Baseline Ecological Insights of Vegetation and Carbon Stocks Assessment in Probolinggo Natural Mangrove Forests

Abstract

Flooding and sea-level rise are recurrent challenges in Probolinggo Regency, driven by the anthropogenic degradation of mangrove forests. Although restoration initiatives are ongoing, the vegetation condition of natural mangrove forests remain poorly characterized. The aim of this study was to provide a baseline ecological assessment of natural mangrove forests across Probolinggo Regency by evaluating vegetation structure and carbon stocks. Using a purposive sampling method, species composition, vegetation height, and diameter at breast height (DBH) were measured in 33 plots across eight subdistricts. Avicennia marina and Rhizophora mucronata were the dominant species, with relative abundances varying spatially. Saplings represented the most abundant growth stage. Kraksaan subdistrict exhibited the highest Shannon–Wiener diversity index (H’ = 1.8), whereas Sumberasih had the lowest (H’ = 0.9). Species richness (R) ranged from low to moderate, evenness (E) was consistently high, and dominance (C) was low in all subdistricts. Carbon stocks were highest in Dringu (508.1 Mg C ha⁻¹) and lowest in Tongas (87.6 Mg C ha⁻¹). Overall, the natural mangrove forests in Probolinggo Regency appeared to be in an early to mid-successional stage because of past degradation, highlighting the need for continuous monitoring to support vegetation recovery and sustain ecosystem services.

1. Introduction

Mangroves play a crucial ecological role in coastal protection, biodiversity conservation, and safeguarding the livelihoods of coastal communities [1,2]. In Probolinggo Regency, mangrove ecosystems are under severe anthropogenic pressure, which causes climate change impacts such as sea-level rise and coastal hazards [3,4,5]. Effective mangrove restoration therefore requires a robust ecological understanding to ensure long-term sustainability.

Natural mangrove forests provide essential ecosystem services, including significant carbon sinks [6,7,8,9], biodiversity support, shoreline protection, and climate regulations [10,11,12,13]. Assessing their ecological condition through analyses of species diversity and composition is important for determining their health and resilience. Ecological assessments include measurements of vegetation structure, species presence and dominance, and productivity, which determine the effects of environmental stress on anthropogenic pressures [14]. In this context, the estimation of biomass and carbon stocks is critical for evaluating the contribution of existing mangrove forests to the global carbon cycle, as mangroves store substantial amounts of both above- and belowground carbon. Integrated ecological assessments are essential for establishing a scientific evidence-based baseline for identifying conservation priorities and guiding the improvement of restoration programs.

Probolinggo Regency, like many coastal regions in Indonesia—particularly on Java Island—has experienced extensive degradation of natural mangrove forests owing to aquacultural expansion and human development [15,16,17]. Studies on vegetation and ecological assessment in this region are spatially limited [18], with most focusing on faunal ecology or socio-economic aspects. To address this gap, this study evaluated the current ecological condition of natural mangrove forests across all subdistricts of Probolinggo Regency by analyzing vegetation structure and composition and estimating biomass and carbon stocks. These results provide a comprehensive overview of the present ecological state, supporting the development of more effective and ecologically informed restoration strategies that align with original habitat characteristics and enhance climate regulation through carbon sequestration and storage.

In this study, we hypothesized that: (i) species diversity differs significantly among subdistricts, indicating environmental variations and disturbance history; (ii) species dominance patterns, as indicated by the Importance Value Index (IVI), richness, evenness, and dominance, vary across subdistricts, indicating species adaptability to environmental variability; and (iii) biomass and carbon stocks vary among subdistricts, corresponding to differences in species composition and structure. These findings are intended to establish a scientifically grounded reference to inform restoration strategies that align species selection with ecological conditions for long-term ecosystem resilience and carbon sequestration.

2. Materials and Methods

2.1. Study Site

This study was conducted in the natural mangrove forests of Probolinggo Regency, East Java, Indonesia, which comprises nine coastal subdistricts. Eight of these subdistricts—Kraksaan, Pajarakan, Gending, Mayangan, Kademangan, Sumberasih, Dringu, and Tongas—were selected for ecological assessment from east to west. Paiton (the easternmost district) was excluded owing to the limited extent of its natural mangrove forests. The natural mangrove forests of Kraksaan, Pajarakan, Gending, Dringu, and Tongas are located downstream of several large rivers that transport sand and mud sediments, resulting in predominantly sand–mud substrates in these areas. In contrast, the mangrove forests in Mayangan, Kademangan, and Sumberasih are characterized by sand-dominated substrates derived from volcanic materials originating from Mount Bromo. Overall, the mangrove substrates across Probolinggo Regency are broadly similar, consisting mainly of sand–mud substrates shaped by sediment inputs and strong wave dynamics. The coastline of Probolinggo Regency spans approximately 74.2 km and has a total mangrove forest area (including both natural and restored forests) of 1286.5 ha [15].

