Sustainability science

From Wikipedia, the free encyclopedia

 

Sustainability science emerged in the 21st century as a new academic discipline. This new field of science was officially introduced with a "Birth Statement" at the World Congress "Challenges of a Changing Earth 2001" in Amsterdam organized by the International Council for Science (ICSU), the International Geosphere-Biosphere Programme (IGBP), the International Human Dimensions Programme on Global Environmental Change and the World Climate Research Programme (WCRP). The field reflects a desire to give the generalities and broad-based approach of “sustainability” a stronger analytic and scientific underpinning as it "brings together scholarship and practice, global and local perspectives from north and south, and disciplines across the natural and social sciences, engineering, and medicine". Ecologist William C. Clark proposes that it can be usefully thought of as "neither 'basic' nor 'applied' research but as a field defined by the problems it addresses rather than by the disciplines it employs" and that it "serves the need for advancing both knowledge and action by creating a dynamic bridge between the two".

The field is focused on examining the interactions between human, environmental, and engineered systems to understand and contribute to solutions for complex challenges that threaten the future of humanity and the integrity of the life support systems of the planet, such as climate change, biodiversity loss, pollution and land and water degradation.

Sustainability science, like sustainability itself, derives some impetus from the concepts of sustainable development and environmental science.^[6] Sustainability science provides a critical framework for sustainability^[7] while sustainability measurement provides the evidence-based quantitative data needed to guide sustainability governance.^[8]

Definition

Consensual definition of sustainability science is as elusive as the definition of "sustainability" or "sustainable development". In an overview presented on its website in 2008 the Sustainability Science Program at Harvard University described the field in the following way, stressing its interdisciplinarity:

'Sustainability science' is problem-driven, interdisciplinary scholarship that seeks to facilitate the design, implementation, and evaluation of effective interventions that foster shared prosperity and reduced poverty while protecting the environment. It is defined by the problems it addresses rather than the disciplines it employs. It thus draws as needed from multiple disciplines of the natural, social, medical and engineering sciences, from the professions, and from the knowledge of practice.^[9]

Susan W. Kieffer and colleagues, in 2003, suggested, more specifically, that sustainability science is:

... the cultivation, integration, and application of knowledge about Earth systems gained especially from the holistic and historical sciences (such as geology, ecology, climatology, oceanography) coordinated with knowledge about human interrelationships gained from the social sciences and humanities, in order to evaluate, mitigate, and minimize the consequences, regionally and worldwide, of human impacts on planetary systems and on societies across the globe and into the future – that is, in order that humans can be knowledgeable Earth stewards.^[10]

It has been noted that the new paradigm

... must encompass different magnitudes of scales (of time, space, and function), multiple balances (dynamics), multiple actors (interests) and multiple failures (systemic faults).^[11]

Others take a much broader view of sustainability science, emphasizing the need to analyze the root causes of the fundamental unsustainability of the prevailing economic system, such as the emphasis on growth as key to solving political and social problems and advancing society's well-being. In a 2012 article entitled "Sustainability Science Needs to Include Sustainable Consumption," published in Environment: Science and Policy for Sustainable Development, Halina Brown argues that sustainability science must include the study of the sociology of material consumption and the structure of consumerist society, the role of technology in aggravating the unsustainable social practices, as well as in solving the problems they create, the macroeconomic theories that presuppose economic growth as a necessary condition for advancing societal well-being, and others.^[12]

Broad objectives

The case for making research and development an important component of sustainable development strategies was embraced by many international scientific organizations in the mid-1980s, promoted by the Brundtland Commission's report Our Common Future in 1987, and noted in the Agenda 21 plan that emerged from the United Nations Conference on Environment and Development in 1992 and further developed at the World Summit on Sustainable Development, held in Johannesburg in 2002.

The topics of the following sub-headings indicate recurring themes that are addressed in the literature of sustainability science.^[13] In 2010 a compendium of basic papers in this new discipline was published as Readings in Sustainability Science and Technology, edited by Robert Kates, with a preface by William Clark.^[14] The 2012 Commentary by Halina Brown extensively expands the scope of that seminal publication.^[12] This is work in progress. The 2012 Encyclopedia of Sustainability Science and Technology was created as a collaboration of over 1000 scientists to provide peer-reviewed entries covering sustainability research and policy evaluations of technology.^[15]

Knowledge structuring of issues

Knowledge structuring has been identified as an essential first step in the effort to acquire a comprehensive view of sustainability issues which are both complex and interconnected. This is needed as a response to the requirements of academia, industry and government.

