Lowland rainforests in southern Taiwan and Lanyu, at the northern border of Paleotropics and under the influence of monsoon wind

Chao, Wei‐Chun; Song, Guo‐Zhang Michael; Chao, Kuo-Jung; Liao, Chi‐Cheng; Fan, Su-Wei; Wu, Shan-Huah; Hsieh, Tsung‐Hsin; Sun, I‐Fang; Kuo, Yau-Lun; Hsieh, Chang‐Fu

doi:10.1007/s11258-009-9694-0

Cited by 21 publications

(25 citation statements)

References 16 publications

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“…The spatial distributions of plants in Taiwan are strongly affected by climate, elevation, topography, and monsoon winds (Chao et al 2010; Chen et al 1997; Chiou et al 2010; Hsieh et al 1997, 1998; Li 2014; Li et al 2013; Mabry et al 1998; Su 1984, 1985; Zhang et al 2010). Taiwan had been divided into six geographical areas in terms of diverse climatic environments and floristic compositions (Su 1984, 1985).…”

Section: Methodsmentioning

confidence: 99%

Investigation of floristic similarities between Taiwan and terrestrial ecoregions in Asia using GBIF data

Liao

Chen²

2017

Bot Stud

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BackgroundFloristic compositions of non-endemic plants of continental islands were related to the neighboring continents because non-endemic plant species had historically migrated to continental islands from source areas. This study attempts to identify source areas of a continental island by means of floristic analysis and to assess possible migration routes on the basis of geographical distribution ranges of plants. Large quantities of angiosperm data records were downloaded from the Global Biodiversity Information Facility (GBIF). Similarity index and cluster analysis were used to identify the floristic similarities among 22 geographical localities of Taiwan (GLTs) and 34 terrestrial ecoregions in Asia. Geographical distribution ranges of non-endemic angiosperm species in Taiwan (NEASTs) were evaluated to mirror the possible migration routes from different source areas to Taiwan.ResultsThere are 3275 angiosperm species in Taiwan derived from the dataset of GBIF. Among them, 847 are endemic and 2428 are NEASTs. Geographical distribution ranges of the 2428 NEASTs were categorized into 7 distribution groups. They were widely distribution from equator to Siberia (27 species), tropical ecoregions (345 species), tropical and subtropical ecoregions (663 species), tropical to temperate ecoregions (591 species), subtropical ecoregions (265 species), subtropical to temperate ecoregions (387 species), and temperate ecoregions (150 species). Results of similarity indices and cluster analysis demonstrated that high floristic similarities were observed among GLTs at lowland and southern Taiwan and tropical and subtropical ecoregions in Asia. GLTs at high mountains were assumed to have floristic similarity with temperate ecoregions in Asia, whereas the assumption was not supported by our analysis. It is partly because of that angiosperms with tropical and subtropical distributions extend their ranges from low to high elevations in Taiwan.ConclusionsSubtropical ecoregions at southern China and tropical ecoregions at Indochina were more important than temperate ecoregions on playing source areas of NEASTs. Geographical distribution ranges of NEASTs implied that most of the NEASTs were probably migrated from topical or subtropical ecoregions of Asian continent to Taiwan.Electronic supplementary materialThe online version of this article (doi:10.1186/s40529-017-0171-0) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Investigation of floristic similarities between Taiwan and terrestrial ecoregions in Asia using GBIF data

Liao

Chen²

2017

Bot Stud

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“…Several possible reasons for this result are as follows: (a) Illicium–Cyclobalanopsis forest is tropical vegetation exposed to winter monsoon directly, which is characterized by its cold‐humid climate during winter, the high stem density, and richness in sclerophyllous species. This forest type is narrowly restricted to windward hill ridges, but converts to high canopy leeward or to valley forests dramatically as the topography changes (Chao et al, ; Li et al, ). In southern Taiwan, the habitats of Illicium–Cyclobalanopsis forest are usually fragmented and form a mosaic with sub‐montane and foothill forests such as Drypetes–Helicia forest, Ficus–Machilus forest, and Dysoxylum–Machilus forest.…”

Section: Discussionmentioning

confidence: 99%

Climate‐based approach for modeling the distribution of montane forest vegetation in Taiwan

