The Modern Environment is made up of Human and Natural Systems

People have interacted with the biophysical environment since the beginning of human history (Lui et. al., 2007). Preindustrial era changes in the environment on a large scale have been attributed to human influences from as early as the end of the Pleistocene, with the first human migration into the western hemisphere which resulted in major changes in land cover and mass die off of megafauna (Sauer, 1944). A more contemporary preindustrial example is the population crashes associated with Columbian encounters in the late 15^th/ early 16^th centuries (Dull et. al., 2010). Since the industrial revolution, the scope and intensity of human interactions with the natural system have increased dramatically (Lui et al., 2007).  Today human activities have altered most of the world’s ecosystems to a greater or lesser extent (Vitousek et al., 1997; Sanderson et al., 2002).  Either through direct (e.g. removal of natural soil, dam construction, harvesting, pollution, deforestation) or indirect human intervention (e.g. erosion due to lack of vegetation, overgrazing, climate change), humankind has significantly increased their role in the ecosystem (Hobbs et al., 2006). This raises the question of whether there truly exists a natural environment anymore, or is the modern environment made up of both human and natural systems.

Thinking about the environment as a couple human and natural systems (CHANS) is a better framework for analysis of conservation and people’s role in persevering and maintaining the environment. CHANS are systems in which human and natural components interact (Lui et al., 2007).  Research in this framework focuses on linking human and natural systems, not just acknowledging the relationship.  Evaluations of the interconnectedness of the human and natural systems can be seen in works on the effectiveness of protected areas (PAs) in safeguarding ecosystems.  PAs is one of Earth’s most significant land-use designations with nearly every nation of the world participating, and over 100,000 areas of lands being set aside for conservation (Lockwood et al., 2006).  The major question is how effective is this tool at the goal of protecting the environment?  In some cases PAs failed to meet the goal of preserving high quality habitat, like in the case of forest degradation in Myanmar within PAs (see Htun et al., 2006), where establishments of PAs was not enough in preventing degradation of forests, although it did reduce deforestation (Htun et al., 2006).  This outcome was attributed to the continued use of forest by local populations for firewood.  Setting aside the PA did not remove the human need for the land or its resources, thus this policy ignored the human system.  Without fixing the underlying cause for environmental degradation, simply putting the land as protected did not stop its continued ruin.

Human impacts on the environment can come in indirect forms that are unexpected like those associated with climate change due to land cover changes.  The Amazon is an excellent example of how the natural system has complicated interactions between climate and land cover, where reinforcing feedbacks from the forests promotes climatic patterns that sustain the forest.  Walker et al. (2009) evaluated Amazonian PAs to evaluate the influences of land cover of the surrounding areas on regional climate models.  These models showed that PAs are not walled off ecosystems, they are impacted by their surroundings, thus if protecting the PAs is the goal, it is necessary to develop within limits the surrounding.   They found that natural systems are resistant to human interaction up to a tipping point, where rapid changes in the environment take place (Walker et al. 2009). Understanding this coupled system can lead to better management schemes to avoid these points of no return.

The Environment is not just the natural system, but people are part of it too.  Human systems will have interactions and impacts with natural systems creating what we understand as the Environment. When trying to preserve the Environment, it is necessary not only to think about the ecosystem, but also the human systems involved.  The primary goal for environmental protection is to preserve the natural environment, but the problem is that there is no such thing anymore.  The environment is both natural and human, and to preserve it you must look at both aspects.

Works Cited

Dull, R. A., Nevle, R. J., Woods, W. I., Bird, D. K., Avnery, S., & Denevan, W. M. (2010). The Columbian encounter and the Little Ice Age: Abrupt land use change, fire, and greenhouse forcing. Annals of the Association of American Geographers, 100(4), 755-771.

Hobbs, R. J., Arico, S., Aronson, J., Baron, J. S., Bridgewater, P., Cramer, V. A., ... & Zobel, M. (2006). Novel ecosystems: theoretical and management aspects of the new ecological world order. Global ecology and biogeography,15(1), 1-7.

