Patterns of growth, recruitment, mortality and biomass across an altitudinal gradient in a neotropical montane forest, Dominican Republic

2012 ◽  
Vol 28 (5) ◽  
pp. 483-495 ◽  
Author(s):  
Ruth E. Sherman ◽  
Timothy J. Fahey ◽  
Patrick H. Martin ◽  
John J. Battles

Abstract:We examined stand dynamics and biomass along an altitudinal gradient in a tropical montane forest (TMF) in the disturbance-prone Cordillera Central, Dominican Republic. We tested the general hypothesis that chronic disturbance by fire, wind, floods and landslides results in a landscape of relatively low above-ground biomass with high rates of mortality, recruitment and growth as compared with other TMFs. We also expected above-ground biomass to decrease with altitude in part due to declines in growth and increased biomass losses from mortality with increasing altitude. We resurveyed 75 0.1-ha plots distributed across the altitudinal gradient (1100–3100 m asl) 8 y after they were established. Our observations provided mixed evidence on these hypotheses. Turnover rates were high (> 2% y−1) and significantly greater on windward slopes. Above-ground biomass (mean = 306 Mg ha−1, 95% CI = 193–456 Mg ha−1) was highly variable but comparable to other TMFs. Altitudinal patterns of declining biomass and above-ground growth matched observations for other TMFs, whereas mortality and recruitment exhibited no altitudinal trends. More quantitative studies in a variety of TMF settings are needed to better understand how natural disturbance, complex environmental gradients and species dynamics interact to regulate carbon storage, sequestration and turnover across altitudinal gradients in TMFs.

Our Nature ◽  
1970 ◽  
Vol 9 (1) ◽  
pp. 107-111
Author(s):  
D.K. Limbu ◽  
M. Koirala

Rangeland conservation has been increasingly interested for carbon reduction and mitigation of climate change, because of carbon storage. Thus, biomass of the rangeland remains pivotal regarding carbon sequestration on rangeland. Present study was conducted in high altitude rangeland at Jaljale (4000 m), Gorujure (3500 m) and Milke (3000 m) on September, 2010 with an objective to estimate rangeland biomass following the total harvesting method. Result revealed that biomass of high altitude rangeland has relatively high value (1.50 t/ha for both above ground biomass and 43.48 t/ha for below ground biomass) compared to low altitude rangeland (0.35 t/ha for above ground biomass and 16.93 t/ha for below ground biomass). Similarly, monocot plant density play crucial role for biomass contribution of rangeland.DOI: http://dx.doi.org/10.3126/on.v9i1.5740


2014 ◽  
Vol 35 (21) ◽  
pp. 7339-7362 ◽  
Author(s):  
Xin Tian ◽  
Zengyuan Li ◽  
Zhongbo Su ◽  
Erxue Chen ◽  
Christiaan van der Tol ◽  
...  

2017 ◽  
Vol 23 (2) ◽  
Author(s):  
AFSHAN ANJUM BABA ◽  
SYED NASEEM UL-ZAFAR GEELANI ◽  
ISHRAT SALEEM ◽  
MOHIT HUSAIN ◽  
PERVEZ AHMAD KHAN ◽  
...  

The plant biomass for protected areas was maximum in summer (1221.56 g/m2) and minimum in winter (290.62 g/m2) as against grazed areas having maximum value 590.81 g/m2 in autumn and minimum 183.75 g/m2 in winter. Study revealed that at Protected site (Kanidajan) the above ground biomass ranged was from a minimum (1.11 t ha-1) in the spring season to a maximum (4.58 t ha-1) in the summer season while at Grazed site (Yousmarag), the aboveground biomass varied from a minimum (0.54 t ha-1) in the spring season to a maximum of 1.48 t ha-1 in summer seasonandat Seed sown site (Badipora), the lowest value of aboveground biomass obtained was 4.46 t ha-1 in spring while as the highest (7.98 t ha-1) was obtained in summer.


2016 ◽  
Vol 13 (11) ◽  
pp. 3343-3357 ◽  
Author(s):  
Zun Yin ◽  
Stefan C. Dekker ◽  
Bart J. J. M. van den Hurk ◽  
Henk A. Dijkstra

Abstract. Observed bimodal distributions of woody cover in western Africa provide evidence that alternative ecosystem states may exist under the same precipitation regimes. In this study, we show that bimodality can also be observed in mean annual shortwave radiation and above-ground biomass, which might closely relate to woody cover due to vegetation–climate interactions. Thus we expect that use of radiation and above-ground biomass enables us to distinguish the two modes of woody cover. However, through conditional histogram analysis, we find that the bimodality of woody cover still can exist under conditions of low mean annual shortwave radiation and low above-ground biomass. It suggests that this specific condition might play a key role in critical transitions between the two modes, while under other conditions no bimodality was found. Based on a land cover map in which anthropogenic land use was removed, six climatic indicators that represent water, energy, climate seasonality and water–radiation coupling are analysed to investigate the coexistence of these indicators with specific land cover types. From this analysis we find that the mean annual precipitation is not sufficient to predict potential land cover change. Indicators of climate seasonality are strongly related to the observed land cover type. However, these indicators cannot predict a stable forest state under the observed climatic conditions, in contrast to observed forest states. A new indicator (the normalized difference of precipitation) successfully expresses the stability of the precipitation regime and can improve the prediction accuracy of forest states. Next we evaluate land cover predictions based on different combinations of climatic indicators. Regions with high potential of land cover transitions are revealed. The results suggest that the tropical forest in the Congo basin may be unstable and shows the possibility of decreasing significantly. An increase in the area covered by savanna and grass is possible, which coincides with the observed regreening of the Sahara.


2021 ◽  
Vol 21 ◽  
pp. 100462
Author(s):  
Sadhana Yadav ◽  
Hitendra Padalia ◽  
Sanjiv K. Sinha ◽  
Ritika Srinet ◽  
Prakash Chauhan

2020 ◽  
Vol 5 (1) ◽  
pp. 13
Author(s):  
Negar Tavasoli ◽  
Hossein Arefi

Assessment of forest above ground biomass (AGB) is critical for managing forest and understanding the role of forest as source of carbon fluxes. Recently, satellite remote sensing products offer the chance to map forest biomass and carbon stock. The present study focuses on comparing the potential use of combination of ALOSPALSAR and Sentinel-1 SAR data, with Sentinel-2 optical data to estimate above ground biomass and carbon stock using Genetic-Random forest machine learning (GA-RF) algorithm. Polarimetric decompositions, texture characteristics and backscatter coefficients of ALOSPALSAR and Sentinel-1, and vegetation indices, tasseled cap, texture parameters and principal component analysis (PCA) of Sentinel-2 based on measured AGB samples were used to estimate biomass. The overall coefficient (R2) of AGB modelling using combination of ALOSPALSAR and Sentinel-1 data, and Sentinel-2 data were respectively 0.70 and 0.62. The result showed that Combining ALOSPALSAR and Sentinel-1 data to predict AGB by using GA-RF model performed better than Sentinel-2 data.


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