and fisheries vulnerability, respectively).

### Challenges and opportunities for sectorial adaptation

The most vulnerable countries will require transformative changes focusing on adjusting practices, processes, and capital within and across sectors. For example, within-sector strategies such as diversification toward crops with good nutritional value can improve productivity and food security if they match with the future climate conditions (20). Although many opportunities for strategic crop diversification seem to be available under RCP2.6, few options would remain under RCP8.5 (figs. S3 and S4).

In some cases, cross-sector adaptation may be an option by diversifying away from negatively affected sectors and into positively affected ones (i.e., moving out of the loss and into the win sector in win-lose conditions). For example, some countries projected to experience losses in fisheries productivity by 2100 would experience gains in agriculture productivity (Fig. 4 and fig. S1), indicating potential opportunities for national-scale reconfiguration of food production systems. By contrast, few countries are projected to experience gains in fisheries and losses in agriculture (n = 28 under RCP2.6, n = 14 under RCP8.5; Fig. 4).

Opportunities for cross-sector diversification may be constrained not only by climate change policy (see the “Reducing exposure through climate mitigation” section) but also by poor environmental governance. Any identified potential gains in productivity are under the assumption of good environmental management (i.e., crops and fisheries being sustainably managed). Fish stocks and crops in many tropical countries are currently unsustainably harvested (21, 22), which may constrain any potential climate-related gains and increase the global burden, unless major investments in sectorial governance and sustainable intensification are made (20, 23, 24).

### Reducing exposure through climate mitigation

Vulnerability of both agriculture and fisheries to climate change can be greatly reduced if measures to mitigate greenhouse gas emissions are taken rapidly. Under a business-as-usual emission scenario (RCP8.5), almost the entire world’s human population (~97%) is projected to be directly exposed to high levels of change in at least one food production sector by 2100 (outer ring in Fig. 4A and fig. S1). Additionally, 7.2 billion people (~90% of the world’s future population) would live in countries projected to be exposed to lose-lose conditions (i.e., productivity losses in both sectors). These countries generally have high sensitivity and weak adaptive capacity (fig. S1). In contrast, only 0.2 billion people (<3% of the world’s projected population) would live in regions projected to experience a win-win situation under RCP8.5 (i.e., productivity gains in both sectors) by the end of this century (outer ring in Fig. 4B and fig. S1). Under a “strong carbon mitigation” scenario (i.e., RCP2.6), however, lose-lose situations would be reduced by a third, so ~60% of the world’s population, while win-win situations would increase by a third, so up to 5% of the world’s population, mostly because of improved agricultural productivity (Fig. 4).

Although losses in productivity potential would be inevitable in many cases, the magnitude of these losses would be considerably lower under RCP2.6, notably for countries facing lose-lose conditions whose average change in productivity would move from about −25 to −5% for agriculture and from −60 to −15% for fisheries (see change in inner rings in Fig. 4, A and B). Main improvements would occur in Africa (all crops and marine fisheries), Asia (mostly marine fisheries and wheat), and South America (mostly wheat and soy), but also in Europe (mostly marine fisheries) and North America (mostly wheat and marine fisheries; fig. S6). Hence, although negative consequences of climate change cannot be fully avoided in some regions of the world such as Africa, Asia, and Oceania, they have the potential to be drastically lowered if mitigation actions are taken rapidly.

Pathways for reducing exposure to the impacts of climate change through reduced greenhouse gas emissions should include global action and be long lasting to achieve the Paris Agreement targets (a pathway similar to RCP2.6), which can massively reduce human vulnerability to climate change impact on food production systems. Overwhelmingly, net gains (i.e., higher gains, lower losses, or losses to gains) from a successful climate mitigation strategy would prevail over net losses (i.e., higher losses, lower gains, or gains to losses) (Fig. 5A). Most vulnerable countries, in particular, would experience the highest net productivity gains (mostly through lower losses), while least vulnerable countries would benefit less from emission reductions as they would generally experience lower net productivity gains and, in some cases, net productivity losses (Fig. 5A and fig. S7).

Although this may appear as a bleak outlook for global climate mitigation, we show that among the 15 countries currently contributing to ~80% of the global greenhouse gas production, most would experience net productivity gains (lower losses or losses to gains) in agriculture (n = 10) and fisheries (n = 13) from moving from RCP8.5 to RCP2.6. These include countries with large per capita emissions such as the United States, China, and Saudi Arabia. Conversely, countries projected to experience mitigation-induced net losses in productivity would do so via lower gains, regardless of the sector considered (Fig. 5B and table S2). These results strongly suggest that committing to reduced emissions can markedly reduce the burden of climate change, in particular on the most vulnerable regions, while benefitting agricultural and fisheries sectors of most of the largest CO2 producers, thus providing additional incentives for advancing the climate mitigation agenda.

### Caveats and future directions

Although we present a new integrated vision on the challenges faced by two globally important food production sectors, many gaps of knowledge remain. First, the above estimates of people experiencing win-win, win-lose, or lose-lose situations are rough estimates given the uncertainties inherent to the climate impact models that are used to estimate exposure [(10, 12); fig. S5]. In addition, long-term trends in productivity changes overlook extreme or “black swan” events (e.g., pest and diseases, extreme weather, and political crises) that can play a critical role in food (in)stability and therefore food security (25). Although these caveats may weaken the robustness of the conclusions (26), they should not hinder action at this point, as the results remain broadly similar to other assessments that used different modeling approaches, assumptions, and data (1719).