Htun, N. Z., Mizoue, N., Kajisa, T., & Yoshida, S. (2009). Deforestation and forest degradation as measures of Popa Mountain Park (Myanmar) effectiveness. Environmental Conservation, 36(3), 218.

Liu, J., Dietz, T., Carpenter, S. R., Folke, C., Alberti, M., Redman, C. L., ... & Provencher, W. (2007). Coupled human and natural systems. AMBIO: A Journal of the Human Environment, 36(8), 639-649.

Lockwood, M., Worboys, G. L., & Kothari, A. (Eds.). (2006). Managing protected areas: a global guide. Earthscan.

Sanderson, E. W., Jaiteh, M., Levy, M. A., Redford, K. H., Wannebo, A. V., & Woolmer, G. (2002). The Human Footprint and the Last of the Wild: The human footprint is a global map of human influence on the land surface, which suggests that human beings are stewards of nature, whether we like it or not. BioScience, 52(10), 891-904.

Sauer, C. O. (1944). A geographic sketch of early man in America. Geographical Review, 34(4), 529-573.

Vitousek, P. M., Mooney, H. A., Lubchenco, J., & Melillo, J. M. (1997). Human domination of Earth's ecosystems. Science, 277(5325), 494-499.

Walker, R., Moore, N. J., Arima, E., Perz, S., Simmons, C., Caldas, M., ... & Bohrer, C. (2009). Protecting the Amazon with protected areas. Proceedings of the National Academy of Sciences, 106(26), 10582-10586.

Land Change and the Human Element, challenges in the creation of Land Change Models (LCMs)

Humans are like no other force in reshaping the Earth’s surface.  People have impacted climatic and eco-systems through changes in the use of land.  Many of the environmental impacts are unattended, but it is possible to describe the Earth’s surface (land-cover) and project the future land change by using land-change models (LCMs) (NRC, 2013).  Developments of LCMs are critical to evaluating policy and mitigating the impacts of human development. The challenge in developing LCMs is the human element.  LCMs have to model human behavior and then translate individual decisions into collective impacts on the environment.  Uncertainties in environmental models coupled with the challenges in modeling human behavior make LCMs a particular challenge. Land-use change is a complex process that involves many competing actors and factors, from different social and spatial levels (Valbuena et al., 2010).

What LCMs do is generalize the complex interactions of humans with the environment into particular sets of rules, i.e. if one action occurs then a resulting action will take place.  When a system is created into general rules, then it can be parameterized and simulated to either describe current or past land change, or project future land change. For example in a study of the response of landcover changes to road paving in the Amazon,  Soares-Filho et al. (2004) were able to utilize LCMs to integrate our knowledge of Amazon land-use dynamics, and consequently test a large number of hypotheses concerning its landscape evolution.  They were able to explore the causes of deforestation and evaluate factors, and were able to determine that Brazilian Amazonia land cover can be partially explained in relationship to social and economic opportunities in other regions of Brazil (Soares-Filho et al., 2004).  This was accomplished through scenario-generating models coupled to a landscape dynamics simulator. The outputs were transition probability maps that they analyzed to come to their conclusions, which gives insight for development policy. They found that governance or the enforcement of environmental regulations did mitigate some land cover change.

Many frameworks exist in models including, Equation-Based, System, Expert, Evolutionary, and Cell based models (Parker et. al, 2003), but there is a lot of promise in Agent-based models (ABMs).  ABMs analyze and simulate land-use/cover change as the result of individual decisions (Valbuena et al., 2010). It adds a focus on the human element of land change, simulating the behaviors directly. Challenge in ABM is including the diversity of decision-making actors (Valbuena et al., 2010).  Questionnaires are the typical tool of use in ABMs, where surveys are used to create the rules needed to guide the model.  So in general ABMs have been limited to local problems, but regional simulations are beginning to be experimented with.  One approach is through agent topology, or generalizing a larger population to a few typical agents to simulate.  Once rules are developed and choice models created, then random probabilities can be used to simulate what possible outcomes can take place. 

