scholarly journals Natural and Anthropogenic Variation of Stand Structure and Aboveground Biomass in Niger Delta Mangrove Forests

2021 ◽  
Vol 4 ◽  
Author(s):  
Chukwuebuka J. Nwobi ◽  
Mathew Williams
Keyword(s):  
Aboveground Biomass ◽  
Niger Delta ◽  
Stand Structure ◽  
Oil Pollution ◽  
Negative Impact ◽  
Forest Degradation ◽  
Total Biomass ◽  
Mangrove Forests ◽  
Area Index ◽  
Nipa Palm

Mangrove forests are important coastal wetlands because of the ecosystem services they provide especially their carbon potential. Mangrove forests productivity in the Niger Delta are poorly quantified and at risk of loss from oil pollution, deforestation, and invasive species. Here, we report the most extensive stem girth survey yet of mangrove plots for stand and canopy structure in the Niger Delta, across tidal and disturbance gradients. We established twenty-five geo-referenced 0.25-ha plots across two estuarine basins. We estimated aboveground biomass (AGB) from established allometric equations based on stem surveys. Leaf area index (LAI) was recorded using hemispherical photos. We estimated a mean AGB of 83.7 Mg ha–1 with an order of magnitude range, from 11 to 241 Mg ha–1. We found significantly higher plot biomass in close proximity to a protected site and tidal channels, and the lowest in the sites where urbanization and wood exploitation was actively taking place. The mean LAI was 1.45 and ranged fivefold from 0.46 to 2.41 and there was a significant positive correlation between AGB and LAI (R2 = 0.31). We divided the plots into two disturbance regimes and three nipa palm (Nypa fruticans) invasion levels. Lower stem diameter (5–15 cm) accounted for 70% of the total biomass in disturbed plots, while undisturbed regimes had a more even (∼25%) contribution of different diameter at breast height (DBH) size classes to AGB. Nipa palm invasion also showed a significant link to larger variations in LAI and the proportion of basal area removed from plots. We conclude that mangrove forest degradation and exploitation is removing larger stems (>15 cm DBH), preferentially from these mangroves forests and creates an avenue for nipa palm colonization. This research identifies opportunities to manage the utilization of mangrove resources and reduce any negative impact. Our data can be used with remote sensing to estimate biomass in the Niger Delta and the inclusion of soil, leaf properties and demographic rates can analyze mangrove-nipa competition in the region.

scholarly journals Rapid Mangrove Forest Loss and Nipa Palm (Nypa fruticans) Expansion in the Niger Delta, 2007–2017

2020 ◽  
Vol 12 (14) ◽  
pp. 2344
Author(s):  
Chukwuebuka Nwobi ◽  
Mathew Williams ◽  
Edward T. A. Mitchard
Keyword(s):  
Niger Delta ◽  
Mangrove Forest ◽  
Oil Pollution ◽  
Support Vector ◽  
Coastal Protection ◽  
Mangrove Forests ◽  
Alos Palsar ◽  
Mangrove Area ◽  
Nypa Fruticans ◽  
Nipa Palm

Mangrove forests in the Niger Delta are very valuable, providing ecosystem services, such as carbon storage, fish nurseries, coastal protection, and aesthetic values. However, they are under threat from urbanization, logging, oil pollution, and the proliferation of the invasive Nipa Palm (Nypa fruticans). However, there are no reliable data on the current extent of mangrove forest in the Niger Delta, its rate of loss, or the rate of colonization by the invasive Nipa Palm. Here, we estimate the area of Nipa Palm and mangrove forests in the Niger Delta in 2007 and 2017, using 567 ground control points, Advanced Land Observatory Satellite Phased Array L-band SAR (ALOS PALSAR), Landsat and the Shuttle Radar Topography Mission Digital Elevation Model 2000 (SRTM DEM). We performed the classification using Maximum Likelihood (ML) and Support Vector Machine (SVM) methods. The classification results showed SVM (overall accuracy 93%) performed better than ML (77%). Producers (PA) and User’s accuracy (UA) for the best SVM classification were above 80% for most classes; however, these were considerably lower for Nipa Palm (PA—32%, UA—30%). We estimated a 2017 mangrove area of 801,774 ± 34,787 ha (±95% Confidence Interval) ha and Nipa Palm extent of 11,447 ± 7343 ha. Our maps show a greater landward extent than other reported products. The results indicate a 12% (7–17%) decrease in mangrove area and 694 (0–1304)% increase in Nipa Palm. Mapping efforts should continue for policy targeting and monitoring. The mangroves of the Niger Delta are clearly in grave danger from both rapid clearance and encroachment by the invasive Nipa Palm. This is of great concern given the dense carbon stocks and the value of these mangroves to local communities for generating fish stocks and protection from extreme events.

