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A dataset of true mangrove records in Sarangani Bay Protected Seascape, Philippines

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The Sarangani Bay Protected Seascape (SBPS) is located in the southern part of Mindanao, Philippines, bordered by Sarangani Province and General Santos City. It is home to a large number of mangrove species, which mostly form narrow fringes and patches of mangrove forests parallel to the shoreline in rocky, sandy, or riverine areas. This resource contains 152 occurrence records of 22 true mangrove species in SBPS.
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Biodiversity Data Journal 11: e100050
doi: 10.3897/BDJ.11.e100050
Research Article
Species richness, extent and potential threats to
mangroves of Sarangani Bay Protected Seascape,
Philippines
Angelo Rellama Agduma , Kun-Fang Cao
State Key Laboratory for Conservation and Utilization of Subtropical Agrobioresources, Guangxi University, Nanning
530004, Guangxi, China
§ Guangxi Key Laboratory of Forest Ecology and Conservation, College of Forestry, Guangxi University, Nanning 530004,
Guangxi, China
| Ecology and Conservation Research Laboratory, Department of Biological Sciences, College of Science and Mathematics,
University of Southern Mindanao, Kabacan 9407, Cotabato, Philippines
¶ Environmental Conservation and Protection Center, Provincial Capitol Compound, Alabel 9501, Sarangani, Philippines
Corresponding author: Angelo Rellama Agduma (geloagduma@gmail.com)
Academic editor: Quentin Groom
Received: 08 Jan 2023 | Accepted: 18 Mar 2023 | Published: 28 Mar 2023
Citation: Agduma AR, Cao K-F (2023) Species richness, extent and potential threats to mangroves of Sarangani
Bay Protected Seascape, Philippines. Biodiversity Data Journal 11: e100050.
https://doi.org/10.3897/BDJ.11.e100050
Abstract
Mangroves form one of the most vital tropical ecosystems that support many species and
surrounding communities. The Sarangani Bay Protected Seascape (SBPS) in the south of
Mindanao Islands in the Philippines is home to a large number of mangrove species, which
have not been fully explored. We updated the list of true mangrove species for SBPS from
10 to 24 by integrating the results of our survey and other past mangrove assessments. A
practical spatial analysis approach was used to estimate the current mangrove forest
extent of SBPS at 514 ha, as compared to 479 ha and 332 ha in 1998 and 2016,
respectively, from other independent reports. Mangrove cover was negatively related to
built area, cropland, bare ground, rangeland and total human population, but positively
related to the number of fishing boats and total tree cover. In addition, we identified other
potential anthropogenic threats to mangroves and categorised them into forest clearing or
deforestation, over-extraction and pollution. The benefits of mangrove cover expansion,
adoption of mangrove-friendly aquaculture and revitalising degraded mangrove forests
‡,§,|,¶ ‡,§
© Agduma A, Cao K. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC
BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are
credited.
outweigh their constraints. Our work provided a locally relevant understanding of the
potential causes of mangrove loss and the values of human actions in mangrove
dynamics, which will contribute to reliable and informed decision-making for the
conservation of mangrove species and restoration of mangrove forests in SBPS.
Keywords
Coastal biodiversity, Mindanao, occurrence, remote sensing, Sarangani, true mangrove
Introduction
Mangroves thrive in saline and anaerobic tidal flats and banks of rivers and seas in tropical
and subtropical coastal zones of the world (Friess et al. 2019). They were once regarded
as useless wastelands (Spalding et al. 1997), but are now being recognised to perform
critical ecosystem processes and provide many ecosystem services. They support the
cycle of nutrients and carbon, help maintain adjacent ecosystems and protect coastal
areas, together with other direct services for the survival and welfare of coastal
communities (Spalding et al. 1997, Hamilton and Friess 2018, Alongi 2020). Despite these
benefits, mangroves continually face a rapid decrease in cover extent and decline in
habitat quality driven by anthropogenic and stochastic threats throughout their range
(Valiela et al. 2001, Gilman et al. 2008, Feller et al. 2010, Polidoro et al. 2010, Donato et al.
2011, Primavera et al. 2016b, Friess et al. 2019, Goldberg et al. 2020). The original
mangrove forests of the world had been reduced by approximately 35% in the twentieth
century and were subjected to a worldwide mean deforestation rate of approximately
2.07% per year (Valiela et al. 2001). About 3.4% loss per year was documented from 1996
to 2020, which was approximately twice that of worldwide gain in mangrove areas (Bunting
et al. 2022). Six of the 10 nations with the highest total areal mangrove loss are in Asia,
including the Philippines (Bryan-Brown et al. 2020). In 1920 the Philippines had 450,000 ha
of mangrove forests but lost about 317,500 ha by 1990 (Primavera 1995). Recent
estimates of Philippine mangrove cover were approximately 256,185 ha in the year 2000
(Long and Giri 2011) and 240,824 ha in 2010 (Long et al. 2014) using Landsat satellite
data, while in 2019, the national mangrove area was estimated at 227,808 ha (Neri et al.
2021) using Sentinel 2-based mangrove vegetation index (MVI) (Baloloy et al. 2020).
However, the Forest Management Bureau of the Department of Environment and Natural
Resources (DENR-FMB) of the Philippines estimated the country’s mangrove cover at
311,400 ha in 2020 (FMB 2021).
The most comprehensive inventory of Philippine mangrove species is probably that of
Primavera et al. (2016a). They identified 33 true mangroves, that is, exclusive to the
intertidal saline zones (Quadros et al. 2021), including Rhizophora x lamarckii, a hybrid of
R. apiculata and R. stylosa. This differs from the earlier report of Fernando and Pancho
(1980) which listed 39 species and one variety, while Calumpong and Meñez (1997)
included 39 species in their account. To date, substantial development in the inventory of
Philippine mangroves has been made. Some species were removed, while others were
2Agduma A, Cao K
renamed or added to the list. For example, Acrostichum spp., Heritiera littoralis and
Excoecaria agallocha were classified as mangrove associates, i.e. non-exclusive to
mangrove forest (Quadros et al. 2021), based on ecological, osmotic and leaf properties
(Wang et al. 2011). Primavera et al. (2004) previously regarded Aegialitis annulata and H.
littoralis as true mangroves, but these are now reclassified, based on the criteria set by
Wang et al. (2011), although E. agallocha has been retained as a true mangrove in the
Philippines (Primavera et al. 2016a). Calumpong and Meñez (1997) did not include
Camptostemon philippinense in their mangrove species list for the Philippines, while
Fernando and Pancho (1980), Primavera et al. (2004) and Primavera et al. (2016a)
included the species in their records. Morphological and molecular evidence shows that
Ceriops decandra and C. zippeliana are distinct species and the latter is the one that is
found in the Philippines (Sheue et al. 2009). Therefore, Primavera et al. (2016a) corrected
the widely known C. decandra in Aklan Panay Province as C. zippeliana.
The Sarangani Bay Protected Seascape (SBPS), located in the southernmost part of
Mindanao Islands in the Philippines, is home to a large number of mangrove species, yet it
is not well-explored. The mangroves of SBPS mostly form narrow fringes and patches
parallel to the shoreline in rocky, sandy or riverine areas. Some grow in between taller
trees such as coconut and other beach forest species and are interspersed with small
houses of coastal dwellers along the shore and mudflats. No detailed taxonomic and
ecological accounts, as well as their distribution, are publicly available for the mangroves in
the area. For example, information on mangrove species diversity in SBPS is limited to
specific mangrove stands and localities only (Mullet et al. 2014, Natividad et al. 2014,
Natividad et al. 2015, Barcelete et al. 2016, Bigsang et al. 2016, Lagnason et al. 2016,
Jumawan 2022). Indeed, the total number of mangrove species in SBPS is unknown,
scattered and unconsolidated. Furthermore, SBPS is not included in the global map of
mangrove extent of Global Mangrove Watch version 3.0 (Bunting et al. 2022). The SBPS
was also missed out on the 2019 Philippine Mangrove Extent Map using the MVI (Baloloy
et al. 2020) due to several limitations (Neri et al. 2021). Moreover, mangroves in SBPS are
not spared from various potential threats which are sparsely documented.
This study aimed to database true mangrove species in SBPS; map the extent of
mangrove forests; and examine the potential threats to mangroves in SBPS. This is to
construct a mangrove diversity profile of SBPS, which will aid in better understanding what
frame the structure, processes and services of the mangrove forests. It will facilitate further
comprehensive studies to reduce the gap in our current understanding of the mangrove
flora in the area and will provide information on the mangrove ecosystem health towards a
well-informed conservation priority and management in SBPS.
Species richness, extent and potential threats to mangroves of Sarangani ... 3
Materials and Methods
Study area
The SBPS is located between 5°33’25” and 6°6’15” N and 124°22’45” and 125°19’45” E in
the south of Mindanao, Philippines, bordered by the Sarangani Province and General
Santos City, hereafter "SarGen" (Fig. 1). The SBPS has a total area of 215, 950 ha and a
coastline of 218.18 km. The climate is monsoonal, with the influences of the northeast
monsoon from November to March and the southwest monsoon from June to October. The
mean annual precipitation is 960 mm and is evenly distributed throughout the year. The
mean annual temperature of the area is 27.85°C, with a mean annual relative air humidity
of 79.38% (Emperua et al. 2018, USAID Oceans 2019). The SBPS sea water has a mean
pH of 8.16 and a mean salinity of 23.80 parts per thousand (ppt). Its mean annual nitrate
content is 0.21 mgl , while its phosphate content is 0.15 mgl (data from Department of
Environment and Natural Resources-Environment Management Bureau, Region 12,
Philippines).
-1 -1
Figure 1.
