Early growth performance of native and introduced fast growing tree species in wet to sub-humid climates of the Southern region of Costa Rica

2007 ◽  
Vol 242 (2-3) ◽  
pp. 227-235 ◽  
Author(s):  
J.C. Calvo-Alvarado ◽  
D. Arias ◽  
D.D. Richter
2018 ◽  
Vol 2 (6) ◽  
Author(s):  
Tatek Dejene Bekele ◽  
Berhane Kidaneb ◽  
Tinsae Bahirua ◽  
Mihret Semerea ◽  
Kibruyesfa Sisaya ◽  
...  

2021 ◽  
Vol 918 (1) ◽  
pp. 012025
Author(s):  
F G Dwiyanti ◽  
H H Rachmat ◽  
A Susilowati ◽  
I Z Siregar ◽  
K S Yulita

Abstract Enhancing green open spaces in cities and their buffer areas has gained increasing recognition. While creating a more sustainable, liveable, and comfortable environment, green spaces could also provide an effort for plant domestication and conservation. We consider the potential urban greening and conservation action by planting five tree species consisting of one highly valuable and slow-growing species Eusideroxylon zwageri trees from four different origins and four fast-growing species of Duabanga moluccana, Anthocephalus macrophyllus, Duabanga grandifolia, and kayu papaya at the water reserve in suburban Ciherang-Bogor. Growth performance on mortality rate and the average height of the 4.5-year-old planted seedlings were observed to evaluate the adaptability and suitability of the species in the area. The results of mortality rate revealed that E. zwageri seedlings were ranged from 35% (from South Kalimantan) to 50% (from Jambi), while the four fast-growing species were ranged from 14% (Kayu papaya) to 83% (Duabanga moluccana) indicated that the mortality rate for the five species of seedlings planted varied. Whereas, the results of average height showed that E. zwageri seedlings were ranged from 196.15 cm (South Kalimantan) to 332.50 cm (Natuna), and four fast-growing species was ranged from 582.35 cm (Duabanga grandiflora) to 1411.10 cm (Anthocephalus macrophyllus) indicated that planting fast-growing trees in the suburban area is suitable to increase land coverage in a relatively short time, while slow-growing species are more suitable for species preservation purposes.


2019 ◽  
Vol 51 (2) ◽  
pp. 132-143
Author(s):  
Andi Sri Rahayu Diza Lestari ◽  
Yusuf Sudo Hadi ◽  
Dede Hermawan ◽  
Adi Santoso ◽  
Antonio Pizzi

2021 ◽  
Vol 13 (6) ◽  
pp. 3563
Author(s):  
Marianthi Tsakaldimi ◽  
Panagiota Giannaki ◽  
Vladan Ivetić ◽  
Nikoleta Kapsali ◽  
Petros Ganatsas

Pinus nigra is one of the most widely used tree species for reforestation within its geographical distribution, as well as being a potential substitute for other tree species in Central Europe under future climate scenarios. P. nigra is transplanted into the field as two-year or three-year old seedlings because of its relatively low growth rate in the nursery. This study investigated the effects of fertilization programs and shading on P. nigra seedlings, aiming to accelerate early growth, and thus to reduce the nursery rearing time. The experiment (a completely randomized block design) was conducted in an open-air nursery by sowing seeds from Grevena, Northern Greece, in Quick pots filled with peat and perlite in a 2:1 ratio. The seedlings were subjected to two levels of fertilization—5 and 10 g L−1 NPK (30-10-10)—and two shading levels: 50% and 70%. At the ends of the first and second nursery growing season, we recorded the seedlings’ above- and below-ground morphology and biomass data. The results show that the application of all of the treatments produced seedlings which met the targeted quality standards for outplanting. However, the combination of a high fertilization rate and low shading level resulted in seedlings of a higher morphological quality, which is often considered to be an indicator for a successful seedling establishment in the field.


Author(s):  
Jose Carranza-Rojas ◽  
Erick Mata-Montero

In the last decade, research in Computer Vision has developed several algorithms to help botanists and non-experts to classify plants based on images of their leaves. LeafSnap is a mobile application that uses a multiscale curvature model of the leaf margin to classify leaf images into species. It has achieved high levels of accuracy on 184 tree species from Northeast US. We extend the research that led to the development of LeafSnap along two lines. First, LeafSnap’s underlying algorithms are applied to a set of 66 tree species from Costa Rica. Then, texture is used as an additional criterion to measure the level of improvement achieved in the automatic identification of Costa Rica tree species. A 25.6% improvement was achieved for a Costa Rican clean image dataset and 42.5% for a Costa Rican noisy image dataset. In both cases, our results show this increment as statistically significant. Further statistical analysis of visual noise impact, best algorithm combinations per species, and best value of k , the minimal cardinality of the set of candidate species that the tested algorithms render as best matches is also presented in this research.


2020 ◽  
Vol 6 (2) ◽  
pp. 234-238
Author(s):  
Yahya Ahmad Zuhaidi ◽  
Hassan Nor Hasnida ◽  
Loon Ng Tong ◽  
Heng Lai Hong ◽  
Zorkarnain Fauzeyana Ain

2021 ◽  
Vol 33 (1) ◽  
pp. 69-76
Author(s):  
N Mohammad ◽  
M Rajkumar ◽  
K Singh ◽  
NPS Nain ◽  
S Singh ◽  
...  

2001 ◽  
Vol 47 (4) ◽  
pp. 499-511 ◽  
Author(s):  
Gufu Oba ◽  
Inger Nordal ◽  
Nils C. Stenseth ◽  
Jørn Stave ◽  
Charlotte S. Bjorå ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document