ABMs are powerful at simulating reality, and LCMs in general give a lot of insight into how the world works.  It must be always taken into account when working with LCMs, that one is working with a simulation.  It is a model, and explaining the model does not always make sense when translating finding to reality.  Simulations have to rely on simplification of reality.  General rules replace complex interaction.  Rational thought is assumed over emotional decision-making.  So it is imperative to always bring your model back to reality when creating them, constantly reference real life, and ground truthing results.

Works Cited

National Research Council. Advancing Land Change Modeling: Opportunities and Research Requirements. Washington, DC: The National Academies Press, 2013.

Parker, D. C., Manson, S. M., Janssen, M. A., Hoffmann, M. J., & Deadman, P. (2003). Multi-agent systems for the simulation of land-use and land-cover change: a review. Annals of the Association of American Geographers, 93(2), 314-337.

Soares‐Filho, B., Alencar, A., Nepstad, D., Cerqueira, G., Diaz, V., del Carmen, M., ... & Voll, E. (2004). Simulating the response of land‐cover changes to road paving and governance along a major Amazon highway: the Santarém–Cuiabá corridor. Global Change Biology, 10(5), 745-764.

Valbuena, D., Verburg, P. H., Bregt, A. K., & Ligtenberg, A. (2010). An agent-based approach to model land-use change at a regional scale. Landscape Ecology, 25(2), 185-199.

Understanding the human dimensions of land change

Land change science (LCS) as a field is involved with modeling, predicting, and understanding the dynamics of land cover and land use as a coupled human–environment system (Turner et al., 2007). Models in LCS give a quantified lens into changes in land cover, revealing trends and driving forces of change. LCS employs GIS and Remote Sensing approaches to understanding land change, but this often limits understanding due to the small scale. A multiscalar approach is necessary in order have a fuller picture into the reasons of land change. This is an aspect of political ecology that when applied to LCS can be very powerful.

Political ecologist, like LCS, also study human-environment systems, but they take into account multiple scales, actors, and views into a problem. Through this approach complexities in human system are highlighted with how they impact the environment. In order to do this work a researcher often has to embed themselves into the communities executing changes in the environment. It is important to ground an understanding of the processes changing the environment to the role of specific actors, thereby rendering these processes more telling and substantial in political terms (Blaikie, 1995).

Political ecologist often look at power, either through the state but also even between groups or individuals. For example, rights, management, and access to environmental resources are often different between genders, and power relations within the household, which influences the control of land, natural resources, labor and capital (Carney, 1993). Furthermore, communities behaviors are not static and do change with changing situations. Oldekop et. al (2012) study on scarcity perceptions of indigenous Amazonian Kichwa communities is evidence that communities adapt management practices to environmental changes. So having one model for actors decision-making process is limiting in understanding how people adapt to the situation they find themselves in.

Political ecologist have shown that the human element in the human-environment system is complex, dynamic, and multiscalar. To improve LCS studies, researchers need to recognize this. Walker et al. (2003) is an example of a LCS study that does addresses theses shortcoming in LCS by utilizing behavioral theory to bridge the divide between the large and small scales. By modeling the spatial decision making of how loggers build road networks in the Amazon, Walker et. al. (2003) were able to explain how loggers shape their road networks, thus influencing land change in the Amazon. Their approach involved survey methods and key informant interviews, bringing researchers to the field. This gained direct insight into how loggers make spatial decisions, and in particular how they collaborate among each other to territorialize their operations so as to avoid conflicts (Walker et. al., 2013). This study was greatly improved by being able to connect on the ground decisions with regional land cover change.

Theoretical development is the cornerstone of academic endeavors in LCS. Being an interdisciplinary field, LCS can integrate not only traditional disciplines, but also borrow theories, methods, and approaches from other interdisciplinary fields like political ecology. Theories should be developed and shared between LCS and other environmental change and sustainability fields.