Occurrence of mangrove species and mangrove cover extent along the coast of Sarangani
Bay Protected Seascape, Philippines. Acor (Aegiceras corniculatum), Aebr (Acanthus ebra-
cteatus), Aflo (Aegiceras floridum), Amar (Avicennia marina), Arum (Avicennia rumphiana),
Bcyl (Bruguiera cylindrica), Bgym (Bruguiera gymnorrhiza), Bsex (Bruguiera sexangula), Cphi
(Camptostemon philippinense), Ctag (Ceriops tagal), Eaga (Excoecaria agallocha), Llit
(Lumnitzera littoralis), Lrac ( Lumnitzera racemosa), Nfru (Nypa fruticans), Paci (Pemphis
acidula), Rapi (Rhizophora apiculata), Rsty (Rhizophora stylosa), Salb (Sonneratia alba), Scas
(Sonneratia caseolaris), Xgra (Xylocarpus granatum), Xmol (Xylocarpus moluccensis) and
Xrum (Xylocarpus rumphii). The georeferenced mangrove distributions are provided in Suppl.
material 1, which can also be accessed through the Global Biodiversity Information Facility
(GBIF) network (Agduma and Cao 2023).
4Agduma A, Cao K
Survey and identification of mangroves
A prior informed consent from the National Commission of Indigenous Peoples, a permit to
study through the Sarangani Bay Protected Seascape Protected Area Management Board
resolution no. 2017-053, s. 2017 and certification control no. SBPS-2017-046 and a
gratuitous permit (no. 284) through the Biodiversity Management Board of the Department
of Environment and Natural Resources, Republic of the Philippines were secured. Only
true or exclusive mangroves following the classification of Primavera et al. (2016a), based
on the criteria of Wang et al. (2011), were the subjects of this study. Primavera et al.
(2016a) identified 33 true mangroves in the Philippines. From this general list, we created
the true mangrove list for SBPS by a complete inventory of mangrove species at known
mangrove sites along the coast of SBPS from January 2018 to December 2019 and June
to October 2022. Additionally, mangrove diversity data from previous surveys (Mullet et al.
2014, Natividad et al. 2014, Natividad et al. 2015, Barcelete et al. 2016, Bigsang et al.
2016, Lagnason et al. 2016, Jumawan 2022) were also used for the list of mangrove
species for SBPS. The conservation status of the mangroves was determined using the
International Union for the Conservation of Nature Red List (IUCN 2022-1) (IUCN 2022).
Furthermore, the national level conservation status of the species was determined
according to the Philippines’ National List of Threatened Flora as specified in the
Department of Environment and Natural Resources Administrative Order No. 2017-11
(DENR 2017).
Mapping mangrove extent, land-use cover and potential threats
We followed a similarly practical approach to mapping mangroves as that of Altamirano et
al. (2010) with modifications to map the extent of mangrove cover on the coastlines of
SBPS. The boundaries of known mangrove sites were initially tracked using a global
positioning system (GPS, Etrex 201x, Garmin Ltd., Kansas, USA) during the mangrove
species surveys. Using the geographical information, the mangrove areas were drawn and
digitised in the Google Earth Pro environment in order to construct the mangrove extent
polygons. To determine the extent of mangrove areas and map mangrove sites detected,
but not visited previously, we compared the characteristics of Google Earth images with
aerial images available from previous studies (e.g. Natividad et al. 2014, Natividad et al.
2015, Barcelete et al. 2016, Bigsang et al. 2016, Lagnason et al. 2016, Baloloy et al. 2020,
Faustino et al. 2020, Neri et al. 2021, Jumawan 2022). From June to October 2022, we
conducted a ground-truth sampling to validate the mangrove layers created and the
suspected mangrove sites based on aerial images. Then, all the mangrove layers were
cleaned and curated. The KML (key-hole mark-up language) versions of the mangrove
layer were imported to QGIS (version 3.26) to measure the extent of the mangrove forests
(ha) and the length (km) of the mangrove extent. The areas and lengths of the mangrove
forests were then measured according to the political boundaries of the coastal areas in
SBPS. A confusion matrix is provided to substantiate the accuracy of the spatial analysis
(overall accuracy = 0.94, Kappa coefficient = 0.88) (Suppl. material 5). Ten-m resolution
land-use/land-cover (LU/LC) data generated from Karra et al. (2021) was used to
determine land-use cover. Using QGIS (WGS 84), the land cover classes, such as trees,
Species richness, extent and potential threats to mangroves of Sarangani ... 5
built areas, crops, bare ground, flooded vegetation, water and rangeland, within each
political boundary were determined. ‘Trees’, hereafter will be called total tree cover, which
refers to “any significant clustering of tall (~ 15 feet or higher) dense vegetation,
typically
with a closed or dense canopy; examples: wooded vegetation, clusters of dense tall
vegetation within savannahs, plantations, swamp or mangroves (dense/tall vegetation with
ephemeral water or canopy too thick to detect water underneath)” (Karra et al. 2021). We
used the land area occupied by built areas, cropland, bare ground and rangeland, derived
above, together with the total human population for the year 2020 (PSA 2021) and the
number of boats (Emperua et al. 2018) in every town or city as proxies of potential threats.
Then, the relationships of mangrove cover to total tree cover and proxies to potential
threats were determined using Spearman’s rho (ρ) correlation in R, version 4.2.2 (R Core
Team 2022). Other perceived potential threats to mangroves were noted during site
surveys.
Results
Status and distribution of mangroves in SBPS
There were 24 true mangroves recorded within SBPS from 10 families and 13 genera
(Table 1). This is approximately 73% of the total true mangroves, 33 species, recorded for
the Philippines (Primavera et al. 2016a). Twenty-two of these were documented in our
survey, while other previous works identified 19 species. We noted additional distribution
records of five species in SBPS in our study, namely Aegiceras corniculatum,
Camptostemon philippinense, Lumnitzera littorea, Rhizophora stylosa and Sonneratia
caseolaris. Three species are listed as threatened on the International Union for
Conservation of Nature Red List (IUCN 2022-1) (IUCN 2022). Camptostemon
philippinense is currently on the Endangered (EN) list, while Avicennia lanata and
Avicennia rumphiana are listed as Vulnerable (VU). Aegiceras floridum is listed as near
threatened (NT), while other remaining species are classified by IUCN as least concern
(LC). The Philippines’ National List of Threatened Flora, specified in the Department of
Environment and Natural Resources Administrative Order No. 2017-11, identified C.
philippinense and Pemphis acidula as the only locally threatened mangroves and are
placed under the EN category, while all other species are classified as Other Wildlife
Species (OWS) (DENR 2017). The OWS is defined as “non-threatened species,
subspecies, varieties or other infraspecific categories that have the tendency to become
threatened due to destruction of habitat or other similar causes” (DENR 2017). The
occurrence and distribution of mangroves are shown in Fig. 1 and Suppl. material 1. They
can also be accessed through the Global Biodiversity Information Facility (GBIF) network
(Agduma and Cao 2023). Representative photographs of mangroves in the study site are
also shown in Fig. 2.
6Agduma A, Cao K
Family Species IUCN DENR ALA GLA KIA MAA MAI MAL GES
Acanthaceae Acanthus ebracteatus Vahl LC OWS 8 5
Acanthaceae Avicennia lanata Ridl. VU OWS 4
Acanthaceae Avicennia marina (Forssk.)
Vierh.
LC OWS 3, 4, 6,
7, 8
1, 8 2, 6,
7, 8
8 1, 5, 8 8
Acanthaceae Avicennia rumphiana Hallier
f
VU OWS 1, 8 8 8 1, 5, 8
Arecaceae Nypa fruticans (Thunb.)
Wurmb.
LC OWS 8 8 8 8 5, 8
Bombacaceae Camptostemon philippinense
(S.Vidal) Becc.
EN EN 8
Combretaceae Lumnitzera littorea (Jack)
Voigt.
LC OWS 8 8
Combretaceae Lumnitzera racemosa Willd. LC OWS 3, 6, 7,
8
8 8 5, 8
Euphorbiaceae Excoecaria agallocha L. LC OWS 8 8 8 5, 8
Lythraceae Pemphis acidula J.R. Forst.
& G. Forst.
LC EN 3, 6, 7,
8
8 6, 7 5, 8
Meliaceae Xylocarpus granatum
J.Koenig
LC OWS 3, 6, 7 8 8 5, 6, 7
Meliaceae Xylocarpus moluccensis
(Lam.) M. Roem.
LC OWS 3, 8 8 8 5
Myrsinaceae Aegiceras corniculatum (L.)
Blanco
LC OWS 8
Myrsinaceae Aegiceras floridum Roem. &
Schult.
NT OWS 3, 4, 6,
7, 8
5, 8
Rhizophoraceae Bruguiera cylindrica (L.)
Blume
LC OWS 3, 6, 7,
8
8 6, 7, 8 5
Table 1.
List of true mangrove species documented in various sites within Sarangani Bay Protected
Seascape, Philippines. The numbers indicate the reference sources: 1: Barcelete et al. (2016), 2:
Bigsang et al. (2016), 3: Jumawan (2022), 4: Lagnason et al. (2016), 5: Mullet et al. (2014), 6:
Natividad et al. (2014), 7: Natividad et al. (2015), 8: This study. Legend: IUCN: Red List of
Threatened Species of the International Union for Conservation of Nature (IUCN 2022-1); DENR:
Department of Environment and Natural Resources Updated National List of Threatened Philippine
Plants and Their Categories (DAO 2017-11); EN: endangered, VU: vulnerable, NT: near-
threatened, LC: least concern, OWS: other wildlife species; Site Codes: ALA: Alabel, GLA: Glan,
KIA: Kiamba, MAA: Maasim, MAI: Maitum, MAL: Malapatan, GES: General Santos City.
Species richness, extent and potential threats to mangroves of Sarangani ... 7
Family Species IUCN DENR ALA GLA KIA MAA MAI MAL GES
Rhizophoraceae Bruguiera gymnorrhiza (L.)
Lam.
LC OWS 3, 6, 7,
8
1 8 2, 6,
7, 8
5
Rhizophoraceae Bruguiera sexangula (Lour.)
