Modelling establishment probabilities of an exotic plant, Rhododendron ponticum, invading a heterogeneous, woodland landscape using logistic regression with spatial autocorrelation

Stephenson, Catriona M.; MacKenzie, Monique; Edwards, Colin; Travis, Justin M. J.

doi:10.1016/j.ecolmodel.2005.09.007

Cited by 44 publications

(35 citation statements)

References 40 publications

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“…Distance from the closest seed source and substrate conditions were important predictors of an invader seedling establishment (Stephenson et al 2006). Long jumps in distance dispersal are much more influential than the small steps in determining the geographical distribution of invasive plant species (Nathan 2006).…”

Section: Discussionmentioning

confidence: 99%

“…At an environmental level, soil, climate (Mann et al 1999;de Blois et al 2002;Shea and Chesson 2002;Sugiyama 2003;Retuerto and Carballeira 2004;Härdtle et al 2005;Milberg et al 2006) and the plant community structure (Inderjit et al 2005) modulate the geographical distribution of a nonnative invader. Environmental characteristics can be used to quantify the probability of establishment of an invader (Stephenson et al 2006).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Migration pattern suggested by terrestrial proximity as possible origin of wild annual Helianthus populations in central Argentina

Cantamutto

Torres²,

Presotto

et al. 2009

Biol Invasions

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There is a high interest to understand and recreate the invasive process of successful non-native plant invaders. The genetic tools provide scanty information when the invasion is recent and there is gene flow among the invader and its crop relative. The concern about the government and private companies' responsibilities in the diffusion process and the risk of occupancy of new areas motivated the interest in two wild annual Helianthus species naturalized in the central agricultural lands of Argentina. We used multivariate techniques and random tests to estimate the successive steps accomplished by the plant invaders across transportation routes, following an environmental and ecological gradient. A minimum connection tree through road distances was created considering dispersal from a unique dispersal point for each species. The proposed tree minimized, at the same time, the environmental and the ecological distances calculated by Euclidean and Gower indexes with abiotic and biotic habitat variables, being significantly different from random (P B 0.05). Our methodology allowed the development of an approach for the best estimation of the invasion route. This could be used to clarify the role of different agents involved in the diffusion process and to develop management strategies to prevent the plant invasion. The migration pattern suggests that after their historical introduction, both wild species moved in successive steps across a biotic and abiotic gradient, aided by anthropogenic activity along the road connection infrastructure. There were no evidences of escapes from sunflower breeding stations.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Migration pattern suggested by terrestrial proximity as possible origin of wild annual Helianthus populations in central Argentina

Cantamutto

Torres²,

Presotto

et al. 2009

Biol Invasions

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“…The physical, chemical, and biological properties of soil affected the distribution and establishment of plants. Previous studies [25,83,84] emphasized the importance of soil characteristics in species distribution.…”

Section: Sub-order Soilmentioning

confidence: 99%

Prediction of Dominant Forest Tree Species Using QuickBird and Environmental Data

Abdollahnejad

Panagiotidis

Shataee

et al. 2017

Forests

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Abstract:Modelling the spatial distribution of plants is one of the indirect methods for predicting the properties of plants and can be defined based on the relationship between the spatial distribution of vegetation and environmental variables. In this article, we introduce a new method for the spatial prediction of the dominant trees and species, through a combination of environmental and satellite data. Based on the basal area factor (BAF) frequency for each tree species in a total of 518 sample plots, the dominant tree species were determined for each plot. Also, topographical maps of primary and secondary properties were prepared using the digital elevation model (DEM). Categories of soil and the climate maps database of the Doctor Bahramnia Forestry Plan were extracted as well. After pre-processing and processing of spectral data, the pixel values at the sample locations in all the independent factors such as spectral and non-spectral data, were extracted. The modelling rates of tree and shrub species diversity using data mining algorithms of 80% of the sampling plots were taken. Assessment of model accuracy was conducted using 20% of samples and evaluation criteria. Random forest (RF), support vector machine (SVM) and k-nearest neighbor (k-NN) algorithms were used for spatial distribution modelling of dominant species groups using environmental and spectral variables from 80% of the sample plots. Results showed physiographic factors, especially altitude in combination with soil and climate factors as the most important variables in the distribution of species, while the best model was created by the integration of physiographic factors (in combination with soil and climate) with an overall accuracy of 63.85%. In addition, the results of the comparison between the algorithms, showed that the RF algorithm was the most accurate in modelling the diversity.

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“…In our study, according to Table 6, soil characteristics such as soil nutrients, soil depth, soil humidity and types of soil were some of the most important factors in the distribution of tree species because they influence site conditions (McKenney, Pedlar 2003;Stephenson et al 2006).…”

Section: Discussionmentioning

confidence: 99%

Investigation of a possibility of spatial modelling of tree diversity using environmental and data mining algorithms

Abdollahnejad¹,

Panagiotidis²,

Surový³

2016

J. For. Sci.

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Biological diversity is the basis for a wide array of goods and services provided by forests. The variety of forest trees and shrubs plays a vital role in the daily life of forest communities. The purpose of this study is to investigate the possibility of modelling the diversity of tree species by characteristics of topography, soil and climate, using data mining algorithms k-NN, RF and SVM in Dr. Bahramnia forestry plan in the north of Iran. Based on the basal area factor for each species in a total of 518 sample plots, diversity indices such as species richness, evenness and heterogeneity were calculated for each plot. Topographic maps of primary and secondary properties were prepared using the digital elevation model. Categories of the soil and climate maps database of Dr. Bahramnia forestry plan were extracted. Modelling rates of tree and shrub species diversity using data mining algorithms, with 80% of the sampling plots were taken. Assessment of the model accuracy, using 20% of samples and evaluation criteria, was conducted. Results showed that topographic features, especially elevation, had the highest impact on the species diversity index. The modelling results also showed that Camargo evenness index had lowest root mean square error (RMSE) (0.14) and RMSE% (24.35), compared to other indicators of diversity. In addition, the results of the comparison between the algorithms showed that the random forest algorithms were more accurate in modelling the diversity.

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Modelling establishment probabilities of an exotic plant, Rhododendron ponticum, invading a heterogeneous, woodland landscape using logistic regression with spatial autocorrelation

Cited by 44 publications

References 40 publications

Migration pattern suggested by terrestrial proximity as possible origin of wild annual Helianthus populations in central Argentina

Migration pattern suggested by terrestrial proximity as possible origin of wild annual Helianthus populations in central Argentina

Prediction of Dominant Forest Tree Species Using QuickBird and Environmental Data

Investigation of a possibility of spatial modelling of tree diversity using environmental and data mining algorithms

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