LANDSCAPE ECOLOGY: A COMPLEX APPROACH

This is the essay I wrote for the Honours mid-year Theory Seminars, it's quite long and complex but I really enjoyed writing it and maybe it will actually be read here.

Introduction

The biggest questions facing humanity, and especially ecologists, in the 21^st century involve our relationship with our surroundings. Advances in technology and industry, as well as an exponentially expanding population, result in an immense pressure that is placed on the ecosystem. For this reason special attention is required to understand the systems that we rely on and which are most affected by our actions. Landscape ecology is one field which offers a host of tools to study ecosystems with a sociological component. Landscapes exist as a manifestation of ecosystems on a scale that is specifically and explicitly important to humans. The scale at which humans interact with the environment is critically relevant in this field of ecology.

 A key problem facing ecologists is the loss of biodiversity and the potential implications for services on which humans depend. Loss of services includes, among others, decreased water quality and disrupted pollination systems or nutrient cycles. An understanding of the fundamental processes which govern these systems seems imperative to ensure a healthy socio-ecological future. However, the ecosystems which govern these relationships form extremely complex systems in which interactions at macro-scales influence processes, trophic-structures, productivity and nutrient fluxes among components and various scales. The interactions of the components of the system accordingly feed back into the macro-scale resulting in a hyper complex system, the understanding of which is vital in resolving the issues facing mankind today (Levin 1998).

Our current understanding of the systems that govern ecology encompasses various facets from community compositions to molecular ecology and from the study of a single plant to the biogeography of biomes. Major jumps in our understanding of the processes entailed in ecology are rare, and in this sense the emergence of a new field is particularly noteworthy. One field specifically studying the relationships between patterns and processes is the relatively young field of landscape ecology. The development of this field has been aided by increases in landscape use and change over the last century (Risser and Iverson 2013) and the field has undergone an interesting evolution from its founding days as a subject struggling to combine small scale biotic studies with large scale land use changes to one which is multidisciplined and actively incorporates a range of scales. The field has grown from one with little definition into one of the most mathematically intriguing and complex fields in ecology today. The search for multiscale patterns has extracted landscape ecology from a simple descriptive field into one that may blur the lines between mathematics, physics, chemistry and ecology. In addition landscape ecology has approached a fascinating point in which the human imposed definitions are likely to be redefined through the application of complex systems theory. The complex practices entailed in landscape ecology today may be one of our greatest defences in a rapidly changing and unpredictable world.

The emergence of Landscape Ecology

                For decades, if not centuries, the need to understand our surroundings has both captivated and haunted biologists and geographers. Those most afflicted with the desire, dedicated their lives to the understanding of landscapes, and this work was encouraged by the historic need for planning in increasingly human-dominated landscapes. Before biologist and botanist Carl Troll coined the term Landscape Ecology in 1939, the bulk of work on this topic was constrained to geography, botany and ecology in a land-use framework (Risser et al 1984). At this time there was no canonical definition of a landscape and the pioneers of landscape ecology had varying ways in which they approached the topic but it was essentially viewed as landscape geography. The foundation of the subject has firm rooting in Europe; however the field had little focus as evident by the many definitions of the subject and the approaches used. For example Troll defined landscapes as an objective “organic entity” (Troll 1950), while his contemporary Ernst Neef, defined landscapes in terms of the uniformity and specificity of their land-use (Neef 1967). These two definitions are inherently different: Troll’s view, contrary to Neef’s, leads to the understanding that a landscape is not a mental construct which can be redefined in an anthropocentric relativistic way. The view of a landscape as separate from the definitions imposed by human understanding is paramount to the development of landscape ecology.

The simultaneous shift in ecological studies from individual organisms, populations and community structure to ecosystem analysis, from the 1940s to the 1960s, aided the development of the field of landscape ecology (Risser and Iverson 2013). In the 1970s “landscape-level” studies attained a “level” of prominence, especially in Europe where the field was recognized as landscape geography (Risser et al 1984). In addition theoretical and technical advancements in ecology such as island biogeographic theory, patch dynamics and spatial simulation modelling, were steadily growing and raising interest in the spatially heterogeneous and complex processes governing patterns. Despite this interest, by the beginning of the 1980s there was still no generally accepted framework which could incorporate the diverse ideas of multiple landscape patterns and the movement of energy and organisms across spatially heterogeneous landscapes. Developments in the use of mathematical models, especially in population biology (Levin 1968), began to play a role in landscape ecology and allowed for growth in ecosystem science.  Very little attention, however, was paid to spatial heterogeneity, and very few models incorporated a spatial component (Risser and Iverson 2013).

In the early 1970s the United States of America’s National Science Foundation (NSF) ran the International Biome Program (IBP) which conducted studies on managed and unmanaged geographic ecosystem types; it involved measurements within ecosystem types as well as ecosystem-level mathematical models. The studies began to recognize the importance of heterogeneity in the interactions between sub-units. High levels of heterogeneity complicated attempts to select and interpret the roles of driving variables. The results of the IBP led to the NSF’s Long-Term Ecological Research project (running from the late 1970s and continuing today) which aimed to include landscape heterogeneity in its design and in its measurement of biodiversity, productivity and abiotic cycles (Risser and Iverson 2013). In light of these programmes and the undeniable importance of heterogeneity in landscape research, the NSF granted funding to the Illinois Natural History Survey – whose goal had been to develop a large Geographic Information System for Illinois – to hold a workshop which would strive to outline and contextualise the directions and approaches of “landscape ecology” as a developing field. Little did the attendees of the workshop realise that the discussions of those three days in rainy Allerton Park, Illinois, would define a new paradigm in ecology, especially in the United States (Risser and Iverson 2013). The workshop was led by Paul Risser, Richard Forman and James Karr with 25 participating ecologists, including one representative each from Canada and France, and the remainder from the United States (Risser and Iverson 2013). All of the attendees were experts in their field and none realised that they were outlining an essentially new multifaceted field in ecology (Risser 1984,Wu 2013).

