Pub Date : 2024-03-18DOI: 10.2989/20702620.2023.2284753
Patrícia Fukushima de Souza, M. Navroski, Mariane de Oliveira Pereira, Marcos Filipe Nicoletti, Ramon Silveira de Andrade
{"title":"Growth, vegetative rescue and vegetative propagation in\u0000 Eucalyptus\u0000 species and hybrids","authors":"Patrícia Fukushima de Souza, M. Navroski, Mariane de Oliveira Pereira, Marcos Filipe Nicoletti, Ramon Silveira de Andrade","doi":"10.2989/20702620.2023.2284753","DOIUrl":"https://doi.org/10.2989/20702620.2023.2284753","url":null,"abstract":"","PeriodicalId":21939,"journal":{"name":"Southern Forests: a Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140231451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-29DOI: 10.2989/20702620.2023.2273479
C. Brand Wessels, Christel Malek, Gary R Hodge, B. Balboni
{"title":"An investigation into the flexural properties of sawn timber and poles of South African grown\u0000 Pinus maximinoi\u0000 (H.E.Moore)","authors":"C. Brand Wessels, Christel Malek, Gary R Hodge, B. Balboni","doi":"10.2989/20702620.2023.2273479","DOIUrl":"https://doi.org/10.2989/20702620.2023.2273479","url":null,"abstract":"","PeriodicalId":21939,"journal":{"name":"Southern Forests: a Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140408682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-07DOI: 10.2989/20702620.2023.2279054
M. Tarigan, Michael J Wingfield, F. Jami, Yosep Man Marpaung, A. Durán, N. Q. Pham
{"title":"Pathogenicity of\u0000 Chrysoporthe deuterocubensis\u0000 on eucalypts in Indonesia","authors":"M. Tarigan, Michael J Wingfield, F. Jami, Yosep Man Marpaung, A. Durán, N. Q. Pham","doi":"10.2989/20702620.2023.2279054","DOIUrl":"https://doi.org/10.2989/20702620.2023.2279054","url":null,"abstract":"","PeriodicalId":21939,"journal":{"name":"Southern Forests: a Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139796668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-07DOI: 10.2989/20702620.2023.2279054
M. Tarigan, Michael J Wingfield, F. Jami, Yosep Man Marpaung, A. Durán, N. Q. Pham
{"title":"Pathogenicity of\u0000 Chrysoporthe deuterocubensis\u0000 on eucalypts in Indonesia","authors":"M. Tarigan, Michael J Wingfield, F. Jami, Yosep Man Marpaung, A. Durán, N. Q. Pham","doi":"10.2989/20702620.2023.2279054","DOIUrl":"https://doi.org/10.2989/20702620.2023.2279054","url":null,"abstract":"","PeriodicalId":21939,"journal":{"name":"Southern Forests: a Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139856670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-31DOI: 10.2989/20702620.2024.2312024
{"title":"Amendment notice","authors":"","doi":"10.2989/20702620.2024.2312024","DOIUrl":"https://doi.org/10.2989/20702620.2024.2312024","url":null,"abstract":"","PeriodicalId":21939,"journal":{"name":"Southern Forests: a Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140476309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-07DOI: 10.2989/20702620.2023.2257657
B. Nero, Maxwell Asuenabisa
{"title":"Effects of thinning on growth performance of teak (\u0000 Tectona grandis\u0000 ) plantations in Tain II Forest Reserve, Ghana","authors":"B. Nero, Maxwell Asuenabisa","doi":"10.2989/20702620.2023.2257657","DOIUrl":"https://doi.org/10.2989/20702620.2023.2257657","url":null,"abstract":"","PeriodicalId":21939,"journal":{"name":"Southern Forests: a Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138590264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.2989/20702620.2023.2239197
Simon A Mng’omba
AbstractFlacourtia indica (Burm.f.) Merr. is an important fruit and medicinal tree in Southern Africa. Efforts to achieve early fruiting have failed with juvenile propagules (planting materials) such as seed. Assessing rooting ability of mature (fruit bearing) F. indica stem cuttings is vital to attaining early fruiting, or precocious fruiting, which reduces the long juvenile phase experienced by many woody fruit trees when propagated from seeds (juvenile planting materials). The objectives of this study were to assess responses of mature stem cuttings to different application times of rooting hormone (Seradix® No. 2) and collection times of stem cuttings, and also to identify important pheno-phases in the yearly tree growth cycle of F. indica. A significantly higher rooting percentage (p < 0.001) was obtained with delayed Seradix® No. 2 application than with immediate application. Stem cuttings collected at flowering and leaf fall seasons were responsive to Seradix® No. 2 application, but all stem cuttings collected at fruiting time failed to produce roots. For stem cuttings collected during flowering time, immediate Seradix® application resulted in significantly (p = 0.0482) more roots than in stem cuttings subjected to delayed Seradix® application. The failure to produce roots of cuttings collected at fruiting time could be due to low sugars (carbohydrates) in the stem cuttings. The study concluded that the best time to collect stem cuttings from mature F. indica trees for rooting is either at flowering or leaf fall stages and that delayed Seradix® No. 2 application improves rooting of stem cuttings from mature F. indica trees.Keywords: carbohydratesfruiting precocityindole-3-butyric acidphenologyroot length