Bordering the Madura Strait, the coastline is exposed to strong wave action and high tidal currents, which present significant challenges for mangrove reforestation and natural regeneration. The ongoing loss of mangrove cover has increased the region’s vulnerability to natural hazards, including strong winds, tidal inundation, sea-level rise, and flooding (Figure 1). These impacts have adversely affected local tourism and livelihoods have been adversely affected, contributing to economic instability and raising concerns regarding long-term environmental sustainability.

Data on the mangrove and aquaculture areas in Probolinggo Regency were extracted from the 2023 spatial database of TGE Watershed and Natural Resource Management Agency, Ministry of Forestry, Indonesia. Aquaculture expansion continues to exceed mangrove conservation efforts, with aquaculture areas covering approximately 1.5 times the area of remaining mangrove forest. Maps of the study sites and the distribution of mangrove forests and aquaculture areas are shown in Figure 2 and Figure 3, respectively.

2.2. Vegetation Inventory

Vegetation data inventories were conducted from September 2024 to February 2025 using a quantitative, field-based approach to document the taxonomic composition and spatial distribution of mangrove species across eight subdistricts of Probolinggo Regency. This study focused exclusively on natural mangrove forests to assess the existing plant species without the influence of restoration interventions. Prior to field surveys, satellite imagery was used to identify candidate sampling areas. Mangrove stands exhibiting heterogeneous canopy colors were classified as natural mangrove forests, whereas areas with uniform canopy colors were excluded because they were considered monospecific or planted areas. Candidate areas were subsequently verified through field survey to confirm accessibility.

A total of 33 permanent sampling plots established using purposive sampling, with the number of plots in each subdistrict varying depending on the extent of mangrove coverage and field accessibility (

Table 1. Plots allocation and coordinates in each subdistrict.

Subdistrict	Total Plots	Village	Latitude	Longitude
Kraksaan	5	Asembagus	−7.737120	113.407738
		Asembagus	−7.741248	113.395615
		Kebonagung	−7.727806	113.449539
		Kebonagung	−7.731936	113.442137
		Kebonagung	−7.734851	113.435823
Pajarakan	5	Sukokerto	−7.748847	113.372955
		Karanggeger	−7.758505	113.359979
		Gejugan	−7.769597	113.346757
		Penambangan	−7.746376	113.387308
		Penambangan	−7.743814	113.384527
Gending	4	Pantai Bentar	−7.782892	113.277441
		Pantai Bentar	−7.774474	113.319236
		Pesisir	−7.774616	113.335947
		Klaseman	−7.776330	113.326551
Dringu	6	Dringu	−7.746932	113.249160
		Dringu	−7.746491	113.249380
		Dringu	−7.746225	113.248350
		Randu putih	−7.765788	113.264720
		Kalisalam	−7.761690	113.264895
		Randu putih	−7.776819	113.261895
Kademangan	3	Mangunharjo	−7.743704	113.193253
		Pilang	−7.740415	113.191823
		Ketapang	−7.746534	113.180512
Mayangan	3	Pantai Permata	−7.739707	113.234780
		Pantai Mutiara	−7.739456	113.226763
		Pantai Takad	−7.739938	113.280700
Sumberasih	3	Ketapang	−7.746546	113.179568
		Pantai Takad	−7.727808	113.171128
		Pesisir	−7.736515	113.170306
Tongas	4	Pantai Bahak	−7.724502	113.113954
		Pantai Bahak	−7.725982	113.118545
		Renek	−7.718378	113.106768
		Pantai Tambakrejo	−7.702466	113.100909

). Although zonation-based sampling (seaward–middle–landward) was initially considered, this approach could not be applied consistently because middle or landward zones had been partially or completely lost in several subdistricts owing to land conversion. Therefore, purposive sampling targeting the remaining natural mangrove stands was adopted to ensure comparability among the subdistricts.