Poir.
LC OWS 1 8
Rhizophoraceae Ceriops zippeliana (Griff.)
Ding Hou
LC OWS 3, 6, 7,
8
6, 7 5
Rhizophoraceae Ceriops tagal (Perr.)
C.B.Rob.
LC OWS 3, 4, 6,
7, 8
1, 8 8 1, 8
Rhizophoraceae Rhizophora apiculata Blume LC OWS 3, 4, 6,
7, 8
1, 8 8 2, 6,
7, 8
8 1, 5, 8 8
Rhizophoraceae Rhizophora mucronata Lam. LC OWS 3, 6, 7 2, 6, 7 1, 5
Rhizophoraceae Rhizophora stylosa Griff. LC OWS 8 8 8 8 8 8 8
Sonneratiaceae Sonneratia alba J. Smith LC OWS 3, 4, 6,
7, 8
1, 8 8 2, 8 8 1, 5, 6,
7, 8
8
Sonneratiaceae Sonneratia caseolaris (L.)
Engl.
LC OWS 8 8
Total Species: 24 Species per
town:
18 14 10 15 8 20 4
Mangrove map and cover extent
Fig. 1 shows the mangrove extent map for SBPS, while the measured mangrove cover
extent and length of the mangrove extent of the coastal towns are reflected in Table 2.
Maitum and Glan have the longest extent of mangrove forests with 12.67 km and 11.07
km, respectively. However, Maitum has 60.01% of its coast covered by mangroves, while
only 19% of the shoreline in Glan is covered by mangroves. Almost 68% of the coast of
Alabel is lined by mangrove forests, the highest in the entire SarGen. Of the 40-km
coastline of Kiamba, only 6% of it is occupied by mangroves. In terms of mangrove extent,
Maitum has the largest area, with 138 ha contributing to 26.89% of the total mangrove area
estimated for SBPS, followed by Glan with 129 ha, while General Santos City and Maasim
have the least mangrove extent with 37 ha and 29 ha, respectively. In addition, it was
revealed that Alabel has the largest mangrove area relative to the length of its coast (7.63
ha/km).
Potential threats to mangroves in SBPS
We believe that land-use change plays an important role in mangrove diversity and
distribution. Here, we determined which of the different land-use classifications, based on
the European Space Agency (ESA) Sentinel-2 (Karra et al. 2021), occupy the largest areas
8Agduma A, Cao K
within SarGen (Fig. 3, Suppl. material 2). The largest area is occupied by total tree cover
followed by rangeland. However, cropland and built area are also markedly high, especially
in General Santos City and Alabel. It was revealed that cropland, built area, bare ground,
rangeland and the total human population had negative relationships with mangrove cover,
while the relationships of mangrove cover with the number of fishing boats and total tree
cover were positive. However, all correlations were not statistically significant (Fig. 4,
Suppl. material 3).
Town/City Coastal
Length
(km)
Mangrove
Extent Length
(km)
Mangrove Extent
Length Proportion
(%)
Mangrove
Extent (ha)
Coastal length
corrected mangrove
area (ha/km)
Contribution
(%)
Alabel 10.24 6.93 67.66 78.11 7.63 15.20
General
Santos
28.30 3.95 13.95 36.85 1.30 7.17
Figure 2.
Mangrove forest types and some mangrove species in Sarangani Bay Protected Seascape,
Philippines, Left (mangrove forest types): Top - Rocky; Middle - Sandy; Bottom - Basin, Right
(mangroves): Top - Bruguiera cylindrica; Middle - Rhizophora stylosa; Bottom - Sonneratia
alba.
Table 2.
Measured coastal length, mangrove extent and extent length of different coastal towns surrounding
the Sarangani Bay Protected Seascape, Philippines.
Species richness, extent and potential threats to mangroves of Sarangani ... 9
Town/City Coastal
Length
(km)
Mangrove
Extent Length
(km)
Mangrove Extent
Length Proportion
(%)
Mangrove
Extent (ha)
Coastal length
corrected mangrove
area (ha/km)
Contribution
(%)
Glan 59.60 11.07 18.57 128.76 2.16 25.05
Kiamba 39.96 2.56 6.40 37.24 0.93 7.24
Maasim 41.39 3.12 7.55 29.40 0.71 5.72
Maitum 21.11 12.67 60.01 138.21 6.55 26.89
Malapatan 17.58 9.11 51.80 65.46 3.72 12.74
SBPS
(Total)
218.18 49.40 22.64 514.03 2.36 100.00
Note: Bold numbers emphasise the highest record for each item amongst coastal towns.
Moreover, the observed potential anthropogenic threats to mangroves in SBPS were
classified into: (1) forest clearing, (2) over-extraction and (3) pollution. Clearing of
mangrove forests in SBPS makes way for the construction of commercial establishments,
canneries, residential settlements, aquaculture ponds (shrimp and fish), agriculture
production (rice, corn and coconut), tourism and recreation and infrastructure (roads,
bridges, ports, fishing wharves etc.). Additionally, the inhabitants of the area extract
mangroves for fuelwood, charcoal and timber and as ornamental plants ('bonsai'). Potential
pollution of seawater threatens mangroves as well from oil, solid wastes, silt, pesticides,
Figure 3.
Land-use/land-cover proportions in every town/city around Sarangani Bay Protected
Seascape, Philippines.
10 Agduma A, Cao K
fertilisers, effluents from aquaculture, livestock, domestic and urban areas and smoke from
charcoal production.
Discussion
Mangrove species richness
The primary aim of this work was to generate a list of true mangrove species for SBPS by
integrating the results of our survey and previous reports. Ten species were reported by de
Jesus et al. (2001) and Alcala et al. (2008) along Sarangani Bay (Glan, Malapatan, Alabel,
General Santos City and a portion of Maasim), but only eight of these were exclusive to the
mangrove ecosystem (Primavera et al. 2016a). Subsequent works focused only on specific
mangrove stands and localities along the coast of SBPS (Sarangani Bay plus the
remaining parts of Maasim, Kiamba and Maitum). We summarised the species and their
distribution in the coastal areas that line SBPS, based on publicly available assessments
Figure 4.
Relationship (Spearman’s ρ) of mangrove cover with total tree cover and some potential
threats to mangroves in Sarangani Bay Protected Seascape, Philippines.
Species richness, extent and potential threats to mangroves of Sarangani ... 11
(Mullet et al. 2014, Natividad et al. 2014, Natividad et al. 2015, Barcelete et al. 2016,
Bigsang et al. 2016, Lagnason et al. 2016, Jumawan 2022) and our survey (Table 1).
Mullet et al. (2014) documented 13 true mangroves in Malapatan and reported for the first
time A. rumphiana, Bruguiera cylindrica, B. gymnorrhiza, Xylocarpus granatum, X.
mollucensis and Nypa fruticans in SBPS, which are important additions to the list.
Natividad et al. (2014) and Natividad et al. (2015) evaluated selected sites in Maasim and
Alabel and reported 12 species that added Ceriops tagal and L. racemosa to the SBPS
mangrove list. Lagnason et al. (2016) noted six mangroves, including A. lanata, in Kawas
Marine Sanctuary in Alabel. However, this species had never been previously reported in
the area and the Philippines lies outside its distribution range as previously reported (Chua
1998). Approximately the same year, Barcelete et al. (2016) and Bigsang et al. (2016)
studied mangroves at other sites and the former documented another new species record
for SBPS, B. sexangula, in Glan. Furthermore, Jumawan (2022) reported the same species
as that of Natividad et al. (2014) and Natividad et al. (2015), but with one addition, X.
mollucensis, in Alabel, whereas five true mangrove species were newly reported by the
present survey in SBPS. Therefore, the cumulative true mangrove species tally for SBPS
increased to 24 species from previous studies and our data. The highest true mangrove
species richness was documented in Malapatan and Alabel, while General Santos City had
the lowest mangrove record of species.
Previous studies of Jumawan (2022) and Mullet et al. (2014) reported C. decandra in
SBPS, particularly in Alabel and Malapatan, while we found samples of the species in
Alabel only. Additionally, Natividad et al. (2014)and Natividad et al. (2015) found the
species, along with B. cylindrica and P. acidula, outside of their sampling plots. However, it
is not clear at which study site, Alabel or Maasim, they were found; hence, we added the
three species to the Alabel as well as to the Maasim list. Ceriops zippeliana is found in the
Malay Peninsula, Singapore, Bintan Island, Thailand, Vietnam, Borneo, Java, Sulawesi,
Lesser Sunda Islands, Moluccas and the Philippines, while C. decandra occurs in India,
Bangladesh, Myanmar and Thailand (Sheue et al. 2009). Consequently, Primavera et al.
(2016a) updated the name of C. decandra to C. zippeliana in their book, Mangroves and
Beach Forest Species in the Philippines. This misidentification is not surprising because
the two species closely resemble each other, based on recent morphological and
phylogenetic analyses (Ruang-areerate et al. 2022). Therefore, this study also updates the
name of C. decandra in SBPS to C. zippeliana, until the emergence of further evidence
that will prove otherwise. The new species distribution records for SBPS were found in
Kiamba, Maitum, Maasim and Malapatan. Aegiceras corniculatum thrives abundantly in a
riverine/estuarine mangrove forest in Nalus, Kiamba, while a mangrove site in Kiambing,
Maitum is a sanctuary for S. caseolaris. On the other hand, a small population of L. littorea
grows in Tinoto, Maasim, as well as in Pananggalon, Poblacion, Malapatan together with
the endangered C. philippinense. Remarkably, none of the previous surveys recorded R.
stylosa. We found that this species is one of the most widespread taxa in SBPS along with
R. apiculata and Sonneratia alba. Furthermore, most of the previous studies identified R.
mucronata at their study sites. These recent findings support the call for more
comprehensive surveys on mangrove diversity in SBPS clarifying the identity and
distribution of A. lanata, C. zippeliana, R. stylosa and R. mucronata. The possibility that
12 Agduma A, Cao K
new species, new distribution records and other amendments to our species list (Table 1)
are expected in future studies.