Distribution and increment of biomass in adjacent young Douglas-fir stands with different early growth rates

1987 ◽  
Vol 17 (7) ◽  
pp. 722-730 ◽  
Author(s):  
Miguel A. Espinosa Bancalari ◽  
David A. Perry
Keyword(s):  
Growth Rates ◽  
Aboveground Biomass ◽  
Early Growth ◽  
Douglas Fir ◽  
Rooting Depth ◽  
Summer Drought ◽  
Total Biomass ◽  
Area Index ◽  
Biomass Increment ◽  
Anaerobic Soils

Total biomass increments were determined for three adjacent 22-year-old Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco) plantations in the Oregon Coast Range that had widely different early growth rates. Estimated total aboveground biomass of the stands, designated slow, intermediate, and fast, was 98.7, 148.7, and 203.7 Mg•ha−1, respectively; estimated mean biomass increment in the 5 years previous to sampling was 8.9, 12.6, and 12.3 Mg•ha−1•year−1. The slow stand had a greater proportion of aboveground biomass in branches and a smaller proportion in stem wood than the intermediate and fast stands. Differences in biomass increment were primarily due to stem rather than crown growth. Total below ground biomass was highest in the fast stand, the difference being due to roots >5 mm in diameter; weight of roots <5 mm was greater in the slow and intermediate stands. Roots >5 mm comprised about 77% of the total root system in those stands and 90% in the fast stand. Increment of roots >5 mm was 2.2, 2.5, and 3.0 Mg•ha−1•year−1 in the slow, intermediate, and fast stands. The ratio of productivity to total leaf nitrogen suggests that nitrogen is a principal limiting resource in the intermediate stand. The fast stand, with a leaf area index 50% greater than the others, is probably limited by light. The slow stand has anaerobic soils during at least part of the year, which may restrict rooting depth and thereby induce water stress during summer drought.

scholarly journals Linking remotely sensed vegetation structure and soil contamination data to monitor oil spill driven degradation in the Niger Delta Mangrove

2020 ◽  
Author(s):  
Matthew Brolly ◽  
Isa Kwabe ◽  
Raymond Ward ◽  
Christopher Joyce
Keyword(s):  
Ecosystem Services ◽  
Soil Contamination ◽  
Oil Spill ◽  
Vegetation Structure ◽  
Niger Delta ◽  
Oil Spills ◽  
Remotely Sensed ◽  
Soil Sampling ◽  
Mangrove Forests ◽  
Area Index

&lt;p&gt;In this study, soil sampling, vegetation analysis, and remotely sensed indices are used to devise a framework for monitoring impact of oil pollution on Mangrove forests. Mangroves are under threat from resource extraction and associated degradation. As a result of their inter-tidal location, Mangroves provide habitat for terrestrial and aquatic organisms and are important components of coastal ecosystems, providing a range of naturally available ecosystem services. Despite the widely accepted and documented range of ecosystem services provided by mangroves, they have nevertheless, experienced a worldwide degradation resulting from various anthropogenic activities including oil exploitation.&lt;/p&gt;&lt;p&gt;This research is conducted in the Niger Delta where the largest spatial extent of Mangrove forests in Africa is located, consisting of 7% of global stock. Hydrocarbon exploitation in the Niger Delta region is one of several resource extractions undertaken in the area and as a result associated environmental pollution has caused a drastic decline in the region&amp;#8217;s biodiversity and ecological resources. Of interest to this study is the effect of associated oil spills on the Mangrove forest ecosystem and their detection.&lt;/p&gt;&lt;p&gt;This study undertook a detailed field exercise over three seasons across the Niger Delta within close proximity to recorded oil spills; as noted in the NOSDRA (National Oil Spill Detection &amp; Response Agency) archive. Soil sampling and laboratory analyses were conducted to establish the level and nature of contamination and supported by complementary vegetation structure analysis evaluating Leaf Area Index (LAI) from ground (LAI2200C) and spaceborne (Landsat archive) systems. Levels of soil contamination were significant with respect to control areas regarding both presence and concentration of heavy metal pollutants (Cr, Mn, Fe, Zn, Pb, Al and Hg). Additionally, negative structural impacts were detected on the local soil via Bulk Density reductions, known to impact soil function, as high as 0.566 g/cm&lt;sup&gt;3&lt;/sup&gt; when comparing control Estuarine with high polluted locations, and Soil Organic Matter (SOM) reductions indicated by a mean percentage difference to the control of 11% for high polluted Fringing locations. These results highlight the immediate harm from spills, with degraded areas visually recorded and validated via ground measurements with mean LAI in high polluted Estuarine locations recording 1.8 higher. Linking vegetation structure in the Mangrove system with soil contamination allows the use of remote sensing to identify areas of degradation and subsequently to model the level and nature of contamination. The correlation between &amp;#160;ground and spaceborne measurements of LAI (eg. r=0.62 p&lt;0.005 for fringing low pollution locations), allows machine learning approaches to be used to model LAI given the presence of contaminants and to provide a framework for supporting the detection and recording of areas at risk. Success will be expanded upon through use of GEDI lidar waveforms in the near future to improve the remotely derived description of forest structure.&lt;/p&gt;

