Determination of ecological scale

Carlile, D.W.; Skalski, John R.; Batker, John E.; Thomas, John; Cullinan, Valerie I.

doi:10.1007/bf00125091

Cited by 78 publications

(37 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The scale at which a system is observed affects relationships between pattern and process, and between space, time, and organizational complexity (Levin 1992, 2000, Levin et al 1997, Tilman and Kareiva 1997, Tyre et al 1997, Dieckmann et al 2000, Wilson and Keeling 2000, Molofsky et al 2002. While investigators have acknowledged the need to address ecological questions at appropriate scales (Carlile et al 1989, Wiens 1989, De Roos et al 1991, how these ''appropriate scales'' are identified is often ambiguous. The application of methods from nonlinear time series analysis (Rand and Wilson 1995, Keeling et al 1997, Pascual and Levin 1999 of the study of scale in ecology, allowing a shift in focus from observing mean behaviors to extracting the deterministic signal from dynamical systems.…”

Section: Discussionmentioning

confidence: 99%

“…E-mail: craig.johnson@utas.edu.au ticularly to monitor and detect meaningful change in ecosystem state (Rand 1994, Bishop et al 2002. The search for a means to identify natural or ''characteristic'' length scales (hereafter CLSs) in ecological systems stems back at least to the 1950s (Grieg-Smith 1952, Kershaw 1957, but several more recent attempts have also addressed the problem (e.g., Carlile et al 1989, De Roos et al 1991, Schneider 1994. Most approaches have assumed either that ecological systems are stationary in space and time, that fluctuations are random around a stationary global average (e.g., Rand and Wilson 1995), or that any trends detected are linear (see Turner et al 1991).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Determining Natural Scales of Ecological Systems

Habeeb¹,

Trebilco²,

Wotherspoon³

et al. 2005

Ecological Monographs

View full text Add to dashboard Cite

Abstract. A key issue in ecology is to identify the appropriate scale(s) at which to observe trends in ecosystem behavior. The characteristic length scale (CLS) is a natural scale of a system at which the underlying deterministic dynamics are most clearly observed. Any approach to estimating CLSs of a natural system must be able to accommodate complex nonlinear dynamics and must have realistic requirements for data. Here, we compare the robustness of two methods to estimate CLSs of dynamical systems, both of which use attractor reconstruction to account for the complex oscillatory dynamics of ecological systems. We apply these techniques to estimate CLSs of spatial multispecies systems of varying complexity, and show that both methods are robust for the simplest system, but as model complexity increases, the Pascual and Levin metric is more robust than that of Keeling et al. Both methods demonstrate some sensitivity to the choice of species used in the analysis, with closely connected species producing more similar CLSs than loosely connected species. In this context, connectivity is determined both by the topology of the interaction network and spatial organization in the system. Notably, systems showing complex spatial self-organization can yield multiple CLSs, with larger length scales indicating the emergent dynamics of interactions between patches. While the prediction r 2 metric of Pascual and Levin is suitable to estimate CLSs of complex systems, their method is not suitable to apply to most real ecosystems because of the requirement of long time series for attractor reconstruction. We offer two alternatives, both based on prediction r 2 , but where repetition in space is largely (the ''short time series'' method) or wholly (the ''sliding window'' method) substituted for repetition in time in attractor reconstruction. Both methods, and in particular the short time series based on only three or four sequential observations of a system, are robust in detecting the primary length scale of complex systems. We conclude that the modified techniques are suitable for application to natural systems. Thus they offer, for the first time, an opportunity to estimate natural scales of real ecosystems, providing objectivity in important decisions about scaling in ecology.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Determining Natural Scales of Ecological Systems

Habeeb¹,

Trebilco²,

Wotherspoon³

et al. 2005

Ecological Monographs

View full text Add to dashboard Cite

show abstract

“…The exact relationship between variability and window size is difficult to predict (see empirical methods, for example, in Kershaw 1957, Cain and Castro 1959, Greig-Smith 1964, Mead 1974), but will be determined by the way spatial correlations fall off with distance (see, for example, Hubbell and Foster 1983, Robertson et al 1988, Carlile et al 1989. In general, the relationship will follow a power law within the correlation length of the system (which is determined by such influences as the disturbance size distribution, and the dispersal curve), and then will fall off asymptotically as the inverse of the number of cells in the window.…”

