Cross-scale Morphology Geometry And Dynamics Of Ecosystems Pdf

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The availability of habitat structure across spatial scales can determine ecological organization and resilience.

Cross-Scale Morphology, Geometry, and Dynamics of Ecosystems

Landscapes and the ecological processes they support are inherently complex systems, in that they have large numbers of heterogeneous components that interact in multiple ways, and exhibit scale dependence, non-linear dynamics, and emergent properties. The emergent properties of landscapes encompass a broad range of processes that influence biodiversity and human environments. These properties, such as hydrologic and biogeochemical cycling, dispersal, evolutionary adaptation of organisms to their environments, and the focus of this article, ecological disturbance regimes including wildfire , operate at scales that are relevant to human societies.

These scales often tend to be the ones at which ecosystem dynamics are most difficult to understand and predict. We identify three intrinsic limitations to progress in landscape ecology, and ecology in general: 1 the problem of coarse-graining, or how to aggregate fine-scale information to larger scales in a statistically unbiased manner; 2 the middle-number problem, which describes systems with elements that are too few and too varied to be amenable to global averaging, but too numerous and varied to be computationally tractable; and 3 non-stationarity, in which modeled relationships or parameter choices are valid in one environment but may not hold when projected onto future environments, such as a warming climate.

Modeling processes and interactions at the landscape scale, including future states of biological communities and their interactions with each other and with processes such as landscape fire, requires quantitative metrics and algorithms that minimize error propagation across scales. We illustrate these challenges with examples drawn from the context of landscape ecology and wildfire, and review recent progress and paths to developing scaling laws in landscape ecology, and relatedly, macroecology.

We incorporate concepts of compression of state spaces from complexity theory to suggest ways to overcome the problems presented by coarse-graining, the middle-number domain, and non-stationarity.

Ecological landscapes have feedbacks and interactions across scales, and show scale dependence, whether they appear to be simple or complex Wu and David, ; Figure 1. Indeed, properties such as scale dependence and emergence are not simply features that complex systems share; they are diagnostic attributes of them.

Figure 1. Landscapes vary in complexity. Panel A shows a southern Arizona grassland at Las Cienegas National Conservation Area, illustrating a landscape with low taxonomic diversity, plant functional trait diversity, and topographic complexity. Panel B by comparison, has higher complexity, with a clear legacy of disturbance by wildfire, high plant functional diversity and topographic complexity, and more interactions among a higher number of species.

Ecosystems and ecology are shaped dynamically by bottom-up factors such as local topography, spatial clustering of resources, and stochastic events such as ignitions, as well as top-down processes and controls such as temperature, precipitation, and other climatic factors.

Disturbances such as wildfire and insect outbreaks are influenced by these factors and others, including phylogenetic history of organisms and their disturbance adaptations, physical structure and demography of organisms, and landscape history. However, knowing all of this information perfectly is not sufficient to predict fire behavior, initial ignition points, or extent of insect-caused mortality, because the features of emergent phenomena such as disturbance regimes are highly sensitive to initial conditions and may not be deterministic.

Photo credits: E. Various definitions for complexity have been proposed in different contexts Kolmogorov, ; Gell-Mann and Lloyd, ; Bialek et al. Models of a complex system may also be complex Kolmogorov, ; Edmonds, , or have simple rules generating complexity, as in the case of fractals ; and model complexity is sometimes used as an overall measure of relative complexity.

In these ways, complexity and information theory Shannon, are fundamentally linked. Complexity is sometimes associated with the physical entropy , rather than information entropy of a system Figure 2 , and quantitative relationships between complexity and both types of entropy have been proposed Wolpert, Table 1.

Common terms in complexity science, as related to landscape complexity. Figure 2. Schematic relationship between entropy and complexity. In region 1 , models are deterministic and exactly solvable. In region 2 , complex behavior of the system is controlled by interacting top-down and bottom-up processes, and models therefore will not provide perfect predictions of data. In region 3 , statistics are highly aggregated for large numbers of interacting elements, and general laws emerge for example, the Ideal Gas Law, the species area relationship in macroecology, or annual wildfire burned area at subcontinental scales.

As landscape ecology continues to develop as a field, it will be productive to engage the knowledge and terminology that have been developed in complexity science to define avenues of progress.

In this paper, we approach landscapes as complex systems, and give examples of phenomena associated with landscape-level complexity that are challenges to defining models that cross scales of patterns and processes. We do not address complexity per se , which is itself a subject of much theoretical work see Gell-Mann and Lloyd, Instead, we focus on three features of complexity that are intrinsic limitations, or challenges, to progress in landscape ecology.