Second, our metric of agriculture exposure adds together various globally important crops, out of which a substantial proportion (36%) is used to feed animals (27). While projections for other crops such as ground nuts, roots, peas, and other cereals suggest similar geographical patterns of change (figs. S4 and S8), changes for other locally and/or nutritionally important crops (e.g., fruits and legumes) (28) remain largely unknown, highlighting an important area for future model development.

Third, each vulnerability dimension interacts with global forces that remain largely unpredictable. These include how governments will prioritize these sectors in the future, changes in trade policies, shifting dietary preferences, changes in technologies, advances in gene editing techniques increasing crop yields, and changes in arable land and cropping density due to the interactions between arable land extension, production intensification, and soil erosion and degradation eliminating areas for cultivation, among others. Together, these gaps provide a strong motivation for more detailed integration of insights from several disciplines (29, 30).

Fourth, while we decided to limit the scope of our analysis to food production sectors for which global climate change projections were well developed, it is worth noting that different patterns of vulnerability may emerge if different sectors were included. Considering freshwater fisheries, for instance, would provide valuable insights into new opportunities (or challenges) in vulnerable countries that have a notable inland fishery sector (e.g., Malawi, Sierra Leone, Uganda, Guyana, or Bangladesh). The evidence so far seems to suggest that there is not much potential for increased inland fisheries productivity because of increased competition for waters and the current high proportion (90%) of inland catch coming from already stressed systems (31). Low-value freshwater species cultured domestically—an important component of food security globally and in many food-insecure regions [in particular in East and Southeast Asia; (32)]—may be subject to the same constraints. The global potential of marine aquaculture production that does not rely on inputs from wild-capture feeds (i.e., shellfish) is expected to decline under climate change, although regions such as Southeast Asia may become more suitable in the future [fig. S9; (33)]. For the livestock sector, decline in pasture productivity in many regions with notable broad-care grazing industry (e.g., Australia and South America; see relative changes in managed grass in fig. S4) combined with additional stresses (e.g., stock heat and water stress low-latitude regions, pests, and rainfall events) is likely to outweigh potential benefits, while disruption of major feed crops (e.g., maize; fig. S3) and marine fish stocks (Fig. 2B) used for fishmeal would affect the intensive livestock industries (34). Overall, climate change impacts on other food production sectors indicate the potential for further negative impacts on the global food system, but analyses that integrate multiple sectors are still nascent and sorely needed (35, 36).

## CONCLUSION

The goal of this analysis has been to consider the many dimensions of multisector vulnerability to inform a transition toward more integrated climate policy. On the basis of our approach and models, we conclude that although lose-lose situations will be pervasive and profound, affecting several billion people in the most food-insecure regions, climate action can markedly minimize future impacts and benefit the overwhelming majority of the world’s population. We have shown that climate action can benefit both the most vulnerable countries and large greenhouse gas emitters to provide substantial incentives to collectively reduce global CO2 emissions. The future will nevertheless entail societal adaptation, which could include adjustments within and across food production sectors.

## MATERIALS AND METHODS

### Overview

Each vulnerability dimension (exposure, sensitivity, and adaptive capacity) was evaluated using a set of quantitative indicators at the country level. Exposure was projected to the end of the century (2090–2099) using two emission scenarios (RCP2.6 and RCP8.5), which provided insights into exposure levels in the case of highly successful reduction of greenhouse gas emissions (RCP2.6) and a continued business-as-usual scenario (RCP8.5). We also accounted for future development trends by incorporating gross domestic product (GDP) per capita (an indicator of adaptive capacity) projected for 2090–2100 under a “middle of the road” scenario in which social, economic, and technological trends do not shift markedly from historical patterns Shared Socioeconomic Pathway 2 (SSP2). Projections were unfortunately not available for other indicators. Hence, we used multiple present-day indicators to capture important aspects of the sensitivity dimension. This works under the assumption that no major turnover would occur in the rankings (e.g., most dependent countries at present remain the most dependent in 2100), which is reasonable considering historical trends (fig. S10). Table S1 summarizes sources and coverage of data for each indicator. In the sections below, we describe each dimension and their underlying indicators but do not elaborate methods as they are fully described in each data source.

### Agriculture exposure

To assess exposure of countries’ agricultural sector to climate change, we used yield projections from an Inter-Sectoral Impact Model Intercomparison (ISI-MIP) Project Fast Track experiment dataset of global gridded crop model simulations (37). We considered relative yield changes across four major rainfed crop types (maize, rice, soy, and wheat) between two 10-year periods: 2001–2010 and 2090–2099. Outputs from five global 0.5° resolution crop models (EPIC, GEPIC, pDSSAT, IMAGE, and PEGASUS) based on five general circulation models (GCMs; GFDL-ESM2M, HadGEM2-ES, IPSL-CM5ALR, MIROC-ESM-CHEM, and NorESM1-M) were used. Models assume that soil quality, depth, and hydraulic properties are sufficient for sustained agricultural production. Crop models are described in full detail in (12). Model uncertainties are available in fig. S5.