Section: Pattern and Scale In Terrestrial Systemsmentioning

confidence: 99%

Untitled

1992

Ecology

View full text Add to dashboard Cite

Abstract. It is argued that the problem of pattern and scale is the central problem in ecology, unifying population biology and ecosystems science, and marrying basic and applied ecology. Applied challenges, such as the prediction of the ecological causes and consequences of global climate change, require the interfacing of phenomena that occur on very different scales of space, time, and ecological organization. Furthermore, there is no single natural scale at which ecological phenomena should be studied; systems generally show characteristic variability on a range of spatial, temporal, and organizational scales. The observer imposes a perceptual bias, a filter through which the system is viewed. This has fundamental evolutionary significance, since every organism is an "observer" of the environment, and life history adaptations such as dispersal and dormancy alter the perceptual scales of the species, and the observed variability. It likewise has fundamental significance for our own study of ecological systems, since the patterns that are unique to any range of scales will have unique causes and biological consequences.The key to prediction and understanding lies in the elucidation of mechanisms underlying observed patterns. Typically, these mechanisms operate at different scales than those on which the patterns are observed; in some cases, the patterns must be understood as emerging from the collective behaviors oflarge ensembles of smaller scale units. In other cases, the pattern is imposed by larger scale constraints. Examination of such phenomena requires the study of how pattern and variability change with the scale of description, and the development of laws for simplification, aggregation, and scaling. Examples are given from the marine and terrestrial literatures.

show abstract

“…Any change or deterioration in these conditions has a direct or indirect effect on the hydraulic conditions, and becomes an important stress factor affecting instream biota and ecological integrity. The considerable literature, dating back more than five decades, dealing with the influence of scale (Harvey, 1967;Penning-Rowsell and Townshend, 1978;Carlisle et al, 1989;Levin, 1992), and stream channel characteristics (Leopold and Wolman, 1957;Strahler, 1964;Hynes, 1975;Frissell et al, 1986;Hawkins et al, 1993) is evidence of the importance of the physical habitat as a driver of ecological responses. During the last decade the increasing use of remotely-sensed datasets and Geographic Information Systems means that studies involving multiple spatial scales linked with land cover patterns have become widespread (see Orr et al, 2008;Buffagni et al, 2009;Kail et al, 2009;Sandin, 2009;Vaughan et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Links between stream reach hydromorphology and land cover on different spatial scales in the Adour-Garonne Basin (SW France)

Tudesque

Lek

2011

Knowl. Managt. Aquatic Ecosyst.

View full text Add to dashboard Cite

Key-words:hydromorphology, land cover, spatial scale, Random Forests, streamWe report an investigation aimed at improving the understanding of the relationships between hydromorphology and land cover, and in particular aimed at identifying the spatial scale on which land cover patterns best account for the hydromorphology at a stream reach. This investigation was carried out in the Adour-Garonne basin. Several key findings emerged from the use of a new modeling procedure called "Random Forests". Firstly, we established a typology of sites showing an upstream/downstream gradient structured by geographical descriptors and catchment hydromorphological features. Secondly, we found that the relationships between hydromorphology and the different spatial scales of land cover responded to a longitudinal gradient. Upstream, no noticeable difference was observed whatever the land cover pattern considered, whereas downstream, larger scales were strongly related to the hydromorphology. Thirdly, a specific land cover effect on each hydromorphological type was seen. Along the gradient, the contribution of the land cover variables structuring the hydromorphological types decreased and become homogeneous. Fourthly, stronger correlations were established with individual hydromorphological variables using the larger scales of land cover. This paper contributes to a better understanding of landscape ecology and fits well with the European Water Framework Directive that requires long-term sustainable management. In the context of natural conditions, we advise that the catchment scale should be given high priority when connected with land cover/uses; local and riparian environments being more valuable and complementary in the case of impacted sites. RÉSUMÉRelations entre l'hydromorphologie de section de cours d'eau et l'occupation du sol à différentes échelles spatiales dans le bassin Adour-Garonne (S-O France) Mots-clés :échelle spatiale, hydromorphologie, occupation du sol, Nous présentons les résultats d'une étude destinée à accroître la compréhension des relations entre l'hydromorphologie d'une portion de cours d'eau et l'occupation du sol, et particulièrement à identifier l'échelle spatiale pour laquelle l'emprise de l'occupation du sol est la plus déterminante. Cette étude a été conduite dans le bassin Adour-Garonne. Plusieurs résultats majeurs ont émergé suite à l'utilisation d'une technique récente de modélisation appelée « Ramdom Forests ». Random Forests, rivièrePremièrement, nous avons mis en évidence une typologie des sites d'étude, montrant un gradient amont/aval, structurée à la fois par les descripteurs géo-graphiques et les caractéristiques hydromorphologiques des bassins. Deuxième-ment, nous avons trouvés que les relations entre l'hydromorphologie et les diffé-rentes échelles spatiales répondaient également à un gradient longitudinal. Dans les zones amont, aucune différence notables n'a été observée quelque soit le type d'occupation du sol considéré, alors qu'en aval, les larges échelles spatiales étaient...

show abstract

Determination of ecological scale

Cited by 78 publications

References 17 publications

Determining Natural Scales of Ecological Systems

Determining Natural Scales of Ecological Systems

Untitled

Links between stream reach hydromorphology and land cover on different spatial scales in the Adour-Garonne Basin (SW France)

Contact Info

Product

Resources

About