Table_1_Macrobenthic community of an anthropogenically influenced mangrove associated estuary on the East coast of India: An approach for ecological assessment.xlsx

The Mahanadi Estuarine System (MES), with a complex network of freshwater channels, rivers, and mangroves, is a leading seaport in State Odisha on the east coast of India, but subjected to intense human activity in recent years. Such anthropic impingements are known to impact sediment-dwelling biota adversely. However, information on the macrobenthic community of the MES is not well documented yet. Therefore, the primary objectives of this study (February 2013-March 2017) were to address knowledge gaps on the macrobenthic community structure vis-à-vis local environmental conditions and to evaluate the extent of anthropogenic disturbances on macrobenthos. The results from 264 benthic grab samples (van Veen, 0.04 m2; 2 replicates × 12 GPS fixed locations × 3 seasons) revealed 73 taxa representing 64 genera and 48 families of macrobenthic fauna. The polychaetes (81.41%) and crustaceans (15.42%) were significant faunal groups that contributed mainly to the benthic population and diversity. Multivariate approaches using benthic community attributes and biotic indices (AMBI and M-AMBI) as proxy measures of environmental disturbances proved effective for appraisal. The correlations between the environmental parameters (temperature, pH, salinity) and community estimates were statistically significant. Hierarchical clustering analysis disclosed three major groups (Global R 0.70; p < 0.002) influenced by tolerant/opportunist species. The lower abundance, richness, diversity, and dominance of opportunistic species mark the signs of environmental stress. The community health status remained unbalanced, as indicated by AMBI scoring. M-AMBI analysis contributed best in differentiating areas exposed to diverse impacts and indicated polluted community health status with moderate ecological quality. Our results reiterate the effective use of macrobenthos as bioindicators for ecological status and monitoring. The findings could be utilized for future monitoring assessments, translated into valuable information, and designed into well-defined sustainable management strategies for the MES.</p

Table_2_Macrobenthic community of an anthropogenically influenced mangrove associated estuary on the East coast of India: An approach for ecological assessment.xlsx

The Mahanadi Estuarine System (MES), with a complex network of freshwater channels, rivers, and mangroves, is a leading seaport in State Odisha on the east coast of India, but subjected to intense human activity in recent years. Such anthropic impingements are known to impact sediment-dwelling biota adversely. However, information on the macrobenthic community of the MES is not well documented yet. Therefore, the primary objectives of this study (February 2013-March 2017) were to address knowledge gaps on the macrobenthic community structure vis-à-vis local environmental conditions and to evaluate the extent of anthropogenic disturbances on macrobenthos. The results from 264 benthic grab samples (van Veen, 0.04 m2; 2 replicates × 12 GPS fixed locations × 3 seasons) revealed 73 taxa representing 64 genera and 48 families of macrobenthic fauna. The polychaetes (81.41%) and crustaceans (15.42%) were significant faunal groups that contributed mainly to the benthic population and diversity. Multivariate approaches using benthic community attributes and biotic indices (AMBI and M-AMBI) as proxy measures of environmental disturbances proved effective for appraisal. The correlations between the environmental parameters (temperature, pH, salinity) and community estimates were statistically significant. Hierarchical clustering analysis disclosed three major groups (Global R 0.70; p < 0.002) influenced by tolerant/opportunist species. The lower abundance, richness, diversity, and dominance of opportunistic species mark the signs of environmental stress. The community health status remained unbalanced, as indicated by AMBI scoring. M-AMBI analysis contributed best in differentiating areas exposed to diverse impacts and indicated polluted community health status with moderate ecological quality. Our results reiterate the effective use of macrobenthos as bioindicators for ecological status and monitoring. The findings could be utilized for future monitoring assessments, translated into valuable information, and designed into well-defined sustainable management strategies for the MES.</p

Schematic representation showing the Matang mangrove management system (A); (B) the present observations on <i>Rhizophora apiculata</i> – (a) stem size (D₁₃₀) and, (b) biomass distribution at different forest blocks: (i) VJR: Virgin Jungle Reserve, (ii) MF15: Managed Forest at 15 years old, (iii) MF20: Managed Forest at 20 years old and, MF30: Managed Forest at 30 years old; B (I–II): the computed biomass of <i>R. apiculata</i> after the first and second thinnings.

<p>The green coloured rectangle (dashed box) in B (ii-a to iv-a) shows the expected/required stem size by the State Forestry Department of Perak.</p

Schematic chart showing the century-old mangrove management at the Matang Mangrove Forest Reserve (MMFR) as a global reference for sustainable silviculture.

<p>While the bold-line arrows indicate the features available for Matang (A–B), the dotted-line arrows show the features that could be considered by other mangrove locations for their improved/sustainable mangrove management. Some of the ongoing silvicultural and ecological concerns (C) represented by dotted-arrows, are applicable to the both MMFR and other mangrove locations elsewhere.</p

The distance-based redundancy analysis (dbRDA) showing variations between virgin and managed mangrove forest blocks in relation to their – (A) juvenile, (B) young and, (C) adult vegetation at the Matang Mangrove Forest Reserve.