Lin

Chen

et al. 2020

Applied Vegetation Science

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Aims Climate shapes forest types on our planet and also drives the differentiation of zonal vegetation at regional scale. A climate‐based ecological model may provide an effective alternative to the traditional approach for assessing limitations, thresholds, and the potential distribution of forests. The main objective of this study is to develop such a model, with a machine‐learning approach based on scale‐free climate variable estimates and classified vegetation plots, to generate a fine‐scale predicted vegetation map of Taiwan, a subtropical mountainous island. Location Taiwan. Methods A total of 3,824 plots from 13 climate‐related forest types and 57 climatic variable estimates for each plot were used to build an individual ecological niche model for each forest type with random forest (RF). A predicted vegetation map was developed through the assemblage of RF predictions for each forest type at the spatial resolution of 100 m. The accuracy of the ensemble RF model was evaluated by comparing the predicted forest type with its original classification by plot. Results The climate environment of regions higher than 100 m above sea level in Taiwan was classified into potential habitats of 13 forest types by using model predictions. The predicted vegetation map displays a distinct altitudinal zonation from subalpine to montane cloud forests, followed by the latitudinal differentiation of subtropical mountain forests in the north and tropical montane forests in the south, with an average mismatch rate of 6.59%. An elevational profile and 3D visualization demonstrate the excellence of the model in estimating a fine, precise, and topographically corresponding potential distribution of forests. Conclusions The machine‐learning approach is effective for handling a large number of variables and to provide accurate predictions. This study provides a statistical procedure integrating two sources of training data: (a) the locations of field sampling plots; and (b) their corresponding climate variable estimates, to predict the potential distribution of climate‐related forests.

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“…This forest was dominated by Schefflera octophylla, Psychotria rubra, Castanopsis cuspidata var. carlesii, and Illicium arborescens (Chao et al 2010). CHPs were acquired with a Sigma 4.5 mm F2.8 EX DC HSM circular fish-eye lens (Kanagawa, Japan) attached to a Nikon D5000 camera.…”

Section: Acquisition Of Chpsmentioning

confidence: 99%

Improving accuracy of canopy hemispherical photography by a constant threshold value derived from an unobscured overcast sky

et al. 2014

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High image discrimination threshold values tend to be given to canopy hemispherical photographs (CHPs) with high exposure (resulting in bright images), but the effects of exposure on image threshold have been overlooked. A model canopy system was developed to precisely manipulate exposure (in relation to reference exposure measured from an unobscured overcast model sky), canopy openness, gap fragmentation and sky illumination of CHPs. We showed that there was a numerical trade-off relationship between exposure and image threshold of CHPs, whereas the last three factors had negligible effects on image threshold. A new thresholding method based on this relationship was shown to be applicable in the field and to allow users of hemispherical photography (HP) to compensate for the effects of higher exposure on CHPs with higher empirical threshold values. The advantages of this method are as follows: (i) it is an objective method; (ii) its overall performance is better than that of automatic thresholding methods throughout a wide range of canopy openness and exposure; and (iii) its efficiency of image analysis is higher than that of conventional manual and automatic thresholding methods, because all CHPs can be analysed with a constant empirical threshold value. Our results highlight the necessity of integrating both exposure and thresholding for optimal CHP results and the contribution that model canopies can make to methodological studies of HP.Résumé : Des valeurs élevées de seuil de mobilité de l'image ont tendance à être attribuées aux photographies hémisphériques du couvert forestier (PHCF) avec un long temps de pose. Cela produit des images lumineuses mais on ne s'est pas préoccupé des effets du temps de pose sur le seuil de l'image. Un système de modélisation du couvert forestier a été développé pour manipuler avec précision le temps de pose (en relation avec un temps de pose de référence mesuré à partir de la modélisation d'un ciel couvert non obstrué), l'ouverture du couvert forestier, la fragmentation due aux trouées et l'éclairage du ciel des PHCF. Nous avons montré qu'il y avait une relation de compensation numérique entre le temps de pose et le seuil de l'image des PHCF tandis que les trois derniers facteurs avaient des effets négligeables sur le seuil de l'image. Nous avons aussi démontré qu'une nouvelle méthode de seuillage fondée sur cette relation était applicable sur le terrain et permettait aux utilisateurs de la photographie hémisphérique (PH) de compenser les effets d'un plus long temps de pose sur les PHCF par des valeurs empiriques de seuil plus élevées. Les avantages de cette méthode sont : (i) l'objectivité de la méthode, (ii) une performance globale meilleure que celle des méthodes d'autoseuillage pour une large gamme d'ouvertures du couvert forestier et de temps de pose, et (iii) une analyse de l'image plus efficace que celle des méthodes de seuillage manuelles ou automatiques conventionnelles parce que toutes les PHCF peuvent être analysées avec une valeur de seuil empirique constante. Nos ...

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Lowland rainforests in southern Taiwan and Lanyu, at the northern border of Paleotropics and under the influence of monsoon wind

Cited by 21 publications

References 16 publications

Investigation of floristic similarities between Taiwan and terrestrial ecoregions in Asia using GBIF data

Investigation of floristic similarities between Taiwan and terrestrial ecoregions in Asia using GBIF data

Climate‐based approach for modeling the distribution of montane forest vegetation in Taiwan

Improving accuracy of canopy hemispherical photography by a constant threshold value derived from an unobscured overcast sky

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