A decision tree approach modelling functional group abundance in a pasture ecosystem

Zhang, Baisen; Valentine, Ian; Kemp, Peter

doi:10.1016/j.agee.2005.04.017

Cited by 19 publications

(21 citation statements)

References 31 publications

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“…In a related study in New Zealand (Zhang et al 2005), soil P and the rate of annual fertiliser P applications were found to be important determinants of fertility-responsive grass and legumes functional groups as was the case in this trial with Farmlet A.…”

Section: Discussionsupporting

confidence: 57%

Changes in botanical composition on three farmlets subjected to different pasture and grazing management strategies

et al. 2013

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Abstract. As part of the Cicerone Project's farmlet experiment, conducted on the Northern Tablelands of New South Wales, Australia, between July 2000 and December 2006, this study assessed the effects of varying soil fertility, pasture species and grazing management on the botanical composition of three 53-ha farmlets subjected to different management strategies. Starting with the same initial conditions, the farmlets were managed to reach different target levels of soil phosphorus (P) and sulfur (S); Farmlet A aimed at 60 mg/kg of Colwell P and 10 mg/kg S (KCl 40 ) whereas Farmlets B and C both aimed at 20 and 6.5 mg/kg of P and S, respectively. Pastures were renovated on six out of eight paddocks on Farmlet A, but only one paddock of each of Farmlets B (typical management) and C (intensive rotational grazing) was renovated. Flexible rotational grazing was employed on Farmlets A and B (each of eight paddocks) while Farmlet C used intensive rotational grazing over its 17 major paddocks, which were further subdivided into 37 subpaddocks. This paper focuses on the botanical composition dynamics observed across all three farmlets and the explanatory variables associated with those changes. Eight assessments of botanical composition were carried out at approximately annual intervals across each of the 37 major paddocks distributed across the farmlets and the results for each of 49 species were aggregated into seven functional groups for analysis. The strongest correlation found was a negative curvilinear relationship between sown perennial grasses (SPG) and warm-season grasses (WSG). The most significant factors affecting the functional group changes were soil P, sowing phase, paddock and date. These factors led to significant increases in SPG and correspondingly lower levels of WSG on Farmlet A compared with Farmlet B. Farmlets B and C experienced similar, declining levels of SPG, and increasing levels of WSG suggesting that intensive rotational grazing did not lead to substantial changes in botanical composition, compared with flexible rotational grazing, in spite of the fact that intensive rotational grazing had much longer grazing rests and shorter graze periods than the other two farmlets. Soil P levels were also significantly associated with levels of cool-season annual grasses, legumes and herbs, especially on Farmlet A. In general, the largest differences in botanical composition were between Farmlet A and the other two farmlets; these differences were most closely associated with those plants categorised as sown, introduced, C 3 pasture species. The levels of legume were generally low on all farmlets, due largely to the dry seasons experienced over most of the trial. Efforts to increase the legume composition on all farmlets were more successful on Farmlet A than on the other two farmlets due, presumably, to higher soil fertility on Farmlet A. Farmlet C, with its long rest periods and short graze periods, had a small proportion of legumes, due to the competitive effects of the accumulated tall grass herbage...

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Section: Discussionsupporting

confidence: 57%

Changes in botanical composition on three farmlets subjected to different pasture and grazing management strategies

et al. 2013

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“…The rationales for this choice are: DTs and ANNs are the most frequently used AI algorithms in environmental and ecological studies (Kim and Park 2009), and compared to the number of input variables (i.e., 7), the size of the measured target variable data (i.e., 196) was too small to use ANN algorithms but large enough to use DT algorithms (Kim and Park 2009). Furthermore, DT algorithms are relatively stable and accurate (Breiman et al 1984;Moret et al 2006;Scheffer 2002;Sesnie et al 2008;Vayssieres et al 2000;Yang et al 2003;Zhang et al 2005). Especially DT does not require any assumption about the frequency distributions of target variable data and is relatively insensitive to outlying values (Breiman et al 1984).…”