There were two essential outcomes of the Allerton Park workshop, as outlined in Risser and Iverson’s 30 year anniversary review (Risser and Iverson 2013). The first served to define landscape ecology and the second solidified the importance of the field in the understanding of ecological processes with respect to heterogeneity. Risser (1984) reported on the workshop and describes the outline of what was to become the North American vision of landscape ecology:

“Landscape ecology is not a distinct discipline or simply a branch of ecology, but rather is the synthetic intersection of many related disciplines…, viewing landscape ecology as a branch of ecology, would…tend to exclude the formal analysis of human cultural processes that form landscapes…. Understanding landscapes requires that we deal with human impacts contributing to the landscape phenomenon, without attempting to draw the traditional distinction between basic and applied ecological science or ignoring the social sciences”

In the last three decades of landscape ecology key questions, the basis of which were raised at the Allerton Park workshop, have been expanded upon and defined. A review of landscape ecology on the 30^th anniversary of the workshop by Wu (2013) outlines some of the defining questions and topics of landscape ecology, as demarcated then and as facing the science today. The report released after the workshop (Risser et al 1984) defined the questions as follows: (1) “How are fluxes of organisms, materials and energy related to landscape heterogeneity?” (2) “What past and present processes result in the patterns seen in landscapes?” (3) “How is the spread of disturbance affected by landscape heterogeneity?” (4) “How can an understanding of landscape ecology improve resource management practices?” These four basic questions are no less valid today than they were 30 years ago, although the science has come a long way in answering parts of them (Wu 2013). Wu (2013) outlines an updated version of these questions. As the science has grown, so have the sciences on which landscape ecology can draw, especially those lending to analytical processing, computing capacity and mathematics of complex systems, allowing an expansion of the questions that landscape ecology can ask, and concurrently answer. In 2001 the US Association of Landscape Ecology held their 16^th symposium at which the “Top 10 List for Landscape Ecology in the 21^st Century” was produced through contributions from 15 leading landscape ecologists. Wu (2013) elaborates on these 10 key research topics, as follows: (1) ecological flows in heterogeneous landscapes, (2) processes, causes and consequences of land-use and land cover change, (3) nonlinear dynamics and landscape complexity, (4) scaling, (5) methodological development, (6) landscape metrics and related processes, (7) integrating anthropogenic effects into landscape ecology, (8) optimization of landscape pattern, (9) landscape sustainability, and (10) data acquisition and accuracy assessment. The four original questions outlined at Allerton Park are still prevalent in ecology today, allowing for some modernization while the introduced questions show the range of interest that has developed in the field.

Of the 10 key topics that outline the direction of landscape ecology, the concept of nonlinear dynamics and complexity has led to a remarkable coalition of the fields of ecology and mathematics. The need to identify patterns, already in themselves complex, at various scales of space, time and organizational complexity, is a cornerstone of landscape ecology. Due to this feature of the science the adoption of the concept of complex adaptive systems has benefited the field of landscape ecology. Before the idea of complex adaptive systems was introduced to landscape ecology by figure heads such as Milne (1998) and Levin (1998), the main approach to understanding the complexity of landscapes was the paradigm of hierarchies (Urban et al 1987). By the late 1980s the idea of a landscape as a mosaic of patches generated by processes operating at various scales was widely accepted (Urban et al 1987). The formation of these patterns had been in consideration for some years, with Levin’s (1978) work on planktonic communities as an ideal study for patterns functioning over patches. Based on this research, patterns were thought to be results of disturbances, biotic processes and environmental constraints with each of these processes acting at different scales, both within and across processes (Levin 1978). This level of complexity in landscape ecology has been approached from two main perspectives in the last 30 years; that of a set of nested levels of processes and interactions (the “hierarchy approach”), and that of studying each level and the translation from one level to the next (the “complex adaptive systems approach”).Both ideas, which are indeed linked, will be discussed in the following section of this essay.

Tackling Complexity

The inherent complexity of landscapes necessitates a multiscale or hierarchical approach in its analysis. Urban et al (1987) applies a definition to landscapes which has become somewhat traditional, specifically that landscapes are seen as a mixture of patches of various size, of various origins, in various stages of regeneration, approaching microenvironmental equilibria at various rates. Hierarchy theory views the complexity of this landscape as patterns organized in a special way, with processes and patches occurring at characteristic scales. In particular these scales are positively correlated in space and time (Figure 1). In general, low-level events occur on a smaller scale with more frequency than do large-scale events. The characterisation of these scales allows for the complexity to be viewed as containing a degree of organization which can be broken down into levels. Hierarchy theory provides guidelines for defining the levels of a system.

Figure 1. The scaling of vegetation patterns across time and space (Urban et al 1987)

The levels of the system are nested and when viewed as individual parts, can contribute to an understanding of the complexities of the landscape. Hierarchy theory thus allows for explanations of landscape ‘behaviour’ as the interaction among the parts, and of patterns that translate across the hierarchical scales. Importantly the levels of a system are related to each other and are functionally defined. This is a mentally constructed way of viewing a landscape, the primary benefit of which is the ability to resolve the complexity of dynamics and spatial patterns at a range of scales into a few variables and a set of constraints each relative to the reference level.

Hierarchy theory did not evolve as a consequence of landscape ecology, rather it is a concept already viewed as classical by Urban et al (1987), which was merely applied as a paradigm for understanding the complexity of landscapes. The formal view of hierarchy theory is commonly thought to have been introduced to landscape ecology by Allen and Starr (1982); however Urban et al (1987) recognise the early work by Watt (1947) and Whittaker (1953) in defining the concept.

Hierarchy theory as formally applied defines a three-tiered nested system in which the levels are relatively isolated and each level operates at distinct scales; however the boundaries of the levels may be difficult to define. Concepts of the theory usually apply to scale-related principles while many of the real world applications involve organizations defined by human-centric concepts such as populations or biomes, which may be inappropriate for the description of underlying processes (Hay 2002). Despite this downfall in hierarchy theory, the idea of levels in a landscape is exceedingly useful and likewise plays a part in complex theory.

The arrival of Remote Sensing as a tool to capture the patterns of landscapes allowed for a new framework to be adopted by landscape ecologist. The plethora of information available, in addition to the increase in computational power, made the processing of characteristics of systems with a large number of components interacting in non-linear fashions and exhibiting adaptive properties possible.  This new framework builds on Complex Systems theory and mathematics from the 1960s and 1970s and has been used in economics, computer science and more recently, ecology (Hay 2002). Landscapes when viewed from a complex systems approach have an updated definition from the one outlined by Urban et al (1987).In this light, landscapes can be seen as “open systems that extract high quality energy from the sun, and respond with the spontaneous emergence of organized behaviour so that their structure and function are maintained” (Kay and Schneider 1995). An important characteristic of complex systems is that they lend themselves to a nested hierarchical structure, and complexity theory views these hierarchies in a slightly different way to that of conventional hierarchy theory. A fundamental characteristic of Complex Systems is the appearance of levels and of self-organization.