Each main plot measured 20 m × 20 m and was used to record vegetation height, diameter at breast height (DBH), and species identity. Within each main plot, subplots of 10 m × 10 m and 5 m × 5 m were established to record tree (DBH > 20 cm), pole (10 ≥ DBH < 19 cm), and sapling (DBH < 10 cm) stages, respectively [16]. The DBH was measured approximately 1.3 m above the highest prop root for Rhizophora spp. and 1.3 m aboveground level for the other species. Local community guides assisted with site access and navigation; however, they had no influence on plot placement or measurements.

2.3. Species Composition and Diversity

Species composition and diversity assesment are essential for understanding ecological conditions and species roles within natural mangrove forests. Ecological indices were used to evaluate disturbance levels and successional status across subdistricts. The results are expected to give explicit recommendations on disturbance level and successional status of the mangrove forests using ecological indices.

The Importance Value Index (IVI) was calculated to assess the ecological significance of each mangrove species within the study area [17]. IVI is derived from three components: Relative Density (RD), Relative Frequency (RF), and Relative Dominance (RDo). These indices provide insights into the dominance or influence of a species in an ecosystem. RD refers to the proportion of individuals of a particular species relative to the total number of individuals of all species in the sampling area. RF indicates how frequently a species appears across sampling plots and is expressed as a percentage of the total species frequency. RDo is based on the total basal area occupied by a species relative to the total basal area of all species within a plot. Higher IVI values indicate greater ecological importance of the species in the community. The formulas used were as follows:

$${\mathrm{R}\mathrm{D}}_{\mathrm{i}}(\mathrm{\%})={\displaystyle \frac{\mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r} \mathrm{o}\mathrm{f} \mathrm{i}\mathrm{n}\mathrm{d}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{d}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{s} \mathrm{o}\mathrm{f} \mathrm{i} \mathrm{s}\mathrm{p}\mathrm{e}\mathrm{c}\mathrm{i}\mathrm{e}\mathrm{s}}{\mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r} \mathrm{o}\mathrm{f} \mathrm{a}\mathrm{l}\mathrm{l} \mathrm{r}\mathrm{e}\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{d}\mathrm{e}\mathrm{d} \mathrm{i}\mathrm{n}\mathrm{d}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{d}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{s} \mathrm{o}\mathrm{f} \mathrm{a}\mathrm{l}\mathrm{l} \mathrm{s}\mathrm{p}\mathrm{e}\mathrm{c}\mathrm{i}\mathrm{e}\mathrm{s} \mathrm{a}\mathrm{t} \mathrm{a} \mathrm{p}\mathrm{l}\mathrm{o}\mathrm{t}}}\times 100\mathrm{\%}$$

$${\mathrm{R}\mathrm{F}}_{\mathrm{i}}(\mathrm{\%})={\displaystyle \frac{\mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r} \mathrm{o}\mathrm{f} \mathrm{s}\mathrm{u}\mathrm{b}\mathrm{p}\mathrm{l}\mathrm{o}\mathrm{t}\mathrm{s} \mathrm{w}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e} \mathrm{i} \mathrm{s}\mathrm{p}\mathrm{e}\mathrm{c}\mathrm{i}\mathrm{e}\mathrm{s} \mathrm{f}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{d}}{\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{f}\mathrm{r}\mathrm{e}\mathrm{q}\mathrm{u}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{y} \mathrm{o}\mathrm{f} \mathrm{a}\mathrm{l}\mathrm{l} \mathrm{s}\mathrm{p}\mathrm{e}\mathrm{c}\mathrm{i}\mathrm{e}\mathrm{s} \mathrm{a}\mathrm{t} \mathrm{a} \mathrm{p}\mathrm{l}\mathrm{o}\mathrm{t}}}\times 100\mathrm{\%}$$