Coordination of data

The key research and data for sustainability are sourced from many scientific disciplines, topics and organisations. A major part of knowledge structuring will entail building up the tools that provide an “overview” of what is known. Sustainability science can construct and coordinate a framework within which the vast amount of data can be easily accessed.

Interdisciplinary approaches

The attempt, by sustainability science, to understand the integrated “whole” of planetary and human systems requires cooperation between scientific, social and economic disciplines, public and private sectors, academia and government. In short it requires a massive global cooperative effort and one major task of sustainability science is to assist integrated cross-disciplinary coordination.

Journals

• Consilience: The Journal of Sustainable Development, seminannual journal published since 2009, now "in partnership with Columbia University Libraries".^[16]
• International Journal of Sustainable Development & World Ecology, journal with six issues per year, published since 1994 by Taylor & Francis.^[17]
• Surveys and Perspectives Integrating Environment & Society (S.A.P.I.EN.S.), semiannual journal published by Veolia Environment from 2008-2015.^[18] A notable essay on sustainability indicators by Paul-Marie Boulanger appeared in the first issue.^[19]
• Sustainability Science, journal launched by Springer in June 2006.^[20]
• Sustainability: Science, Practice, Policy, an open-access journal for sustainable solutions launched in March 2005. Now published by Taylor & Francis.^[21]
• Sustainability: The Journal of Record, bimonthly journal published by Mary Ann Liebert, Inc. beginning in December 2007.^[22]
• A section dedicated to sustainability science in the multidisciplinary journal Proceedings of the National Academy of Sciences was launched in 2006.^[23]
• GAIA: Ecological Perspectives for Science and Society / GAIA: Ökologische Perspektiven für Wissenschaft und Gesellschaft, a quarterly inter- and transdisciplinary journal for scientists and other interested parties concerned with the causes and analyses of environmental and sustainability problems and their solutions. Launched in 1992 and published by oekom verlag on behalf of GAIA Society – Konstanz, St. Gallen, Zurich.^[24]

List of sustainability science programs

In recent years, more and more university degree programs have developed formal curricula which address issues of sustainability science and global change:

Bachelor's

• B.A. or B.S. Sustainability at Arizona State University, USA
• B.S. Sustainability Studies at Florida Institute of Technology, USA
• B.S. or B.S./M.S. combined - Sustainability Science at Montclair State University, NJ, USA
• B.Sc. Environmental Sciences at Leuphana University Lueneburg, Germany
• B.Sc. Environmental and Sustainability Studies at Leuphana University Lueneburg, Germany
• B.Sc. Sustainability Science at Solent University, UK

Master's

• M.S. Sustainability: Science and Society at Brock University, ON, Canada
• M.Sc. Sustainability Science and Solutions, Lappeenranta University of Technology, Finland
• M.Sc. Sustainability Science at Montclair State University, NJ, USA
• M.Sc. Sustainability Science at Leuphana University Lueneburg, Germany
• MBA Sustainability Management at Leuphana University Lueneburg, Germany
• Master's degree at the IATEUR - Urban, Regional Planning and Sustainability Science Institute, Reims University, France
• M.Sc. "Sustainability Science and Policy" at Maastricht University - ICIS, The Netherlands
• MS/MBA Erb Institute for Sustainable Enterprise (multiple sub specialties) at the University of Michigan, USA
• M.Sc. "Sustainable Resource Management" at the Technical University of Munich, Germany
• M.Sc. "Global Change Ecology" at the University of Bayreuth, Germany
• M.Sc. "Global Change Management" at the University of Applied Sciences Eberswalde, Germany
• M.Sc. "Environmental Change and Global Sustainability" at the University of Helsinki, Finland
• M.Sc. "Environmental Studies and Sustainability Science" at the University of Lund, Sweden
• "Master of Development Practice Degree Program" at the University of Minnesota, USA
• "Lund University's International Master's Programme in Environmental Studies and Sustainability Science" at Lund University, Sweden.
• "Master`s Degree in Creative Sustainability" at Aalto University, Finland
• M.Sc. Strategic Leadership towards Sustainability at Blekinge Institute of Technology, Karlskrona, Sweden
• Master's in Sustainable Product-Service System Innovation at Blekinge Institute of Technology, Karlskrona, Sweden
• MSc Environmental Technology at Imperial College London, UK, offers eight specialist streams in: water, pollution, business, global environmental change & policy, economics & policy, ecological management, environmental analysis & assessment, energy policy.
• MPhil in Engineering for Sustainable Development, University of Cambridge, UK
• M.Sc. Sustainability Science, University of Massachusetts Amherst, USA
• MSEM (Professional Masters in Sustainability and Environmental Management), at the University of Saskatchewan, School of Environment and Sustainability, Saskatoon, SK, Canada
• M.S. Sustainability Management, Columbia University, USA

