Assessing forest products usage and local residents' perception of environmental changes in peri-urban and rural mangroves of Cameroon, Central Africa

(IF2011 = 2.392; CHL = 4.4)info:eu-repo/semantics/publishe

An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia

Time series of satellite sensor data have been used to quantify mangrove cover changes at regional and global levels. Although mangrove forests have been monitored using remote sensing techniques, the use of time series to quantify the regeneration of these forests still remains limited. In this study, we focus on the Matang Mangrove Forest Reserve (MMFR) located in Peninsular Malaysia, which has been under silvicultural management since 1902 and provided the opportunity to investigate the use of Landsat annual time series (1988-2015) for (i) detecting clear-felling events that take place in the reserve as part of the local management, and (ii) tracing back and quantifying the early regeneration of mangrove forest patches after clear-felling. Clear-felling events were detected for each year using the Normalized Difference Moisture Index (NDMI) derived from single date (cloud-free) or multi-date composites of Landsat sensor data. From this series, we found that the average period for the NDMI to recover to values observed prior to the clear-felling event between 1988 and 2015 was 5.9 ± 2.7 years. The maps created in this study can be used to guide the replantation strategies, the clear-felling planning, and the management and monitoring activities of the MMFR.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Spatial analysis of early mangrove regeneration in the Matang Mangrove Forest Reserve, Peninsular Malaysia, using geomatics

Successful mangrove tree regeneration is required to maintain the provision of wood for silviculturally managed mangrove forest areas and to ensure mangrove rehabilitation in disturbed areas. Successful natural regeneration of mangroves after disturbance depends on the dispersal, establishment, early growth and survival of propagules. Focusing on the Matang Mangrove Forest Reserve (MMFR) in Peninsular Malaysia, we investigated how the location of a mangrove forest patch might influence the early regeneration of mangroves after clear-felling events that regularly take place on an approximately 30-year rotation as part of local management. We used Landsat-derived Normalized Difference Moisture Index (NDMI) annual time series from 1988 to 2015 to indicate the recovery of canopy cover during early regeneration, which was determined as the average time (in years) for the NDMI to recover to values associated with the mature forests prior to their clear felling. We found that clear-felled mangrove patches closer to water and/or to already established patches of Rhizophora regenerated more rapidly than those farther away. In contrast, patches located closer to dryland forests regenerated slower compared to patches that were farther away. The study concludes that knowledge of the distribution of water, hydro-period and vegetation communities across the landscape can indicate the likely regeneration of mangrove forests through natural processes and identify areas where active planting is needed. Furthermore, time-series comparisons of the NDMI during the early years of regeneration can assist monitoring of mangrove establishment and regeneration, inform on the success of replanting, and facilitate higher productivity within the MMFR.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Monitoring Matang's Mangroves in Peninsular Malaysia through Earth Observations: A Globally Relevant Approach

Expansion of rotational timber harvesting of mangroves is set to increase, particularly given greater recognition of the economic, societal and environmental benefits. Generic and standardized procedures for monitoring mangroves are, therefore, needed to ensure their long-term sustainable utilisation. Focusing on the Matang Mangrove Forest Reserve (MMFR), Perak State, Peninsular Malaysia, thematic and continuous environmental descriptors with defined codes or units, including lifeform, forest age (years), canopy cover (%), above-ground biomass (Mg ha−1) and relative amounts of woody debris (%), were retrieved from time-series data from spaceborne optical and single/dual polarimetric and interferometric RADAR. These were then combined for multiple points in time to generate land cover and evidence-based change maps according to the Food and Agriculture Organisation (FAO) Land Cover Classification System (LCCS) and using the framework of the Earth Observation Data for Ecosystem Monitoring (EODESM). Change maps were based on a pre-defined taxonomy, with focus on clear cutting and regrowth. Uncertainties surrounding the land cover and change maps were based on those determined for the environmental descriptors used for their generation and through comparison with independent retrieval from other EO data sources. For the MMFR and also for other mangroves worldwide where harvesting is occurring or being considered, a new approach and opportunity for supporting management of mangroves is presented, which has application for future planning of mangrove resources.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Structural characterisation of mangrove forests achieved through combining multiple sources of remote sensing data

Temporal information on mangrove extent, age, structure and biomass provides an important contribution towards understanding the role of these ecosystems in terms of the services they provide (e.g. in relation to storage of carbon, conservation biodiversity), particularly given the diversity of influences of human activity and natural events and processes. Focusing on the Matang Mangrove Forest Reserve (MMFR) in Perak Province, Peninsular Malaysia, this study aimed to retrieve comprehensive information on the biophysical properties of mangroves from spaceborne optical and Synthetic Aperture Radar (SAR) to support better understanding of their dynamics in a managed setting. For the period 1988 to 2016 (29 years), forest age was estimated on at least an annual basis by combining time-series of Landsat-derived Normalised Difference Moisture Index (NDMI) and Japanese L-band Synthetic Aperture Radar (SAR) data. The NDMI was further used to retrieve canopy cover (%). Interferometric Shuttle Radar Topographic Mission (SRTM) X/C-band (2000), TanDEM-X-band (2010–2016) and stereo WorldView-2 stereo (2016) data were evaluated for their role in estimating canopy height (CH), from which above ground biomass (AGB, Mg ha−1) was derived using pre-established allometry. Whilst both L-band HH and HV data increased with AGB after about 8–10 years of growth, retrieval was compromised by mixed scattering from varying amounts of dead woody debris following clearing and wood material within regenerating forests, thinning of trees at ~15 and 20 years, and saturation of L-band SAR data after approximately 20 years of growth. Reference was made to stereo Phantom-3 DJI stereo imagery to support estimation of canopy cover (CC) and validation of satellite-derived CH. AGB estimates were compared with ground-based measurements. Using relationships with forest age, both CH and AGB were estimated for each date of Landsat or L-band SAR observation and the temporal trends in L-band SAR were shown to effectively track the sequences of clearing and regeneration. From these, four stages of the harvesting cycle were defined. The study provided new information on the biophysical properties and growth dynamics of mangrove forests in the MMFR, inputs for future monitoring activities, and methods for facilitating better characterisation and mapping of mangrove areas worldwide.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Citizen science frontiers horseshoe crab population regain at their spawning beach in East Peninsular Malaysia