The methods to summarize change in agriculture productivity globally were adapted from previous work (11, 12, 38, 39). First, we calculated each country’s total productivity for each crop averaged over each period and measured country-level relative changes as the log ratio of total productivity projected in the 2090–2099 period to baseline total productivity of 2001–2010. We repeated this process for every pair of crop model–GCM, with and without CO2 fertilization effects, for both RCPs, and assumed present-day distributions of farm management and production area. All models included explicit nitrogen, temperature, and water stresses on each crop, except PEGASUS for which results on rice were not available. Only experiments that were available for both RCP scenarios were included. We then obtained the median yield changes for each crop type and calculated the average yield change across the four crops to create the final relative change per country (i.e., our measure of agriculture exposure). Average yield changes for individual crops are presented in fig. S3 along with six additional crops (cassava, millet, ground nut, sorghum, peas, and managed grass) modeled according to the same process (fig. S4).

The impact of climate mitigation on agriculture (Fig. 5) was measured for each country as the difference between projected changes in agriculture productivity under RCP2.6 and projected changes in agriculture productivity under 8.5 averaged across all crops (maize, rice, soy, and wheat). Positive values thus indicate that climate mitigation would benefit agriculture (greater gains, lower losses, or loss to gain), and negative values indicate that climate mitigation would affect agriculture (lower gains, greater losses, or gains to losses).

### Marine fisheries exposure

To assess exposure of countries’ marine fisheries sector to climate change, we used projections of a proxy of maximum sustainable yield of the fish stocks, maximum catch potential (MCP), from the dynamic bioclimate envelope model (DBEM) (40). Contrary to other available global projections (19), the DBEM focuses largely on exploited marine fishes and invertebrates, which makes projections directly relevant to vulnerability assessment in relation to seafood production. MCP is dependent on changes in body size, carrying capacity of each spatial cell for fish stocks (dependent on the environmental suitability for their growths as well as primary productivity), and spatial population dynamics as a result of temperature, oxygen, salinity, advection, sea ice, and net primary production. Catches from each fish stock are calculated by applying a fishing mortality needed to achieve maximum sustainable yield. The DBEM thus assumes that the environmental preferences of species can be inferred from their biogeography and that the carrying capacity of the population is dependent on the environmental conditions in relation to the species’ inferred environmental preferences. It also assumes that species’ environmental preferences will not evolve in response to climate change. Last, it does not account for interspecific interactions. A more detailed list of assumptions in DBEM is provided in (40). Model uncertainties are available in fig. S5.

We considered relative MCP changes between two 10-year periods, 2001–2010 and 2090–2099, using the DBEM outputs driven by three GCMs (GFDP, IPSL, and MPI). We evaluated marine fisheries exposure by summing MCP across each country’s exclusive economic zones over each period and measured country-level relative changes as the log ratio of total MCP projected in the 2090–2099 period to baseline total MCP of 2001–2010. We repeated this process for each GCM and used the average MCP change as a final relative change per country (i.e., our measure of fisheries exposure).

The impact of climate mitigation on fisheries (Fig. 5) was measured for each country as the difference between projected changes in MCP under RCP2.6 and projected changes in MCP under 8.5. Positive values thus indicate that climate mitigation will benefit fisheries (greater gains, lower losses, or loss to gain), and negative values indicate that climate mitigation will affect fisheries (lower gains, greater losses, or gains to losses).

### Agriculture sensitivity

Sensitivity in the context of agriculture was assessed by combining metrics reflecting the contribution of agriculture to countries’ economy (economic dependency), employment (job dependency), and food security (food dependency). We calculated the percentage of GDP contributed by agricultural revenue based on the World Bank’s World Development Indicators (41) for our metric of economic dependency to agriculture. Employment data from FAOSTAT (42) were used to measure job dependency on the agricultural sector (sensu International Standard Industrial Classification divisions 1 to 5). Since these data include fishing, we subtracted the number of people employed in fisheries (see the “Fisheries sensitivity” section) to calculate the percentage of the workforce employed by land-based agriculture as a metric of job dependency. Last, we used the share of dietary energy supply derived from plants (2011–2013 average) from FAOSTAT’s Suite of Food Security Indicators (42) to evaluate food dependency on agriculture.

### Fisheries sensitivity

Similar to agriculture sensitivity, and in accordance with previous global assessment of human dependence on marine ecosystems (43), sensitivity in the context of fisheries was assessed by combining indicators of the country-level contribution of fisheries to the economy (economic dependency), employment (job dependency), and food security (food dependency). We obtained the percentage of GDP contributed by reported and unreported seafood landings in 2014 from the Sea Around Us project (44) to estimate economic dependency. We used a database of marine fisheries employment compiled in (5) to calculate the percentage of the workforce employed in fisheries and thus measure countries’ dependency on this sector for employment. Last, we used the food supply dataset from FAOSTAT (42) to compute the fraction of consumed animal protein supplied by seafood and evaluate food dependency on fisheries.

We considered that adaptive capacity was not differentiated by sector, and evaluated each country’s future adaptive capacity using the average per capita GDP for the years 2090–2100 using GDP and population projections (45). We used the intermediate development scenario for the purpose of comparability between RCP scenarios. In countries where projected GDP per capita was not available (mostly small island nations), we used the gridded (0.5°) population and GDP version developed in (46) based on data from (45).

GDP per capita is a commonly used metric to estimate countries’ ability to mobilize resources to adapt to climate change. Current GDP per capita was strongly and positively correlated with other indicators of adaptive capacity that could not be projected to 2100 including key dimensions of governance (voice and accountability, political stability and lack of violence, government effectiveness, regulatory quality, rule of law, and control of corruption) and economic flexibility (fig. S11).