These features are: 1 coarse-graining , or how to optimally aggregate fine-scale processes to larger scales in a robust manner that minimizes error Levitt and Warshel, ; Turner et al.

Even with expected ongoing improvements in modeling, data collection, and data processing, these limitations are less tractable than other types of ecological modeling problems, such as missing data or variables. These limitations therefore represent underlying conceptual challenges in the field of landscape ecology. We describe different conceptual approaches that have been applied to modeling of scaling and complexity for landscapes, review their limitations and potential, and suggest potentially fruitful directions for future research in landscape ecology.

Complex systems such as landscapes or general ecological systems have characteristics such as non-linearity, scale dependence, and emergence that make physical and ecological phenomena difficult to parse into independent variables, and prevent easy transference across space or time, or to different physical scales Wiens, ; Yates et al.

Simplifying assumptions about complex systems, such as not accounting for basic physical constraints e. In a complex system, emergent dynamics are not explained completely by simple reducible components, future states of the system may be deterministic and chaotic, or may contain stochastic components, and causal mechanisms are challenging to identify because any given component can act as both a driver and a response due to feedback mechanisms. Furthermore, the issue of prediction in complex systems poses a major challenge, because many future outcomes are possible, and these systems have high sensitivity to initial states of the system.

The global climate system is a well-known example of a complex system with these properties. Because outcomes will be sensitive to initial conditions and may not be entirely deterministic, predictions about emergent behavior will never be perfectly accurate, even with increasing amounts of data and better computational resources e. However, despite these limitations, reliable predictions are possible over short time horizons and for well-delimited questions where appropriate empirical data are available.

Landscape ecology, and particularly issues related to wildfire a major focus of this manuscript , exemplifies many of these properties of complex systems. For example, in landscape fire, we often study the interplay and feedbacks between large-scale, top-down drivers of wildfire, such as climate and human land-use Gill and Taylor, , and more mechanistic and smaller-scale bottom-up drivers, such as ignitions, fuel patterns, and local topography Falk et al.

Landscape ecology seeks to describe the dynamic relationships between ecological patterns and processes across spatial scales, from plot or forest-stand level to watersheds, from local regions to ecosections, or globally. Properties common to all complex systems, including self-organization, non-linearity, feedbacks, and robustness including lack of central control are reviewed in Ladyman et al. In studying the landscape ecology of wildfire, complexity is particularly expressed as emergence section Emergence , landscape memory section Landscape Memory , landscape resistance section Landscape Resistance , and contagion section Contagion.

As a consequence, landscape fire ecologists inevitably confront modeling complexity, and must grapple with these problems through choice of variables, scale, and delimitation of a system that lacks closed boundaries. Emergence refers to new patterns, processes, or structures that appear at higher levels of organization in the observation of phenomena that are not present at lower levels of organization.

Emergent phenomena are the products of causal mechanisms at lower levels of organization, but they are expressed primarily in behavior of high-order components. For example, many individual mechanical parts of a watch, when organized correctly, can track time together, but the individual parts cannot do this by themselves. Similarly, the functioning of social insect colonies results from the actions of individual worker insects with different tasks, and vehicle traffic patterns are the emergent result of individual drivers' choices about travel.

The property of life in organisms is itself an emergent property of the organization of molecules and biochemical pathways. Emergent processes must be consistent with finer-scale laws and cannot violate them; for example, biological processes have independent dynamics not fully explained by the laws of physics, but they are nonetheless subject to them. Many phenomena of landscapes result from emergence, including community-level structure and function, disturbance regimes, physiognomy of vegetation forested landscapes vs.

Landscape patch patterns are often a legacy of many disturbance events Cuddington, ; Figure 3. Landscape patches are identifiably distinct areas of any size in the spatial pattern of a landscape, such as the mosaic of burned and unburned areas in a large landscape wildfire. Burn-severity patches are the emergent result of the landscape distribution of fuels and fuel conditions, individual plant susceptibility to heat damage to living tissues, topographic influences on fire spread, fine-scale patterns of wind, and combustion physics at the submeter scale.

The size distribution and spatial structure of the post-fire patches are primary drivers of finer-scale landscape-ecological processes such as tree regeneration, which is constrained by seed availability and suitable recruitment environment, and future fire spread, which can either be constrained or accelerated by fuel availability Collins et al. Figure 3. Relationships between landscape memory and scales of time T and space S of landscape disturbances.