$${\mathrm{R}\mathrm{D}\mathrm{o}}_{\mathrm{i}}\mathrm{\%}={\displaystyle \frac{\mathrm{B}\mathrm{a}\mathrm{s}\mathrm{a}\mathrm{l} \mathrm{a}\mathrm{r}\mathrm{e}\mathrm{a} \mathrm{o}\mathrm{f} \mathrm{i} \mathrm{s}\mathrm{p}\mathrm{e}\mathrm{c}\mathrm{i}\mathrm{e}\mathrm{s}}{\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{b}\mathrm{a}\mathrm{s}\mathrm{a}\mathrm{l} \mathrm{a}\mathrm{r}\mathrm{e}\mathrm{a} \mathrm{o}\mathrm{f} \mathrm{a}\mathrm{l}\mathrm{l} \mathrm{i}\mathrm{n}\mathrm{d}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{d}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{s} \mathrm{o}\mathrm{f} \mathrm{a}\mathrm{l}\mathrm{l} \mathrm{s}\mathrm{p}\mathrm{e}\mathrm{c}\mathrm{i}\mathrm{e}\mathrm{s} \mathrm{a}\mathrm{t} \mathrm{a} \mathrm{p}\mathrm{l}\mathrm{o}\mathrm{t}}}\times 100\mathrm{\%}$$

$${\mathrm{I}\mathrm{V}\mathrm{I}}_{\mathrm{i}}=\mathrm{R}\mathrm{D}+\mathrm{R}\mathrm{F}+\mathrm{R}\mathrm{D}\mathrm{o}$$

Species diversity was assessed using the Shannon–Wiener index (H’), which quantifies species heterogeneity within a community. Species diversity was calculated using the following formula:

$$\mathrm{H}\mathrm{’}=-\sum {\mathrm{P}}_{\mathrm{i}}\mathrm{l}\mathrm{n}{\mathrm{P}}_{\mathrm{i}}$$

where H’ is the value of Shannon–Wiener diversity index; P_i is the proportion of individuals of species relative to the total number of individuals; and ln denotes the natural logarithm of P_i. The following scores were used for the standard assessment [18]:

• H’ ≤ 1 = Low diversity;
• 1 > H’ < 3 = Intermediate diversity;
• H’ ≥ 3 = High diversity.

The richness index (R) was calculated to compare biodiversity among different areas or to track changes in biodiversity over time within a specific area. The evenness index (E) was calculated to determine how evenly individuals were distributed among other species within a community. The Simpson’s dominance index (D) was calculated to understand how evenly individuals in a community were distributed among different species. The results of all indices were compared to each subdistrict using the formulas in

Table 2. Mathematical formulas and assessment score for richness (R), evenness (E), and Simpson’s dominance (D) indices.

Formula	Abbreviation	Assessment Score
$R={\displaystyle \frac{S-1}{\ln N}}$	R = Index of richness	R $\le$ 3.5	=	Low richness
	S = number of species in study area	3.5 $>$ R $<$ 5	=	Intermediate richness
	N = total number of all species in study area	R $\ge$ 5.0	=	High richness [18]
$E={\displaystyle \frac{H^{’}}{\ln S}}$	E = index of evenness	0 $<$ E $\le$ 0.4	=	Low evenness
	$H^{’}$ = index of diversity	0.4 $>$ E $\le$ 0.6	=	Intermediate evenness
	S = number of species in study area	0.6 $>$ E $\le$ 1.0	=	High evenness [19]
$D=\sum {\displaystyle \frac{n_i}{N}}$	D = Index of dominance by Simpson	0 $<$ D $\le$0.5	=	Low dominance
	$n_i$ = number of individuals of species	0.5 $>$ D $\le$ 0.75	=	Intermediate dominance
	$N$ = total number of individuals	0.75 $>$ D $\le$ 1.0	=	High dominance [20]

. These indices are independent of the total sampling area, allowing valid comparisons among the subdistricts.

2.4. Estimation of Above- and Belowground Biomass and Carbon Stock

The estimation of biomass and carbon stock is a critical component in providing information on forest structure (e.g., tree size and stand density) and quantifying the value and contribution of natural mangrove forests to carbon sequestration and storage. These estimations provide information for evaluating the role of Probolinggo Regency’s natural mangrove forests within global carbon pools.