{"title":"Delayed rooting hormone application and stem cutting collection time improved <i>Flacourtia indica</i> rooting ability and root growth","authors":"Simon A Mng’omba","doi":"10.2989/20702620.2023.2239197","DOIUrl":"https://doi.org/10.2989/20702620.2023.2239197","url":null,"abstract":"AbstractFlacourtia indica (Burm.f.) Merr. is an important fruit and medicinal tree in Southern Africa. Efforts to achieve early fruiting have failed with juvenile propagules (planting materials) such as seed. Assessing rooting ability of mature (fruit bearing) F. indica stem cuttings is vital to attaining early fruiting, or precocious fruiting, which reduces the long juvenile phase experienced by many woody fruit trees when propagated from seeds (juvenile planting materials). The objectives of this study were to assess responses of mature stem cuttings to different application times of rooting hormone (Seradix® No. 2) and collection times of stem cuttings, and also to identify important pheno-phases in the yearly tree growth cycle of F. indica. A significantly higher rooting percentage (p < 0.001) was obtained with delayed Seradix® No. 2 application than with immediate application. Stem cuttings collected at flowering and leaf fall seasons were responsive to Seradix® No. 2 application, but all stem cuttings collected at fruiting time failed to produce roots. For stem cuttings collected during flowering time, immediate Seradix® application resulted in significantly (p = 0.0482) more roots than in stem cuttings subjected to delayed Seradix® application. The failure to produce roots of cuttings collected at fruiting time could be due to low sugars (carbohydrates) in the stem cuttings. The study concluded that the best time to collect stem cuttings from mature F. indica trees for rooting is either at flowering or leaf fall stages and that delayed Seradix® No. 2 application improves rooting of stem cuttings from mature F. indica trees.Keywords: carbohydratesfruiting precocityindole-3-butyric acidphenologyroot length","PeriodicalId":21939,"journal":{"name":"Southern Forests: a Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135272830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AbstractTachigali vulgaris is a tree with high potential for energy purposes in Brazil. However, there is little information about genetic variability that can be applied to plant breeding. Here, we quantified genetic variability based on biometric and emergence traits of T. vulgaris seeds from the native population of the Brazilian Amazon. The biometric aspects, moisture content, emergence, emergence speed index, and average emergence time of the seeds were evaluated. Genotypic values and genetic parameters were analysed using the mixed model methodology in a completely randomised design with 12 genotypes and four replications of 25 seeds. All biometric and emergence traits of seeds showed phenotypic and genetic variabilities. Heritability was high for all traits evaluated (0.66 to 0.97), and genetic accuracy showed high experimental precision and reliable results (≥ 0.90). Grouping by the Tocher, unweighted pair group with arithmetic mean and principal component analysis methods based on genetic traits returned four groups: Group 1 by Genotypes 1, 4, 5, 6, 7, 8, 9, 10 and 12; Group 2 by Genotype 3; Group 3 by Genotype 2; and Group 4 by Genotype 11. In addition, Genotypes 1, 3–10 and 12 displayed seeds with superior physical and physiological traits and a high probability of genetic gain. Our findings can be used in the selection and marking of trees with a broad genetic base for seed production and plant breeding of this species.Keywords: conservation geneticsphenotypic diversityplant breedingseed character
{"title":"Genetic variability of <i>Tachigali vulgaris</i> trees based on seed morphophysiological traits","authors":"Noemi Vianna Martins Leão, Sérgio Heitor Sousa Felipe, Ricardo Gallo, Elizabeth Santos Cordeiro Shimizu","doi":"10.2989/20702620.2023.2226335","DOIUrl":"https://doi.org/10.2989/20702620.2023.2226335","url":null,"abstract":"AbstractTachigali vulgaris is a tree with high potential for energy purposes in Brazil. However, there is little information about genetic variability that can be applied to plant breeding. Here, we quantified genetic variability based on biometric and emergence traits of T. vulgaris seeds from the native population of the Brazilian Amazon. The biometric aspects, moisture content, emergence, emergence speed index, and average emergence time of the seeds were evaluated. Genotypic values and genetic parameters were analysed using the mixed model methodology in a completely randomised design with 12 genotypes and four replications of 25 