Mangrove areal extent
Bunting et al. (2022) found that the extent of mangroves in the Philippines decreased by
7,934 ha between 1996 and 2020. However, in this global map of mangrove extent, the
mangroves in SBPS were not included. The MVI developed by Baloloy et al. (2020), which
was used to generate the 2019 Philippine Mangrove Extent Map, also missed the
mangroves in SBPS (Neri et al. 2021). Some structural and environmental constraints
affect the detectability of mangroves with remote sensing models. For example, the sparse
canopy and short stature of mangroves relative to other trees cause their limited visibility
(Hickey and Radford 2022). The mangroves in SBPS form narrow fringes and small
patches of stands (Fig. 5), while some grow in between houses of dwellers and taller trees
along the coast. Tidal inundation can also affect the spectral signatures of the mangroves
(Neri et al. 2021) such that the spectra of the mangroves and the water during high tide are
the same (Hu et al. 2020).
The coastal areas of SarGen have gone through rapid changes over the years (de Jesus et
al. 2001, Cabigas et al. 2012). There is approximately 514 ha of mangroves in SBPS
following our estimate, in which the most extensive mangrove areas are on the east coast
(Table 2). More than 60% of these are found in Glan, Malapatan, Alabel and General
Figure 5.
Examples of (A) fringing and (B) patchy mangrove forests in Sarangani Bay Protected
Seascape, Philippines.
Species richness, extent and potential threats to mangroves of Sarangani ... 13
Santos City, while nearly 40% are on the west coast. Fig. 6 compares mangrove forests in
different areas within SBPS using previous independent reports. The mangrove cover in
SBPS was estimated in 1998 at 479 ha as such Maasim was lined by 152 ha of mangrove
forests, the highest amongst all municipalities at that time (de Jesus et al. 2001). While in
2016, the mangrove forest cover of SBPS dropped to 332 ha (USAID Oceans 2019) and,
in Maasim, it heavily shrank to only 29.73 ha 18 years later. Our estimate is also higher
than the data presented by the DENR-FMB with 171 ha in the year 2010 (FMB 2012) and
328 ha in the year 2020 (FMB 2021). There are no mangrove cover data for General
Santos City in these FMB reports. We used the data for South Cotabato since the city was
part of the congressional representation of South Cotabato Province until 14 September
2021 and was the only coastal city of the Province.
No mangrove cover data were reported in Maitum in 1998 (de Jesus et al. 2001). In our
measurement, Maitum has the largest area of mangrove forests within SBPS with 138 ha,
a significant increase from only 28 ha recorded in 2016 (USAID Oceans 2019). Glan’s
mangrove cover increased to 129 ha from 103 ha six years earlier. However, the extent of
mangroves in Maasim, Kiamba and General Santos City did not change substantially from
2016 to 2022. Furthermore, these three areas have a low proportion of mangrove extent
lengths in relation to the length of their coasts. Currently, the total extent of mangroves of
SBPS has been estimated 35.46% higher than six years ago (Fig. 6, Suppl. material 4).
Figure 6.
Total mangrove cover of every coastal town/city that surrounds the Sarangani Bay Protected
Seascape, Philippines.
14 Agduma A, Cao K
This increase may be attributed to massive mangrove reforestation by the government,
various civil society groups and other stakeholders (Gubalani 2021, Jumangit 2022) and
community-based programmes that support sound coastal resource management (Calva
2018).
Anthropogenic activities and threats
The growth and density of the human population adversely affect mangrove forests. The
more people living in or near mangroves, the more anthropogenic impacts on the forests
there will be (Alongi 2002). Rapid loss and degradation of forest cover have been reported
in many mangrove ecosystems in large cities around the world (Branoff 2017). On the
contrary, the fragmented mangrove forests in urban areas of Penang, Malaysia had more
species and trees than the mangrove forests in rural areas. Around 40% of the total
mangrove cover in 1990 was lost by 2000 in the Greater Bay Area of Guangdong, Hong
Kong and Macao, mainly attributed to the increase in aquaculture ponds and built-up
areas. However, it was observed that the mangrove area at the same site almost tripled
after 18 years of conservation and restoration (Wang et al. 2021). Thus, mangrove forest
structure is strongly determined by human actions and people can become partners in
forest management (Walters 2004). Total tree cover is a rudimentary measure of
environmental integrity. All else being equal, it may also indicate the capability and
willingness of a political area to protect its natural environment, for example, in Tanalgo et
al. (2022). A positive correlation between total tree cover and mangrove cover implies that,
while forest trees are protected, mangrove deforestation is also prevented. The highest
total tree cover and mangrove cover were in Maitum and Glan; therefore, they probably
have the strictest regulations when it comes to protecting their biodiversity, while General
Santos City and Maasim were low in both. General Santos City is leading in terms of
economic growth in SarGen and, thus, the most able amongst areas to protect its natural
environment. However, its mangrove forest cover remains low (Fig. 6, Suppl. material 4)
while urban expansion continues. Fortunately, the city has been acting recently to protect
and stabilise its shores (CMGC 2019, DENR 2021). While the mangrove and total tree
covers of Alabel and Malapatan were relatively lower than in other municipalities, their
proportions of mangrove forest extents relative to their coastal lengths were highest,
indicating active and successful mangrove forest protection programmes implemented
within their respective coastal territories.
We found that the number of boats in SBPS was positively correlated with the total
mangrove area (Fig. 4, Suppl. material 3). Camacho and Bagarinao (1986) also showed
that mangrove cover was directly related to the number of fish landings, highlighting the
support value of mangroves for local fisheries (Rönnbäck 1999). With increased mangrove
cover, more economically important fishes and invertebrates thrive in the area and more
local people are encouraged to venture into fishing. However, with a growing number of
fishermen, fish catch also decreases (Santos et al. 2017). To compensate, the human
population looks for alternatives to meet its consumption needs. Agriculture and
aquaculture seem to be amongst the plausible solutions to reduce the gap between food
supply and demand (Hashim et al. 2021), putting more pressure on mangrove ecosystems.
Species richness, extent and potential threats to mangroves of Sarangani ... 15
Indeed, changes in land-use and -cover are amongst the strong forces driving mangrove
forest loss in the world (Bunting et al. 2022), but differ in magnitude from country to country
(Goldberg et al. 2020). It can lead to the failure to deliver ecosystem services and turn
them from carbon (C) sinks to carbon sources contributing to global climate change
(Donato et al. 2011, Alongi 2020, Harishma et al. 2020, Sasmito et al. 2020). Being at the
interface of land and sea (Kumari et al. 2020) with large amounts of organic matter in their
soils (Hossain and Nuruddin 2016), mangrove forests are a perfect place for agriculture
and aquaculture production (Garcia et al. 2014). In Myanmar, rice cultivation has been an
important driver of the decline in mangrove areas, while in Indonesia and Malaysia, the
expansion of oil palm plantations resulted in the decrease of mangrove forest areas,
whereas all of these activities have largely been held responsible for mangrove forest
clearing in the Philippines (Richards and Friess 2016). In SBPS, onshore crops cultivated
are mainly rice, corn and coconut. However, aquaculture farms, particularly for shrimp, are
more widespread in the area. The worldwide loss of mangrove to aquaculture conversion
between the 1970s, when the aquaculture industry started to flourish (Hashim et al. 2021)
and 2009 was estimated at 544,000 ha or 28% of the total areal mangrove loss (Hamilton
2013), while 90% of the reported mangrove forest losses in the south and southeast Asia
were caused by agriculture and shrimp farm developments (DasGupta and Shaw 2013).
The aquaculture industry in SarGen is expanding even more. From 8000 metric tonnes in
2016, shrimp production in the area grew to 12,000 metric tonnes in 2018 from 850 ha
operated by at least 35 growers and companies. Further expansion has been pushed to
meet the increasing global demand (PNA 2018). This attempt poses additional potential
threats to SBPS waters. Substances for soil and water treatment, such as lime and zeolite,
growth inhibitors, such as antibiotics, disinfectants, pesticides and algicides and growth
promoters including fertilisers, added vitamins and minerals in feeds are some of the
chemicals used in shrimp farms in the Philippines (Primavera et al. 1993, Primavera 2006).
Notwithstanding the unwanted effects of growth inhibitors on biodiversity and the
environment (Chen et al. 2018, Olsvik et al. 2019, Pepi and Focardi 2021), fertilisers and
other growth enhancers from aquaculture and agriculture sources cause eutrophication
which leads to unwarranted algal growth, depleting oxygen, reducing water quality and
endangering aquatic life (Streicher et al. 2021, Jwaideh et al. 2022). Moreover, wood
smoke emission from charcoal production is one of the potential threats to mangroves
observed in SBPS. Smokes have a high concentration of ethylene (Morgott 2015) which
may cause physiological impairments, such as reduction of photosynthesis (Calder et al.
2010), induction of senescence and necrosis leading to plant death (Iqbal et al. 2017).
Small-time charcoal factories were observed inside and nearby mangrove forests in some
localities, which not only released smoke, but also had mangrove deforestation
implications. A die-off of 40 trees of S. alba (Fig. 7) and one A. marina, making up an area
of approximately 4,802 m in Kawas, Alabel, Sarangani Province took place in July 2018.
We observed that only a specific portion of the forest was affected and it occurred on the
upper part of the trees first and then progressed down. The possibility that the water
quality, substrate characteristic, climatic condition, pesticide, insect infestation or disease
as the cause of the die-off were excluded. However, about 25 m away from the back of the
mangrove forest, a coconut shell charcoal factory was operating during night-time only,
according to the residents. Thus, this defoliation event could be attributed to excessive
2
16 Agduma A, Cao K
smoke exposure coming from the nearby charcoal processing plant. Other observable
evidence was the dying-off of the bananas around the factory, as well as the observable
soot particles that were sticking to the bark of the mangroves.