Complexity as a science is difficult to define as it entails a vast assembly of contrasting approaches. A few of the many concepts and approaches include cellular automata, interacting particle systems, self-organization, non-linear dynamic systems, fractals, and artificial life (Milne 1998). Complexity in itself can be approached in two distinct ways, one way embraces the complexity as an inevitability and studies it by breaking it down into subsets defined and controlled by a small number of processes. This first view correlates well with the hierarchies paradigm, however if the complexity of the living system emerges from a large number of random associations and interacting factors then the system is appropriately complex to be studied through the framework of complexity theory, the second way in which to view a complex system. Complexity theory draws on ideas, concepts and theories from Catastrophe theory, Chaos theory, Hierarchy theory, Non-Equilibrium Thermodynamics and Self-Organization theory (Hay 2002). According to complexity theory the levels that emerge are a result of the systems self-organization.

By applying a complex systems approach to ecology, the natural levels which emerge in the complex system can be investigated through the analysis of a multitude of variables in multifarious models in which the levels and hierarchies are made obvious by scale thresholds separating scale domains represented by sharp transitions in patterns (Meentemeyer 1989). The advances in complexity theory provide opportunities for landscape ecology as the study of a non-linear system which includes feedbacks leading to a self-organized behaviour over a wide range of spatial and temporal scales (Levin 1992). In addition a complex systems approach enables a synthesis of the understandings developed for each level in a system and translating that theory from one layer to another (Milne 1998). One aspect that may help to cement the application of complexity theory to landscape ecology can be seen in the study of scaling relations. Scale, as mentioned, is one of the key aspects of landscape ecology, the search for invariant scaling relations and the possible processes that generate them makes up a large portion of the work done in the field (Wiens and Milne 1989). Scaling relations can be used to delineate the domain of a hierarchy level (Milne 1998).

The discovery of scaling relationships that exist in this way would indicate that the system is controlled by first principle rules that occur across a range of scales (Meakin 1993). Traditionally biological sciences operate in a framework that emphasizes analysis of variance in a somewhat descriptive sense. Descriptions tend to be based on interest levels which exist in the frame of the viewer, as such processes and patterns tend to be anthropocentrically defined. The search for invariant scaling relations is in contrast with these ideas, complexity theory searches for invariant system properties which may transcend the boundaries of the human conceptual frameworks. The current state of the application of complex theory is working to objectively reveal domains of length and time scales over which processes operate (Wiens and Milne 1989).

Complex Adaptive Systems

The ecosystem is a complex system which presents itself in a different way to other complex systems as it involves adaptability and sustained diversity. These two points define the biosphere as a special type of complex system known as a complex adaptive system (CAS). Descriptions of other CAS’s can be found in Arthur et al (1997) especially as applied to any economy. Examples of CAS’s are found in everything from cells to meta-communities and the idea was applied to ecosystems as recently as 15 years ago. Levin (1998) championed the usefulness of a CAS approach to ecosystems, in particular as a tool to investigate the relationship between the organization of biodiversity and the functioning of systems.

Not all complex, self-organising systems are adaptive and Levin (2003) outlines the point that in order to be considered adaptive some form of selection must take place, and in these situations it is crucial to distinguish at what levels selection is taking place. This task is non-trivial, and may be impossible as selection may be occurring on multiple interacting scales. In general Levin (2003) defines CAS’s according to three properties: (1) Diverse range of individual components, (2) localized interactions among components, and (3) a self-directed process that uses feedback systems and the outcomes of the interactions in order to enhance the state of the system. Complex adaptive systems are thought to contain a level of self-organization which emerges in the form of patterns at higher levels and are a result of localized interactions and selection processes at lower levels (Levin 1998).

The basic properties of a CAS have been proposed in many different ways (Levin 1998), one slightly different way was outlined by Holland (1995) in identifying four properties of any CAS:

Aggregation – Basic elements of a system are inhomogeneously organized, as such patterns of hierarchies are a natural consequence of self-organization and an essential element in the development of a system. It is important that the hierarchies and assemblages are not imposed on the system by any human definition; rather they emerge as a feature of CAS’s.

Non-linearity – Local rules of interactions in a system change as the system develops. This is seen in the systems dependence on the chance events which occur at the system’s inception. The events at the beginning set the system on a path which it is in some way restricted to. This feature manifests as resilience in some systems.

Diversity – The generation and maintenance of diversity is fundamental to adaptive evolution and it is therefore necessary in adaptive systems. Diversity within functional groups allows for buffering and homeostasis for critical ecosystem processes.

Flows – Fluxes of energy, material and information characterise any system and allow for interconnectedness of the components of an adaptive system, without which individuals would be existing in random collections. Flows are responsible for the way in which the self-organization emerges.

The ecosystem displays these properties (Levin 1998) and therefore the application of complex theory to ecosystems is opening up a new way in which to view the systems landscape ecologists have been attempting to understand for centuries.

Applications of Complex Systems Theory

In the case of CAS’s, and complex theory in general, a major deterrent to its entrance into the main stream is the host of non-trivial mathematics that accompany the theories. Although mathematics and complexity are daunting subjects, they are inherently objective and can therefore enlighten our understanding of systems if understood and appropriately applied. The field of complex systems is relatively new and applications and empirical evidence is not something that can easily be found in landscape ecology. However there are a few interesting studies which are applying the concept of complex theory to ecosystems and in this way revealing a host of promising and interesting ways in which landscapes and ecosystems can be understood.

One such example of this is in the prediction of critical transitions in systems (Scheffer et al 2009). Complex systems have been shown to have tipping points in which a sudden shift to a contrasting regime may occur, this is apparent in many systems including medicine and economics but has also been seen in ecosystems (Scheffer et al 2001). By adopting the complex systems approach these points may be predicted (Scheffer et al 2009). So far work on basic models has produced remarkable accuracy in predicting transition points, while application of the method to more complex systems is showing promise. Examples in landscape ecology have been found, such as self-organization in vegetation patterns possibly indicating imminent vegetation loss (Rietkerk et al 2004), and, in systems ruled by local disturbance, scaling laws which govern the structure of patterns have been found to vanish as a critical transition approaches (Kéfi et al 2007).