seeds. All biometric and emergence traits of seeds showed phenotypic and genetic variabilities. Heritability was high for all traits evaluated (0.66 to 0.97), and genetic accuracy showed high experimental precision and reliable results (≥ 0.90). Grouping by the Tocher, unweighted pair group with arithmetic mean and principal component analysis methods based on genetic traits returned four groups: Group 1 by Genotypes 1, 4, 5, 6, 7, 8, 9, 10 and 12; Group 2 by Genotype 3; Group 3 by Genotype 2; and Group 4 by Genotype 11. In addition, Genotypes 1, 3–10 and 12 displayed seeds with superior physical and physiological traits and a high probability of genetic gain. Our findings can be used in the selection and marking of trees with a broad genetic base for seed production and plant breeding of this species.Keywords: conservation geneticsphenotypic diversityplant breedingseed character","PeriodicalId":21939,"journal":{"name":"Southern Forests: a Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135435705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-02DOI: 10.2989/20702620.2023.2267043
T. Gotore, Sam Bowers, Hilton GT Ndagurwa, S. Kativu, A. Muchawona, P. Mutete, M. Tembani, R. Murepa, A. Mureva, Casey Ryan, Denis Gautier, L. Gazull
Globally, Miombo woodlands store important quantities of carbon, with tree cover and carbon stocks strongly determined by human use. We assessed woodland cover and aboveground carbon (AGC) stocks of miombo along a utilisation gradient on three different land use types, that is, a national park, a buffer zone and a communal area. Woodland cover and carbon stock changes were assessed through mapping of AGC between 2007 and 2017 using Phased Array L-Band Synthetic Aperture Radar observations (ALOS-PALSAR 1 and 2). Woodland cover was higher in the national park and the buffer zone than in the communal area for both 2007 and 2017. In 2007, mean AGC stock was not significantly different (p = 0.05) across all three land use types. However, in 2017, mean AGC was significantly lower (p < 0.001) in the buffer zone and communal area than in the national park. In all three land use types, Miombo woodland cover and mean AGC gains outweighed losses over the 10-year period. AGC gains were significantly higher (p < 0.001) in the national park than in both the buffer zone and the communal area. Results of the study indicate that woodland cover and aboveground carbon increased in all three land use types despite the observed human disturbance over the study period. Both variables recorded a lower increase with elevated utilisation. The study concluded that sustainable resource utilisation is possible without loss of such ecosystem services as carbon sequestration and climate change mitigation.
{"title":"Woody biomass increases across three contrasting land uses in Hurungwe, mid-Zambezi valley, Zimbabwe","authors":"T. Gotore, Sam Bowers, Hilton GT Ndagurwa, S. Kativu, A. Muchawona, P. Mutete, M. Tembani, R. Murepa, A. Mureva, Casey Ryan, Denis Gautier, L. Gazull","doi":"10.2989/20702620.2023.2267043","DOIUrl":"https://doi.org/10.2989/20702620.2023.2267043","url":null,"abstract":"Globally, Miombo woodlands store important quantities of carbon, with tree cover and carbon stocks strongly determined by human use. We assessed woodland cover and aboveground carbon (AGC) stocks of miombo along a utilisation gradient on three different land use types, that is, a national park, a buffer zone and a communal area. Woodland cover and carbon stock changes were assessed through mapping of AGC between 2007 and 2017 using Phased Array L-Band Synthetic Aperture Radar observations (ALOS-PALSAR 1 and 2). Woodland cover was higher in the national park and the buffer zone than in the communal area for both 2007 and 2017. In 2007, mean AGC stock was not significantly different (p = 0.05) across all three land use types. However, in 2017, mean AGC was significantly lower (p < 0.001) in the buffer zone and communal area than in the national park. In all three land use types, Miombo woodland cover and mean AGC gains outweighed losses over the 10-year period. AGC gains were significantly higher (p < 0.001) in the national park than in both the buffer zone and the communal area. Results of the study indicate that woodland cover and aboveground carbon increased in all three land use types despite the observed human disturbance over the study period. Both variables recorded a lower increase with elevated utilisation. The study concluded that sustainable resource utilisation is possible without loss of such ecosystem services as carbon sequestration and climate change mitigation.","PeriodicalId":21939,"journal":{"name":"Southern Forests: a Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139324881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-02DOI: 10.2989/20702620.2023.2251946
Collins Matiza, O. Mutanga, K. Peerbhay, J. Odindi, R. Lottering