Master's and doctoral

• M.Sc/M.A/Ph.D in Sustainability Science at School of Sustainability, Arizona State University, Tempe, USA
• M.Sc. in Sustainability Science and PhD in Environmental Management at Montclair State University, NJ, USA
• M.Sc./Ph.D. "Building Science and Sustainability" in the Department of Architecture at the University of California, Berkeley, USA
• M.Sc. Sustainability/PhD in Sustainability Science at the United Nations University Institute for the Advanced Study of Sustainability, Tokyo, Japan
• M.Sc./Ph.D. in Environment and Sustainability at the University of Saskatchewan, School of Environment and Sustainability, Saskatoon, SK, Canada
• "Graduate Program in Sustainability Science" at the University of Tokyo, Japan
• "Graduate Program in Sustainability Science" at Hosei University, Japan
• M.Sc/Ph.D. in Sustainability Science at the National Autonomous University of Mexico (UNAM), Mexico City, Mexico
• Ph.D. in Sustainable Development, Columbia University, USA

Other

• Course on the Science of Sustainability by the department of Earth and Environmental Sciences at Indian Institute of Science Education & Research, Bhopal.
• Environmental Science and Policy Program at Clark University, Worcester, MA, USA, offers a graduate seminar "Sustainable Consumption Production."
• "Global Change Ecology" at the University of California, Irvine, USA
• "Sustainability Specialization" at Michigan State University, USA
• Graduate Certificate in Sustainability at Michigan Technological University, USA [3]
• Undergraduate certificate in environment and sustainability at the University of Saskatchewan, School of Environment and Sustainability, Saskatoon, SK, Canada
• Minor in Global Environmental Sustainability and Sustainable Water Interdisciplinary Minor (SWIM) at the School of Global Environmental Sustainability at Colorado State University [4], USA

Recently, numbers of people doing a PhD gather under the title of sustainable sciences purposes. They come from different backgrounds and work around this topic. This sort of work enables the topic to be interdisciplinary and improve the work of PhDs. Here is an example of such gathering : BhIOSS Group (Birmingham Initiative on Sustainable Sciences)

Ecological yield

From Wikipedia, the free encyclopedia

Ecological yield is the harvestable population growth of an ecosystem. It is most commonly measured in forestry: sustainable forestry is defined as that which does not harvest more wood in a year than has grown in that year, within a given patch of forest.

However, the concept is also applicable to water, soil, and any other aspect of an ecosystem which can be both harvested and renewed—called renewable resources. The carrying capacity of an ecosystem is reduced over time if more than the amount which is "renewed" (refreshed or regrown or rebuilt) is consumed.

Ecosystem services analysis calculates the global yield of the Earth's biosphere to humans as a whole. This is said to be greater in size than the entire human economy. However, it is more than just yield, but also the natural processes that increase biodiversity and conserve habitat which result in the total value of these services. "Yield" of ecological commodities like wood or water, useful to humans, is only a part of it.

Very often an ecological yield in one place offsets an ecological load in another. Greenhouse gas released in one place, for instance, is fairly evenly distributed in the atmosphere, and so greenhouse gas control can be achieved by creating a carbon sink literally anywhere else.

History

Some of the earliest academic papers on the subject were researching methods of sustainable fishing. Work of Russel et al. in 1931 observed in particular that ”it appears that the ideal of a stabilised fishery yielding a constant maximum value is impractical.”^[1] This work was mostly theoretical. Practical work would begin later, performed by industry and government agencies.