Carcinoscorpius rotundicauda and Tachypleus gigas may co-exist and share common spawning grounds elsewhere but at Balok (East Coast of Peninsular Malaysia), C. rotundicauda is an understudied species. Neglected as research candidate because of inaccessible spawning grounds, smaller size and less commercial value than T. gigas and also, difficulty to attain from the wild has made C. rotundicauda population status remaining unidentified at Balok. This standpoint drove the present attempt because anthropic activities like structure placement and mining are point-source for runoffs that load sediments into Balok River. While erosion-accretion events have altered Balok River width, the shore sediments in Balok Beach were transitioned between medium-fine and fine sand between years 2012 and 2016. Eventually by year 2016, the C. rotundicauda were depositing 5117 eggs in 91 nests from 200 to 1000 m range along this corridor facing South China Sea. From this yield, C. rotundicauda released 2880 eggs in 56 nests during the Southwest monsoon, 1254 eggs in 19 nests during the Northeast monsoon and 983 eggs in 16 nests during the Inter-monsoon seasons. Though female C. rotundicauda opted to lay their eggs in shallow burrows at lower shorelines, the absence of erosion and substantial silt and clay (>20%) deposition facilitates C. rotundicauda embryogenesis with brief periods of temperature and salinity shocks during day-time falling tides. This encourages C. rotundicauda to emerge with increasing abundance and carry out bi-monthly spawning at Balok Beach. In short, shore restoration initiatives like systematic boat docking, proper disposal of nets and waste and, periodic fish-catching operations were effectively led by the Balok fisher citizen scientist. This successful community joint-cooperation proves that citizen-led caretaking of degraded beaches offers marine life protection and are practical for coastal area management especially at areas where other oviparous animals such as turtles and crocodiles are harboured

Effects of shore sedimentation to tachypleus gigas (Müller, 1785) spawning activity from Malaysian waters

Ripraps, land reclamation and fishing jetty renovation were perturbing Balok Beach shores between the years 2011 and 2013 and visible impacts were scaled using horseshoe crab spawning yields. Initially, placement of ripraps at Balok Beach effectively reduced erosion and created a suitable spawning ground for the horseshoe crab, Tachypleus gigas. However sediments begun to gather on the beach onward year 2012 which increased shore elevation and caused complete shore surface transition into fine sand properties. This reduced sediment compaction and made Balok Beach less favourable for horseshoe crab spawning. During the dry Southwest monsoon, Balok River estuary retains more dense saline water which assists with sediment circulation at the river mouth section. Comparatively, the less dense freshwater during the wet Northeast monsoon channels sediments shoreward. Circa-tidal action that takes place at Balok River sorts the shore sediments to produce an elevated and steep beach. Hence, the reduced number of T. gigas nests and eggs retrieved during year 2013 (after comparing with yield of year 2012) at Balok Beach are indicating impacts from anthropic-caused sedimentation. Models need to be constructed and associated with T. gigas spawning-migration to fully understand sediment transport especially at coastal areas that need or are undergoing nourishment

Weight Prediction for Fishes in Setiu Wetland, Terengganu, using Machine Learning Regression Model

Predicting fish weight holds several essential implications in ecology, such as population assessment, trophic interactions within ecosystems, biodiversity studies of fish communities, ecosystem modelling, habitat evaluation for different fish species, climate change research, and support fisheries management practices. The objective of the studies is to analyse the prediction performance of machine learning (ML) regression models by applying different statistical analysis techniques. This study collected biometric measurements (total length and body weight) for 19 fish families from three locations in Setiu Wetland, Terengganu, captured between 2011 and 2012. The study adopts two regression types: Linear Regression (i.e., Multiple Linear, Lasso, and Ridge model) and Tree-based Regression (i.e., Decision Tree, Random Forest, and XGBoost model). Mean absolute error (MAE), root-mean-square error (RMSE), and coefficient of determination (R2) were used to evaluate performance. The results showed that the proposed ML regression models successfully predicted fish weight in Setiu Wetlands, and the Tree-based Regression model provides more accurate prediction results than the Linear Regression model. As a result, Random Forest is the best predictive model out of the six suggested ML regressions, with the highest accuracy at 96.1% and the lowest RMSE and MAE scores at 3.352 and 0.880, respectively. In conclusion, the use of machine learning is crucial for rapid, precise, and cost-effective fish weight measurement. By incorporating weight prediction into ecological research and management practices, we may make informed decisions supporting the conservation and sustainable use of fish populations and their habitats