scholarly journals Integrating liana abundance and forest stature into an estimate of total aboveground biomass for an eastern Amazonian forest

2000 ◽  
Vol 16 (3) ◽  
pp. 327-335 ◽  
Author(s):  
Jeffrey John Gerwing ◽  
Damião Lopes Farias
Keyword(s):  
Aboveground Biomass ◽  
Amazon Basin ◽  
Forest Disturbance ◽  
Weighted Average ◽  
Canopy Height ◽  
Total Biomass ◽  
Biomass Equation ◽  
Area Index ◽  
Amazonian Forest ◽  
Live Biomass

This study provides an estimate of aboveground live biomass for an intact eastern Amazonian forest. An allometric regression biomass equation was developed to estimate the aboveground biomass of live lianas. This equation, together with a previously published equation for trees, was then used to estimate the contributions of lianas and trees to the total biomass of forest patches in four stature classes: gap (openings in the canopy of at least 25 m2 with the dominant vegetation < 3 m high), low (3–15 m canopy height), medium (15–25 m canopy height), and high (> 25 m canopy height). Total stand-level biomass was estimated as the weighted average of the stature classes. In 130 ha of surveyed forest, forest stature classes were found in the following proportions: gap phase 8%; low stature 31%; medium stature 44%; and high stature 17%. Total aboveground biomass was found to be three times higher in high stature forest than in low. Liana biomass, however, showed the opposite result, being three times higher in low stature forest. Stand-level aboveground live biomass was estimated at 314 t ha−1 of which 43 t ha−1 (14%) was lianas. Liana leaf area index (LAI) ranged from 1.3 m m−2 in high stature forest to 5.3 m m−2 in low stature. Abundant lianas are generally interpreted as a sign of past forest disturbance. As forests throughout the Amazon basin are increasingly disturbed through human activities, it is likely that their biomass will be underestimated if the contribution of lianas is ignored.

Economic value analysis of mangrove forest ecosystems in Sorong, West Papua Province

2014 ◽  
pp. 39
Author(s):  
Roger R Tabalessy
Keyword(s):  
Mangrove Forest ◽  
Economic Value ◽  
Forest Degradation ◽  
Primary Data ◽  
Mangrove Forests ◽  
Value Analysis ◽  
Human Needs ◽  
The People ◽  
West Papua ◽  
Mangrove Wood

Coastal areas can either meet the human needs or give great contribution to the development. However, rapid infrastrural development in Sorong, west Papua, has been followed by high demand for mangrove timber and caused mangrove forest degradation due to exploitation. This exploitation could also result from high economic value of the mangrove timber. This study was done to analyze the economic value of mangrove wood utilized by the people to support the development process in Sorong. This study used primary data obtained through interviews and the economic value calculation of mangrove forests. It found that Sorong had mangrove economic value of IDR 165,197,833, 491. Wilayah pesisir selain dapat memenuhi kebutuhan hidup manusia juga memberikan kontribusi yang besar bagi pembangunan. Cepatnya pembangunan infrastruktur di Kota Sorong diikuti pula dengan tingginya permintaan akan kayu mangrove dan menyebabkan terjadinya degradasi hutan mangrove akibat eksploitasi. Eksploitasi ini disebabkan juga akibat kayu mangrove memiliki nilai ekonomi. Penelitian yang dilakukan ini bertujuan untuk menganalisis nilai ekonomi kayu mangrove yang dimanfaatkan oleh masyarakat Kota Sorong dalam proses menunjang pembangunan. Penelitian ini menggunakkan data primer yang diperoleh melalui hasil wawancara dan perhitungan nilai ekonomi hutan mangrove. Hasil penelitian ini menunjukkan nilai ekonomi ekosistem hutan mangrove yang berada di Kota Sorong adalah Rp165.197.833.491.