The technique of renormalization group analysis is one that was developed in physics (Creswick et al 1992) and can be applied to landscape ecology in a complex systems approach. The technique allows for thresholds and domains to be detected as critical phenomena (Milne 1998). The renormalization strategy aims to determine processes at the level of the individual and aggregate the system to coarse scales in order to make predictions of scaling exponents for macroscopic patterns (Creswick et al 1992). An example of the application of this concept to a landscape occupied by trees is provided in detail in Milne (1998). Scaling and renormalization approaches contrast with traditional approaches to ecology which tend to focus on empiricism and analysis of variance, this approach searches for invariant system properties (Milne 1998) and can be thought of as a more “first principles” approach to modelling systems.

The acceptance of landscapes as complex systems has facilitated collaboration between ecology and computer science, especially in the form of remote sensing and spatial analysis. Growth in technology of data collection at large scales and extents with high resolution has provided an excess of multi-spatial, multi-spectral, and multi-temporal resolution data (Hay 2002). This ability to observe landscapes at a large scale, along with complex data analysis tools such as Scale-Space theory (Lindeberg 1994), creates the possibility of a framework which may assist in automatically defining critical landscape thresholds, domains of scale, ecotone boundaries, and the grain and extent at which scale-dependent ecological models could be developed  (Hay 2002, Blaschke and Hay 2001).

A Better Approach

The use of a complex systems approach to landscape ecology works to fundamentally remove any bias that could be applied to ecosystems by the human scale that we perceive the world to function at. By fully embracing the complex systems approach it seems it may be possible to allow landscape ecology to express its own laws and define its own boundaries. Although many of the boundaries and patterns that we observe may be rightly attributed to processes, especially as some may coincide with the scale at which we perceive the environment, however the possibility of revealing unknown processes, scales or levels is too exciting to ignore.

Given the necessity to understand the processes that govern the ecosystem that we depend on a solid framework for viewing the landscapes is imperative. Ernst Neef may have been introducing the bias of human construct to landscapes when he classed them as large scale spatial arenas in which humans interact with the environment, but he was not wrong. Our landscapes, although separate entities which have their own processes and patterns, are the most direct link that humans have to the ecosystem. For this reason, I believe that an understanding of the complexity of the processes that govern the patterns of the ecosystem in which we exist, is of the utmost relevance. There is no doubt that by understanding the mechanisms behind biodiversity, species assemblages, vegetation patterns or energy flows through a system, we can optimize our management of these systems and thus better utilise and conserve them.

The growth of landscape ecology over the last 30 years is a remarkable story on its own. Adding in the revolutionary approach of conceptualising systems as complex entities which create patterns as a result of finite local processes results in an exciting new age for landscape ecology and ecology as a whole. Landscape ecology seems to be rushing forward towards a multidisciplinary field in which the tools to answer questions as well as discover questions never asked may be possible. Perhaps it may at least be possible to separate the knowable unknown from the truly unknown, as Levin (2002) eloquently said in reference to the development of statistical mechanisms. The daunting introduction of complex mathematical notions to practitioners more comfortable in the physical world should be mollified by the exciting possibilities that the coalition of fields creates.

References

Arthur W. B., Durlauf S. N., Lane D. (1997). Introduction. In: Arthur WB, Durlauf SN, Lane D, editors. The economy as an evolving complex system II. Reading (MA): Addison-Wesley. p 1–14.

Blaschke, T., and Hay, G. J. (2001). Object-oriented image analysis and scale-space: theory and methods for modeling and evaluating multiscale landscape structure. International Archives of Photogrammetry and Remote Sensing 34(4): 22-29.

Creswick R. J., Farach H. A., Poole C. P. Jr. (1992). Introduction to renormalization group methods in physics. New York: John Wiley and Sons.

Hay, G. J., Dubé, P., Bouchard, A., & Marceau, D. J. (2002). A scale-space primer for exploring and quantifying complex landscapes. Ecological Modelling,153(1): 27-49.

Kay, J., and Schneider, E. (1995). Embracing complexity: the challenge of the ecosystem approach. In: Westra, L., Lemons, J. (Eds.), Perspectives on Ecological Integrity. Kluwer, Dodrecht, pp. 49–59.

Kéfi, S., Rietkerk, M., Alados, C. L., Pueyo, Y., Papanastasis, V. P., ElAich, A., and De Ruiter, P. C. (2007). Spatial vegetation patterns and imminent desertification in Mediterranean arid ecosystems. Nature, 449(7159): 213-217.

Lindeberg, T. (1994). Scale-space theory: A basic tool for analyzing structures at different scales. Journal of applied statistics, 21(1-2): 225-270.

Levins, R. (1968). Evolution in Changing Environments: Some Theoretical Explorations. (MPB-2)(Vol.2). Princeton University Press.

Levin, S. A. (1992). The problem of pattern and scale in ecology.Ecology 73: 1943–67.

Levin, S. A. (1998). Ecosystems and the biosphere as complex adaptive systems. Ecosystems, 1(5): 431-436.

Levin, S. (2003). Complex adaptive systems: exploring the known, the unknown and the unknowable. Bulletin of the American Mathematical Society, 40(1): 3-19.

Meakin P. (1993). The growth of rough surfaces and interfaces. Phys Lett 235:189-289.

Meentemeyer, V. (1989). Geographical perspectives of space, time, and scale. Landscape Ecol. 3: 163–173.

Milne, B. T. (1998). Motivation and benefits of complex systems approaches in ecology. Ecosystems, 1(5): 449-456.

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Rietkerk, M., Dekker, S. C., de Ruiter, P. C., and van de Koppel, J. (2004). Self-organized patchiness and catastrophic shifts in ecosystems. Science, 305(5692): 1926-1929.

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Risser, P. G., & Iverson, L. R. (2013). 30 years later—landscape ecology: directions and approaches. Landscape Ecol, 28: 367-369.