Revised, with permission, from McKenzie et al. Landscape memory or ecological memory, is a generic term for the legacies of landscape process and pattern, including their longevity and the strength of their influence on current landscape dynamics Peterson, ; Turner, ; Johnstone et al.

It also includes concepts of legacy effects of prior disturbances and use of the landscape Cuddington, Johnstone et al. A grassland with frequent fire and rapid regrowth may have a relatively short-term landscape memory for any particular fire event, whereas the legacy of wildfire in a forest with long-lived tree species may persist for multiple centuries Figure 3. McKenzie et al. In wildland fire, the legacy of individual fire events and the properties of the dominant plant community form a dynamic system in space and time.

For example, the behavior of a wildfire rate of spread, flame length, heat output per unit area and time is conditioned at each moment of combustion by multiple properties of topography slope, aspect, topographic position , weather wind direction, air temperature and humidity, precipitation, ignition sources such as lightning , and vegetation woody and herbaceous biomass, three-dimensional spatial distribution, water content of live and dead fuels. Fire behavior interacts with species' life-history traits and effects on soils to constrain individual survivorship and mortality, the primary metrics of fire severity Keeley, Plant condition and prior fire exposure also influences post-fire mortality van Mantgem et al.

The behavior and effects of wildfire then set the stage for post-fire ecological and hydrologic processes. Soil stability and permeability strongly regulate the speed with which vegetation can become re-established; severely burned hydrophobic soils take longer to become plant-suitable, and some plant guilds may be excluded initially by soil properties alone.

These areas must be recolonized by dispersing seeds from relict tree islands or adjacent surviving trees, which is a strongly scale-regulated process because the effective seed dispersal radius of many species is m or less, and successful seedling establishment can be limited by the availability of safe sites and suitable climate Stevens-Rumann and Morgan, ; Davis et al.

Recolonization of large high-severity patches can take decades or even centuries, leaving a persistent legacy of plant age classes, forest physiognomy, and species distributions that create the conditions that will regulate the next fire event Collins et al. Landscape resistance is a spatially structured characteristic of landscapes, quantifying resistance to movement with respect to a particular agent or process.

Typically, this concept is applied to animal movement Keeley et al. In the former, it is often a function of variation in habitat suitability or topography; with fire, it is a function of barriers or pathways to fire spread, such as steep topography or rivers and other non-flammable elements.

Landscape resistance controls the optimal paths of fire spread and the minimum travel time of a disturbance between locations, primarily through the influence of topography and fuels over landscape space Finney, For example, Conver et al. The inverse of resistance is connectivity, which is a combined effect of various landscape properties that facilitates the flow of mass or energy, and is related to contagion.

Resistance connectivity is an emergent landscape property resulting from the condition and spatial distribution of large number of individual plants, as well as their associated soils and topographic position. Contagion is a property of disturbances that propagate within a conducive medium. Connectivity allows the spread of a disturbance from one part of the medium to another, whereas inertia represents the ability of the disturbance to overcome some threshold and be passed from one unit to another.

Contagion is sometimes modeled as connectivity of networks, with the nodes in a network representing actors in the network, and edges representing the connections between them as the specific interaction being modeled. Nodes may be species, individuals, or locations; edges may represent disease or bark beetle outbreaks.

For example, infectious disease, such as root rot in trees, is a contagious disturbance that be modeled as an interaction network Delmas et al. The two nodes representing hosts or potential hosts of the disease would have one edge between them, representing an interaction of passing an infectious agent, if one party has infected another. Inertia in this case may represent the disease having to overcome a host's immune response. Networks may also be modeled with latency, to mimic dynamics and time-dependence of infection and spread.

Contagion can alternately be modeled without the network paradigm Peterson, For example, wildfire spreads through the medium of flammable vegetation and must cross the threshold of ignition temperatures to initiate fuel pre-heating and pyrolysis, which ultimately set up the chain reaction that allows fire to spread from one flammable element to another in space and time.

Similarly, insect outbreaks propagate through vulnerable host species of the correct age or size, overcoming the defensive mechanisms of trees to make use of the individual tree. In these cases, contagion is often modeled as a function of proximity of one grid cell, representing either an area or an agent, to another. With wildfire, both contagion and landscape resistance are relevant primarily within at medium spatial and temporal scales that have high complexity region 2 in Figure 2 , ranging from submeter scales to tens of kilometers.

For example, models of fire spread at the degree or half-degree grid spacing of global climate models are extrapolated outside the domain of contagion, as the spatial variation that controls fire spread is much more finely scaled McKenzie et al.

This middle domain of spatial scales has the greatest complexity section The Middle-Number Problem.