Works Cited

Blaikie, P. 1995. Changing environments or changing views? A political ecology for developing countries. Geography, 203-214.

Carney, J. 1993. Converting the wetlands, engendering the environment: the intersection of gender with agrarian change in The Gambia. Economic Geography, 69(4), 329-348.

Oldekop, J. A., Bebbington, A. J., Truelove, N. K., Holmes, G., Villamarín, S., & Preziosi, R. F. 2012. Environmental impacts and scarcity perception influence local institutions in indigenous Amazonian Kichwa communities. Human Ecology, 40(1), 101-115.

Turner, B. L., Lambin, E. F., & Reenberg, A. 2007. The emergence of land change science for global environmental change and sustainability. Proceedings of the National Academy of Sciences, 104(52), 20666-20671.

Walker, R., Arima, E., Messina, J., Soares-Filho, B., Perz, S., Vergara, D., ... & Castro, W. 2013. Modeling spatial decisions with graph theory: logging roads and forest fragmentation in the Brazilian Amazon. Ecological Applications, 23(1), 239-254.

Remote sensing the power to ask big questions

Remote sensing is a powerful set of technologies that has enabled Land Change Science (LCS) to develop as a field. It is a major tool for LCS and its use in distinguishes LCS from other environmental change disciplines. It empowers researcher to ask big questions, questions that are not possible to answer without a complete global view of the world or an extensive availability of data. Questions like ‘What types of lands are being converted for agricultural use?’ (Gibbs et al, 2009; Koh et al. 2010), or ‘How many times a year do smallholders crop their fields?’ (Jain et. al.,2013), or even ‘What was the global land cover like through history?’ (Ramankutty and Foley, 1999).

Remote sensing can provides global datasets, which LCS researchers can exploit to discover the mechanisms driving land change. Gibbs et al. (2009) is an example of a question that would not be able to be answered without remote sensing. Through the utilizing of randomly sampled Landsat imagery, which was classified and measured for land change from forested to agricultural lands, they were able to determine that the global demand for agricultural products is being supplied through converting of tropical forest land to farms and pastures. They found that between 1980 and 2000 more than 55% of new agricultural land came at the expense of intact forests, and another 28% came from disturbed forests. This question on such a large scale could not have been answered without the use of remote sensing.

The Gibbs et al. (2009) study would not had been possible to do without satellite imagery spanning 3 decades, and this show the importance of not only global but continuous collection of remotely sensed data. Many environmental models are limited by the availability of land use data. Remote sensing satellites missions like Landsat Thematic Mapper (TM) have only around since 1982 (Markham et al. 2004), limiting the scope of data available. For this reason backcasting land use is important, like in the work of Ramankutty & Foley (1999). In this study the authors estimated landuse over three centuries by backcasting 1992 land cover data, reconstructing historical croplands based off of databases and land cover models. This dataset can only be seen as an estimate, and some of the land covers can be debated, but it provides a reasonable predication of what the world has looked like in term of human use over the last three centuries.

Although remote sensing can answer the big questions, it can also have applications on the smaller scale like in Jain et al. (2013) study on cropping intensity of smallholder farms. This paper showed the possibilities of overcoming limits in spatial and spectral resolution through the integration of multiple sensors. Answering a question from space about smallholders crop intensity, or how many crops they plant per year, seems like a impossible feat, but the development of such tools are important in assessing food security, especially since about half rural populations accesses food through small holding means. The Jain et al. (2003) pushed remote sensing to the limits finding creative ways to overcome challenges by integrating multiple data sources over different methods. Some issues like climatic patterns, or cloud cover due to monsoonal season where impossible to overcome. It shows that LCS is never going to happen in a controlled environment, since the data collected is from the world, there will always be challenges with it’s application.

Remote sensing is an amazing technique that has made and will continue to make a difference in LCS research. It is plagued with challenges in data collection, intermittent availability, and difference is spectral and spatial resolutions, but its potential at opening our eyes to how the world works is immense. Remote sensing technology is still relatively cutting edge and young compared to many techniques, but as it continues to develop, our understanding of the world will develop as well.

