Landscape Ecology Models & Theories PDF

LANDSCAPE ECOLOGY Introduction to Landscape Ecology: Theories & Models Department of Geography and Regional Planning University of Cape Coast  Introduction to Landscape Ecology LANDSCAPE LANDSCAPE ECOLOGY...

LANDSCAPE ECOLOGY Introduction to Landscape Ecology: Theories & Models Department of Geography and Regional Planning University of Cape Coast  Introduction to Landscape Ecology LANDSCAPE LANDSCAPE ECOLOGY ECOLOGY Sketch, Portrait (Artist) Plant Physical/Natural Animals Cultural Plants & Animals Physical/Natural & Culture Processes Designing Carl Troll (1939) coined the term Landscape (Geo/Spatial) Ecology (Functioning)  Definition Landscape ecology emphasizes the interaction between spatial pattern and ecological process—that is, the causes and consequences of spatial heterogeneity across a range of scales (Turner et al, 2015) Landscape ecology focuses; 1. Spatial relationships among landscape elements, or ecosystems 2. Flows of energy, mineral nutrients, and species among the elements 3. Ecological dynamics of the landscape mosaic/pattern through time  Components Landscape Ecology Composition: Elements or patches making up a landscape. Biotic and abiotic components of an ecological system Structure: Physical configuration or geometry of landscape components Process: Flows of organisms, materials, or disturbances through the mosaic. Mechanisms that convert inorganic material and energy  Theories in Landscape Ecology Theory: Framework or system of concepts and propositions that provides causal explanations of phenomena within a particular domain Landscape Ecology been shaped by the following; ▪ General System Theory (von Bertlanffy 1969a) ▪ Autopoiesis Theory (Maturana & Varela 1980) ▪ Ecological Theory (Scheiner & Willig 2007) ▪ Chaos Theory (Lorenz, Mandelbrot)  Theories in Landscape Ecology General System Theory (von Bertalanffy 1969) General Systems Theory (GST), emphasizes that systems, whether biological, ecological, or social, should not be studied in isolation but as interconnected parts of a whole. This perspective aligns closely with the principles of landscape ecology, where landscapes are considered as hierarchical systems with interacting ecological processes across scales. In landscape ecology, GST facilitates the understanding of landscapes as systems composed of multiple interacting components, like patches, corridors, and the background matrix, which together influence ecological functions and processes.  Theories in Landscape Ecology Strength & Weaknesses of General System Theory A key strength of GST in landscape ecology is its ability to foster a systems-level view, which facilitate an understanding of how spatial structure, interactions, and processes at one scale can influence other scales within a landscape. This allows landscape ecologists to model complex interactions between components of a landscape, which provide insights into ecosystem resilience, and habitat connectivity. However, GST faces criticism that the broad, overarching nature of it may lead to overly generalized models that fail to capture the specific complexities of localized ecological phenomena. Again, applying GST can sometimes result in difficulties in defining system boundaries and components, especially in heterogeneous and dynamic landscapes.  Theories in Landscape Ecology Autopoiesis Theory (Maturana & Varela 1980) This Theory defines living systems as self-organizing, self- producing entities that maintain their boundaries through internal regulatory processes. In landscape ecology, autopoiesis is valuable for understanding landscapes as dynamic systems capable of self-organization and resilience. The theory emphasizes that ecosystems can adapt and restructure in response to internal and external changes, making the theory useful for studying how landscapes respond to disturbances like climate change, deforestation, or human development. Landscape ecologists apply autopoietic concepts to explain how individual components contribute to the maintenance of larger ecosystem structures.  Theories in Landscape Ecology Strength and Weaknesses of Autopoiesis Theory One strength of the Theory in landscape ecology is its focus on the self-maintaining processes that allow ecosystems to retain their integrity over time. This approach aligns well with sustainability goals, as it highlights the importance of internal feedback and regulatory mechanisms that can sustain ecological health even amid external pressures. Some ecologists argue that autopoiesis can be overly abstract and challenging to apply practically to ecological models, especially when addressing highly complex ecosystems. Additionally, critics suggest that while autopoiesis focuses on internal dynamics, it may inadequately address the role of external forces such as human intervention in shaping ecosystems.  Theories in Landscape Ecology Ecological Theory (Scheiner and Willig 2007) Ecological Theory provides a framework for understanding the relationships and processes that shape ecological systems. Scheiner and Willig argue that ecological phenomena must be considered across various spatial and temporal scales to capture the complexity of interactions between organisms and their environments. This broad, integrative approach allows landscape ecologists to analyze how biotic and abiotic factors combine to influence ecosystem processes, structure, and function. It is particularly useful for addressing spatial heterogeneity and temporal dynamics, which are central to understanding landscape patterns and their ecological implications.  