### Missing data

The main data sources (table S1) allowed estimation of vulnerability for 84.8% of the world’s population. Territories and dependencies with missing data were assigned their sovereign’s values, which increased the total proportion of the population represented to 98.4%. Last, the remaining 1.6% was imputed using boosted regression trees to predict each individual indicator using all other indicators, with the exception of a few areas (<0.1% of total population) for which one indicator (agriculture exposure) was not imputed because it could not be treated as a regression problem; i.e., it depends on future climatic conditions rather than on current countries’ socioeconomic and governance indicators.

### Aggregated vulnerability index

To combine each vulnerability dimension (exposure, sensitivity, and adaptive capacity) into a single country-level metric of vulnerability per sector and per-emission scenario, we first standardized all the indicators to a scale ranging from 0 to 100 using the following formula (47, 48)

Indicatori=100*exp[ln(0.5)*(Fi/F50)]

(1)where Fi is the factor (e.g., % of workforce employed in fisheries, percentage of GDP contributed by agriculture, and governance status) for the ith unit (e.g., a country, state, or territory) under consideration and F50 is the median of the full range of values for this factor across all units. When needed, indicators were reversed so that high values convey high levels of a given vulnerability dimension (e.g., highly negative changes in agriculture productivity relate to high exposure). Each normalized indicator was then aggregated into its corresponding vulnerability dimension (e.g., job, revenue, and food dependency combined into a single metric of sensitivity) by averaging the standardized indicators. Last, the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) aggregation method was used to calculate the country-level vulnerability index

Vi,s=d+i,s/(d+i,s+di,s)*100

(2)where Vi,s is the composite index of vulnerability of the country i for the sector s (agriculture or marine fisheries), d+i,s is the distance to the positive ideal solution (i.e., minimum exposure and sensitivity, and maximum adaptive capacity; A+) of the ith country’s sector s in the Euclidean space, and di,s

is the distance to the negative ideal solution (i.e., maximum exposure and sensitivity, and minimum adaptive capacity; A) of the ith country’s sector s in the Euclidean space. The vulnerability index may range from 0, when the vulnerability dimensions correspond to A+, to 100, when they correspond to A. This approach assumes that exposure, sensitivity, and adaptive capacity equally determine overall vulnerability (unweighted). Given that vulnerability dimensions are highly correlated (fig. S2), an unequal weighting scheme would have little effect on the final vulnerability metric.

Overall, our dataset covers 240 and 194 countries/states/territories for agriculture and for fisheries, respectively, thus providing the most comprehensive assessment of vulnerability to climate change impacts on agriculture and marine fisheries to date. Analyses on the interactions between agriculture and fisheries vulnerability (e.g., Fig. 3) were only performed on multisector countries (i.e., landlocked countries were not considered). All data analyses were performed using R.

### Greenhouse gas emissions

The most up-to-date data available on countries’ total amount of CO2 emitted from the consumption of fossil fuels (2014) were retrieved from Carbon Dioxide Information Analysis Center (49). RCP2.6 is a strong mitigation greenhouse gas emission scenario, which, by the end of the 21st century, is projected to lead to a net radiative forcing of 2.6 W m2. RCP8.5 is a high business-as-usual greenhouse gas emission scenario that projects a net radiative forcing of 8.5 W m2 by the end of this century.

### Human population estimates

Country-level projected human populations to 2090–2100 were obtained from the SSP Database 2.0 (50) using the intermediate shared socioeconomic pathway (SSP2) to allow comparison of population comparison between RCP scenarios. Population projections under SSP2 assume medium fertility, medium mortality, medium migration, and the Global Education Trend (GET) education scenario for all countries. In countries where projected population was not available, we used the gridded (0.5°) population and GDP version developed in (46) based on data from (45).

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99 Comments on "90% Of The World Population Will Be Food Stressed By 2100"

1. Davy on Sun, 1st Dec 2019 5:11 am

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2. Get up Stupid!! on Sun, 1st Dec 2019 5:14 am

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4. REAL Green on Sun, 1st Dec 2019 5:24 am