Motivation

Ecological yield is a theoretical construct which aggregates information from several physically measurable quantities. It can be used to reason about other ecological indicators such as the footprint. It can also be used as a decision-making tool for governments and corporations.

Ecological footprint

The idea of ecological footprints is to measure the cost of economic activity in terms of the amount of ecologically productive land required to sustain it. Doing this accurately requires estimating how productive the land is; in other words, it requires measuring ecological yield. Conversely, one can extract ecological yield estimates from ecological footprint estimates.

Avoiding overexploitation

Corporations take out loans to buy equipment and land use rights. In order to pay back these loans, they must extract and sell resources from the land. If the corporation is ignorant of the yield of the land in question, then the debt instruments may demand a yield greater than the ecological capacity to renew. Green economics links this process with ecocide and poses solutions through monetary reform.

Even well-meaning corporations may systematically overestimate the yield of an ecosystem. In the case of multiple corporations bidding for land rights, an economic phenomenon known as the winner's curse causes the winning party to systematically overestimate the economic value of the land. Typically the economic value comes mostly from the ecological yield, in which case the corporation will overestimate that as well.

Another form of overestimation may come from generalizing data from other ecosystems. For example, the same species of fish in two different systems may have significantly different diets. If its diet in one region consists mostly of algae but in another region consists largely of smaller fish, then it will be more expensive for the latter ecosystem to produce the fish. Yield will be correspondingly lower in the second region. This example illustrates the need for ecosystem-specific study and monitoring in order to reason about ecological yield.

Definition and properties

One may define yearly ecological yield for a fixed ecological product as follows: the yield is the amount of the product which may be removed from the ecosystem so that it is capable of recovering in one year. As a theoretical property of ecosystems, it cannot be measured directly but only estimated. Note that definition is sensitive to the time period which is allowed for recovery: the amount of product one can remove which regenerates over 3 years is not necessarily 3 times that which one can remove and regenerate over 1 year. The yearly ecological yield is most useful because of the cycle of seasons and the commercial notion of the fiscal year. The seasons affect growth through temperature, sunlight, and rain, especially at the lowest trophic level. The fiscal year affects decisions by corporations to harvest resources: they may choose to harvest at or above ideal levels based on their need for short-term cash flow.

Calculation techniques

Yield of the whole biosphere

In 1986, Vitousek et al.^[2] estimated that humans made use of 50 petagrams (50 billion tons) per year of biomass produced from photosynthesis. They also estimated that these 50 billion tons comprised between 20% and 40% of photosynthetic activity on earth. Separately, the Global Footprint Network estimates the total human footprint as 1.6 times the total biosphere. ^[3] This implies that ecosystems are overexploited by a factor of 1.6 on average.

Theoretical prediction

In most biomes, the only form of primary production is photosynthesis. In other words, all new biomass can be traced back to photosynthetic plants and algae by a chain of predation. Therefore, one can predict the yield of one organism in an ecosystem as a function of the yield of its primary producers. When the biomass from prey is converted into biomass in its predator, some losses occur due to biological and thermodynamic inefficiency. The conversion rate is typically about 10%. In other words, 100 kg of plant matter may be converted into 10 kg of herbivores, which then may be converted to 1 kg of carnivores who exclusively eat herbivores. One can compute the trophic level of an organism as the weighted average of length of the predation chain from the organism to a primary producer. This trophic level determines an exponential multiplier to convert from primary producer biomass to the organism's biomass.

Measurement techniques

Measuring forests

One can measure the amount of wood removed from a forest by asking the company who removed it; typically only one company has the logging rights to any given plot of land. In order to measure the regrowth of the forest in the coming year, typically one picks a representative subsample of the region and tracks every single tree in the subsample.

One such study measured growth in a section of the Tapajós National Forest for 13 years after logging activity.^[4] The loggers intended to harvest on a 30-year cycle. Logging in this region is restricted to mature trees measuring at least 45 cm DBH. Before logging, the region had somewhere between 150 m³ and 200 m³ of mature tree volume per hectare. Loggers removed about 75 m³ of tree per hectare, between 40% and 50% of the standing mass.

