Measurement of soil compaction tolerance of Lagestromia speciosa (L.) Pers. using chlorophyll fluorescence

Philip, Elizabeth; Azlin, Y. Noor

doi:10.1016/j.ufug.2005.04.003

Cited by 20 publications

(8 citation statements)

References 9 publications

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“…Previous studies also found a decline of Fv/Fm induced by soil compaction for crops (maize: Zea mays L., and triticale: Â Triticosecale Wittm.) (Grzesiak, 2009) and ornamental trees (Lagerstroemia speciosa) (Philip and Azlin, 2005). The extent of photoinhibition can be considered as a consequence of photodamage to PSII and repair of the damage (Ohad et al, 1984).…”

Section: Effects On Seedling Performancementioning

confidence: 99%

Compaction by a forest machine affects soil quality and Quercus robur L. seedling performance in an experimental field

Cambi

Hoshika²,

Mariotti

et al. 2017

Forest Ecology and Management

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Section: Effects On Seedling Performancementioning

confidence: 99%

Compaction by a forest machine affects soil quality and Quercus robur L. seedling performance in an experimental field

Cambi

Hoshika²,

Mariotti

et al. 2017

Forest Ecology and Management

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“…In the plains, the area percentage of EcoLSP was less than 10% (Table 3), the degree of EcoLSP fragmentation was high, the area percentage of ArtLS was large, the population was concentrated, and the artificial heat emission was large. The urban environmental stress made the forest vegetation growth worse, resulting in weak vegetation transpiration (Philip & Azlin, 2005). In the plateau area, although the area percentage of EcoLSP was 44.20%, GraLS was the main EcoLSP, which had a smaller cooling capacity than ForLS, and the area percentage of FarmLS was 48.77%.…”

Section: Discussionmentioning

confidence: 99%

Analyzing the interpretative ability of landscape pattern to explain thermal environmental effects in the Beijing-Tianjin-Hebei urban agglomeration

Wang

Sun

Chen

et al. 2019

PeerJ

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The development of the urban agglomeration has caused drastic changes in landscape pattern and increased anthropogenic heat emission and lead to the urban heat island (UHI) effect more serious. Therefore, understanding the interpretation ability of landscape pattern on the thermal environment has gradually become an important focus. In the study, the spatial heterogeneity of the surface temperature was analyzed using the hot-spot analysis method which was improved by changing the calculation of space weight. Then the interpretation ability of a single landscape and a combination of landscapes to explain surface temperature was explored using the Pearson correlation coefficient and ordinary least squares regression from different spatial levels, and the spatial heterogeneity of the interpretation ability was explored using geographical weighted regression under the optimal granularity (5 × 5 km). The results showed that: (1) The hot spots of surface temperature were distributed mainly in the plains and on the southeast hills, where the landscapes primarily include artificial landscape (ArtLS) and farmland landscape (FarmLS). The cold spots were distributed mainly in the northern hills, which are dominated by forest landscape (ForLS). (2) On the whole, the interpretative ability of ForLS, FarmLS, ArtLS, green space landscape pattern, and ecological landscape pattern to explain surface temperature was stronger, whereas the interpretative ability of grassland landscape and wetland landscape to explain surface temperature was weaker. The interpretation ability of landscape pattern to explain surface temperature was obviously different in different areas. Specifically, the ability was stronger in the hills than in the plain and plateau. The results are intended to provide a scientific basis for adjusting landscape structural, optimizing landscape patterns, alleviating the UHI effect, and coordinating the balance among cities within the urban agglomeration.

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“…In the plains, the area percentage of EcoLSP was less than 10% (Table 3), the degree of EcoLSP fragmentation was high, the area percentage of ArtLS was large, the population was concentrated, and the artificial heat emission was large. The urban environmental stress made the forest vegetation growth worse, resulting in weak vegetation transpiration (Philip et al, 2005). In the plateau area, although the area percentage of EcoLSP was 44.20%, GraLS was the main EcoLSP, which had a smaller cooling capacity than ForLS, and the area percentage of FarmLS was 48.77%.…”

Section: Interpretative Ability Of Landscape Pattern To Explain Surfamentioning

confidence: 99%

Peer Review #2 of "Analyzing the interpretative ability of landscape pattern to explain thermal environmental effects in the Beijing-Tianjin-Hebei urban agglomeration (v0.2)"

2019

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The development of the urban agglomeration has caused drastic changes in landscape pattern and increased anthropogenic heat emission and lead to the urban heat island (UHI) effect more serious. Therefore, understanding the interpretation ability of landscape pattern on the thermal environment has gradually become an important focus. In the study, the spatial heterogeneity of the surface temperature was analyzed using the hotspot analysis method which was improved by changing the calculation of space weight. Then the interpretation ability of a single landscape and a combination of landscapes to explain surface temperature was explored using the Pearson correlation coefficient and ordinary least squares (OLS) regression from different spatial levels, and the spatial heterogeneity of the interpretation ability was explored using geographical weighted regression (GWR) under the optimal granularity (5 km × 5 km). The results showed that: (1) The hot spots of surface temperature were distributed mainly in the plains and on the southeast hills, where the landscapes primarily include ArtLS and FarmLS. The cold spots were distributed mainly in the northern hills, which are dominated by ForLS. (2) On the whole, the interpretative ability of ForLS, FarmLS, ArtLS, GreenLSP and EcoLSP to explain surface temperature was stronger, whereas the interpretative ability of GraLS and WetLS to explain surface temperature was weaker. The interpretation ability of landscape pattern to explain surface temperature was obviously different in different areas. Specifically, the ability was stronger in the hills than in the plain and plateau. The results are intended to provide scientific basis for adjusting landscape structural, optimizing landscape patterns, alleviating the UHI effect and coordinating the balance among cities within the urban agglomeration.

show abstract

Measurement of soil compaction tolerance of Lagestromia speciosa (L.) Pers. using chlorophyll fluorescence

Cited by 20 publications

References 9 publications

Compaction by a forest machine affects soil quality and Quercus robur L. seedling performance in an experimental field

Compaction by a forest machine affects soil quality and Quercus robur L. seedling performance in an experimental field

Analyzing the interpretative ability of landscape pattern to explain thermal environmental effects in the Beijing-Tianjin-Hebei urban agglomeration

Peer Review #2 of "Analyzing the interpretative ability of landscape pattern to explain thermal environmental effects in the Beijing-Tianjin-Hebei urban agglomeration (v0.2)"

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