Scheffer, M., Carpenter, S., Foley, J. A., Folke, C., & Walker, B. (2001). Catastrophic shifts in ecosystems. Nature, 413(6856), 591-596.

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Well-Ordered Science

Why do we do science? At the heart of every answer to this question is one of two basic points, to improve our lives by developing understandings that are useful to society or to improve our understanding in a purely epistemic fashion, that is, because the new knowledge is interesting. Given this, science has two sorts of problems that it sets out to solve, the type that yields obviously useful answers and the type which yields answers that are purely interesting. Typical examples of these two types of projects are medical research for the former, and theoretical physics projects, such as the Large Hadron Collider, for the latter. Both types of projects require funding and both have impacts on the lives of every person in society, especially in the case of government funding which is essentially sourced from the public. How then should we decide which problems are awarded funding and which problems aren't? These ideas are put forward by the philosopher Philip Kitcher in his quest to form an idealised picture of “well-ordered science”. According to Kitcher, well-ordered science should satisfy the preferences of all the citizens of society. The ideal way in which to achieve this is by no means one that can easily be adopted by a practical society, a fact that Kitcher himself admits, however it may work as a tool to judge our current distribution of funds and a guideline to improve these systems. According to Kitcher all members of the community should be equally informed and have equal say in the distribution of funds, the process he outlines is long winded and impractical and often in stark contrast to what actually makes up the decision making process for scientific funding in today’s society.  The idea of well-ordered science was recently introduced to me and I decided to take a look at a case which might enlighten me as to where our current society sits on the well-ordered scale.

Policy forums are designed in order to educate and discuss important ideas and problems which require solving and practices which call for implementation. Science magazine details the proceedings of some of these forums with an occasional article. At the beginning of this year the idea of restoration took precedent in one such forum with an article by Menz, Kingsley and Hobbs who detailed some of the “Hurdles and Opportunities for Landscape-Scale Restoration”.  The United Nations Conferences on sustainable development are the closest our society has come to the idealised aspects of well-ordered science, with the aim of uniting multidisciplinary figures in order to best solve the problems facing the world today. This policy forum outlines a task set as a priority after the Rio+20 Conference in 2012 which is estimated to cost US $18billion per year while contributing US$84 billion per year to the global economy. The target set is to restore 150 million hectares of disturbed and degraded land by 2020, the cost of which cannot be taken lightly. Aspects of well-ordered science can in some ways lend to the successful implantation of a project of this magnitude.

The authors of this paper outline four main points which they believe are critical in ensuring that the restoration projects sustain and enhance ecological values in an efficient and scalable manner:

1.  Identify focal regions

In order to maximise the effect of these projects they should be applied in ecosystems which are likely to respond favourably to the efforts of practitioners. Menz et al (2013) wisely point out that this is most effectively done through collaboration of multiple sectors which can lend information in order to maximize the effectiveness of the resources.  They suggest areas providing important ecosystem services as well as those effecting large percentages of the population

2.  Identify knowledge gaps and prioritize research needs

It is of little use if areas are chosen for restoration when very little is known about the functioning of the local ecosystem or the value the system offers. In these cases successful restoration is very unlikely. In order to avoid wasted efforts, interdisciplinary programs which encourage involvement from umbrella organizations, universities, locals in the area of interest, and funding agencies is necessary. This integration moves society towards well-ordered science.

3. Create restoration hubs

Part of developing a citizenship capable of well-ordered science is effective communication and education of members in order to close the science-practice gap. The authors recognise the importance of this and encourage a dialogue between restoration ecologists and participators. Given the communication technology of this age there is little excuse for there to not be open communication between researchers, practitioners, policy makers and the public.

4. Ensure political viability of restored ecosystems

Integrating the goals of scientists and politicians allows for a combined motivation to continue and maintain restoration work as well as working towards conservation which may limit the need for expensive restoration projects. Both social and scientific members of society need to shift their focus and widen their range in order to contemplate and facilitate the needs of the other sectors. In particular, scientists need to understand the responsibility that knowledge of these systems awards them, and shift focus away from journal writing and towards educating the public and political parties.

My first introduction to well-ordered science left me with a sense of hope and the idea that with current technology and the large problems attached to anthropogenic influences which by definition affect all of us, mankind has the opportunity to gather together and take these lessons to ensure a sustainable future for our species as well as the millions of others inhabiting this planet. This article by Menz et al (2013) provided additional comfort and the understanding that I am entering a field of people collectively working to use the knowledge we have to solve problems and improve the state of the environment. I also learned this week that we can take a few very useful lessons from philosophers of science in order to streamline the way we think about the world and the way we implement the findings of our research.

Reference

Menz, M. H., Dixon, K. W., & Hobbs, R. J. (2013). Hurdles and opportunities for landscape-scale restoration. Science, 339(6119), 526-527.

The Positives of Neutral Theory

The question of why species assemble in different patterns with different levels of diversity around the world is one that has received much attention from ecologists. Despite the interest the question is yet to be answered. Darwin made a large jump in our understanding of the diversity of species with his theory of evolution, but little was added to our understanding for almost 100 years after the publication of The Origin of species in 1859. The Island Biogeography theory (MacArthur and Wilson 1967) attempted to explain the difference in species abundance on islands and mainland patches of the same size, and was the next leap in the quest to understand species distribution and biodiversity. Island Biogeographic theory stood as a lonely and radical theoretical explanation of spatio-temporal dynamics of whole ecological systems for the next 30 years. The major work on biodiversity for that time focused on metapopulation biology with most work being done on population dynamics of single species existing in defined habitat patches. Enter The Unified Neutral Theory of Biodiversity (UNTB), formulated by Stephen Hubbell in the mid-1990s and published in 2001, UNTB is the next big attempt at a theoretical explanation of the origin, maintenance and loss of biodiversity in a biogeographic context. The theory is mathematically non-trivial and therefore not easy to grasp at a fundamental level, however it is an important advance in our need to explain patterns in biodiversity, especially given the large scale threats imposed on diversity through anthropogenic influences.