The authors show that growth rates in the region were elevated for up to 3 years after logging. After 13 years of growth, the basal area reached 75% of its original volume. They also show that logging makes substantial changes to the species composition and canopy structure of the forest. This introduces subjectivity into the notion of "recovery" for an ecosystem.

Maximum sustainable yield

From Wikipedia, the free encyclopedia

 

In population ecology and economics, maximum sustainable yield or MSY is theoretically, the largest yield (or catch) that can be taken from a species' stock over an indefinite period. Fundamental to the notion of sustainable harvest, the concept of MSY aims to maintain the population size at the point of maximum growth rate by harvesting the individuals that would normally be added to the population, allowing the population to continue to be productive indefinitely. Under the assumption of logistic growth, resource limitation does not constrain individuals' reproductive rates when populations are small, but because there are few individuals, the overall yield is small. At intermediate population densities, also represented by half the carrying capacity, individuals are able to breed to their maximum rate. At this point, called the maximum sustainable yield, there is a surplus of individuals that can be harvested because growth of the population is at its maximum point due to the large number of reproducing individuals. Above this point, density dependent factors increasingly limit breeding until the population reaches carrying capacity. At this point, there are no surplus individuals to be harvested and yield drops to zero. The maximum sustainable yield is usually higher than the optimum sustainable yield and maximum economic yield.

MSY is extensively used for fisheries management. Unlike the logistic (Schaefer) model,^[1] MSY has been refined in most modern fisheries models and occurs at around 30% ^[2] of the unexploited population size. This fraction differs among populations depending on the life history of the species and the age-specific selectivity of the fishing method.

However, the approach has been widely criticized as ignoring several key factors involved in fisheries management and has led to the devastating collapse of many fisheries. As a simple calculation, it ignores the size and age of the animal being taken, its reproductive status, and it focuses solely on the species in question, ignoring the damage to the ecosystem caused by the designated level of exploitation and the issue of bycatch. Among conservation biologists it is widely regarded as dangerous and misused.^[3][4]

History

The concept of MSY as a fisheries management strategy developed in Belmar, New Jersey, in the early 1930s.^[5][6][7] It increased in popularity in the 1950s with the advent of surplus-production models with explicitly estimate MSY.^[1] As an apparently simple and logical management goal, combined with the lack of other simple management goals of the time, MSY was adopted as the primary management goal by several international organizations (e.g., IWC, IATTC,^[8] ICCAT, ICNAF), and individual countries.^[9]

Between 1949 and 1955, the U.S. maneuvered to have MSY declared the goal of international fisheries management (Johnson 2007). The international MSY treaty that was eventually adopted in 1955 gave foreign fleets the right to fish off any coast. Nations that wanted to exclude foreign boats had to first prove that its fish were overfished.^[10]

As experience was gained with the model, it became apparent to some researchers that it lacked the capability to deal with the real world operational complexities and the influence of trophic and other interactions. In 1977, Peter Larkin wrote its epitaph, challenging the goal of maximum sustained yield on several grounds: It put populations at too much risk; it did not account for spatial variability in productivity; it did not account for species other than the focus of the fishery; it considered only the benefits, not the costs, of fishing; and it was sensitive to political pressure.^[11] In fact, none of these criticisms was aimed at sustainability as a goal. The first one noted that seeking the absolute MSY with uncertain parameters was risky. The rest point out that the goal of MSY was not holistic; it left out too many relevant features.^[10]

Some managers began to use more conservative quota recommendations, but the influence of the MSY model for fisheries management still prevailed. Even while the scientific community was beginning to question the appropriateness and effectiveness of MSY as a management goal,^[11][12] it was incorporated into the 1982 United Nations Convention for the Law of the Sea, thus ensuring its integration into national and international fisheries acts and laws.^[9] According to Walters and Maguire, an ‘‘institutional juggernaut had been set in motion’’, climaxing in the early 1990s with the collapse of northern cod.^[13]

Modelling MSY

Population growth

The key assumption behind all sustainable harvesting models such as MSY is that populations of organisms grow and replace themselves – that is, they are renewable resources. Additionally it is assumed that because the growth rates, survival rates, and reproductive rates increase when harvesting reduces population density,^[5] they produce a surplus of biomass that can be harvested. Otherwise, sustainable harvest would not be possible.
Another assumption of renewable resource harvesting is that populations of organisms do not continue to grow indefinitely; they reach an equilibrium population size, which occurs when the number of individuals matches the resources available to the population (i.e., assume classic logistic growth). At this equilibrium population size, called the carrying capacity, the population remains at a stable size.^[14]

