The passage is adapted from Ngonghala CN, et. al’s “Poverty, Disease, and the Ecology of Complex Systems” © 2014 Ngonghala et al.

In his landmark treatise, An Essay on the Principle of Population, Reverend Thomas Robert Malthus argued that population growth will necessarily exceed the growth rate of the means of subsistence, making poverty inevitable. The system of feedbacks that Malthus posited creates a situation similar to what social scientists now term a “poverty trap”: i.e., a self-reinforcing mechanism that causes poverty to persist. Malthus’s erroneous assumptions, which did not account for rapid technological progress, rendered his core prediction wrong: the world has enjoyed unprecedented economic development in the ensuing two centuries due to technology-driven productivity growth.

Nonetheless, for the billion people who still languish in chronic extreme poverty, Malthus’s ideas about the importance of biophysical and biosocial feedback (e.g., interactions between human behavior and resource availability) to the dynamics of economic systems still ring true. Indeed, while they were based on observations of human populations, Malthus ideas had reverberations throughout the life sciences. His insights were based on important underlying processes that provided inspiration to both Darwin and Wallace as they independently derived the theory of evolution by natural selection. Likewise, these principles underlie standard models of population biology, including logistic population growth models, predator-prey models, and the epidemiology of host-pathogen dynamics.

The economics literature on poverty traps, where extreme poverty of some populations persists alongside economic prosperity among others, has a history in various schools of thought. The most Malthusian of models were advanced later by Leibenstein and Nelson, who argued that interactions between economic, capital, and population growth can create a subsistence-level equilibrium. Today, the most common models of poverty traps are rooted in neoclassical growth theory, which is the dominant foundational framework for modeling economic growth. Though sometimes controversial, poverty trap concepts have been integral to some of the most sweeping efforts to catalyze economic development, such as those manifest in the Millennium Development Goals.

The modern economics literature on poverty traps, however, is strikingly silent about the role of feedbacks from biophysical and biosocial processes. Two overwhelming characteristics of under-developed economies and the poorest, mostly rural, subpopulations in those countries are (i) the dominant role of resource-dependent primary production—from soils, fisheries, forests, and wildlife—as the root source of income and (ii) the high rates of morbidity and mortality due to parasitic and infectious diseases. For basic subsistence, the extremely poor rely on human capital that is directly generated from their ability to obtain resources, and thus critically influenced by climate and soil that determine the success of food production. These resources in turn influence the nutrition and health of individuals, but can also be influenced by a variety of other biophysical processes. For example, infectious and parasitic diseases effectively steal human resources for their own survival and transmission. Yet scientists rarely integrate even the most rudimentary frameworks for understanding these ecological processes into models of economic growth and poverty.

This gap in the literature represents a major missed opportunity to advance our understanding of coupled ecological-economic systems. Through feedbacks between lower-level localized behavior and the higher-level processes that they drive, ecological systems are known to demonstrate complex emergent properties that can be sensitive to initial conditions. A large range of ecological systems—as revealed in processes like desertification, soil degradation, coral reef bleaching, and epidemic disease—have been characterized by multiple stable states, with direct consequences for the livelihoods of the poor. These multiple stable states, which arise from nonlinear positive feedbacks, imply sensitivity to initial conditions.

While Malthus’s original arguments about the relationship between population growth and resource availability were overly simplistic (resulting in only one stable state of subsistence poverty), they led to more sophisticated characterizations of complex ecological processes. In this light, we suggest that breakthroughs in understanding poverty can still benefit from two of his enduring contributions to science: (i) models that are true to underlying mechanisms can lead to critical insights, particularly of complex emergent properties, that are not possible from pure phenomenological models; and (ii) there are significant implications for models that connect human economic behavior to biological constraints.

Which of the following conclusions is best supported by the two graphs?

The passage is adapted from Ngonghala CN, et. al’s “Poverty, Disease, and the Ecology of Complex Systems” © 2014 Ngonghala et al.