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“Lumos, which has already fitted more than 100,000 solar home systems around Nigeria, will receive a fee for each new installation from the Rural Electrification Agency, known as REA, Gordon said. The Amsterdam-based company isn’t targeting only rural areas that are not served by the electricity grid but also towns and cities where power outages are frequent and households rely, at least partly, on generators. Lumos’ offering of solar panels and a battery enables families to spend a flat fee of around $15 per month rather than three or four times as much on kerosene or diesel, according to Gordon. The company expects to sign up more than a million households by the middle of next decade, he said.” 5. REAL Green on Sun, 1st Dec 2019 5:43 am “A Brief History of Wheat” https://tinyurl.com/ukgc9o7 resilience “In a regenerative farming system, I’m looking for flavour and resilience,” says Fred. “And by resilience, I mean varieties that have genetic diversity and traits that put crop resources into physiological traits such as root density and crop height that buffer fluctuations in climate and pathogen pressure. These, in theory, are going to impact the yield. But there is a trade-off between resources being put into yield or traits which improve resilience: height improves weed competition, restricts fungal spread upwards through the plant, genetic diversity restricts susceptibility to particular strains of infection, and so on.” In addition, there has been an increase in demand for sourdough bread, as well as a rise in awareness about the health benefits of whole grains. But the modern wheat we grow in this country is suited to neither market. “Thick branned wheat that’s suitable for roller wheat is no good for stone milling,” Ed points out. “You want a variety with a thinner bran because all the bran is going to go in the flour.” Similarly, the gluten levels in the flour will be different than those used in Chorleywood bread, meaning these flours aren’t ideal for sourdough baking. It’s clear our modern wheats, bred for high input farming systems and roller milling, aren’t suitable for agroecological farming or whole wheat baking. So, what grains should we be growing? How can we rebuild genetic diversity in our wheat? And can we re-localise our supply chains?” 6. Cloggie on Sun, 1st Dec 2019 5:46 am ““Dutch Company to Light a Million Nigerian Homes With Solar Power”” Nice find, here is the video: https://deepresource.wordpress.com/2019/12/01/and-the-lights-went-on-in-nigeria/ 7. Where is stupid?? on Sun, 1st Dec 2019 5:59 am Stupid id your juanpee chronic depression flaring up? Is that why you are not up trolling like a mindless idiot? LMFAO 8. REAL Green on Sun, 1st Dec 2019 6:50 am “Defending Degrowth is not Malthusian” https://tinyurl.com/rxf4vub resilience “In my book I show how such romantic (and related socialist, feminist and anarchist) ideas articulate a notion of limits as a source of freedom and abundance. Likewise, those of us who defend degrowth today do not call for limits because the world is running out of stuff. We are not worried that growth might come to an end – we want to end growth and stop its catastrophic and meaningless path, despoiling the abundance of this planet that we can enjoy in common. To put it differently: environmentalists like us are not warning of limits. We want limits. Limits in order to stop ecological and social destruction. Limits to stop in its tracks a capitalist system that knows no limits and is exploitative and ugly. Limits to leave space for others, human and non-human. Limits bring freedom. A pianist can make infinite music with a limited keyboard. Give the pianist an infinite keyboard, and she or he would paralyze. Limitless choice is debilitating. Capital’s limitless and senseless pursuit of more is not freedom – it is slavery. The call for ‘self-limitation’ is different from (neo)Malthusian views of limits as a natural property of the world. The atmosphere is not a limited ‘sink’ (what a terrible way to think of the sky) – it is we who should limit emissions so as not to screw the climate. The limit is on us, not the sky. There are no ‘natural limits’ that force us to do this or that. There is an ethical and political imperative not to: not to do everything that can be done, not to despoil the beauty we have inherited. Self-limitation the way I see it is not about constraining, but about defining collectively as societies our limits. Collective self-limitation is the essence of democracy. This is why capitalism has always had little tolerance for real democracy.” 9. REAL Green on Sun, 1st Dec 2019 6:51 am REAL Green is for degrowth. REAL Green believes in limits both planetary limits and personal limits. What REAL Green says on the subject is society can not and will not limit itself. This is because of competitive and cooperative globalism in a carbon trap with path dependencies. What this means is we are systematically determined and limited to what we are doing now. If there are any efforts at degrowth and respect for limits it will be around the edges. To change this determined condition is to collapse it. This is the position global society is in but nature has a different scenario. The planetary system is about planetary cycles of the carbon, nutrient, and hydrologic cycles that behave in a way that seeks balance. This means human forcing of the planetary cycles will cause imbalances that self-correct. We are now in a self-correction event. Science tells us this and what it means is an end of business as usual at an unknow point in the future. No amount of FAKE Green techno optimism or Brown DENIALISM will change that. It is determined there will be consequences for the extreme human actions of the Anthropocene. It is science and it is happening. So, what REAL Green says is decline now and bet the rush. Withdraw to a local that offers relative resilience and sustainability. If you can and if you can’t withdraw in your mind. What this means is an ascetic “characterized by or suggesting the practice of severe self-discipline and abstention from all forms of indulgence, typically for religious reasons.” Insert planetary reasons instead of religious and adapt it further with relative effort. This can be a religious experience and or an add on to your higher power purpose. This means Spartan living “showing the indifference to comfort or luxury traditionally associated with ancient Sparta” this is again REAL Green adapted. This means stoic living “a person who can endure pain or hardship without showing their feelings or complaining” again REAL Green adapted. This adaption is relative to your local and part of your local is your significant others. A local is physical and the abstract of relationships and intelligence. What this means is you have done the Kubler Roth and like Arthur Schopenhauer observed as you do “all truth passes through three stages: first, it is ridiculed; second, it is violently opposed; and third, it is accepted as self-evident.” What this means is the decline of the collapse process has a scientific expression. It is self-evident in human history and planetary ecology. A REAL Green embraces this truth and emulates it with personal lifestyle. A REAL Green lives succession. To live succession means to embrace abandonment, dysfunction, and the irrational of the scientific force of chaos. The act of embracing decline with its destructive effects allows a REAL Green to create constructive forces of change that yield and adapt to the destructive planetary changes and human socioeconomic decline. A REAL Green knows he can’t leave the status quo so he leverages it to leave it as much as he can in relation to what is more resilient and sustainable. REAL Green is then is a state of mind and action that is a hybrid. You triage out the worst and incorporate the best into an adapted lifestyle. To know what dead wood to clear and what seeds to plant is an individual and local effort constantly being pursued. It revolves around the old ways and the best of the new ways particular to your local but also borrowing from best practices of other locals. The reason this effort has to be constant is entropy never rests. Your local and your life system will be under constant threat. You embrace this as away of life adapting with a lower footprint but higher meaning. This takes you to an ascending level of activity. A REAL Green is first awakened to the truth of the paradigm of decline. REAL Green then embraces action and goes forth into a collapsing world to build a monastery. The monastery might be very small or larger like a community of enlightened individuals. The monastery is the place where the status quo is adapted in a hybrid life of living in it to survive but leaving it to plant the seeds of a new life that is on the horizon. This may not be your life. It may be for others. REAL Green is other orientated and planetary which means you live a life of making and giving in respect for the planet and your neighbor. You do this relatively and local. The bigger world is crashing down around us. You study this and follow trends not because you think you can change it but because you want to get out ahead of the gradient of the collapse process with proactive efforts that will have staying power. You may only buy yourself a little time in a collapse but REAL Green is about the journey not the destination. We are all dead in the end even the pyramids will be washed away someday. REAL Green is about life now in vitality in a painful world of decline. 10. Symptoms of schizophrenia on Sun, 1st Dec 2019 7:49 am DELUSIONS: These are false beliefs that are not based in reality. For example, you think that you’re being harmed or harassed….. certain gestures or comments are directed at you….. you have exceptional ability or fame….. or a major catastrophe is about to occur….. Delusions occur in most people with schizophrenia. speech may include putting together meaningless words that can’t be understood, sometimes known as word salads….. 11. Cloggie on Sun, 1st Dec 2019 8:02 am “REAL Green is for degrowth. REAL Green believes in limits both planetary limits and personal limits.‘ Clogg believes in a “refactored industrial civilization”, with many gigawatt-sized offshore windfarms and ditto electrolyzers, ever increased carbon tax to help phasing out fossil fuel. I believe in e-vehicles, autonomous or otherwise, e-flying and in the hydrogen economy and in the Paris Accords and EU renewable energy policy. There is a general planetary growing awareness that the old ways should be abandoned, sometimes bordering the hysterical. That awareness can be used to push through otherwise unpopular measures, like increasing the price of tourism travel. Heinberg and ASPO were wrong, we do not need to worry about fossil fuel running out. If we proceed with the renewable energy path, spearheaded by the EU, we can expect that the transition will be smooth and completed in Europe before 2050, with the rest following later this century. It is open how deep climate change will happen. Perhaps half of my country will disappear under the waves, perhaps things will not be that bad (I think the latter). The real change in the coming years will be geopolitical, the growing “emancipation” of Eurasia, away from Washington-lead “global integration” towards a more identitarian multi-polar world. It depends on the reaction of the stakeholders of empire, how messy that geopolitical transition is going to be. 12. Davy on Sun, 1st Dec 2019 8:17 am good job cloggo, saved this to my notes. At least you believe in something unlike stupid who is a mindless egotistical asshole. 13. Davy on Sun, 1st Dec 2019 8:19 am BTW, cloggo, I am calling you TECHNO Power. lol. better than MINDLESS Stupid of our board troll, juanPee 14. JuanP the idiot on Sun, 1st Dec 2019 8:22 am MINDLESS Stupid is up Symptoms of schizophrenia said DELUSIONS: These are false beliefs that are not ba… 15. Cloggie on Sun, 1st Dec 2019 8:22 am “Europe gets a$15.9 billion funding boost for its space exploration plans”