All mangrove individuals with a DBH ≥ 5 cm were included in the estimation of above and belowground biomass and carbon stock. Aboveground biomass was estimated using allometric equations developed by Chave et al. 2005 [21], while belowground biomass was estimated using equations proposed by Komiyama et al. 2005 [22]. These equations were selected because of their broad applicability to diverse mangrove species, many of which occur in the study area. Wood density ($\rho$) values were obtained from the Global Wood Density Database [23], International Tropical Timber Organization (ITTO), Komiyama et al. (2005) [22], and Kauffman and Donato (2012) [24]. Total above- and belowground biomass was obtained by summing the biomass of all measured trees within each subdistrict, and the results were expressed on a per-hectare basis (${\mathrm{M}\mathrm{g} \mathrm{h}\mathrm{a}}^{-1}$). Carbon stock was estimated by applying a carbon conversion factor to the total biomass and was expressed in megagrams of carbon per hectare ${(\mathrm{M}\mathrm{g} \mathrm{C} \mathrm{h}\mathrm{a}}^{-1})$ [24,25]. Additionally, carbon values were converted into carbon dioxide equivalents (CO₂eq) and reported in ${\mathrm{M}\mathrm{g} {\mathrm{C}\mathrm{O}}_2 \mathrm{h}\mathrm{a}}^{-1}$ to reflect the potential climate mitigation value of the mangrove forests. The equations for estimating the biomass and carbon stocks are as follows:

$$\mathrm{A}\mathrm{G}\mathrm{B}=\mathsf{\rho }\times \mathrm{e}\mathrm{x}\mathrm{p}(-1.349+1.980\ln \left(\mathrm{D}\right)+0.207{\left(\ln \left(\mathrm{D}\right)\right)}^2-0.00281\left(\ln {(\mathrm{D}))}^3\right)$$

$$\mathrm{B}\mathrm{G}\mathrm{B}=0.199{\mathsf{\rho }}^{0.899}{\mathrm{D}}^{2.22}$$

$$\mathrm{T}\mathrm{G}\mathrm{B}=\mathrm{A}\mathrm{G}\mathrm{B}+\mathrm{B}\mathrm{G}\mathrm{B}$$

$$\mathrm{A}\mathrm{G}\mathrm{C}=\mathrm{A}\mathrm{G}\mathrm{B}\times 0.47$$

$$\mathrm{B}\mathrm{G}\mathrm{C}=\mathrm{B}\mathrm{G}\mathrm{B}\times 0.39$$

$$\mathrm{T}\mathrm{G}\mathrm{C}=\mathrm{A}\mathrm{G}\mathrm{C}+\mathrm{B}\mathrm{G}\mathrm{C}$$

$${\mathrm{C}\mathrm{O}}_2\mathrm{e}\mathrm{q}=\mathrm{T}\mathrm{G}\mathrm{C}\times 3.67$$

• AGB: aboveground biomass (${\mathrm{M}\mathrm{g} \mathrm{h}\mathrm{a}}^{-1}$).
• BGB: belowground biomass (${\mathrm{M}\mathrm{g} \mathrm{h}\mathrm{a}}^{-1}$).
• TGB: total of above- and belowground biomass (${\mathrm{M}\mathrm{g} \mathrm{h}\mathrm{a}}^{-1}$).
• AGC: aboveground carbon stock ${(\mathrm{M}\mathrm{g} \mathrm{C} \mathrm{h}\mathrm{a}}^{-1})$.
• BGC: belowground carbon stock ${(\mathrm{M}\mathrm{g} \mathrm{C} \mathrm{h}\mathrm{a}}^{-1})$.
• TGC: total of above- and belowground carbon stock ${(\mathrm{M}\mathrm{g} \mathrm{C} \mathrm{h}\mathrm{a}}^{-1})$.
• ${\mathrm{C}\mathrm{O}}_2\mathrm{e}\mathrm{q}$: amount of carbon dioxide (${\mathrm{M}\mathrm{g} \mathrm{C} \mathrm{h}\mathrm{a}}^{-1}$).

2.5. Data Analysis

Species diversity indices and compositions were calculated of each subdistrict and compared to assess community structure and species dominance patterns. Biomass and carbon stock estimation were compared to each of the subdistricts to evaluate the capacity of natural mangrove forests in each subdistrict to sequester and store carbon. Both integrated datasets allowed the structural attributes (species diversity and composition) to align directly with ecosystem functions (biomass production and carbon stocks), thereby strengthening the ecological assessment of natural mangrove forests.

3. Results

3.1. Species Taxonomy

Table 3. List of mangrove species observed in the natural mangrove forests of Probolinggo Regency.