Works Cited

Gibbs, H. K., Ruesch, A. S., Achard, F., Clayton, M. K., Holmgren, P., Ramankutty, N., & Foley, J. A. (2010). Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. Proceedings of the National Academy of Sciences, 107(38), 16732-16737.

Jain, M., Mondal, P., DeFries, R. S., Small, C., & Galford, G. L. (2013). Mapping cropping intensity of smallholder farms: A comparison of methods using multiple sensors. Remote Sensing of Environment, 134, 210-223.

Koh, L. P., Miettinen, J., Liew, S. C., & Ghazoul, J. (2011). Remotely sensed evidence of tropical peatland conversion to oil palm. Proceedings of the National Academy of Sciences, 108(12), 5127-5132.

Markham, B. L., Storey, J. C., Williams, D. L., & Irons, J. R. (2004). Landsat sensor performance: history and current status. Geoscience and Remote Sensing, IEEE Transactions on, 42(12), 2691-2694.

Ramankutty, N., & Foley, J. A. (1999). Estimating historical changes in global land cover: Croplands from 1700 to 1992. Global biogeochemical cycles, 13(4), 997-1027.

The smallholder’s dream of a livelihood

Smallholders are rural cultivators of small plots within densely populated areas practicing permanent, diversified agriculture (Netting, 1993) and they typically practice subsistence farming, but some portion of their yields is often sold within the local economy.  It is a livelihood that is highlighted in a positive light in academia for its resilience, sustainability, and it ability to provide for so much of the world population.  However from the point of view of the smallholder, or even more the children of a smallholder, is this the livelihood that they want? Is this model truly sustainable in the sense of human development?

The typical smallholder enterprise is made of the family unit, with parents, children, and in some cases others with kinship relationships.  Unlike the western family unit, built strengthen by blood relationships or shared experiences; the smallholder family unit is strengthen by work (Netting, 1993).  The family works together to survive making most everything they need, which forms indebtedness to each other. This intergenerational connection is where the model derives it strengthens of sustainability.

Smallholder model of livelihood is often associated with underdeveloped nations, but in many ways the sustainability aspects of the model follows what developed nations have been working for as outlined in the Brundtland Report, or  “meting the needs of the present without compromising the ability of future generations to meet their own” (Brundtland et al., 1987, p. 43).  The aspect of intergenerational indebtedness of parents and children instills a sense of protecting of the environments ability to provide livelihoods. The people in this model have a connection to the environment that does not exist in the western world.

While smallholder model is associated with rural livelihoods in undeveloped regions, it has a role in urbanizations and it has been transposed into urban areas migrating with people into cities. For example, within the cities of the Brazilian Amazon, urban gardening is providing an informal system of production, exchange, and knowledge important for survival (WinklerPrins and Souza, 2005). Despites 70% of Brazilian populations living in urban places (IBGE, 2002), urban economies have not developed at a rate to keep up with urbanizations leading to ‘over-urbanized’ regions (Browder and Godfrey, 1997; WinklerPrins and Souza, 2005).  Smallholders tactics are helping in survival of this transition population providing livelihoods when the formal economy has failed.

There is a lot to learn from smallholder model of livelihoods, but it is not the ideal model.  The model can be romanticized in academia much like Voltaire’s Candide, where it is “best to cultivate our garden”, where the beaten optimist at the end disengages with the world and is self-reliant.  Smallholder model is seen in positive light by academics living a far in the western world trying to find solutions for the world ills like Candide did, but when not finding they resort to the same conclusion to disengage and farm.  The evidence of mass migration of young people into the cities throughout the world shows that the dream of a better life is not in the smallholder model, and the disruption of indebtedness of the intergenerational ties by globalization forces creates a need for a new model for continued survival of billions of people.