In 2006 Alonso, Etienne and McKane published a review of neutral theory aimed at identifying the merits of the theory despite the various attempts to falsify it. The theory is the first major work in combining the fields of biogeography and biodiversity in a theoretical and testable manner. Defining features of Hubbells theory are that it is formulated entirely in term of chance, defining it as a stochastic theory; it is a sampling theory dealing with formulae that predict abundance and composition which can then be empirically tested; and it deals with dispersal. The largest criticism that the theory receives is focused on the part after which it is named: neutrality. The concept of a neutral theory in ecology focuses on individuals of the same species being ecologically equivalent; that is, although individuals might be different, there is no difference in the way the rules of life apply to each of them. According to Alonso et al (2006), in combining stochasticity, species equivalence and dispersal limitation that exists as a sampling theory, UNTB exceeds previous neutral theories, which lacked these aspects.

In research we aim to explain a unknown with as simple a theory as possible, minimising parameters that require estimation, and assumptions which often cannot be met in the real world. UNTB has strength in that it relies on only two basic observations: one, that different individuals from different species living in functionally similar ecological communities are controlled by similar birth, death and dispersal rates (the basic concept behind neutrality), and two, that ecological systems are saturated. The saturation point implies that the community is “full”, all resources are being effectively utilised and the community is in equilibrium so that new individuals can only join the community if they replace emigrated or deceased members. Although these assumptions receive a lot of criticism the neutrality is accepted as a null model for community structure, which is the equivalent of saying that we think a community could be different to the null model but we can compare it to this model to check if it is. If nothing else UNTB works as a stepping stone to better formulations of alternative models which can be similarly tested through empirical sampling. 

The authors of the review praise Hubbell’s theory as one that makes the difficult jump from population-level descriptions with only a few species, to the paradigm shifted individual-based approach. In addition they point out that neutral theory is the first theory to include stochastic dynamics of species from origin to extinction, spatial formulation, and the dynamics of discrete individuals. The combination of these “ingredients” results in the ability to make quantitative predictions about general patterns, my holy grail of ecology. The desirous link between theory and empirical research extends to the fact that UNTB can be applied to a community as well as samples of the community, this feature elevates the theory above those commonly used which require additional complications in order to scale the theory from sample to community level.

By looking at developments and prospects of UNTB, Alonso et al (2006) paint a bright picture for the future of the theory, it is suggested that with some work the concept of neutrality could be relaxed. The benefits of understanding biodiversity in terms of functional diversity and redundancy are also vaguely pointed out. The idea seems to be that by understanding how different a community or assemblage is from neutral, and at what level the neutrality is functional, we can determine how at risk the community is to fatal disturbance. If all species are affected similarly (as with neutrality) will they all be wiped out by a disturbance, or will the redundancy allow for an overall resilience to change? These are questions that may one day be answered through applying Hubbell’s theory and there-by understanding the dynamics of biodiversity.

According to Hubbell (2001) our understanding of biodiversity is currently equivalent to that of a Middle Age understanding of medicine. It is important to remember that although The Unified Neutral Theory of Biodiversity and Biogeography is a major leap in an attempt to understand the complexity of biodiversity, it does not apply to all communities and situations. Its main contribution, in my opinion, will be as a reminder of how little we theoretically understand about biodiversity as a concept, and as such, as an inspiration and guidance to develop innovative theories about the mechanisms influencing biodiversity. I think it is easy to get caught up in the idea that many of the great scientific breakthroughs have been made but UNTB reminds us that it wasn't so long ago that we knew how little we know and that there is still great room to grow our understanding of the principles governing our world.

Alonso, D., Etienne, R. S., & McKane, A. J. (2006). The merits of neutral theory. Trends in Ecology & Evolution, 21(8), 451-457.

Hubbell, S. P. (2001). The unified neutral theory of biodiversity and biogeography. Princeton University Press.

MacArthur, R. H., & Wilson, E. O. (1967). The theory of island biogeography(Vol. 1). Princeton University Press.

Easy-Going Plankton

The importance of phytoplankton in the global carbon cycle seems to be gaining recognition resulting in many studies being performed to better understand factors that affect the size and productivity of phytoplankton communities. This trend is not surprising as the need to sequester carbon is only increasing. Anthropogenic effects continue to raise the level of carbon dioxide in the atmosphere year by year, in fact global CO₂ hit a multi-million year high of 398.35 parts per million in April this year (up from 396.45ppm in 2012), and exceeded 400ppm for the first time in recorded history, on the 9^th of May. With this in mind it is clear that an understanding of the organisms responsible for nearly half of global primary productivity is paramount. Primary productivity, in this case, is the production of organic compounds from CO₂ through the process of photosynthesis. The modelling of phytoplankton communities is of interest to me as I will be building a phytoplankton biomass model as one of my honours projects. Many of the processes determining the growth and life cycle of these organisms are well understood through decades of empirical research, and the extension into mathematical modelling is allowing for fascinating predictions and insights into the future of the marine environment.

Phytoplankton are at the bottom of the oceans very complicated food web and can be thought of as micro-plants of the ocean which absorb CO₂ through the process of photosynthesis. The productivity of this reaction is dependent on nutrient concentrations and environmental conditions such as light availability, mixed layer depth and temperature. Temperature plays an important role in marine and estuarine systems as it affects water stratification, most current work involves the modelling of this relationship. A recent paper by Thomas et al (2012), titled “A global Pattern of Thermal Adaption in MarinePhytoplankton” published in Science magazine, investigates the direct impact of temperature on marine phytoplankton. The authors point out that not only is phytoplankton sensitive to temperature, but this sensitivity is skewed, with higher temperatures having significantly worse consequences for many phytoplankton species. With global ocean temperatures set to rise, the future of phytoplankton appears rather dark. Given that a large portion of global atmospheric carbon is sequestered by phytoplankton, it is useful to understand how predicted changes in ocean water temperatures will affect the productivity and community structure of phytoplankton populations.

In order to understand how ocean warming will affect phytoplankton productivity and distribution the authors attempted to understand the current relationships between productivity and temperature and the global distribution of phytoplankton. The analysis of 194 strains of phytoplankton from information gleamed from over 80 publications from 1935 - 2011 revealed a strong trend in the latitudinal distribution of phytoplankton and the optimum temperature for productivity (the authors sneakily point out that this suggests a global trend in a microbial trait, which is currently unidentified). An even stronger trend between that optimum and the mean annual temperature at the population’s location was found. This suggests that phytoplankton populations are highly adapted to local temperatures.  Interestingly polar and temperate optimum temperatures were found to be higher than the annual temperatures at these points, which got me thinking, if oceanic temperatures are set to rise (which models predict to be the case in many regions) then surely phytoplankton with optima above current average temperatures will thrive? Unfortunately the predicted overall increase in temperature is not globally uniform and some regions around the poles and temperate regions are expected to remain constant and even possibly decrease.

