Comparison of spatial patterns of soil seed banks between larch plantations and adjacent secondary forests in Northeast China: implication for spatial distribution of larch plantations

Yan, Qiaoling; Zhu, Jiaojun; Gang, Qun

doi:10.1007/s00468-013-0920-y

Cited by 26 publications

(21 citation statements)

References 18 publications

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“…In summer, spectral signal from coniferous forest is different from broadleaf forest; in winter, larch shed their leaves and it hereby can be discriminated from the other evergreen coniferous tree species. Furthermore, most of LPs in China are a single species monoculture [5]. These multi-seasonal textures measures may help to extract the seasonal dynamic of pure forests more accurately.…”

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Mapping Spatial Distribution of Larch Plantations from Multi-Seasonal Landsat-8 OLI Imagery and Multi-Scale Textures Using Random Forests

et al. 2015

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Abstract:The knowledge about spatial distribution of plantation forests is critical for forest management, monitoring programs and functional assessment. This study demonstrates the potential of multi-seasonal (spring, summer, autumn and winter) Landsat-8 Operational Land Imager imageries with random forests (RF) modeling to map larch plantations (LP) in a typical plantation forest landscape in North China. The spectral bands and two types of textures were applied for creating 675 input variables of RF. An accuracy of 92.7% for LP, with a Kappa coefficient of 0.834, was attained using the RF model. A RF-based importance assessment reveals that the spectral bands and bivariate textural features calculated by pseudo-cross variogram (PC) strongly promoted forest class-separability, whereas the univariate textural features influenced weakly. A feature selection strategy eliminated 93% of variables, and then a subset of the 47 most essential variables was generated. In this subset, PC texture derived from summer and winter appeared the most frequently, suggesting that this variability in growing peak season and non-growing season can effectively enhance OPEN ACCESSRemote Sens. 2015, 7 1703 forest class-separability. A RF classifier applied to the subset led to 91.9% accuracy for LP, with a Kappa coefficient of 0.829. This study provides an insight into approaches for discriminating plantation forests with phenological behaviors.

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Mapping Spatial Distribution of Larch Plantations from Multi-Seasonal Landsat-8 OLI Imagery and Multi-Scale Textures Using Random Forests

et al. 2015

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“…Apart from human disturbance (Mamede, & Araújo, 2008) and the depth of seed deposition in the soil (Yu et al, 2008), there are other variables, such as variation in microhabitats, predation, canopy openness, pathogens and precipitation, that can influence directly or indirectly the richness and density of the soil seed bank (Pugnaire, & Lazaro, 2000;Santos et al, 2010;Santos et al, 2013a;Yan, Zhu, & Gang, 2013). However, although these variables were not monitored in this study, the vertical space alone explained 36% of the variation in species richness and 16% of the variation in density of seeds in the soil bank.…”

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confidence: 99%

¿Qué ocurre con el banco de semillas del suelo 17 años después del corte de la vegetación?

Mendes

Silva

Santos

et al. 2015

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Abstract:Seed banks play an important role in the resilience of potential anthropogenic areas and are influenced by seasonal variation. The spatial and temporal heterogeneity of the forests influences the richness and density of the soil seed bank, but there is a hypothesis that such influence can be changed in anthropogenic areas, where we expect to find lower richness and seed density in relation to the seed bank of mature forests. The richness and seasonal density of seeds in the soil depth of a young caatinga forest, 17 years after an agricultural activity was abandoned, were evaluated and compared with those of a mature forest. The study was conducted at the Instituto Agronômico de Pernambuco -IPA (Estação Experimental José Nilson de Melo), located in Caruaru, Pernambuco, Brazil, in an area of tropical dry forest, known locally as "caatinga". The local climate is seasonal, the dry season occurring from September to February and the rainy season concentrated in the remaining months. The average annual rainfall over time (time series of 30 years) is 692mm. In each climatic season (rainy and dry), the seed bank was sampled in 210 20x20cm plots (105 in the leaf litter and 105 at 5cm soil depth). The richness and seed density of the soil samples were evaluated by the method of seedling emergence. The seed bank had 47 species, with a predominance of herbaceous plants. Seasonal variation in richness and seed density in the soil (leaf litter + soil) was not significant, but 42 species of the mature forest were absent from the seed bank of the young forest, despite 17 years of natural regeneration and its proximity to the mature forest. On its own, the soil has greater richness and density of seeds than the leaf litter. The depth of seed deposition in the soil bank of the young forest significantly explained 36% of the species richness and 16% of the seed density, with a significant interaction effect with the climatic season only on species richness, explaining 4% of the variation recorded. The seed density of the young forest (1 277seeds/m 2 ) was greater than that the mature forest indicating that the time abandoned had not yet been sufficient for complete recovery of plant diversity and there is no longer any seed limitation of pioneer species for regeneration of the young forest. Rev. Biol. Trop. 63 (2): 321-332. Epub 2015 June 01.Key words: semiarid, young forests, savanna, natural regeneration, resilience.The soil seed bank reflects the factors that affect plant reproduction and survival of seeds in time and space (Donohue, Casas, Burghardt, Kovach, & Willis, 2010;López, 2003;Pennington, Lavin, & Oliveira-Filho, 2009; Pugnaire, & Lázaro, 2000;Silva et al., 2013a), and may be depleted in disturbed areas (Mamede, & Araújo, 2008;Wang, Jiang, Toshio, & Zhou, 2013;Williams, Congdon, Grice, & Clarke, 2005). However, the influence of spatial and temporal heterogeneity on the soil seed bank of areas that have undergone the removal of vegetation is still poorly documented, making it difficult to assess the potential f...