Figure 1

The logistic model (or logistic function) is a function that is used to describe bounded population growth under the previous two assumptions. The logistic function is bounded at both extremes: when there are not individuals to reproduce, and when there is an equilibrium number of individuals (i.e., at carrying capacity). Under the logistic model, population growth rate between these two limits is most often assumed to be sigmoidal (Figure 1). There is scientific evidence that some populations do grow in a logistic fashion towards a stable equilibrium – a commonly cited example is the logistic growth of yeast.

The equation describing logistic growth is:^[14]

${\displaystyle N_{t}={\frac {K}{1+{\frac {K-N_{0}}{N_{0}}}e^{-rt}}}}$ (equation 1.1)

The parameter values are:

${\displaystyle N_{t}}$=The population size at time t

${\displaystyle K}$=The carrying capacity of the population

${\displaystyle N_{0}}$= The population size at time zero

${\displaystyle r}$= the intrinsic rate of population increase (the rate at which the population grows when it is very small)

From the logistic function, the population size at any point can be calculated as long as ${\displaystyle r}$, ${\displaystyle K}$, and ${\displaystyle N_{0}}$ are known.

Figure 2

Differentiating equation 1.1 give an expression for how the rate of population increases as t increases. At first, the population growth rate is fast, but it begins to slow as times goes on until it levels off to the maximum growth rate, after which it begins to decrease (figure 2).

The equation for figure 2 is the differential of equation 1.1 (Verhulst's 1838 growth model):^[14]

${\displaystyle {\frac {dN}{dt}}=rN\left(1-{\frac {N}{K}}\right)}$ (equation 1.2)

${\displaystyle {\frac {dN}{dt}}}$ can be understood as the change in population (N) with respect to a change in time (t). Equation 1.2 is the usual way in which logistic growth is represented mathematically and has several important features. First, at very low population sizes, the value of ${\displaystyle {\frac {N}{K}}}$ is small, so the population growth rate is approximately equal to ${\displaystyle rN}$, meaning the population is growing exponentially at a rate r (the intrinsic rate of population increase). Despite this, the population growth rate is very low (low values on the y-axis of figure 2) because, even though each individual is reproducing at a high rate, there are few reproducing individuals present. Conversely, when the population is large the value of ${\displaystyle {\frac {N}{K}}}$ approaches 1 effectively reducing the terms inside the brackets of equation 1.2 to zero. The effect is that the population growth rate is again very low, because either each individual is hardly reproducing or mortality rates are high.^[14] As a result of these two extremes, the population growth rate is maximum at an intermediate population or half the carrying capacity (${\displaystyle N={\frac {K}{2}}}$).

MSY model

Figure 3

The simplest way to model harvesting is to modify the logistic equation so that a certain number of individuals is continuously removed:^[14]

${\displaystyle {\frac {dN}{dt}}=rN\left(1-{\frac {N}{K}}\right)-H}$ (equation 1.3)

Where H represents the number of individuals being removed from the population – that is, the harvesting rate. When H is constant, the population will be at equilibrium when the number of individuals being removed is equal to the population growth rate (figure 3). The equilibrium population size under a particular harvesting regime can be found when the population is not growing – that is, when ${\displaystyle {\frac {dN}{dt}}=0}$. This occurs when the population growth rate is the same as the harvest rate:

${\displaystyle rN\left(1-{\frac {N}{K}}\right)=H}$

Figure 3 shows how growth rate varies with population density. For low densities (far from carrying capacity), there is little addition (or "recruitment") to the population, simply because there are few organisms to give birth. At high densities, though, there is intense competition for resources, and growth rate is again low because the death rate is high. In between these two extremes, the population growth rate rises to a maximum value (${\displaystyle N_{MSY}}$). This maximum point represents the maximum number of individuals that can be added to a population by natural processes. If more individuals than this are removed from the population, the population is at risk for decline to extinction.^[15] The maximum number that can be harvested in a sustainable manner, called the maximum sustainable yield, is given by this maximum point.