Works Cited

Browder, J. O. and B. J. Godfrey. 1997. Rainforest Cities: Urbanization, Development, and

Globalization of the Brazilian Amazon. New York: Columbia University Press.

Brundtland, G. H. (1987). Report of the World Commission on environment and development:" our common future.". United Nations.

IBGE (Instituto Brasileiro de Geografia e Estatistica). 2002. Tabulação Avançada do Censo Demografico 2000 – Resultados Preliminares da Amostra. Rio de Janeiro: IBGE.

Netting, R. M. (1993). Smallholders, householders: farm families and the ecology of intensive, sustainable agriculture. Stanford University Press.

WinklerPrins, A. M., & de Souza, P. S. (2005). Surviving the city: urban home gardens and the economy of affection in the Brazilian Amazon. Journal of Latin American Geography, 4(1), 107-126.

Ruling hypothesis in studying human-environment interactions

The study of the human-environment interaction is an interdisciplinary topic approached by Geographers, Historians, Environmental Scientists, Anthropologists, Sociologists and many other scholars.  It is humanity's original research topic and it is simply asking the question of ‘Why our world is the way it is, and what role do people play in it?”  It is a fundamental question, which we have asked for all recorded history, yet we still do not fully understand the relationship between humans and the environment.  Why is this topic is so complex to understand, yet fundamental to who we are as people?  Furthermore in what ways can we approach this research?

To begin thinking of the human-environment relationship we must first ask ourselves is it possible to study these interactions without inherent bias?  Since we are born, grow, and die in our environment, it is nearly impossible to study it without preconceived notions.  Everything that we know about the world and ourselves up to the point we begin to research human-environment interactions bias us to the core.  We have a working understanding of how the world operates, that is how we each as individuals are able to operate in it. These preconceived notions form our ruling hypothesis, or something that we believe is true thus other possible explanations are discounted and not considered. The method of multiple working hypotheses (Chamberlin, 1965) is one way to mediate this problem. By simply developing, prior to research, several hypotheses that might explain the human-environment phenomenon we want to study, it maybe possible to avoid the trap of the ruling hypothesis and thus makes it more likely that our research will lead to meaningful results.  The challenge here is trying to keep an open mind and look at alternatives that are contrary to our understanding.

An example of how inherent bias must be conquered to advance knowledge is Carl Sauer’s 1944 work, A geographic sketch of early man in America, which outlined how both human beings and the environment are environmental change forces (Sauer, 1944).  He examines the arrival of human beings to the North and South American continent at the end of the Pleistocene, the first human migration into the ‘new world’, investigating the environmental changes that took place. During this time period there were unexplained mass die offs of megafauna, which Sauer attributes to human cause.  This was a radical idea that went against the ruling hypothesis of the time of environmental determinism, or the environment dictates how culture and society form. Sauer argues that the primitive people, even with very limited technology, were able to dominate the natural system affecting major land cover change leading to the mass extinction of megafauna. The technology mode that empowered early man was fire, which Sauer outlines they used to modify land cover to make it more conducive for hunting, and used large scale burns to herd megafauna for effective hunting.

The preconceived notions of people not being able to impact environmental change limited the creative process required to come up with a better theory on man’s role of changing the environment. Before this ‘outside of the box’ thinking environmental determinism dictated that human-environmental interactions were one direction, the environment on to people, because how can people impact something so large as the Earth systems.  Sauer opened the door to a bilateral relationship between humans and the environment.

The human-environment interaction is complex to study because it is a study of our surroundings and ourselves.  It is impossible to divorce the researcher from the study making objectivity hard and preconceived notions easy to dominate our thinking.  The way we should approach this research is to develop as many hypothesis as possible and then eliminate the ones that do not work.  This is why being creative and open-minded are two qualities required to be an effective researcher.

Works Cited

T.C. Chamberlin, The Method of Multiple Working Hypotheses, Science 148:754-759 (1965, reprint of 1890 original)

Sauer, C. O. (1944). A geographic sketch of early man in America. Geographical Review, 34(4), 529-573.