In his landmark treatise, An Essay on the Principle of Population, Reverend Thomas Robert Malthus argued that population growth will necessarily exceed the growth rate of the means of subsistence, making poverty inevitable. The system of feedbacks that Malthus posited creates a situation similar to what social scientists now term a “poverty trap”: i.e., a self-reinforcing mechanism that causes poverty to persist. Malthus’s erroneous assumptions, which did not account for rapid technological progress, rendered his core prediction wrong: the world has enjoyed unprecedented economic development in the ensuing two centuries due to technology-driven productivity growth.

Nonetheless, for the billion people who still languish in chronic extreme poverty, Malthus’s ideas about the importance of biophysical and biosocial feedback (e.g., interactions between human behavior and resource availability) to the dynamics of economic systems still ring true. Indeed, while they were based on observations of human populations, Malthus ideas had reverberations throughout the life sciences. His insights were based on important underlying processes that provided inspiration to both Darwin and Wallace as they independently derived the theory of evolution by natural selection. Likewise, these principles underlie standard models of population biology, including logistic population growth models, predator-prey models, and the epidemiology of host-pathogen dynamics.

The economics literature on poverty traps, where extreme poverty of some populations persists alongside economic prosperity among others, has a history in various schools of thought. The most Malthusian of models were advanced later by Leibenstein and Nelson, who argued that interactions between economic, capital, and population growth can create a subsistence-level equilibrium. Today, the most common models of poverty traps are rooted in neoclassical growth theory, which is the dominant foundational framework for modeling economic growth. Though sometimes controversial, poverty trap concepts have been integral to some of the most sweeping efforts to catalyze economic development, such as those manifest in the Millennium Development Goals.

The modern economics literature on poverty traps, however, is strikingly silent about the role of feedbacks from biophysical and biosocial processes. Two overwhelming characteristics of under-developed economies and the poorest, mostly rural, subpopulations in those countries are (i) the dominant role of resource-dependent primary production—from soils, fisheries, forests, and wildlife—as the root source of income and (ii) the high rates of morbidity and mortality due to parasitic and infectious diseases. For basic subsistence, the extremely poor rely on human capital that is directly generated from their ability to obtain resources, and thus critically influenced by climate and soil that determine the success of food production. These resources in turn influence the nutrition and health of individuals, but can also be influenced by a variety of other biophysical processes. For example, infectious and parasitic diseases effectively steal human resources for their own survival and transmission. Yet scientists rarely integrate even the most rudimentary frameworks for understanding these ecological processes into models of economic growth and poverty.

This gap in the literature represents a major missed opportunity to advance our understanding of coupled ecological-economic systems. Through feedbacks between lower-level localized behavior and the higher-level processes that they drive, ecological systems are known to demonstrate complex emergent properties that can be sensitive to initial conditions. A large range of ecological systems—as revealed in processes like desertification, soil degradation, coral reef bleaching, and epidemic disease—have been characterized by multiple stable states, with direct consequences for the livelihoods of the poor. These multiple stable states, which arise from nonlinear positive feedbacks, imply sensitivity to initial conditions.

While Malthus’s original arguments about the relationship between population growth and resource availability were overly simplistic (resulting in only one stable state of subsistence poverty), they led to more sophisticated characterizations of complex ecological processes. In this light, we suggest that breakthroughs in understanding poverty can still benefit from two of his enduring contributions to science: (i) models that are true to underlying mechanisms can lead to critical insights, particularly of complex emergent properties, that are not possible from pure phenomenological models; and (ii) there are significant implications for models that connect human economic behavior to biological constraints.

Which of the following conclusions is best supported by the two graphs?

This passage is adapted from “Flagship Species and Their Role in the Conservation Movement” (2020)

Until recently, two schools of thought have dominated the field of establishing “flagship” endangered species for marketing and awareness campaigns. These flagship species make up the subset of endangered species conservation experts utilize to elicit public support - both financial and legal - for fauna conservation as a whole.

The first concerns how recognizable the general public, the audience of most large-scale funding campaigns, finds a particular species, commonly termed its “public awareness.” This school of thought was built on the foundation that if an individual recognizes a species from prior knowledge, cultural context, or previous conservational and educational encounters (in a zoo environment or classroom setting, for instance) that individual would be more likely to note and respond to the severity of its endangered status. However, recently emerging flagship species such as the pangolin have challenged the singularity of this factor.