The assessment of carbon storage in natural forests is paramount in the ongoing efforts against climate change. While traditional field-based methods for quantifying carbon storage pose challenges, recent advancements in remote sensing and machine learning offer efficient and innovative alternatives. This systematic literature review investigates the latest developments in utilising optical, radar, and light detection and ranging (LiDAR) remote sensing data, coupled with cutting-edge machine learning algorithms, to estimate carbon storage in natural forests. Non-parametric machine-learning algorithms commonly applied to multispectral datasets have emerged as prominent tools for predicting aboveground carbon storage. Nonetheless, accurately assessing forest carbon storage using remote sensing data can be arduous in regions characterised by complex terrain and diverse species where dataset noise may be pronounced. Alternatively, the adoption of freely available optical sensors with moderate resolution has showcased reliability in estimating forest carbon storage. Hence, leveraging the integration of multi-sensor data with machine learning techniques has yielded substantial improvements in the accuracy of carbon storage estimation. This study identifies the most sensitive remote sensing variables that correlate with measurable biophysical parameters, thus highlighting the pivotal role of geospatial technologies in estimating terrestrial aboveground carbon storage. The study also delineates gaps and limitations inherent in current practices, underscoring the need for further investigations in this rapidly evolving field. Through the unification of conventional methods with state-of-the-art technologies, this study contributes to the advancement of accurate and efficient carbon storage assessments. By assuming such a transformative role, this research holds substantial promise in bolstering global climate change mitigation efforts. Ultimately, the purpose of this study was to demonstrate to researchers, policy makers and practitioners the importance of embracing the combined power of remote sensing and machine learning as a tool for safeguarding our natural forests and fight against climate change.
{"title":"A systematic review of remote sensing and machine learning approaches for accurate carbon storage estimation in natural forests","authors":"Collins Matiza, O. Mutanga, K. Peerbhay, J. Odindi, R. Lottering","doi":"10.2989/20702620.2023.2251946","DOIUrl":"https://doi.org/10.2989/20702620.2023.2251946","url":null,"abstract":"The assessment of carbon storage in natural forests is paramount in the ongoing efforts against climate change. While traditional field-based methods for quantifying carbon storage pose challenges, recent advancements in remote sensing and machine learning offer efficient and innovative alternatives. This systematic literature review investigates the latest developments in utilising optical, radar, and light detection and ranging (LiDAR) remote sensing data, coupled with cutting-edge machine learning algorithms, to estimate carbon storage in natural forests. Non-parametric machine-learning algorithms commonly applied to multispectral datasets have emerged as prominent tools for predicting aboveground carbon storage. Nonetheless, accurately assessing forest carbon storage using remote sensing data can be arduous in regions characterised by complex terrain and diverse species where dataset noise may be pronounced. Alternatively, the adoption of freely available optical sensors with moderate resolution has showcased reliability in estimating forest carbon storage. Hence, leveraging the integration of multi-sensor data with machine learning techniques has yielded substantial improvements in the accuracy of carbon storage estimation. This study identifies the most sensitive remote sensing variables that correlate with measurable biophysical parameters, thus highlighting the pivotal role of geospatial technologies in estimating terrestrial aboveground carbon storage. The study also delineates gaps and limitations inherent in current practices, underscoring the need for further investigations in this rapidly evolving field. Through the unification of conventional methods with state-of-the-art technologies, this study contributes to the advancement of accurate and efficient carbon storage assessments. By assuming such a transformative role, this research holds substantial promise in bolstering global climate change mitigation efforts. Ultimately, the purpose of this study was to demonstrate to researchers, policy makers and practitioners the importance of embracing the combined power of remote sensing and machine learning as a tool for safeguarding our natural forests and fight against climate change.","PeriodicalId":21939,"journal":{"name":"Southern Forests: a Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139324187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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