<p>While density of the juvenile and the young vegetation was estimated for nos. ha⁻¹, the adult tree density was estimated for no. stems ha⁻¹ (VJR: Virgin Jungle Reserve; MF15, MF20 and MF30: Managed Forest blocks at 15, 20 and 30 years old) (circles in all panels represent correlation circles, and the orientation of mangrove species' lines approximate their correlation to the ordination axes).</p

Matang Mangrove Forest Reserve in the state of Perak on the West coast of Peninsular Malaysia (A) (dotted square represents the study zone); (B) Location (yellow circle with red dots) of the Virgin Jungle Reserve (VJR) and the Managed Mangrove Forest (MF with 15, 20 and 30 year old vegetation) blocks considered for silvimetric measurements in the present study (image source: Landsat 7 dated 27 Dec 1999 from the NASA's Earth Observatory).

<p>Matang Mangrove Forest Reserve in the state of Perak on the West coast of Peninsular Malaysia (A) (dotted square represents the study zone); (B) Location (yellow circle with red dots) of the Virgin Jungle Reserve (VJR) and the Managed Mangrove Forest (MF with 15, 20 and 30 year old vegetation) blocks considered for silvimetric measurements in the present study (image source: Landsat 7 dated 27 Dec 1999 from the NASA's Earth Observatory).</p

Adult tree density (stems ha⁻¹) and frequency (%) at Matang Mangrove Forest Reserve.

<p>The values under thinnings I and II are the computed stem density which is likely to be present after the thinning events at MF15 and MF20. VJR is Virgin Jungle Reserve; MF15, MF20 and MF30 are the Managed Forest blocks at 15, 20 and 30 years old. MST is multiple-stemmed tree. Except <i>Rhizophora</i>, all other species encountered during inspection visits and/or thinning operations at the managed forest blocks will be clear-felled.</p><p>*found only at single plot.</p

Density (no. ha⁻¹) and frequency (%) of the juvenile and young vegetation at Matang Mangrove Forest Reserve.

<p>VJR, MF15, MF20 and MF30 are the Virgin Jungle Reserve and the Managed Forest blocks at 15, 20 and 30 years old. Den is density, Freq is frequency.</p

El umbral y el limite: reflexiones sobre el sentido etico-politico de la alteridad en la era global

Satellite data and aerial photos have proved to be useful in efficient conservation and management of mangrove ecosystems. However, there have been only very few attempts to demonstrate the ability of drone images, and none so far to observe vegetation (species-level) mapping. The present study compares the utility of drone images (DJI-Phantom-2 with SJ4000 RGB and IR cameras, spatial resolution: 5cm) and satellite images (Pleiades-1B, spatial resolution: 50cm) for mangrove mapping—specifically in terms of image quality, efficiency and classification accuracy, at the Setiu Wetland in Malaysia. Both object- and pixel-based classification approaches were tested (QGIS v.2.12.3 with Orfeo Toolbox). The object-based classification (using a manual rule-set algorithm) of drone imagery with dominant land-cover features (i.e. water, land, Avicennia alba, Nypa fruticans, Rhizophora apiculata and Casuarina equisetifolia) provided the highest accuracy (overall accuracy (OA): 94.0±0.5% and specific producer accuracy (SPA): 97.0±9.3%) as compared to the Pleiades imagery (OA: 72.2±2.7% and SPA: 51.9±22.7%). In addition, the pixel-based classification (using a maximum likelihood algorithm) of drone imagery provided better accuracy (OA: 90.0±1.9% and SPA: 87.2±5.1%) compared to the Pleiades (OA: 82.8±3.5% and SPA: 80.4±14.3%). Nevertheless, the drone provided higher temporal resolution images, even on cloudy days, an exceptional benefit when working in a humid tropical climate. In terms of the user-costs, drone costs are much higher, but this becomes advantageous over satellite data for long-term monitoring of a small area. Due to the large data size of the drone imagery, its processing time was about ten times greater than that of the satellite image, and varied according to the various image processing techniques employed (in pixel-based classification, drone &gt;50 hours, Pleiades &lt;5 hours), constituting the main disadvantage of UAV remote sensing. However, the mangrove mapping based on the drone aerial photos provided unprecedented results for Setiu, and was proven to be a viable alternative to satellite-based monitoring/management of these ecosystems. The improvements of drone technology will help to make drone use even more competitive in the future

Stepwise protocol and the technical processes involved in drone and satellite remote sensing data analyses for mangrove mapping at the Setiu Wetland.

<p>The 10 ROI sets were named 1A-1B to 5A-5B. Except the manual rule-set algorithm, the remaining algorithms i.e., automatic, maximum likelihood and spectral angle mapping, were used 10 times (10×) for running the object- and pixel-based classification approaches (grey and white shades are for visualization purposes).</p