Mangrove-friendly approaches
To minimise mangrove loss problems, the adoption of an integrated mangrove-aquaculture
production system known as silvoaquaculture or silvofisheries seems promising. It is a
mangrove-friendly alternative to aquaculture pond development that can sustain not only
productivity and livelihood, but also the conservation of mangrove ecosystems (Primavera
et al. 2000, Susilo et al. 2018). It is a low-input farming system, which is mainly based on
the harmonious interactions of marine and terrestrial resources (Udoh 2016) that form the
biophysical condition of the mangrove forest. It was initially developed in Myanmar and
later introduced in Indonesia in 1978 (Fitzgerald 2000, Takashima 2000). Although it has a
few restrictions, other countries have embraced it and later introduced various models,
including Nigeria (Akinrotimi et al. 2011, Udoh 2016), Malaysia, Philippines and Thailand
(Primavera et al. 2000, Tanan and Tansutapanich 2000). In addition, utilising unproductive
and abandoned aquaculture ponds for mangrove reforestation is another viable option
(Wang et al. 2021), since they mostly lie in areas where mangroves had grown in the past
(Stevenson et al. 1999). This strategy already worked in privately-owned abandoned
fishponds of the Mallare clan in Nalus, Kiamba, Sarangani Province. The owners let the
fishponds turn into a mangrove forest, now known as Mallare Mangroves. Today,
mangroves thrive well in the area and the forest cover continues to expand, filling empty
ponds with native mangroves. It is currently being established as a mangrove eco-park to
help raise awareness of the socio-ecological importance played by mangroves and provide
Figure 7.
Defoliated Sonneratia alba trees (Photo © MENRO, Alabel, Sarangani Province).
Species richness, extent and potential threats to mangroves of Sarangani ... 17
additional income for the local communities surrounding the mangrove site. The same has
also been implemented in Leganes, Ilo-ilo, Philippines, now known as Katunggan Park, for
the mitigation of climate change and has later become a tourist and learning destination as
the result of the community-based mangrove rehabilitation programme of the local
government unit of Leganes and Zoological Society of London-Philippines (Mayuga 2017).
This work generated the first comprehensive and current list of mangrove species diversity
and a mangrove extent map for SBPS in the southern Philippines. Due to the sparse
stature of the mangroves and patchy and fringing nature of the mangrove forests in SBPS,
they are difficult to map using previously developed remote sensing models (Baloloy et al.
2020, Neri et al. 2021). Consequently, mangroves of SBPS are not receiving appropriate
conservation attention compared to other mangrove forests in the country. Yet, a simple
and practical method allowed us to provide valuable information about the mangrove areal
extent in SBPS. Additionally, although we did not explore the degree of impacts of specific
threats, we have provided a preview of potential threats to the mangroves of SBPS,
particularly forest clearing, over-extraction and pollution. In-depth exploration addressing
such a limitation is warranted for future research. Furthermore, we highlighted the value of
expanding mangrove cover, the potential of mangrove-friendly aquaculture and the
reforestation of degraded lands. To implement these successfully, we underscored the
importance of understanding the causes of mangrove loss and the roles humans play in
the dynamics of mangrove forest structure. These substantial results filled the knowledge
gap about mangroves to guide future policies on the conservation and management of
mangrove ecosystems within SBPS.
Data resources
The georeferenced mangrove distributions can be accessed through the Global
Biodiversity Information Facility (GBIF), https://doi.org/10.15468/pz5yp6 (Agduma and Cao
2023).
Acknowledgements
We thank the editors and the three anonymous reviewers for their insighful comments and
suggestions that improved the quality of the manuscript. We also thank all local
government units and key offices of Sarangani Province and various levels of management
and bureaus of the Department of Environment and Natural Resources of the Republic of
the Philippines. Other private and public institutions and individuals who generously
supported this study are also gratefully acknowledged.
Author contributions
ARA and KFC conceived the original idea and contributed to the design of the research.
ARA gathered the data, performed the analysis and wrote the first draft of the manuscript.
18 Agduma A, Cao K
KFC aided in the interpretation of the results and provided critical feedback to the
manuscript. ARA and KFC discussed and agreed to the final draft of the manuscript
References
Agduma A, Cao K (2023) A dataset of true mangrove records in Sarangani Bay
Protected Seascape, Philippines. Biodiversity Data Journal https://doi.org/10.15468/
pz5yp6
Akinrotimi OA, Abu OM, Aranyo AA (2011) Transforming aquaculture from subsistence
to commercial level for sustainable development in Niger Delta Region of Nigeria.
Journal of Agriculture and Social Research 11 (2): 2233. https://doi.org/10.4314/
jasr.v11i2
Alcala A, Ingles J, Bucol A (2008) Review of the biodiversity of southern Philippine seas.
The Philippine Scientist 45: 161. https://doi.org/10.3860/psci.v45i0.991
Alongi D (2002) Present state and future of the world's mangrove forests.
Environmental Conservation 29: 331349. https://doi.org/10.1017/S0376892902000231
Alongi D (2020) Carbon cycling in the world’s mangrove ecosystems revisited:
Significance of non-steady state diagenesis and subsurface linkages between the forest
floor and the coastal ocean. Forests 11 (977): 117. https://doi.org/10.3390/f11090977
Altamirano J, Primavera J, Banaticla MR, Kurokura H (2010) Practical techniques for
mapping small patches of mangroves. Wetlands Ecology and Management 18 (6):
707715. https://doi.org/10.1007/s11273-010-9190-2
Baloloy A, Blanco A, Sta. Ana R, Nadaoka K (2020) Development and application of a
new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping.
ISPRS Journal of Photogrammetry and Remote Sensing 166: 95117. https://doi.org/
10.1016/j.isprsjprs.2020.06.001
Barcelete RC, Palmero EM, Buay BM, Apares CB, Dominoto LR, Apares C, Lipae H,
Cabrera LM, Torres MA, Requieron EA (2016) Species diversity and above-ground
carbon stock assessments in selected mangrove forests of Malapatan and Glan,
Sarangani Province, Philippines. Journal of Biodiversity and Environmental Sciences 8
(2): 265274.
Bigsang RT, Agonia NB, Toreta CG, Nacin CJ, Obemio CD, Martin TT (2016)
Community structure and carbon sequestration potential of mangroves in Maasim,
Sarangani Province, Philippines. AES Bioflux 8 (1): 613.
Branoff B (2017) Quantifying the influence of urban land use on mangrove biology and
ecology: A meta-analysis. Global Ecology and Biogeography 26 (11): 13391356.
https://doi.org/10.1111/geb.12638
Bryan-Brown D, Connolly R, Richards D, Adame F, Friess D, Brown C (2020) Global
trends in mangrove forest fragmentation. Scientific Reports 10 (1): 7117. https://doi.org/
10.1038/s41598-020-63880-1
Bunting P, Rosenqvist A, Hilarides L, Lucas R, Thomas N, Tadono T, Worthington T,
Spalding M, Murray N, Rebelo L (2022) Global mangrove extent change 1996-2020:
Global mangrove watch version 3.0. Remote Sensing 14 (15): 3657. https://doi.org/
10.3390/rs14153657
Species richness, extent and potential threats to mangroves of Sarangani ... 19
Cabigas RB, Manzano LL, Nobukazu N (2012) Success and failure of marine protected
area management affecting the fish catch by adjacent fishermen in Sarangani Bay,
Mindanao, Philippines. South Pacific Studies 33 (1): 123.
Calder WJ, Lifferth G, Moritz M, St. Clair S (2010) Physiological effects of smoke
exposure on deciduous and conifer tree species. International Journal of Forestry
Research17. https://doi.org/10.1155/2010/438930
Calumpong H, Meñez EG (1997) Field guide to the common mangroves, seagrasses
and algae of the Philippines. Bookmark, 19 pp. [ISBN 978-971-569-197-0]
Calva JC (2018) Community-based organizations: Role on coastal resource
management in the Sarangani Bay area. Journal of Health Research and Society 1:
516.
Camacho AS, Bagarinao T (1986) Impact of fishpond management on the mangrove
ecosystem in the Philippines. In: Mangroves of Asia and the Pacific: Status and
management. Natural Resources Management Center and National Mangrove
Committee, Ministry of Natural Resources, Quezon City, Metro Manila. pp. 383405.
URL: https://repository.seafdec.org.ph/handle/10862/260
Chen X, Lai C, Wang Y, Wei L, Zhong Q (2018) Disinfection effect of povidone-iodine in
aquaculture water of swamp eel (Monopterus albus). PeerJ 6 (e5523). https://doi.org/
10.7717/peerj.5523
Chua LS (1998) Avicennnia lanata. The IUCN Red List of Threatened Species 1998:
e.T31819A9662485. https://doi.org/10.2305/IUCN.UK.1998.RLTS.T31819A9662485.en
CMGC (2019) SHEC initiates mangrove tree planting 2019. Citra Mina Group of
Companies. URL: https://www.citraminagroup.com/index.php/shec-initiates-
mangrovetree- planting-2019/
DasGupta R, Shaw R (2013) Cumulative impacts of human interventions and climate
change on mangrove ecosystems of south and southeast Asia: An overview. Journal of
Ecosystems 379429: 115. https://doi.org/10.1155/2013/379429
de Jesus EA, Diamante-Fabunan DA, Nañola CL, White AT, Cabangon H (Eds) (2001)
Coastal environmental profile of the Sarangani Bay area, Mindanao, Philippines.
Coastal Resource Management Project, Cebu City Philippines, 102 pp.
DENR (2017) DENR Administrative Order No. 17-11: Updated national list of threatened
Philippine plants and their categories. Department of Environment and Natural
Resources, Quezon City, Philippines.