Theories in Landscape Ecology Strengths and Weaknesses of Ecological Theory A significant strength of Ecological Theory in landscape ecology is its capacity for cross-scale analysis, which is essential when dealing with complex, multi- layered landscapes. By adding elements from various ecological subfields, the theory encourages landscape ecologists to look beyond isolated factors, considering how multiple ecological processes interact to influence landscapes. This holistic approach is valuable for identifying the drivers of biodiversity, species distribution, and landscape connectivity, aiding in effective conservation strategies and management practices. However, the theory also faces criticism as some ecologists argue that its broad scope can make it difficult to apply specifically, as the inclusion of numerous interacting variables may lead to overly complicated models that are hard to test or interpret. Additionally, the emphasis on general principles in Ecological Theory may sometimes make localized or unique factors that play significant roles in specific ecosystems unclear.  Theories in Landscape Ecology Chaos Theory Chaos Theory pioneered by Lorenz and Mandelbrot, explores the behavior of complex systems that are highly sensitive to initial conditions, leading to seemingly random, unpredictable outcomes. In landscape ecology, the Theory provides a framework for understanding and modeling the dynamic and often unpredictable interactions within ecosystems, where minor changes in one part of a system can lead to significant shifts over time. For instance, delicate variations in environmental factors, like temperature or precipitation, can drastically influence species distributions, ecosystem resilience, and landscape patterns in unexpected ways. This sensitivity is essential for landscape ecologists as it helps explain the non-linear and dynamic nature of landscapes and their responses to environmental pressures.  Theories in Landscape Ecology Strengths and Weaknesses of Chaos Theory A key strength of this Theory in landscape ecology lies in its ability to acknowledge and accommodate the inherent uncertainty and unpredictability of ecological systems. It encourages ecologists to account for variability and to approach landscape models with flexibility, acknowledging that deterministic models might not fully capture the complex behaviors of natural systems. Chaos Theory helps reveal patterns within apparent disorder, which can aid in understanding ecosystem resilience and adaptability, as well as informing conservation efforts under fluctuating environmental conditions. However, Chaos Theory also faces criticism for its limitations in practical application. The theory's inherent focus on unpredictability and sensitivity can make it difficult to develop precise models for landscape management or conservation planning.  Models in Landscape Ecology A model is an abstract representation of a system or process All models are wrong, but some are useful (Box, 1979) Models Hierarchy Percolation Helps define the problem Meta-population Articulate concepts Source-Sink Means to analysis data Ecotones Make predictions Island biogeography  Models in Landscape Ecology Hierarchy Model ▪ Hierarchy Model in landscape ecology is a framework that conceptualizes ecological systems as structured, multi-level organizations, where each level of the hierarchy has its own processes and behaviors that influence and constrain levels above and below it. ▪ A core strength of Hierarchy model is its emphasis on scale, which enables landscape ecologists to investigate ecological patterns within contextually relevant scopes rather than being overwhelmed by vast, interconnected details. ▪ Additionally, the model supports a structured approach to landscape modeling, making complex ecological data more manageable and helping to clarify which levels of hierarchy are most pertinent to particular ecological questions. ▪ However, Hierarchy model faces criticism, as some ecologists argue that this tiered perspective can overlook the fluidity between hierarchical levels, as real- world ecological processes often cross these theoretical boundaries. ▪ Another critique involves the difficulty of empirically defining these hierarchical levels and distinguishing their boundaries in nature, which may lead to a disconnect between theoretical models and actual ecological observations.  Models in Landscape Ecology Percolation Model (Stuaffer, 1985) ▪ Percolation Model provides a framework for understanding spatial connectivity and fragmentation within ecological landscapes. ▪ Percolation Model is especially relevant for studying the "critical thresholds" in landscapes - points at which the structure or connectivity of habitats undergoes significant changes, impacting species survival, dispersal, and ecosystem processes. ▪ One of the strengths of Percolation Model lies in its ability to offer quantifiable metrics that help landscape ecologists model the impacts of habitat fragmentation and understand connectivity thresholds critical for species survival. ▪ A notable criticism is that the model often assumes a homogeneous landscape, which may not reflect the actual diversity and complexity found in natural ecosystems, where varying topographies, vegetation types, and other factors affect connectivity differently across regions. ▪ Also, it traditionally considers only the spatial aspects of connectivity, often overlooking temporal dynamics, species-specific behaviors, and ecological interactions that can alter connectivity and landscape functionality over time.  Models in Landscape Ecology Meta-Population Model (Levins, 1970) ▪ Meta-Population Model posits that species exists not as a single, large, continuous population, but rather as a network of smaller, semi-isolated populations, referred to as subpopulations, spread across discrete patches within a landscape. ▪ In landscape ecology, this model is particularly useful for explaining how species survive in fragmented habitats by frequently re-colonizing patches where local extinctions may occur. ▪ The strength of Meta-Population Model lies in its application to conservation and land management, especially in fragmented ecosystems. It provides a framework for designing conservation strategies that prioritize maintaining connectivity between patches, thus facilitating gene flow and recolonization. ▪ One limitation is its simplicity; it often assumes uniformity in patch quality, dispersal rates, and extinction probabilities across patches, which may not hold in complex, heterogeneous landscapes where environmental variability is high.  Thank You (Questions & Comments)