https://edition.cnn.com/2019/11/28/europe/european-space-agency-budget-scn/index.html

Budgets:

ESA $16B NASA$19B

Only a matter of time…

16. Helping Someone with schizophrenia on Sun, 1st Dec 2019 8:29 am

People with schizophrenia often lack awareness that their difficulties stem from a mental disorder that requires medical attention.

If you think someone you know may have symptoms of schizophrenia, talk to him or her about your concerns.

Laws on involuntary commitment for mental health treatment vary by state. You can contact community mental health agencies or police departments in your area for details.

17. Davy on Sun, 1st Dec 2019 8:31 am

https://tinyurl.com/y9gamzlr statista

“Sunday marks World AIDS Day, which aims to promote awareness of the disease and mourn those who have died from it. The event came into existence in 1988 and it has been widely observed by health officials, governments and non-governmental organizations since then.

One aspect of HIV which needs to be highlighted more frequently is its growing infection rate across Eastern Europe and Russia in particular. According to new data from the European Centre for Disease Prevention and Control and World Health Organization, there were 71 new HIV diagnoses per 100,000 people in Russia last year. Ukraine came a distant second with 37 while third-placed Belarus had 26. The lowest rates of new diagnoses per 100,000 people were recorded in Bosnia and Herzegovina (0.3), Slovakia (1.3) and Slovenia (1.9).”

only a matter of time

18. Habitual Liars Club on Sun, 1st Dec 2019 8:36 am

Why does Davy use various sock puppets when he constantly accuses others?

DavySkum is the worst hypocrite and pathological liar ever encountered. No wonder he is a full-fledged Trumptard. Birds of a feather always flock together.

Habitual Liars Club: Trump and DavySkum lifelong membership.

19. JuanP Idiot on Sun, 1st Dec 2019 8:57 am

lol Mindless Stupid is triggered

Habitual Liars Club said Why does Davy use various sock puppets when he co…

20. JuanP Idiot wife on Sun, 1st Dec 2019 8:58 am

JuanPee is your ugly wife part of the MINDLESS Stupid club? She has to be being your better half. LMFAO

21. JuanP on Sun, 1st Dec 2019 10:45 am

The solution is very simple: reduce the global population rapidly by offering free sex education, abortions, contraceptives, and condoms to everyone in the world. Also, we need to educate, empower, and employ all the women in the world. We also need to provide free education and health care to everyone in the world.