Figure 3 also shows several possible values for the harvesting rate, H. At ${\displaystyle H_{1}}$, there are two possible population equilibrium points: a low population size (${\displaystyle N_{a}}$) and a high one (${\displaystyle N_{b}}$). At ${\displaystyle H_{2}}$, a slightly higher harvest rate, however there is only one equilibrium point (at ${\displaystyle N_{MSY}}$), which is the population size that produces the maximum growth rate. With logistic growth, this point, called the maximum sustainable yield, is where the population size is half the carrying capacity (or ${\displaystyle N={\frac {K}{2}}}$). The maximum sustainable yield is the largest yield that can be taken from a population at equilibrium. In figure 3, if ${\displaystyle H}$ is higher than ${\displaystyle H_{2}}$, the harvesting would exceed the population's capacity to replace itself at any population size (${\displaystyle H_{3}}$ in figure 3). Because harvesting rate is higher than the population growth rate at all values of ${\displaystyle N}$, this rate of harvesting is not sustainable.

An important feature of the MSY model is how harvested populations respond to environmental fluctuations or illegal offtake. Consider a population at ${\displaystyle N_{b}}$ harvested at a constant harvest level ${\displaystyle H_{1}}$. If the population falls (due to a bad winter or illegal harvest) this will ease density-dependent population regulation and increase yield, moving the population back to ${\displaystyle N_{b}}$, a stable equilibrium. In this case, a negative feedback loop creates stability. The lower equilibrium point for the constant harvest level ${\displaystyle H_{1}}$ is not stable however; a population crash or illegal harvesting will decrease population yield farther below the current harvest level, creating a positive feedback loop leading to extinction. Harvesting at ${\displaystyle N_{MSY}}$ is also potentially unstable. A small decrease in the population can lead to a positive feedback loop and extinction if the harvesting regime (${\displaystyle H_{2}}$) is not reduced. Thus, some consider harvesting at MSY to be unsafe on ecological and economic grounds. The MSY model itself can be modified to harvest a certain percentage of the population or with constant effort constraints rather than an actual number, thereby avoiding some of its instabilities.^[15]

The MSY equilibrium point is semi-stable – a small increase in population size is compensated for, a small decrease to extinction if H is not decreased. Harvesting at MSY is therefore dangerous because it is on a knife-edge – any small population decline leads to a positive feedback, with the population declining rapidly to extinction if the number of harvested stays the same.

The formula for maximum sustained harvest (${\displaystyle H}$) is one-fourth the maximum population or carrying capacity (${\displaystyle K}$) times the intrinsic rate of growth (${\displaystyle r}$).^[17]

${\displaystyle H={\frac {Kr}{4}}}$

For demographically structured populations

The principle of MSY often holds for age-structured populations as well.^[18] The calculations can be more complicated, and the results often depend on whether density dependence occurs in the larval stage (often modeled as density dependent reproduction) and/or other life stages.^[19] It has been shown that if density dependence only acts on larva, then there is an optimal life stage (size or age class) to harvest, with no harvest of all other life stages.^[18] Hence the optimal strategy is to harvest this most valuable life-stage at MSY.^[20] However, in age and stage-structured models, a constant MSY does not always exist. In such cases, cyclic harvest is optimal where the yield and resource fluctuate in size, through time.^[21] In addition, environmental stochasticity interacts with demographically structured populations in fundamentally different ways than for unstructured populations when determining optimal harvest. In fact, the optimal biomass to be left in the ocean, when fished at MSY, can be either higher or lower than in analogous deterministic models, depending on the details of the density dependent recruitment function, if stage-structure is also included in the model.^[22]

Implications of MSY model

Starting to harvest a previously unharvested population will always lead to a decrease in the population size. That is, it is impossible for a harvested population to remain at its original carrying capacity. Instead, the population will either stabilize at a new lower equilibrium size or, if the harvesting rate is too high, decline to zero.

The reason why populations can be sustainably harvested is that they exhibit a density-dependent response.^[15][16] This means that at any population size below K, the population is producing a surplus yield that is available for harvesting without reducing population size. Density dependence is the regulator process that allows the population to return to equilibrium after a perturbation. The logistic equation assumes that density dependence takes the form of negative feedback.^[16]

If a constant number of individuals is harvested from a population at a level greater than the MSY, the population will decline to extinction. Harvesting below the MSY level leads to a stable equilibrium population if the starting population is above the unstable equilibrium population size.