The collaboration between optimum temperatures and location was not enough for the authors to confirm an adaptive relationship (one where strains possess the characteristics they do as a result of their environment) and so an eco-evolutionary model was run on the strains of phytoplankton in question. The model worked by “forcing” differences in strains of phytoplankton to be the same so that only temperature tolerance could be compared, essentially simplifying the system enough that the strains are comparable. For each location the optimum temperature was allowed to evolve, based on an evolutionary algorithm. This gives an output of the best strategy at each location based on temperature tolerance. The results showed that optimum temperature for phytoplankton primary production should in fact increase with increasing local mean temperatures. I consider this result great news for phytoplankton, as it indicates that they are in fact able to adapt to changes in temperature. However there is no current understanding of the rate at which strains are able to adapt to changing temperatures.

The paper goes on to a species distribution model which matches the current requirements of phytoplankton communities with the predicted available environments for 2091-2100. From this point of view large decreases in diversity are expected as regions become more or less favourable, with a dominant shift pole-ward for most species and a drastic decrease in diversity at the tropics. Without an understanding of the rate at which phytoplankton can adapt to environmental conditions, a species distribution model seems unimportant. Most biologists will agree that high diversity is an imperative characteristic of a healthy ecosystem and in this regard the movement of plankton strains is of interest, however these predictions carry little weight when it is known that phytoplankton are able to adapt to changing temperatures, additionally, given their rapid rate of reproduction and short lifespan, they are increasingly likely to evolve under strong temperature pressures. What would be of greater interest to me would be if the increasing temperatures where likely to lead to decreased population sizes, and not just decreased diversity.

Halfway There

In high school I was introduced to the concept of “global warming”; the idea that the lifestyle I had been living was causing harmful, irreversible change to the environment shocked me and redirected my life immediately. Since then the term has lost some of its credibility and has subsequently been replaced by “global climate change” mostly, in my opinion, to remove ammunition from the sceptics proclaiming that a longer summer and less harsh winter might be quite enjoyable. In the last 8 years the term has adapted in my life and been subdivided into multiple categories which all come down to “anthropogenic effects”. With this term I encompass (to name a few) habitat fragmentation, loss of biodiversity and perhaps most importantly, urbanisation. All three of these concepts are dealt with in this month’s chosen article: “Global forecasts of urbanexpansion to 2030 and direct impacts on biodiversity and carbon pools” by Seto, Güneralp and Hutyra (2012). As an “environmentalist” (read: person aware of the severity of the situation facing humans today) my biggest problem is trying to get my peers to understand that nothing is localised, that everything has an impact and that our actions are affecting the world in a temporally specific manner. This article is the latest weapon in my arsenal.

A large part of being informed about the severity of the global situation is feeling an obligation to educate those who don’t, and within that to work towards mitigating the problems. I see this paper as vital movement towards quantifying the possible path our civilisation is on. The fact that most people see urbanisation as a localised issue is one that sits with me daily and is a major tenant of the article. The world is getting smaller and smaller every day and our ability to mark the planet is increasing exponentially. This article makes the point that in one generation we will possibly globally urbanise land the equivalent size of South Africa. That is, there is a probability greater than 75% that 1,2 million square kilometres of land will be expanded into. Although the authors do not go into great detail about the methods they used to calculate these probabilities, they do explain that a probabilistic model was created using global land cover from 2000, urban population projections and gross domestic profit, and that five sources were used to create the model. As someone who enjoys mathematics, statistics and models, I would have liked more information about the workings of the model but the paper speaks loud enough to drown out my worries about fairly calculated probabilities.

I understand that with an increasing population, urbanisation is, to some extent, inevitable; but is it too much to ask that that expansion be efficient? The authors point out that urban area is expanding on average twice as fast as urban populations are. The denialist retort in this case could be that if space is a limited resource, at some point we will reach a sort of “equilibrium”, and that reaching that “equilibrium” is inevitable so it doesn't matter if it happens now or 50 years from now. Although this might be true it is our job as “environmentalists” to point out that every expansion has a cost to biodiversity and ecosystem services. Ecosystem services include the systems that allow us to have clean water, food, a stable climate and crop pollination, and biodiversity plays a role in many of these systems. As human populations grow, demand on these systems increase and it is vital that they are conserved. For this reason the authors include a study of the overlap of areas with a high probability of expansion and global biodiversity hotspots. To localise the point, one of the mentioned biodiversity hotspots is the Cape Floristic region which has a 75% or greater chance of losing 1100 square kilometres to urbanisation by 2030. Overall urbanisation of biodiversity hotspots is expected to increase by 160% from 2000 to 2030 with some areas, such as The Eastern Afromontane, the Guinean Forests of West Africa, and the Western Ghats and Sri Lanka hotspots experiencing increases of urbanisation of between 900% and 1900%. Not only are these regions associated with biodiversity but they additionally act as large carbon stores and the authors dedicate a section of the paper to the impacts that expansion will have on carbon pools. So, not only will the inevitable expansion impact biodiversity, but it could act to increase levels of carbon in the atmosphere (a known driver of climate change). To bring the point home just a little more the authors include an analysis of the endangered and critically endangered animals which occur in the regions likely to be urban by 2030. It is important to note that the paper does not take into account the additional pressures and indirect impact that this expansion could have and as such can be considered a conservative assessment of the situation.

Reading this paper has opened my eyes to the importance of global scale realistic forecasts that explicitly deal with human driven changes. I believe the biggest problem with it could be that the information will reach so few non-environmentalists. Perhaps this blog can work to fix that. Whatever stance you choose to take on politics, religion, social organisation or climate change, the problem of anthropogenic effects on the environment is one that faces us all. The world is smaller than we think and our ability to affect its composition is growing every day. The authors suggest that we look to Aldo Leopold (A 19th century ecologist who developed a set of land ethics) and Sir Alex Gordon (a forward thinking British architect) for guidance in policy making and design, considering development that allows for future changes and moves to sustainable practices. I would include that space-use efficiency and optimisation are of the utmost importance in urban land-use, agriculture, and ecosystem service conservation. As the authors direct you to Leopold and Gordon I add a direction to the concept of biomimicry and the words of Janine Benyus “Anything that we design—a product, a process, or a policy--has to ultimately pass muster in the biological realm. It has to help us thrive, but it also has to keep the habitat intact for our successors. A robin building a nest and an architect building a building should have the same concern: “How will the chicks fare here?”