We have all the necessary resources except human intelligence, mental sanity, understanding, humility, and common sense. This will not end well, and anyone who thinks that more energy is the solution to the current human predicament doesn’t understand the Laws of Thermodynamics and/or human nature.

22. PO.com Thanks You on Sun, 1st Dec 2019 10:50 am

Thank you, JuanP, for a refreshing voice of sanity.

23. PO.com Thanks You on Sun, 1st Dec 2019 10:55 am

Forgot to compliment the DavySkum for connecting the schizophrenia post to himself.

Now that you recognize your mental health challenges, seek treatment before you are forcibly institutionalized for the good of society.

24. JuanP Idiot on Sun, 1st Dec 2019 11:04 am

This is MINDLESS Stupid:

Richard Guenette said I don’t believe a word that Forbes writes.

PO.com Thanks You said Forgot to compliment the DavySkum for connecting t…

Richard Guenette said The US government needs a government that is a dir…

PO.com Thanks You said Thank you, JuanP, for a refreshing voice of sanity…

25. Davy on Sun, 1st Dec 2019 11:10 am

“The solution is very simple: reduce the global population rapidly by offering free sex education, abortions, contraceptives, and condoms to everyone in the world. Also, we need to educate, empower, and employ all the women in the world.”
What a dumbass, there is no way to reduce populations rapidly. Population levels are beyond human control. The only power that can reduce population levels is nature.

“We also need to provide free education and health care to everyone in the world.”
LMFAO, dumbass thinks we can afford that?? He is as stupid as his socialistic asswipe socks he employs here. The problem with Juanpee is he is a high school drop out that thinks he has a PHD in fuckwacking

“We have all the necessary resources except human intelligence, mental sanity, understanding, humility, and common sense.”
You set a great example Juanpee for all the excepts above. Your 2 years of trolling demonstrate how completely fuckup’d and stupid you are.

“ This will not end well, and anyone who thinks that more energy is the solution to the current human predicament doesn’t understand the Laws of Thermodynamics and/or human nature.”
No shit stupid. Where did you figure out that one??

26. PO.com Thanks You on Sun, 1st Dec 2019 11:11 am

for showing juanpee (stupid) the door

27. Symptoms of Schizophrenia for Davy and his friend REAL Green on Sun, 1st Dec 2019 11:22 am

DELUSIONS:

These are false beliefs that are not based in reality. For example,

you think that you’re being harmed or harassed…..

certain gestures or comments are directed at you…..

you have exceptional ability or fame…..

or a major catastrophe is about to occur…..

28. Symptoms of Schizophrenia for Davy and his friend REAL Green on Sun, 1st Dec 2019 11:31 am

Disorganized thinking:

answers to questions may be partially or completely unrelated….

speech may include putting together meaningless words that can’t be understood, sometimes known as word salad….

29. Davy on Sun, 1st Dec 2019 11:37 am

Dear Friends:

Please read my quote at the bottom (or any random quote of mine) for a sample of my civil commentary. Please note my polite, moderate, and balanced approach.

~~Even if a comment is not directed at me, I attack using a familiar litany of playground taunts, insults, and all forms personally demeaning speech.

~~I accuse posters of being a “foreigner”, and I tell them to get out of my country.

~~I address people with condescending names.

~~I make statements without evidence.

~~I always work “hate” into my comments.

~~Always moderate and neuter stupid Democrats and lying liberals.

“STFU annoymouse. You do not have the right to attempt a normal comment. You are are emotional kid with a stalking and trolling problem. Your comments are as stupid as your buddy stupid. Dumbass Canadian waste case.”

30. Duncan Idaho on Sun, 1st Dec 2019 11:41 am

Hint:
The US is not energy independent. Production is ~ 12.5 million per day and consumption is over 20.

https://www.eia.gov/tools/faqs/faq.php?id=33&t=6

It is amazing the ignorance of the US public.
Well, not really

31. Davy on Sun, 1st Dec 2019 11:51 am

Back to the HIV thang. Cus it’s got so much to do with the topic of food stress in 2100.

Here in the US the CDC estimates an average of 39,000 new HIV infections per year. Or around 11 per 100,000 people. As of 2016 there were an estimated 1,140,400 people in the US who were HIV positive. Or about 1 out of every 310 Americans.

https://www.cdc.gov/hiv/pdf/library/reports/surveillance/cdc-hiv-surveillance-supplemental-report-vol-24-1.pdf

That’s a lot!

dumbasses

32. REAL Green on Sun, 1st Dec 2019 11:59 am

Grate comment Davy. We should save that to our notes so we can copy and paste it on our own blog.

33. JuanP is an Idiot liar ID theft asswipe with lunatic socks on Sun, 1st Dec 2019 11:59 am

LOL, did you see MINDLESS Stupid try to make a stab a legitimate comments and fail miserably. This is why the piece of shit has chosen trolling with ID theft and multiple socks instead. He is a failure with intelligent conversation so he turns to dirty backstabbing. Fuck JuanP and his stinky whore wife.