Alongside public awareness, conservation experts have long considered a factor they refer to as a “keystone species” designation in the flagstone selection process. Keystone species are those species that play an especially vital role in their respective habitats or ecosystems. While this metric is invaluable to the environmentalists in charge of designating funds received, recent data has expressed the more minor role a keystone species designation seems to play in the motivations of the public.

Recent scholarship has questioned both the singularity and the extent to which the above classifications impact the decision making of the general public. Though more complicated to measure, a third designation, known as a species’ “charisma,” is now the yardstick by which most flagship species are formally classified. Addressing the charisma of a species involves establishing and collecting data concerning its ecological (interactions with humans/the environments of humans), aesthetic (appealing to human emotions through physical appearance and immediately related behaviors), and corporeal (affection and socialization with humans over the short- and long-terms) characteristics. This process has been understandably criticized by some for its costs and failure to incorporate the severity of an endangered species’ status into designation, but its impact on the public has been irrefutable. While keystone and public awareness designations are still often applied in the field because of their practicality and comparative simplicity, charisma is now commonly accepted as the most accurate metric with which to judge a species’ flagship potential.

The information in the graphs displays the results of a study conducted on a single sample of donors to wildlife conservation efforts. The first displays the percent who stated they were most likely to donate to a cause for each endangered species category based on a brief description of public awareness, keystone designation, and charisma in endangered species, the second graph displays the actual results of their donation choice. Note: each individual prioritized exactly one designation type and donated to exactly one designation type.

Based on the information in the graphs and passage above, which of the following can be concluded?

This passage is adapted from “Flagship Species and Their Role in the Conservation Movement” (2020)

Until recently, two schools of thought have dominated the field of establishing “flagship” endangered species for marketing and awareness campaigns. These flagship species make up the subset of endangered species conservation experts utilize to elicit public support - both financial and legal - for fauna conservation as a whole.

The first concerns how recognizable the general public, the audience of most large-scale funding campaigns, finds a particular species, commonly termed its “public awareness.” This school of thought was built on the foundation that if an individual recognizes a species from prior knowledge, cultural context, or previous conservational and educational encounters (in a zoo environment or classroom setting, for instance) that individual would be more likely to note and respond to the severity of its endangered status. However, recently emerging flagship species such as the pangolin have challenged the singularity of this factor.

Alongside public awareness, conservation experts have long considered a factor they refer to as a “keystone species” designation in the flagstone selection process. Keystone species are those species that play an especially vital role in their respective habitats or ecosystems. While this metric is invaluable to the environmentalists in charge of designating funds received, recent data has expressed the more minor role a keystone species designation seems to play in the motivations of the public.

Recent scholarship has questioned both the singularity and the extent to which the above classifications impact the decision making of the general public. Though more complicated to measure, a third designation, known as a species’ “charisma,” is now the yardstick by which most flagship species are formally classified. Addressing the charisma of a species involves establishing and collecting data concerning its ecological (interactions with humans/the environments of humans), aesthetic (appealing to human emotions through physical appearance and immediately related behaviors), and corporeal (affection and socialization with humans over the short- and long-terms) characteristics. This process has been understandably criticized by some for its costs and failure to incorporate the severity of an endangered species’ status into designation, but its impact on the public has been irrefutable. While keystone and public awareness designations are still often applied in the field because of their practicality and comparative simplicity, charisma is now commonly accepted as the most accurate metric with which to judge a species’ flagship potential.

The information in the graphs displays the results of a study conducted on a single sample of donors to wildlife conservation efforts. The first displays the percent who stated they were most likely to donate to a cause for each endangered species category based on a brief description of public awareness, keystone designation, and charisma in endangered species, the second graph displays the actual results of their donation choice. Note: each individual prioritized exactly one designation type and donated to exactly one designation type.

Based on the information in the graphs and passage above, which of the following can be concluded?