Reference
Seto K. C., Güneralp B., and Hutyra L. R. (2012) Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences 109: 16083‐8.

Panchreston

For my first blog post I chose an article, actually a letter, from the highly acclaimed journal Nature. Nature is a multidisciplinary journal and it is very easy to get lost in the land of science when reading the titles of the articles in each edition. Luckily my brain is tuned to search out phrases like “human disturbance” and “diversity loss” and I quickly found this letter written by A. S. MacDougall with input from R. Turkington, K. S. McCann and G. Gellner titled ‘Diversity loss with persistent human disturbance increases vulnerability to ecosystem collapse’. Any young ecologist would find it difficult to not at least read the abstract. Upon doing so, I learned that the authors embarked on a 10 year experiment aimed at finding empirical evidence that a combination of environmental change and a loss in diversity increases the risk of an ecosystem collapse. My interest was piqued.


In my modest look into the world of ecology I have stumbled across multiple instances where a team of researchers focuses on a question that is easy to answer with a vague reference to some aspect of ecology that is difficult to test but important to assume. In many cases this leads to a necessity for generalisations and perhaps even a picking-and-choosing of relevant information, irrespective of context. These aspects usually involve a host of, in my opinion, vague references. Ecologists, and perhaps all natural scientists, are constantly being forced to build a world on assumptions and uncertainties in order to make one aspect of our understanding of complex systems more certain. The search for answers, and certainty, is why we do what we do. MacDougall et al state that theory predicts that a combination of environmental change and diversity loss increase the risk of abrupt and potentially irreversible ecosystem collapse. The letter cites six papers supposedly deal with this.


Ives and Carpenter (2007), Hooper et al. (2012) Loreau (2010), Barnosky et al. (2012), Kéfi et al. (2007), and Rietkerk et al. (2004) deal with a many aspects of the theory with some small scale empirical studies, and many commentaries on the state of the ecosystems but little comment based on in situ observations of ecosystem collapse as a result of environmental change or biodiversity loss. This is where MacDougall et al really grabbed my attention. Conducting a 10 year experiment of this nature is no mean feat and the results that this experiment yields are on a scale that surpasses most of those mentioned in the literature. All the models in the world are useless without experiments such as these.


There is no doubt that the results of the experiment are interesting. The finding that a negative relationship between diversity and function exist, begs me to ask, what we are actually conserving for? I often find myself wondering what humans are conserving for. Are we conserving out of nostalgia and fear of change or are we conserving our environment in order to better sustain ourselves? Where is the line dividing us from our environment? I grew up on the Gauteng Highveld surrounded by grassland and a large portion of my undergraduate studies dealt with fire regimes in Savanna and Grassland ecosystems. I find the idea of managing with fire interesting as the line dividing humans from being a part of the ecosystem to managers of the ecosystem becomes examinable. MacDougall et al examined the relationship between an altered and diversity poor ecosystem and vulnerability to collapse in degraded but species rich pyrogenic grassland; however, I did not find that the letter set the information into any real world context. The main findings of this experiment verified the theory that biodiversity is functionally significant in pyrogenic ecosystems, as grasslands with greater native species diversity were able to resist woodland invasion after a fire. While the monoculture low diversity areas were unable to stand up to the harsh introduction of a fire regime.

Although the article verifies some very important theory about managing grassland with fire, I felt that many aspects of the bigger questions were left out of the paper. The main benefit that I believe I received from this paper is contemplation into the roles we as humans play in our environment. The diversity-stability debate was not one I had considered before and it will possibly shape many of the conclusions I draw when debating conservation issues. I find myself led on to ask more and more questions about the need to conserve biodiversity and the search for mechanistic evidence that the processes we believe to be important are indeed playing the role in the ecosystem that we believe that they are.


One of my honours projects will be focusing on the connectivity of a landscape. The fundamental idea behind connectivity conservation is that in a fragmented landscape a higher level of connectivity allows for survival of metapopulations. My project will tend towards an analysis of scale and measures of connectivity with my faith being placed on the ideas of those before me, mainly that connectivity has importance. I am embarking on this study with the hope that what I find will be of interest to the community and will benefit the science, but generalisations and assumptions will need to be made. The link between metapopulation survival, connectivity and overall survival is mostly a theoretical one, rarely empirically studied. Perhaps real world investigations are too risky and in that regard I commend MacDougall et al. In the end not every question can be answered by any given study and in systems as complex as those found in nature assumptions will always be necessary. As I am beginning my journey into research biology this is an important lesson to learn in order to avoid feeling overwhelmed by the vastness of the unknown. I may have to build my questions on shaky theories and uncertainties, and I may not be able to solve all of the world’s problems, but, like MacDougall et al. perhaps I can shed some light on some cracks and add a measure of certainty so that



Reference

MacDougall A. S., K. S. McCann, G. Gellner, and R. Turkington, 2012. Diversity loss with persistent human disturbance increases vulnerability to ecosystem collapse. Nature 494: 86–89



pan·chres·ton [pan-kres-tuhn]:

noun a proposed explanation intended to address a complex problem by trying to account for all possible contingencies but typically proving to be too broadly conceived and therefore oversimplified to be of any practical use.

Modules and Models 101

This blog will serve two purposes:

1. To broaden my knowledge of current work in biological fields, including ecology and zoology
2. As an assessment tool to develop my research and writing skills.

These two aims should improve my skills during my honours year at UCT.

I am required to write blogs based on articles published in
Nature
Proceedings of the National Academy of Sciences, USA
Science
Trends in Ecology and Evolution

Although I still do not know what the year holds, I am sure that the content of this blog will be educational and developmental for me, and hopefully interesting for the reader.

I am required to blog a minimum of once a month but I may intersperse these obligatory posts with updates on my modules, projects and ancillary developments along the way.

I hope you enjoy the ride

Kiki