Common Name		Taxonomical Classification
Local	English	Class	Order	Family	Genus	Species
Bakau	Spotted mangrove	Equisetopsida	Malpighiales	Rhizophoraceae	Rhizophora	Rhizophora stylosa
Bakau minyak	Tall-stilt mangrove	Equisetopsida	Malpighiales	Rhizophoraceae	Rhizophora	Rhizophora apiculata
Bakau hitam	Red mangrove	Equisetopsida	Malpighiales	Rhizophoraceae	Rhizophora	Rhizophora mucronata
Api-api putih	Grey mangrove	Equisetopsida	Lamiales	Acanthaceae	Avicennia	Avicennia marina
Api-api	White mangrove	Equisetopsida	Lamiales	Acanthaceae	Avicennia	Avicennia alba
Pidada	Mangrove apple	Equisetopsida	Myrtales	Lythraceae	Sonneratia	Sonneratia alba
Pidada merah	Mangrove apple	Equisetopsida	Myrtales	Lythraceae	Sonneratia	Sonneratia caseolaris
Tanjang/Tumu	Oriental mangrove	Equisetopsida	Malpighiales	Rhizophoraceae	Rhizophora	Bruguiera gymnorrhiza
Nyiri	Cannonball mangrove	Equisetopsida	Sapindales	Meliaceae	Xylocarpus	Xylocarpus granatum
Buta-buta	Milky mangrove	Equisetopsida	Malpighiales	Euphorbiaceae	Excoecaria	Excoecaria agallocha
Gigi gajah	River mangrove/black mangrove	Equisetopsida	Ericales	Primulaceae	Aegiceras	Aegiceras corniculatum
Tengar	Indian mangrove	Equisetopsida	Malpighiales	Rhizophoraceae	Rhizophora	Ceriops tagal

lists the 12 mangrove species identified in the natural mangrove forests along the coastline of Probolinggo Regency. These species belong to six plant families: Rhizophoraceae, Acanthaceae, Lythraceae, Meliaceae, Euphorbiaceae, and Primulaceae. Among these, Rhizophoraceae had the highest species richness, followed by Acanthaceae and Lythraceae. Meliaceae, Euphorbiaceae, and Primulaceae were each represented by a single species. All taxonomic classifications were verified using the Plants of the World Online database (https://powo.science.kew.org, accessed on 28 December 2025) and relevant botanical literature.

3.2. Species Distribution

Among the 12 species, A. marina and R. mucronata were the most dominant in all subdistricts, followed by A. alba which was absent in the Pajarakan subdistrict (

Table 4. Species distribution in each subdistrict. Plus (+) and minus (−) signs represent the existed and not-existed mangrove species, respectively.

No	Species	Subdistricts
		Kraksaan	Pajarakan	Gending	Kademangan	Mayangan	Dringu	Sumberasih	Tongas
1	R. stylosa	+	+	+	+	−	+	−	+
2	R. apiculata	−	+	+	−	−	−	−	−
3	R. mucronata	+	+	+	+	+	+	+	+
4	B. gymnorrhiza	+	+	+	−	−	+	−	+
5	A. marina	+	+	+	+	+	+	+	+
6	A. alba	+	−	+	+	+	+	+	+
7	S. alba	+	+	+	+	−	−	−	−
8	S. caseolaris	+	−	−	−	−	−	−	−
9	X. granatum	−	−	−	−	−	−	−	+
10	E. agallocha	−	−	−	−	−	−	−	+
11	A. corniculatum	−	−	−	−	−	−	−	+
12	C. tagal	−	−	−	−	−	−	−	+
	Total species	7	6	7	5	3	5	3	9

). R. stylosa was also found in most subdistricts but was absent in Mayangan and Sumberasih. Except for R. apiculata, species within the genera Rhizophora and Avicennia were the most abundant across the study area.

Although B. gymnorrhiza and S. alba were less dominant than Rhizophora and Avicennia spp., four species—X. granatum, E. agallocha, A. corniculatum, and C. tagal—were scarce and occurred only in the Tongas subdistrict. The total number of species found in Kraksaan and Gending was the same (seven species), while six species were found in Pajarakan, and five species were found in Kademangan and Dringu. Mayangan and Sumberasih had the smallest number of total species (three species), and Tongas had the highest number of species (nine species). No clear east to west gradient in species richness was observed across Probolinggo Regency. However, eastern subdistricts generally exhibited moderate species richness compared with western subdistricts, with Tongas being a notable exception.