C. S. Holling

Holling, C. Adaptive environmental assessment and management. Fechada: noviembre 19, Cindy Hauser. Thomas Morris.

Holling was one of the conceptual founders of ecological economics. He grew up in Northern Ontario , which was where he first became interested in nature. Holling received his B. Marie, Ontario. Marshall Jr.

Theory posits that community dynamics organize at distinct hierarchical scales of space and time, and that the spatial and temporal patterns at each scale are commensurate. Here we use time series modeling to investigate fluctuation frequencies of species groups within invertebrate metacommunities in 26 boreal lakes over a year period, and variance partitioning analysis to study whether species groups with different fluctuation patterns show spatial signals that are commensurate with the scale-specific fluctuation patterns identified. We identified two groups of invertebrates representing hierarchically organized temporal dynamics: one species group showed temporal variability at decadal scales slow patterns of change , whilst another group showed fluctuations at 3 to 5-year intervals faster change. This pattern was consistently found across all lakes studied. A spatial signal was evident in the slow but not faster-changing species groups. As expected, the spatial signal for the slow-changing group coincided with broad-scale spatial patterns that could be explained with historical biogeography ecoregion delineation, and dispersal limitation assessed through a dispersal trait analysis. In addition to spatial factors, the slow-changing groups correlated with environmental variables, supporting the conjecture that boreal lakes are undergoing environmental change.

Holling, C. S. 1978.

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Allen and C. Allen , C.

Landscapes and the ecological processes they support are inherently complex systems, in that they have large numbers of heterogeneous components that interact in multiple ways, and exhibit scale dependence, non-linear dynamics, and emergent properties. The emergent properties of landscapes encompass a broad range of processes that influence biodiversity and human environments. These properties, such as hydrologic and biogeochemical cycling, dispersal, evolutionary adaptation of organisms to their environments, and the focus of this article, ecological disturbance regimes including wildfire , operate at scales that are relevant to human societies.

Ecosystem Management pp Cite as. Community ecology and ecosystem ecology seem to have existed in different worlds. Levin suggests that the gulf between the two is the consequence of the different historical traditions in each.

Literature Cited in Chapter 2.

Scaling and Complexity in Landscape Ecology

 Не понимаю. Кто будет охранять охранников. - Вот. Если мы - охранники общества, то кто будет следить за нами, чтобы мы не стали угрозой обществу. Сьюзан покачала головой, не зная, что на это возразить. Хейл улыбнулся: - Так заканчивал Танкадо все свои письма ко .

Они сейчас здесь появятся. У нас нет времени, чтобы… - Никакая служба здесь не появится, Сьюзан. У нас столько времени, сколько. Сьюзан отказывалась понимать. Не появится. - Но вы же позвонили… Стратмор позволил себе наконец засмеяться. - Трюк, старый как мир.


Она не обратила внимания на его просьбу. - Сядь.  - На этот раз это прозвучало как приказ. Сьюзан осталась стоять. - Коммандер, если вы все еще горите желанием узнать алгоритм Танкадо, то можете заняться этим без. Я хочу уйти.

 - Pelo rojo, azul, y bianco. Красно-бело-синие волосы. Мужчина засмеялся: - Que fea. Ничего себе зрелище.  - Он покачал головой и возобновил работу. Дэвид Беккер стоял в центре пустого зала и думал, что делать .

Клушар кивнул: - Со спутницей. Роскошной рыжеволосой девицей. Мой Бог.

Сьюзан не могла не поразить идея глобального прорыва в области разведки, который нельзя было себе даже представить. И он попытался сделать это в одиночку. Похоже, он и на сей раз добьется своей цели.

Росио пожала плечами. - Сегодня днем. Примерно через час после того, как его получила.

Приближаясь к пиджаку защитного цвета, он не обращал внимания на сердитый шепот людей, которых обгонял. Прихожане могли понять нетерпение этого человека, стремившегося получить благословение, но ведь существуют строгие правила протокола: подходить к причастию нужно, выстроившись в две линии. Халохот продолжал двигаться. Расстояние между ним и Беккером быстро сокращалось. Он нащупал в кармане пиджака пистолет.

Все это выглядит довольно странно. - Думаешь, надо вернуть им отчет. Она посмотрела на него недовольно. В том, что касалось Мидж Милкен, существовали две вещи, которые никому не позволялось ставить под сомнение.

Cross-scale Structure and Scale Breaks in Ecosystems and Other Complex Systems

 - Следопыт вышел на Хейла. - Следопыт так и не вернулся.


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