Continuum theory revisited: what shape are species responses along ecological gradients?

Oksanen, Jari; Minchin, Peter R.

doi:10.1016/s0304-3800(02)00190-4

Cited by 319 publications

(301 citation statements)

References 33 publications

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“…Separating theory from data availability and model applicability can ensure debates about theory are not confused with differences in data models. See the papers by Oksanen (1997), Austin and Nicholls (1997), Oksanen and Minchin (2002) for a recent example of a debate over theory and data models concerning the shape of species response curves.…”

Section: A Framework For Statistical Modelling In Plant Community Ecomentioning

confidence: 99%

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Spatial prediction of species distribution: an interface between ecological theory and statistical modelling

Austin¹

2002

Ecological Modelling

1,496

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Neglect of ecological knowledge is a limiting factor in the use of statistical modelling to predict species distribution. Three components are needed for statistical modelling, an ecological model concerning the ecological theory to be used or tested, a data model concerning the collection and measurement of the data, and a statistical model concerning the statistical theory and methods used. This component framework is reviewed with emphasis on ecological theory. The expected shape of a species response curve to an environmental gradient is a central assumption on which agreement has yet to be reached. The nature of the environmental predictors whether indirect variables, e.g. latitude that have no physiological impact on plants, or direct variables, e.g. temperature also influence the type of response expected. Straight-line relationships between organisms and environment are often used uncritically. Many users of canonical correlation analysis use linear (straight-line) functions to relate ordination axes to variables such as slope and aspect though this is not a necessary part of the method. Some statisticians have used straight lines for species/environment relationships without testing, when evaluating new statistical procedures. Assumptions used in one component often conflict with those in another component. Statistical models can be used to explore ecological theory. Skewed species response curves predominate contrary to the symmetric unimodal curves assumed by some statistical methods. Improvements in statistical modelling can be achieved based on ecological concepts. Examples include incorporating interspecific competition from dominant species; more proximal predictors based on water balance models and spatial autocorrelation procedures to accommodate non-equilibrium vegetation. #

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Section: A Framework For Statistical Modelling In Plant Community Ecomentioning

confidence: 99%

“…a and b values) were set for modelling individual species. Oksanen and Minchin (2002) have now examined a wider range of possible models for the shape of species response curves. A significant issue remains.…”

Section: Ecological Theory Testedmentioning

confidence: 99%

Spatial prediction of species distribution: an interface between ecological theory and statistical modelling

Austin¹

2002

Ecological Modelling

1,496

1,275

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“…For each species belonging to some of species groups we calculated species response curve to single environmental factors (pH and conductivity) by Huisman, Olff & Fresco (HOF) model of type 5 (Huisman et al 1993) based on logistic regression and following the algorithm of Oksanen & Minchin (2002). The medians of response optima yielded by this method were calculated for each group.…”

Section: Discussionmentioning

confidence: 99%

Formal definitions of Slovakian mire plant associations and their application in regional research

2007

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We applied the Cocktail method to a large data set of 4 117 relevés of all Slovak vegetation types with the aim to create formalised definitions of all Slovakian mire plant associations. We defined 21 groups of species with the statistical tendency of joint occurrences in vegetation. These groups differed substantially in their position along the pH/calcium gradient. We further defined 24 plant associations according to presence and/or absence of certain groups and/or strong dominance of some species. Only six traditional plant associations were not possible to be reproduced this way. We applied our formalised definitions to the regional data set of mires from the surrounding of the Vysoké Tatry Mts. Combined with frequency-positive fidelity index this method has led to the classification of the majority of vegetation plots into ten associations. When the vegetation types obtained from Cocktail-based classification and from cluster analysis were compared with respect to measured pH and conductivity in the study region, 82% of pairs differed significantly either in pH or in water conductivity in the former classification and 69% in the latter one.

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“…Simplicity increases from model V to model I, because the number of estimated parameters declines (although models III and IV contain the same number of parameters). Oksanen and Minchin (2002) produced an algorithm for model selection that proceeds by fitting the most complex model (V) to the species data using maximum likelihood (with a Poisson error structure), and then by reducing model complexity (to IV, then to III, then to II, and finally to I) until deviance increases significantly (an F-ratio test fails, where P ! 0.05).…”

Section: Climate Variable Selection and Evaluationmentioning

confidence: 99%

“…According to their routine, examination of model III occurs only after rejecting model IV over Model V. Therefore, model III may, in fact, represent a superior depiction of the response of some species allocated to model IV. We implemented this procedure for each species detected on at least ten plots and the three selected climate variables with HOF 2.3, an MS-DOS program (Oksanen and Minchin, 2002; available at http://cc.oulu.fi/$jarioksa/) for the quadrat and subplot frequency datasets. For both datasets, nonlinear relationships to climate were statistically significant for most species, and the symmetrical unimodal function was the most common response type (Table 2).…”

Section: Climate Variable Selection and Evaluationmentioning

confidence: 99%

Calibrating vascular plant abundance for detecting future climate changes in Oregon and Washington, USA

Brady

Monleón

Gray

2010

Ecological Indicators

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Continuum theory revisited: what shape are species responses along ecological gradients?

Cited by 319 publications

References 33 publications

Spatial prediction of species distribution: an interface between ecological theory and statistical modelling

Spatial prediction of species distribution: an interface between ecological theory and statistical modelling

Formal definitions of Slovakian mire plant associations and their application in regional research

Calibrating vascular plant abundance for detecting future climate changes in Oregon and Washington, USA

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