DENR (2021) CENRO-Gensan conducts mangrove planting. Department of
Environment and Natural Resources, Philippines. URL: https://r12.denr.gov.ph/
index.php/news-events/photo-releases/1404-cenro-gensan-conducts-mangroveplanting
Donato D, Kauffman JB, Murdiyarso D, Kurnianto S, Stidham M, Kanninen M (2011)
Mangroves among the most carbon-rich forests in the tropics. Nature Geoscience 4 (5):
293297. https://doi.org/10.1038/ngeo1123
Emperua L, Donia E, Biaca M, Pechon R, Pautong A, Balonos TA (2018) The small
pelagic fisheries of Sarangani Bay, southern Mindanao, Philippines. The Philippine
Journal of Fisheries 25 (1): 118127. https://doi.org/10.31398/tpjf/25.1.2017C0014
Faustino AZ, Madela HL, Castor RG, Muroda AP, Chavez MN (2020) Community
mapping and vegetational analysis of the mangrove forest in Calabanga, San Miguel
Bay, Philippines. The Third International Symposium on Marine and Fisheries Research
147: 112. https://doi.org/10.1051/e3sconf/202014702017
20 Agduma A, Cao K
Feller IC, Lovelock CE, Berger U, McKee KL, Joye SB, Ball MC (2010) Biocomplexity in
mangrove ecosystems. Annual Review of Marine Science 2 (1): 395417.
https://doi.org/
10.1146/annurev.marine.010908.163809
Fernando E, Pancho J (1980) Mangrove trees of the Philippines. Sylvatrop, Philippine
Forest Research Journal 5: 3554.
Fitzgerald W (2000) Integrated mangrove forest and aquaculture systems in Indonesia.
In: Primavera JH, Garcia LM, Castaños MT, Surtida MB (Eds) Mangrove-friendly
aquaculture: Proceedings of the workshop on mangrove-friendly aquaculture.
Aquaculture Department, Southeast Asian Fisheries Development Center, Tigbauan,
Iloilo, Philippines, 21-34 pp. URL: https://repository.seafdec.org.ph/handle/10862/1977
[ISBN 978-971-8511-42-8].
FMB (2012) Philippine forestry statistics: 2012. Forest Management Bureau,
Department of Environment and Natural Resources, Philippines. URL: https://
forestry.denr.gov.ph/index.php/statistics/philippines-forestry-statistics
FMB (2021) Philippine forestry statistics: 2021. Forest Management Bureau,
Department of Environment and Natural Resources, Philippines. URL: https://
forestry.denr.gov.ph/index.php/statistics/philippines-forestry-statistics
Friess D, Rogers K, Lovelock C, Krauss K, Hamilton S, Lee SY, Lucas R, Primavera J,
Rajkaran A, Shi S (2019) The state of the world's mangrove forests: Past, present, and
future. Annual Review of Environment and Resources 44 (1): 89115. https://doi.org/
10.1146/annurev-environ-101718-033302
Garcia K, Malabrigo P, Gevaña D (2014) Philippines' mangrove ecosystem: Status,
threats and conservation. In: Faridah-Hanum I, Latiff A, Ozturk M (Eds) Mangrove
ecosystems of Asia. Springer, New York. [ISBN 978-1-4614-8581-0]. https://doi.org/
10.1007/978-1-4614-8582-7_5
Gilman E, Ellison J, Duke N, Field C (2008) Threats to mangroves from climate change
and adaptation options: A review. Aquatic Botany 89 (2): 237250. https://doi.org/
10.1016/j.aquabot.2007.12.009
Goldberg L, Lagomasino D, Thomas N, Fatoyinbo T (2020) Global declines in human
driven mangrove loss. Global Change Biology 26 (10): 58445855. https://doi.org/
10.1111/gcb.15275
Gubalani R (2021) Thousands of mangroves planted in Sarangani Bay area. Philippine
News Agency, Philippines. URL: https://www.pna.gov.ph/articles/1132194
Hamilton S (2013) Assessing the role of commercial aquaculture in displacing
mangrove forest. Bulletin of Marine Science 89 (2): 585601. https://doi.org/10.5343/
bms.2012.1069
Hamilton S, Friess D (2018) Global carbon stocks and potential emissions due to
mangrove deforestation from 2000 to 2012. Nature Climate Change 8 (3): 240244.
https://doi.org/10.1038/s41558-018-0090-4
Harishma KM, Sandeep S, Sreekumar VB (2020) Biomass and carbon stocks in
mangrove ecosystems of Kerala, southwest coast of India. Ecological Processes 9 (1):
19. https://doi.org/10.1186/s13717-020-00227-8
Hashim TM, Ariff EA, Suratman MN (2021) Aquaculture in mangroves. In: Rastogi RP,
Phulwaria M, Gupta DK (Eds) Mangroves: Ecology, biodiversity and management.
Springer, Singapore. [ISBN 978-981-16-2494-0]. https://doi.org/
10.1007/978-981-16-2494-0_18
Species richness, extent and potential threats to mangroves of Sarangani ... 21
Hickey S, Radford B (2022) Turning the tide on mapping marginal mangroves with
multi-dimensional space-time remote sensing. Remote Sensing 14 (14): 3365. https://
doi.org/10.3390/rs14143365
Hossain MD, Nuruddin AA (2016) Soil and mangrove: A review. Journal of
Environmental Science and Technology 9 (2): 198207. https://doi.org/10.3923/jest.
2016.198.207
Hu L, Xu N, Liang J, Li Z, Chen L, Zhao F (2020) Advancing the mapping of mangrove
forests at national-scale using Sentinel-1 and Sentinel-2 time-series data with Google
Earth Engine: A case study in China. Remote Sensing 12 (19): 3120. https://doi.org/
10.3390/rs12193120
Iqbal N, Khan N, Ferrante A, Trivellini A, Francini A, Khan MI (2017) Ethylene role in
plant growth, development and senescence: Interaction with other phytohormones.
Frontiers in Plant Science 8 (475): 11. https://doi.org/10.3389/fpls.2017.00475
IUCN (2022) The IUCN Red List of Threatened Species. Version 2022-2. https://
www.iucnredlist.org.. Accessed on: 2022-10-10.
Jumangit JR (2022) ARDEC extends technical assistance to PENRO-Sarangani on
mangrove plantation establishment, species site matching. URL: https://
erdb.denr.gov.ph/ardec-extends-technical-assistance-to-penro-sarangani-onmangrove-
plantation-establishment-species-site-matching/
Jumawan J (2022) Mangrove biodiversity, GIS weighted overlay analysis, and mapping
of suitable areas in Alabel, Sarangani Province, Philippines. Journal of Ecosystem
Science and Eco-Governance 4 (1): 1123. https://doi.org/10.54610/jeseg/4.1.2022.002
Jwaideh MA, Sutanudjaja E, Dalin C (2022) Global impacts of nitrogen and phosphorus
fertiliser use for major crops on aquatic biodiversity. The International Journal of Life
Cycle Assessment 27 (8): 10581080. https://doi.org/10.1007/s11367-022-02078-1
Karra K, Kontgis C, Statman-Weil Z, Mazzariello JC, Mathis M, Brumby SP (2021)
Global land use/land cover with Sentinel 2 and deep learning. 2021 Institute of Electrical
and Electronics Engineers International Geoscience and Remote Sensing
Symposium47044707. https://doi.org/10.1109/IGARSS47720.2021.9553499
Kumari P, Singh JK, Pathak B (2020) Chapter 1 - Potential contribution of
multifunctional mangrove resources and its conservation. In: Patra JK, Mishra RR,
Thatoi H (Eds) Biotechnological utilization of mangrove resources. Academic Press,
1-26 pp. [ISBN 978-0-12-819532-1]. https://doi.org/10.1016/
B978-0-12-819532-1.00001-9
Lagnason C, Bidad W, Requieron E (2016) Biophysical profile of Kawas Marine
Sanctuary in Alabel Sarangani Province, Philippines. AES Bioflux 8 (1): 2432.
Long J, Giri C (2011) Mapping the Philippines’ mangrove forests using Landsat magery.
Sensors 11 (3): 29722981. https://doi.org/10.3390/s110302972
Long J, Napton D, Giri C, Graesser J (2014) A mapping and monitoring assessment of
the Philippines' mangrove forests from 1990 to 2010. Journal of Coastal Research 30
(2): 260271. https://doi.org/10.2112/JCOASTRES-D-13-00057.1
Mayuga J (2017) A man-made mangrove forest thrives in Iloilo. Business Mirror. URL:
https://fpe.ph/news/a-man-made-mangrove-forest-thrives-in-iloilo-1
Morgott D (2015) Anthropogenic and biogenic sources of ethylene and the potential for
human exposure: A literature review. Chemico-Biological Interactions 241: 1022.
https://doi.org/10.1016/j.cbi.2015.08.012
22 Agduma A, Cao K
Mullet EK, Lacorte GH, Hamiladan RM, Arabit CE, Cuales SO, Lasutan LG, Alagos NJ,
Kamantu HG, Protacio KJ, Jumawan JH (2014) Assessment of mangrove species and
its relation to soil substrates in Malapatan, Sarangani Province, Philippines. Journal of
Biodiversity and Environmental Sciences 5 (4): 100107.
Natividad EM, Dalundong AO, Patriarca AB, Banisil MA, Hingabay VS, Paña BH, Teofilo
RC, Salvatierra LA, Dagoc V, Jumawan JH (2014) Correlation of soil and mangrove
diversity in selected sites of Alabel and Maasim, Sarangani Province, Philippines. AAB
Bioflux 6 (2): 145153.
Natividad EM, Natividad C, Hingabay V, Lipae H, Requieron E, Abalunan AJ, Tagaloguin
P, Flamiano R, Jumawan JH (2015) Vegetation analysis and community structure of
mangroves in Alabel and Maasim, Sarangani Province, Philippines. ARPN Journal of
Agricultural and Biological Science 10 (3): 97102.