This is from stupid:
Davy said Back to the HIV thang. Cus it’s got so much to do…

Davy said Dear Friends: Please read my quote at the bottom (…

Symptoms of Schizophrenia for Davy and his friend REAL Green said Disorganized thinking: answers to questions may be…

Symptoms of Schizophrenia for Davy and his friend REAL Green said DELUSIONS: These are false beliefs that are not ba…

34. JuanP is a dumbasssss lmfao on Sun, 1st Dec 2019 12:00 pm

MINDLESS Stupid ID theft:

REAL Green said Grate comment Davy. We should save that to our not…

35. Davy on Sun, 1st Dec 2019 12:05 pm

Ignore the JuanP is an idiot/ dumbasses troll.

He’s obviously a schizophrenic.

36. Duncan Idaho on Sun, 1st Dec 2019 12:06 pm

“Nobody in 1963 would imagine that the USA of the 2000s would be the USA of finance, of Wall Street; of football players, of the anti-vaxxers, of the flat earthers and of the Kardashians.”

37. Davy on Sun, 1st Dec 2019 12:06 pm

Thanks Green. You’ll always be my one and only BFF.

38. JuanP Idiot on Sun, 1st Dec 2019 1:08 pm

This is ID theft from MINDLESS Stupid otherwise known as JuanP:

Davy said Thanks Green. You’ll always be my one and only BFF…

Davy said Ignore the JuanP is an idiot/ dumbasses troll. He’…

39. REAL Green on Sun, 1st Dec 2019 1:32 pm

Me n Davy invite y’all to check out the link in my handle. (thats why it’s blue and not black like the rest of you dumbasses) it gots some good info on what me n Davy are all about. We’ve decided to make Davys handle blue sometimes too.

40. MINDLESS Stupid on Sun, 1st Dec 2019 2:28 pm

This is my ID theft. I am juanpee pee.

REAL Green said Me n Davy invite y’all to check out the link in my…

41. Davy on Sun, 1st Dec 2019 2:31 pm

That’s a REAL Good idea REAL Green!

That’s why I let you be in charge sometimes.

42. Davy on Sun, 1st Dec 2019 2:33 pm

Ignore the MINDLESS Stupid troll. He’ll eventually get board and fade away.

43. I AM THE MOB on Sun, 1st Dec 2019 4:48 pm

“I didn’t kill any people. Just fascists.”

44. makati1 on Sun, 1st Dec 2019 4:57 pm

Duncan, the US has already slipped down the chute at least half way to the bottom. I graduated high school in 1962. Today’s US is nothing like what I expected it to be, all in the negative. Then, they were talking a George Jetson lifestyle and we got a zombie nation instead. The only difference between an old, pre-civil war plantation and today’s Amerika is; most all Amerikans are slaves to their ‘massahs’, the oligarchs. Chained by debt to serve.

Dumbed down is only part of the problem. What Amerikans do know is mostly propaganda. Not one in 100,000 could point to Afghanistan or Syria or Venezuela on a blank world map. The same ratio could not tell you how their money system works, or even their government.

The older generation worries about their retirement slipping away. The middle generation worries about their debt and paying the bills. And the younger generation is too busy taking selfies and posting what they ate for breakfast, to care about anything.

THAT is Amerika today. Buckle up!

45. REAL Green on Sun, 1st Dec 2019 5:15 pm

So true makato. So true.

46. I AM THE MOB on Sun, 1st Dec 2019 9:25 pm

Official: Russian-owned company attempted Ohio election hack

https://apnews.com/6518b9a986f640c4899a979bbc48390b

This is an act of war!

We cant let Putin destroy the country. Hit him hard. A nuclear first strike. And then take the oil! Annex Russia!

47. Anonymouse on Sun, 1st Dec 2019 9:42 pm

Stfu davy. Gawd damn, you whine about so-called ‘socks’, non-stop, yet you bring that dumbass doppleganger of yours, I AM THE DAVYTARD, out of the outhouse to stink the place up again. Whats the matter? No one paying any attention to that idiotic ‘muzzie’ sock of yours, so now its I AM THE DAVYSOCKs turn again?

loser…

48. Habitual Liars Club on Sun, 1st Dec 2019 10:59 pm

“His Hispanic/black approval ratings are at record levels for a Republican”

Co-founding member of the Habitual Liars Club, DavySkum, continues the charade of lies and hypocrisy.

Regarding Skum’s assertion that Trump’s approval is at “record levels” for Blacks and Hispanics, nothing could be further from the truth.

An amalgamation of approved polls for the preiod ending 11/27 by The Organization for Statistical Sampling Integrity shows Trump’s Black approval rating at 11% Approve and 19% Hispanic.

If Trump’s approval among the two largest minority groups of 11% and 19% represents record levels for Republicans, this is great news.

Jesus wept for the Skum…..

49. JuanP is an Idiot on Mon, 2nd Dec 2019 4:17 am

Stupid pollutes the board with his widdle hurt emotions. What a mental case!

Habitual Liars Club said “His Hispanic/black approval ratings are at…

REAL Green said So true makato. So true.

Richard Guenette said The US military is weak (It is full of defects- f…

Davy said Ignore the MINDLESS Stupid troll. He’ll eventually…

REAL Green said Me n Davy invite y’all to check out the link in my handle.

REAL Green said Me n Davy invite y’all to check out the link in my…

Davy said That’s a REAL Good idea REAL Green! That’s why I let you be in charge sometimes.

Davy on Sun said Ignore the MINDLESS Stupid troll. He’ll eventually get board and fade away.

REAL Green on Sun said So true makato. So true.