The following is adapted from a published article entitled “Dilemmas in Data, the Uncertainty of Impactors on CO2 Emissions.” (2019)

Proposed CO2 reduction schemes present large uncertainties in terms of the perceived reduction needs and the potential costs of achieving those reductions. In one sense, preference for a carbon tax or tradable permit system depends on how one views the uncertainty of costs involved and benefits to be received.

For those confident that achieving a specific level of CO2 reduction will yield very significant benefits then a tradeable permit program may be most appropriate. CO2 emissions would be reduced to a specific level, and in the case of a tradeable permit program, the cost involved would be handled efficiently, but not controlled at a specific cost level. This efficiency occurs because control efforts are concentrated at the lowest-cost emission sources through the trading of permits.

However, if one is more uncertain about the benefits of a specific level of reduction then a carbon tax may be most appropriate. In this approach, the level of the tax effectively caps the marginal control costs that affected activities would have to pay under the reduction scheme, but the precise level of CO2 achieved is less certain. Emitters of CO2 would spend money controlling CO2 emissions up to the level of the tax. However, since the marginal cost of control among millions of emitters is not well known, the overall effect of a given tax level on CO2 emission cannot be accurately forecasted.

A recent study was conducted to assess the impact of a carbon tax implemented in 2008 on the petroleum sales of a sample of cities, both those impacted by the tax, and those that were not. Based on this data, it is clear that enforcing limitations, permits, or taxation has some impact on the purchase decisions of those involved, but the extent of this impact and the best steps for achieving a reduction in carbon emissions remain unknown. In order to more thoroughly understand the impact of these methods on the purchasing decision, and thus, the emissions impact of individuals, further studies will be required.

Which of the following, if true, would weaken the use of the graph to draw the conclusion that “it is clear that enforcing limitations, permits, or taxation has some impact on the purchase decisions of those involved”?

The following is adapted from a published article entitled “Dilemmas in Data, the Uncertainty of Impactors on CO2 Emissions.” (2019)

Proposed CO2 reduction schemes present large uncertainties in terms of the perceived reduction needs and the potential costs of achieving those reductions. In one sense, preference for a carbon tax or tradable permit system depends on how one views the uncertainty of costs involved and benefits to be received.

For those confident that achieving a specific level of CO2 reduction will yield very significant benefits then a tradeable permit program may be most appropriate. CO2 emissions would be reduced to a specific level, and in the case of a tradeable permit program, the cost involved would be handled efficiently, but not controlled at a specific cost level. This efficiency occurs because control efforts are concentrated at the lowest-cost emission sources through the trading of permits.

However, if one is more uncertain about the benefits of a specific level of reduction then a carbon tax may be most appropriate. In this approach, the level of the tax effectively caps the marginal control costs that affected activities would have to pay under the reduction scheme, but the precise level of CO2 achieved is less certain. Emitters of CO2 would spend money controlling CO2 emissions up to the level of the tax. However, since the marginal cost of control among millions of emitters is not well known, the overall effect of a given tax level on CO2 emission cannot be accurately forecasted.

A recent study was conducted to assess the impact of a carbon tax implemented in 2008 on the petroleum sales of a sample of cities, both those impacted by the tax, and those that were not. Based on this data, it is clear that enforcing limitations, permits, or taxation has some impact on the purchase decisions of those involved, but the extent of this impact and the best steps for achieving a reduction in carbon emissions remain unknown. In order to more thoroughly understand the impact of these methods on the purchasing decision, and thus, the emissions impact of individuals, further studies will be required.

Which of the following, if true, would weaken the use of the graph to draw the conclusion that “it is clear that enforcing limitations, permits, or taxation has some impact on the purchase decisions of those involved”?

The following graph displays, for several major categories of public transportation, the share of total trips taken via public transportation in the United States over a year.

What statement is best supported by the data in the figure above?

The following graph displays, for several major categories of public transportation, the share of total trips taken via public transportation in the United States over a year.

What statement is best supported by the data in the figure above?

The following is excerpted from a textbook addressing the breakdown and landmass of the earth. (2018)

Which of the following conclusions cannot be drawn from the graph above?

The following is excerpted from a textbook addressing the breakdown and landmass of the earth. (2018)

Which of the following conclusions cannot be drawn from the graph above?