Contrasting yield formation characteristics in two super-rice hybrids that differ in growth duration

2021 ◽  
pp. 1-10
Author(s):  
Min Huang ◽  
Zui Tao ◽  
Tao Lei ◽  
Fangbo Cao ◽  
Jiana Chen ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Biomass Production ◽  
Field Experiments ◽  
Crop Improvement ◽  
Total Biomass ◽  
Growth Duration ◽  
Area Index ◽  
Rice Hybrid ◽  
Use Efficiency ◽  
Yield Formation

Summary The development of high-yielding, short-duration super-rice hybrids is important for ensuring food security in China where multiple cropping is widely practiced and large-scale farming has gradually emerged. In this study, field experiments were conducted over 3 years to identify the yield formation characteristics in the shorter-duration (∼120 days) super-rice hybrid ‘Guiliangyou 2’ (G2) by comparing it with the longer-duration (∼130 days) super-rice hybrid ‘Y-liangyou 1’ (Y1). The results showed that G2 had a shorter pre-heading growth duration and consequently a shorter total growth duration compared to Y1. Compared to Y1, G2 had lower total biomass production that resulted from lower daily solar radiation, apparent radiation use efficiency (RUE), crop growth rate (CGR), and biomass production during the pre-heading period, but the grain yield was not significantly lower than that of Y1 because it was compensated for by the higher harvest index that resulted from slower leaf senescence (i.e., slower decline in leaf area index during the post-heading period) and higher RUE, CGR, and biomass production during the post-heading period. Our findings suggest that it is feasible to reduce the dependence of yield formation on growth duration to a certain extent in rice by increasing the use efficiency of solar radiation through crop improvement and also highlight the need for a greater fundamental understanding of the physiological processes involved in the higher use efficiency of solar radiation in super-rice hybrids.

scholarly journals Detecting Forest Degradation in the Three-North Forest Shelterbelt in China from Multi-Scale Satellite Images

2021 ◽  
Vol 13 (6) ◽  
pp. 1131
Author(s):  
Tao Yu ◽  
Pengju Liu ◽  
Qiang Zhang ◽  
Yi Ren ◽  
Jingning Yao
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Net Primary Production ◽  
Remote Sensing Data ◽  
Forest Degradation ◽  
Observation Data ◽  
Area Index ◽  
Sensing Data ◽  
Multi Scale

Detecting forest degradation from satellite observation data is of great significance in revealing the process of decreasing forest quality and giving a better understanding of regional or global carbon emissions and their feedbacks with climate changes. In this paper, a quick and applicable approach was developed for monitoring forest degradation in the Three-North Forest Shelterbelt in China from multi-scale remote sensing data. Firstly, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Ratio Vegetation Index (RVI), Leaf Area Index (LAI), Fraction of Photosynthetically Active Radiation (FPAR) and Net Primary Production (NPP) from remote sensing data were selected as the indicators to describe forest degradation. Then multi-scale forest degradation maps were obtained by adopting a new classification method using time series MODerate Resolution Imaging Spectroradiometer (MODIS) and Landsat Enhanced Thematic Mapper Plus (ETM+) images, and were validated with ground survey data. At last, the criteria and indicators for monitoring forest degradation from remote sensing data were discussed, and the uncertainly of the method was analyzed. Results of this paper indicated that multi-scale remote sensing data have great potential in detecting regional forest degradation.

scholarly journals Tree height integrated into pantropical forest biomass estimates

2012 ◽  
Vol 9 (8) ◽  
pp. 3381-3403 ◽  
Author(s):  
T. R. Feldpausch ◽  
J. Lloyd ◽  
S. L. Lewis ◽  
R. J. W. Brienen ◽  
M. Gloor ◽  
...  
Keyword(s):  
East Africa ◽  
Carbon Storage ◽  
Stand Structure ◽  
Forest Biomass ◽  
Small Diameter ◽  
Tree Height ◽  
Total Biomass ◽  
Guiana Shield ◽  
Tree Biomass ◽  
Continental Scale

Abstract. Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

Sign in / Sign up

Export Citation Format

Share Document