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“…is one of the most important planted timber tree species of China (Zhu et al, 2010;Yan et al, 2013;Gao et al, 2015). Since the 1950s, about 3.06 million ha of LP have been planted in North China.…”

Section: Study Areamentioning

confidence: 99%

Timber production assessment of a plantation forest: An integrated framework with field-based inventory, multi-source remote sensing data and forest management history

Gao

Zhu

Deng

et al. 2016

International Journal of Applied Earth Observation and Geoinfor

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a b s t r a c tTimber production is the purpose for managing plantation forests, and its spatial and quantitative information is critical for advising management strategies. Previous studies have focused on growing stock volume (GSV), which represents the current potential of timber production, yet few studies have investigated historical process-harvested timber. This resulted in a gap in a synthetical ecosystem service assessment of timber production. In this paper, we established a Management Process-based Timber production (MPT) framework to integrate the current GSV and the harvested timber derived from historical logging regimes, trying to synthetically assess timber production for a historical period. In the MPT framework, age-class and current GSV determine the times of historical thinning and the corresponding harvested timber, by using a "space-for-time" substitution. The total timber production can be estimated by the historical harvested timber in each thinning and the current GSV. To test this MPT framework, an empirical study on a larch plantation (LP) with area of 43,946 ha was conducted in North China for a period from 1962 to 2010. Field-based inventory data was integrated with ALOS PALSAR (Advanced Land-Observing Satellite Phased Array L-band Synthetic Aperture Radar) and Landsat-8 OLI (Operational Land Imager) data for estimating the age-class and current GSV of LP. The random forest model with PALSAR backscatter intensity channels and OLI bands as input predictive variables yielded an accuracy of 67.9% with a Kappa coefficient of 0.59 for age-class classification. The regression model using PALSAR data produced a root mean square error (RMSE) of 36.5 m 3 ha −1 . The total timber production of LP was estimated to be 7.27 × 10 6 m 3 , with 4.87 × 10 6 m 3 in current GSV and 2.40 × 10 6 m 3 in harvested timber through historical thinning. The historical process-harvested timber accounts to 33.0% of the total timber production, which component has been neglected in the assessments for current status of plantation forests. Synthetically considering the RMSE for predictive GSV and misclassification of age-class, the error in timber production were supposed to range from −55.2 to 56.3 m 3 ha −1 . The MPT framework can be used to assess timber production of other tree species at a larger spatial scale, providing crucial information for a better understanding of forest ecosystem service.

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Comparison of spatial patterns of soil seed banks between larch plantations and adjacent secondary forests in Northeast China: implication for spatial distribution of larch plantations

Cited by 26 publications

References 18 publications

Mapping Spatial Distribution of Larch Plantations from Multi-Seasonal Landsat-8 OLI Imagery and Multi-Scale Textures Using Random Forests

Mapping Spatial Distribution of Larch Plantations from Multi-Seasonal Landsat-8 OLI Imagery and Multi-Scale Textures Using Random Forests

¿Qué ocurre con el banco de semillas del suelo 17 años después del corte de la vegetación?

Timber production assessment of a plantation forest: An integrated framework with field-based inventory, multi-source remote sensing data and forest management history

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