Neri MP, Baloloy AB, Blanco AC (2021) Limitation assessment and workflow refinement
of the mangrove vegetation index (MVI)-based mapping methodology using Sentinel-2
imagery. The International Archives of the Photogrammetry, Remote Sensing and
Spatial Information Sciences LVI-4/W6-2021: 235242. https://doi.org/10.5194/
isprsarchives-XLVI-4-W6-2021-235-2021
Olsvik P, Larsen AK, Berntssen MG, Goksøyr A, Karlsen OA, Yadetie F, Sanden M,
Kristensen T (2019) Effects of agricultural pesticides in aquafeeds on wild fish feeding
on leftover pellets near fish farms. Frontiers in Genetics 10 (794): 118. https://doi.org/
10.3389/fgene.2019.00794
Pepi M, Focardi S (2021) Antibiotic-resistant bacteria in aquaculture and climate
change: A challenge for health in the mediterranean area. International Journal of
Environmental Research and Public Health 18 (11): 5723. https://doi.org/10.3390/
ijerph18115723
PNA (2018) Expansion of shrimp farms in Sarangani, GenSan pushed. Philippine News
Agency, Philippines. URL: https://www.pna.gov.ph/articles/1051407
Polidoro B, Carpenter K, Collins L, Duke N, Ellison A, Ellison J, Farnsworth E, Fernando
E, Kathiresan K, Koedam N, Livingstone S, Miyagi T, Moore G, Nam VN, Ong JE,
Primavera J, Salmo S, Sanciangco J, Sukardjo S, Wang Y, Yong JW (2010) The loss of
species: Mangrove extinction risk and geographic areas of global concern. PLOS One 5
(4): 10095. https://doi.org/10.1371/journal.pone.0010095
Primavera JH, Lavilla-Pitogo CR, Ladja JM, Dela Peña MR (1993) A survey of chemical
and biological products used in intensive prawn farms in the Philippines. Marine
Pollution Bulletin 26 (1): 3540. https://doi.org/10.1016/0025-326X(93)90595-B
Primavera JH (1995) Mangroves and brackishwater pond culture in the Philippines. In:
Wong YS, Tam NF (Eds) Asia-Pacific symposium on mangrove ecosystems. The Hong
Kong University of Science & Technology, September 1-3, 1993. 303-309 pp. [ISBN
978-94-011-0289-6]. https://doi.org/10.1007/978-94-011-0289-6_34
Primavera JH, Garcia LM, Castaños MT, Surtida MB (Eds) (2000) Mangrove-friendly
aquaculture: Proceedings of the workshop on mangrove-friendly aquaculture.
Aquaculture Department, Southeast Asian Fisheries Development Center, Tigbauan,
Iloilo, Philippines URL: https://repository.seafdec.org.ph/handle/10862/1947 [ISBN
978-971-8511-42-8].
Primavera JH, Sadaba R, Lebata M, Altamirano J (2004) Handbook of mangroves in the
Philippines - Panay. Aquaculture Department, Southeast Asian Fisheries Development
Species richness, extent and potential threats to mangroves of Sarangani ... 23
Center, Tigbauan, Iloilo, Philippines, 106 pp. URL: https://repository.seafdec.org.ph/
handle/10862/3053 [ISBN 978-971-8511-65-7]
Primavera JH (2006) Overcoming the impacts of aquaculture on the coastal zone.
Ocean & Coastal Management 49 (9): 531545. https://doi.org/10.1016/j.ocecoaman.
2006.06.018
Primavera JH, Sadaba RB, Lebata-Ramos MJ, Altamirano JP (2016a) Mangroves and
beach forest species in the Philippines. Ecosystems Research and Development
Bureau and Department of Environment and Natural Resources, 238 pp. [ISBN
978-97-188-3149-6]
Primavera JH, dela Cruz M, Montilijao C, Consunji H, dela Paz M, Rollon RN, Maranan
K, Samson MS, Blanco A (2016b) Preliminary assessment of post-Haiyan mangrove
damage and short-term recovery in Eastern Samar, Central Philippines. Marine
Pollution Bulletin 109 (2): 744750. https://doi.org/10.1016/j.marpolbul.2016.05.050
PSA (2021) 2020 census of population and housing (2020 CPH): Population counts
declared official by the President. Philippine Statistics Authority, Philippines. URL:
https:// psa.gov.ph/content/2020-census-population-and-housing-2020-cph-population-
countsdeclared- official-president
Quadros A, Helfer V, Nordhaus I, Reuter H, Zimmer M (2021) Functional traits of
terrestrial plants in the intertidal: A review on mangrove trees. The Biological Bulletin
241 (2): 123139. https://doi.org/10.1086/716510
R Core Team (2022) R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria.
Richards D, Friess D (2016) Rates and drivers of mangrove deforestation in Southeast
Asia, 2000-2012. Proceedings of the National Academy of Sciences 113 (2): 344349.
https://doi.org/10.1073/pnas.1510272113
Rönnbäck P (1999) The ecological basis for economic value of seafood production
supported by mangrove ecosystems. Ecological Economics 29 (2): 235252. https://
doi.org/10.1016/S0921-8009(99)00016-6
Ruang-areerate P, Yoocha T, Kongkachana W, Phetchawang P, Maknual C, Meepol W,
Jiumjamrassil D, Pootakham W, Tangphatsornruang S (2022) Comparative analysis and
phylogenetic relationships of Ceriops species (Rhizophoraceae) and Avicennia lanata
(Acanthaceae): Insight into the chloroplast genome evolution between middle and
seaward zones of mangrove forests. Biology 11 (3): 383. https://doi.org/10.3390/
biology11030383
Santos LC, Gasalla M, Dahdouh-Guebas F, Bitencourt MD (2017) Socio-ecological
assessment for environmental planning in coastal fishery areas: A case study in
Brazilian mangroves. Ocean & Coastal Management 138: 6069. https://doi.org/
10.1016/j.ocecoaman.2017.01.009
Sasmito S, Sillanpää M, Hayes M, Bachri S, SaragiSasmito M, Sidik F, Hanggara B,
Mofu W, Rumbiak V, Hendri, Taberima S, Suhaemi, Nugroho J, Pattiasina T, Widagti N,
Barakalla, Rahajoe J, Hartantri H, Nikijuluw V, Jowey R, Heatubun C, Ermgassen P,
Worthington T, Howard J, Lovelock C, Friess D, Hutley L, Murdiyarso D (2020)
Mangrove blue carbon stocks and dynamics are controlled by hydrogeomorphic settings
and landuse change. Global Change Biology 26 (5): 30283039.
https://doi.org/10.1111/
gcb.15056
Sheue CR, Liu HY, Tsai CC, Rashid SM, Yong JW, Yang YP (2009) On the morphology
and molecular basis of segregation of Ceriops zippeliana and C. decandra
24 Agduma A, Cao K
(Rhizophoraceae) from Asia. Blumea - Biodiversity, Evolution and Biogeography of
Plants 54 (1): 220227. https://doi.org/10.3767/000651909x476193
Spalding MD, Blasco F, Field CD (Eds) (1997) World mangrove atlas. The International
Society for Mangrove Ecosystems, Okinawa, Japan, 178 pp. [ISBN 978-4-906584-03-1]
Stevenson NJ, Lewis RR, Burbridge PR (1999) Disused Shrimp Ponds and Mangrove
Rehabilitation. In: Streever W (Ed.) An International Perspective on Wetland
Rehabilitation277297. https://doi.org/10.1007/978-94-011-4683-8_28
Streicher M, Reiss H, Reiss K (2021) Impact of aquaculture and agriculture nutrient
sources on macroalgae in a bioassay study. Marine Pollution Bulletin 173 (113025).
https://doi.org/10.1016/j.marpolbul.2021.113025
Susilo H, Takahashi Y, Sato G, Nomura H, Yabe M (2018) The adoption of silvofishery
system to restore mangrove ecosystems and its impact on farmers’ income in Mahakam
Delta, Indonesia. Journal of the Faculty of Agriculture, Kyushu University 63 (2):
433442. https://doi.org/10.5109/1955666
Takashima F (2000) Silvofishery: An aquaculture system harmonized with
theenvironment. In: Primavera JH, Garcia LM, Castaños MT, Surtida MB (Eds)
Mangrove-friendly aquaculture: Proceedings of the workshop on mangrove-friendly
aquaculture. Aquaculture Department, Southeast Asian Fisheries Development Center,
Tigbauan, Iloilo, Philippines, 13-19 pp. URL: http://hdl.handle.net/10862/1976 [ISBN
978-971-8511-42-8].
Tanalgo K, Oliveira HM, Hughes AC (2022) Mapping global conservation priorities and
habitat vulnerabilities for cave-dwelling bats in a changing world. Science of The Total
Environment 843 (15): 156909. https://doi.org/10.1016/j.scitotenv.2022.156909
Tanan S, Tansutapanich A (2000) Thailand: Mangrove-friendly shrimp farming. In:
Primavera JH, Garcia LM, Castaños MT, Surtida MB (Eds) Mangrove-friendly
aquaculture: Proceedings of the workshop on mangrove-friendly aquaculture.
Aquaculture Department, Southeast Asian Fisheries Development Center, Tigbauan,
Iloilo, Philippines, 57-65 pp. URL: https://repository.seafdec.org.ph/handle/10862/1982
[ISBN 978-971-8511-42-8].
Udoh JP (2016) Sustainable nondestructive mangrove-friendly aquaculture in Nigeria II:
Models, best practices and policy frame work. AACL Bioflux 9 (1): 151173.