Uses of MSY

MSY has been especially influential in the management of renewable biological resources such as commercially important fish and wildlife. In fisheries terms, maximum sustainable yield (MSY) is the largest average catch that can be captured from a stock under existing environmental conditions.^[23] MSY aims at a balance between too much and too little harvest to keep the population at some intermediate abundance with a maximum replacement rate.

Relating to MSY, the maximum economic yield (MEY) is the level of catch that provides the maximum net economic benefits or profits to society.^[24][25] Like optimum sustainable yield, MEY is usually less than MSY.

Limitations of MSY approach

Although it is widely practiced by state and federal government agencies regulating wildlife, forests, and fishing, MSY has come under heavy criticism by ecologists and others from both theoretical and practical reasons.^[16] The concept of maximum sustainable yield is not always easy to apply in practice. Estimation problems arise due to poor assumptions in some models and lack of reliability of the data.^[9][26] Biologists, for example, do not always have enough data to make a clear determination of the population's size and growth rate. Calculating the point at which a population begins to slow from competition is also very difficult. The concept of MSY also tends to treat all individuals in the population as identical, thereby ignoring all aspects of population structure such as size or age classes and their differential rates of growth, survival, and reproduction.^[26]

As a management goal, the static interpretation of MSY (i.e., MSY as a fixed catch that can be taken year after year) is generally not appropriate because it ignores the fact that fish populations undergo natural fluctuations (i.e., MSY treats the environment as unvarying) in abundance and will usually ultimately become severely depleted under a constant-catch strategy.^[26] Thus, most fisheries scientists now interpret MSY in a more dynamic sense as the maximum average yield (MAY) obtained by applying a specific harvesting strategy to a fluctuating resource.^[9] Or as an optimal "escapement strategy", where escapement means the amount of fish that must remain in the ocean [rather than the amount of fish that can be harvested]. An escapement strategy is often the optimal strategy for maximizing expected yield of a harvested, stochastically fluctuating population.^[27]

However, the limitations of MSY, does not mean it performs worse than humans using their best intuitive judgment. Experiments using students in natural resource management classes suggest that people using their past experience, intuition, and best judgement to manage a fishery generate far less long term yield compared to a computer using an MSY calculation, even when that calculation comes from incorrect population dynamic models.^[28]

For a more contemporary description of MSY and its calculation see ^[29]

Orange roughy

An example of errors in estimating the population dynamics of a species occurred within the New Zealand Orange roughy fishery. Early quotas were based on an assumption that the orange roughy had a fairly short lifespan and bred relatively quickly. However, it was later discovered that the orange roughy lived a long time and had bred slowly (~30 years). By this stage stocks had been largely depleted.

Overfishing

All around the world, from the arctic to the tropics, there is a crisis in the world's fisheries.^[30] Until fairly recently it was assumed that our marine resources were limitless.
In recent years however, an accelerating decline has been observed in the productivity of many important fisheries.^[31] Fisheries which have been devastated in recent times include (but are not limited to) the great whale fisheries, the Grand Bank fisheries of the western Atlantic, and the Peruvian anchovy fishery.^[32] Recent assessments by the United Nations Food and Agriculture Organization (FAO) of the state of the world's fisheries indicate a levelling off of landings in the 1990s, at about 100 million tons.^[33]

In addition, the composition of global catches has changed.^[34] As fishers deplete larger, long-lived predatory fish species such as cod, tuna, shark, and snapper, they move down to the next level – to species that tend to be smaller, shorter-lived, and less valuable.^[35]

Overfishing is a classic example of the tragedy of the commons.^[32]

Optimum sustainable yield

In population ecology and economics, optimum sustainable yield is the level of effort (LOE) that maximizes the difference between total revenue and total cost. Or, where marginal revenue equals marginal cost. This level of effort maximizes the economic profit, or rent, of the resource being utilized. It usually corresponds to an effort level lower than that of maximum sustainable yield. In environmental science, optimum sustainable yield is the largest economical yield of a renewable resource achievable over a long time period without decreasing the ability of the population or its environment to support the continuation of this level of yield.