Section: Resultsmentioning

confidence: 99%

Decision-Tree-based data mining and rule induction for predicting and mapping soil bacterial diversity

Kim

Yoo

et al. 2010

Environ Monit Assess

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Soilmicrobial ecology plays a significant role in global ecosystems. Nevertheless, methods of model prediction and mapping have yet to be established for soil microbial ecology. The present study was undertaken to develop an artificial-intelligence- and geographical information system (GIS)-integrated framework for predicting and mapping soil bacterial diversity using pre-existing environmental geospatial database information, and to further evaluate the applicability of soil bacterial diversity mapping for planning construction of eco-friendly roads. Using a stratified random sampling, soil bacterial diversity was measured in 196 soil samples in a forest area where construction of an eco-friendly road was planned. Model accuracy, coherence analyses, and tree analysis were systematically performed, and four-class discretized decision tree (DT) with ordinary pair-wise partitioning (OPP) was selected as the optimal model among tested five DT model variants. GIS-based simulations of the optimal DT model with varying weights assigned to soil ecological quality showed that the inclusion of soil ecology in environmental components, which are considered in environmental impact assessment, significantly affects the spatial distributions of overall environmental quality values as well as the determination of an environmentally optimized road route. This work suggests a guideline to use systematic accuracy, coherence, and tree analyses in selecting an optimal DT model from multiple candidate model variants, and demonstrates the applicability of the OPP-improved DT integrated with GIS in rule induction for mapping bacterial diversity. These findings also provide implication on the significance of soil microbial ecology in environmental impact assessment and eco-friendly construction planning.

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“…Using NDVI values from remotely sensed images could identify the area of high species richness (Walker et al 1992;Bawa et al 2002). The use of NDVI data has great significance to investigate structure and functional composition of landscapes and is helpful to apply as a tool in landscape management (Zhang et al 2005). Repeated satellite images can be used both for the visual assessment of land resources as well as the quantitative evaluation of land cover changes over time (Tekle andHedlund 2000 cited in Quincey et al 2006).…”

Section: Resultsmentioning

confidence: 99%

Conserving the Himalayan forests: approaches and implications of different conservation regimes

Nautiyal

Kaechele

2007

Biodivers Conserv

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The conservation of Himalayan forests is big concern in view of global agenda. Many studies in this endeavor reported that the rate of forests degradation is posing a severe threat to the landscape and existing biodiversity in the Himalayas. Currently there many conservation approaches exists and of them four are widely recognized (1) Conservation through traditional religious beliefs ''traditional conserved forests'' (TCF); (2) Conservation through governmental planning and schemes ''government conserved forests'' (GCF); (3) Conservation through creation of protected areas (PAF); and (4) Conservation through community efforts ''community conserved forests'' (CCF). Our hypothesis in this direction says that all the conservation approaches lead to same results concerning to forest conservation. To testify our hypothesis we have studied the forests of each conservation regimes and evaluated them based on the identified indicators. We have done empirical studies and following the cloud-free satellite data were used for last three decades (such as Multi-Spectral Scanner, Linear Imaging and Self Scanning, and Enhanced Thematic Mapper ) to study a change in vegetation dynamics of the mountain forests in multi-temporal dimension. Our research concluded that community conservation approach have greater significance for biodiversity conservation and management in the Himalayan region. Here we support the model of CCF for forest ecosystem conservation, alongside the sustainable livelihood of the mountain societies. But every conservation regimes has its own importance in viewpoint of the particular objectives. Therefore, we suggests advancement and revision of PAF and GCF however, some elements of CCF can be introduced in TCF for making up it more sound in view of rapid socio-economic and cultural changes taking place in the communities.

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A decision tree approach modelling functional group abundance in a pasture ecosystem

Cited by 19 publications

References 31 publications

Changes in botanical composition on three farmlets subjected to different pasture and grazing management strategies

Changes in botanical composition on three farmlets subjected to different pasture and grazing management strategies

Decision-Tree-based data mining and rule induction for predicting and mapping soil bacterial diversity

Conserving the Himalayan forests: approaches and implications of different conservation regimes

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