USAID Oceans (2019) Sustainable fisheries management plan for the Sarangani Bay
and Sulawesi Sea: Region 12, Philippines. The United States Agency for International
Development Oceans and Fisheries Partnership. URL: https://
www.seafdecoceanspartnership. org/resource/sustainable-fisheries-management-plan-
for-thesarangani- bay-and-sulawesi-sea-region-12-philippines/
Valiela I, Bowen J, York J (2001) Mangrove Forests: One of the world's threatened
major tropical environments. BioScience 51 (10): 807815. https://doi.org/
10.1641/0006-3568(2001)051[0807:mfootw]2.0.co;2
Walters B (2004) Local management of mangrove forests in the Philippines: Successful
conservation or efficient resource exploitation? Human Ecology 32 (2): 177195. https://
doi.org/10.1023/B:HUEC.0000019762.36361.48
Wang H, Peng Y, Wang C, Wen Q, Xu J, Hu Z, Jia X, Zhao X, Lian W, Temmerman S,
Wolf J, Bouma T (2021) Mangrove loss and gain in a densely populated urban estuary:
Lessons from the Guangdong-Hong Kong-Macao Greater Bay area. Frontiers in Marine
Science 8: 693450. https://doi.org/10.3389/fmars.2021.693450
Species richness, extent and potential threats to mangroves of Sarangani ... 25
Wang L, Mu M, Li X, Lin P, Wang W (2011) Differentiation between true mangroves and
mangrove associates based on leaf traits and salt contents. Journal of Plant Ecology 4
(4): 292301. https://doi.org/10.1093/jpe/rtq00818
Supplementary materials
Suppl. material 1: Georeferenced locations of mangroves in Sarangani Bay
Protected Seascape, Philippines
Authors: Angelo Rellama Agduma, Kun-Fang Cao
Data type: Occurrences of mangroves
Brief description: This data file contains the georeferenced locations (latitude, longitude) of
mangroves in Sarangani Bay Protected Seascape (SBPS), Philippines, their IUCN and DENR
conservation status and their occurrences in different towns surrounding SBPS.
Download file (39.57 kb)
Suppl. material 2: Land use cover of coastal towns of Sarangani Province and
General Santos City, Philippines
Authors: Angelo Rellama Agduma, Kun-Fang Cao
Data type: Measured land-use cover
Brief description: This data file summarises the measured land use cover (km ) of the towns
surrounding Sarangani Bay Protected Seascape, Philippines, based on Sentinel-2 satellite data.
Download file (3.18 kb)
Suppl. material 3: Relationship (Spearman) of mangrove cover with total tree
cover and proxies of potential threats to mangroves in Sarangani Bay Protected
Seascape, Philippines
Authors: Angelo Rellama Agduma, Kun-Fang Cao
Data type: Correlation matrix (Spearman)
Brief description: This data file contains the areas of mangrove cover (ha) and of land-use cover
(km ) (total tree cover, rangeland, cropland, built area, bare ground), the total population and the
number of fishing boats in the coastal towns surrounding Sarangani Bay Protected Seascape,
Philippines (Table 1). The results of correlation of mangrove cover with land-use cover, total
population and number of fishing boats are emphasised in Table 2.
Download file (21.01 kb)
Suppl. material 4: Mangrove cover of Sarangani Bay Protected Seascape,
Philippines
Authors: Angelo Rellama Agduma, Kun-Fang Cao
Data type: Mangrove area
Brief description: This data file summarises the mangrove cover records (hectares) in the
different coastal towns surrounding Sarangani Bay Protected Seascape, Philippines in 1998 (de
Jesus et al. 2001), 2016 (USAID Oceans 2019) and 2022 (this study).
Download file (238.00 bytes)
2
2
26 Agduma A, Cao K
Suppl. material 5: Confusion matrix for the generated extent map for mangroves
of Sarangani Bay Protected Seascape, Philippines
Authors: Angelo Rellama Agduma, Kun-Fang Cao
Data type: Confusion matrix
Brief description: This is a confusion matrix containing the overall accuracy and Kappa
coefficient that tell the validity of the mapping of mangrove areal extent used in the analysis.
Download file (24.00 kb)
Species richness, extent and potential threats to mangroves of Sarangani ... 27
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A high resolution mangrove map (e.g., 10-m), including mangrove patches with small size, is urgently needed for mangrove protection and ecosystem function estimation, because more small mangrove patches have disappeared with influence of human disturbance and sea-level rise. However, recent national-scale mangrove forest maps are mainly derived from 30-m Landsat imagery, and their spatial resolution is relatively coarse to accurately characterize the extent of mangroves, especially those with small size. Now, Sentinel imagery with 10-m resolution provides an opportunity for generating high-resolution mangrove maps containing these small mangrove patches. Here, we used spectral/backscatter-temporal variability metrics (quantiles) derived from Sentinel-1 SAR (Synthetic Aperture Radar) and/or Sentinel-2 MSI (Multispectral Instrument) time-series imagery as input features of random forest to classify mangroves in China. We found that Sentinel-2 (F1-Score of 0.895) is more effective than Sentinel-1 (F1-score of 0.88) in mangrove extraction, and a combination of SAR and MSI imagery can get the best accuracy (F1-score of 0.94). The 10-m mangrove map was derived by combining SAR and MSI data, which identified 20003 ha mangroves in China, and the area of small mangrove patches (<1 ha) is 1741 ha, occupying 8.7% of the whole mangrove area. At the province level, Guangdong has the largest area (819 ha) of small mangrove patches, and in Fujian, the percentage of small mangrove patches is the highest (11.4%). A comparison with existing 30-m mangrove products showed noticeable disagreement, indicating the necessity for generating mangrove extent product with 10-m resolution. This study demonstrates the significant potential of using Sentinel-1 and Sentinel-2 images to produce an accurate and high-resolution mangrove forest map with Google Earth Engine (GEE). The mangrove forest map is expected to provide critical information to conservation managers, scientists, and other stakeholders in monitoring the dynamics of the mangrove forest.
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Global mangrove loss has been attributed primarily to human activity. Anthropogenic loss hotspots across Southeast Asia and around the world have characterized the ecosystem as highly threatened, though natural processes such as erosion can also play a significant role in forest vulnerability. However, the extent of human and natural threats has not been fully quantified at the global scale. Here, using a Random Forest‐based analysis of over one million Landsat images, we present the first 30‐meter resolution global maps of the drivers of mangrove loss from 2000‐2016, capturing both human‐driven and natural stressors. We estimate that 62% of global losses between 2000‐2016 resulted from land‐use change, primarily through conversion to aquaculture and agriculture. Up to 80% of these human‐driven losses occurred within six Southeast Asian nations, reflecting the regional emphasis on enhancing aquaculture for export to support economic development. Both anthropogenic and natural losses declined between 2000‐2016, though slower declines in natural loss caused an increase in their relative contribution to total global loss area. We attribute the decline in anthropogenic losses to the regionally‐dependent combination of increased emphasis on conservation efforts and a lack of remaining mangroves viable for conversion. While efforts to restore and protect mangroves appear to be effective over decadal time scales, the emergence of natural drivers of loss presents an immediate challenge for coastal adaptation. We anticipate that our results will inform decision making within conservation and restoration initiatives by providing a locally‐relevant understanding of the causes of mangrove loss.
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Background Mangroves are important tropical carbon sinks, and their role in mitigating climate change is well documented across the globe. However, the ecosystem carbon stocks in the mangroves of India have not been studied comprehensively. Data from this region is very limited for providing sufficient insights and authentic evaluation of carbon stocks on a regional scale. In this study, we evaluated the ecosystem carbon stock and its spatial variation in mangroves of Kerala, southwest coast of India. Results The mean biomass stored in mangrove vegetation of Kerala is 117.11 ± 1.02 t/ha (ABG= 80.22 ± 0.80, BGB =36.89 ± 0.23 t/ha). Six mangrove species were found distributed in the study area. Among the different species, Avicennia marina had the highest biomass (162.18 t/ha) and least biomass was observed in Sonneratia alba (0.61 t/ha). The mean ecosystem carbon stock of mangrove systems in Kerala was estimated to be 139.82 t/ha, equivalent to 513.13 t CO 2 e/ha with the vegetation and soil storing 58.56 t C/ha and 81.26 t C/ha respectively. Conclusion The present study reveals that Kerala mangroves store sizable volume of carbon and therefore need to be preserved and managed sustainably, to retain along with the increase in carbon storage. This features the need of broadening mangrove cover as well as restoring deteriorated land in the past 50 years. Although mangrove forests in this region are protected by the Kerala Forest Department, they have been frequently facing illegal encroachment, prawn cultivation, and coastal erosion.
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Screening has revealed that modern-day feeds used in Atlantic salmon aquaculture might contain trace amounts of agricultural pesticides. To reach slaughter size, salmon are produced in open net pens in the sea. Uneaten feed pellets and undigested feces deposited beneath the net pens represent a source of contamination for marine organisms. To examine the impacts of long-term and continuous dietary exposure to an organophosphorus pesticide found in Atlantic salmon feed, we fed juvenile Atlantic cod (Gadus morhua), an abundant species around North Atlantic fish farms, three concentrations (0.5, 4.2, and 23.2 mg/kg) of chlorpyrifos-methyl (CPM) for 30 days. Endpoints included liver and bile bioaccumulation, liver transcriptomics and metabolomics, as well as plasma cholinesterase activity, cortisol, liver 7-ethoxyresor-ufin-O-deethylase activity, and hypoxia tolerance. The results show that Atlantic cod can accumulate relatively high levels of CPM in liver after continuous exposure, which is then metabolized and excreted via the bile. All three exposure concentrations lead to significant inhibition of plasma cholinesterase activity, the primary target of CPM. Transcriptomics profiling pointed to effects on cholesterol and steroid biosynthesis. Metabolite profiling revealed that CPM induced responses reflecting detoxification by glutathione-S-transferase, inhibition of monoacylglycerol lipase, potential inhibition of carboxylesterase, and increased demand for ATP, followed by secondary inflammatory responses. A gradual hypoxia challenge test showed that all groups of exposed fish were less tolerant to low oxygen saturation than the controls. In conclusion, this study suggests that wild fish continuously feeding on leftover pellets near fish farms over time may be vulnerable to organophosphorus pesticides.
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