3.3. Species Composition

Mangrove stand structure across Probolinggo Regency was dominated by the sapling stage, indicating an early phase of forest regeneration (Figure 4). The tree stage was scarce, and the pole stage was at an intermediate level. Among all the subdistricts, only Tongas and Sumberasih showed no tree stands (0%), with the highest predominance of the sapling stage (96.4% and 85.7%, respectively) (Figure 4). The two subdistricts are located west of Probolinggo Regency. The Mayangan and Kademangan subdistricts showed low tree proportions (2.4% and 1.8%, respectively), with saplings representing the dominant growth stage (83.9% and 79.2% for Kademangan and Mayangan, respectively). Moving eastward, Gending exhibited a lower proportion of tree-stage individuals than Dringu; however, no subdistricts had tree-stage proportions exceeding 20%.

Pole-stage proportions varied among subdistrics without a consistent east–west pattern. Tongas exhibited the lowest proportion of pole-stage individuals (3.6%), whereas Gending exhibited the highest (39.4%) (Figure 4). None of the subdistricts showed pole-stage dominance exceeding 50%. These results support the fact that natural mangrove forests in Probolinggo Regency are in the early stages of development.

For each species, large variations in stand density at each developmental stage were recognized in all subdistricts (

Table 5. Mean value of sapling, pole, and tree density (stands. ha⁻¹) in each subdistrict of Probolinggo Regency, Indonesia. The N/A represents non-existent individuals of the related species in the subdistrict.

Parameter	Subdistricts
	Kraksaan	Pajarakan	Gending	Dringu	Kademangan	Mayangan	Sumberasih	Tongas	Total
Sapling density (stands. ha−1)
R. stylosa	95	230	42	54	N/A	N/A	N/A	100	521
R. apiculata	N/A	5	25	N/A	N/A	N/A	N/A	N/A	30
R. mucronata	65	150	350	246	175	408	358	150	1903
B. gymnorrhiza	5	40	N/A	4	183	N/A	N/A	N/A	233
A. marina	120	320	117	175	250	350	658	544	2534
A. alba	160	N/A	117	113	175	67	67	169	866
S. alba	25	15	N/A	13	N/A	N/A	N/A	13	65
S. caseolaris	10	N/A	N/A	N/A	N/A	N/A	N/A	N/A	10
X. granatum	N/A	N/A	N/A	N/A	N/A	N/A	N/A	19	19
A. corniculatum	N/A	10	N/A	N/A	N/A	N/A	N/A	175	185
C. tagal	N/A	N/A	N/A	N/A	N/A	N/A	N/A	19	19
Total density (stands. ha−1)	480	770	650	604	783	825	1083	1188
Pole density (stands. ha−1)
R. stylosa	15	5	17	N/A	25	N/A	N/A	N/A	62
R. apiculata	N/A	N/A	33	N/A	N/A	N/A	N/A	N/A	33
R. mucronata	60	N/A	192	13	58	67	83	13	485
B. gymnorrhiza	15	N/A	N/A	N/A	N/A	N/A	N/A	N/A	15
A. marina	50	60	142	67	8	8	17	13	364
A. alba	5	N/A	100	8	33	117	17	N/A	280
S. alba	55	50	N/A	4	8	N/A	N/A	N/A	118
S. caseolaris	30	N/A	N/A	N/A	N/A	N/A	N/A	N/A	30
X. granatum	N/A	N/A	N/A	N/A	N/A	N/A	N/A	19	19
Total density (stands. ha−1)	230	115	483	92	133	192	117	44
Tree density (stands. ha−1)
R. stylosa	10	N/A	N/A	N/A	N/A	N/A	No tree	No tree	10
R. apiculata	N/A	N/A	25	N/A	N/A	N/A			25
R. mucronata	10	N/A	25	4	N/A	8			48
B. gymnorrhiza	5	5	8	N/A	N/A	N/A			18
A. marina	10	20	8	67	N/A	8			113
A. alba	5	N/A	N/A	4	N/A	8			18
S. alba	60	150	25	42	17	N/A			293
S. caseolaris	5	N/A	N/A	N/A	N/A	N/A			15
Total density (stands. ha−1)	105	175	92	117	17	25	0	0

). During the sapling stage, the most dominant species in most subdistricts was A. marina (2534 stands ha⁻¹), followed by R. mucronata (1903 stands ha⁻¹), A. alba (866 stands ha⁻¹), and R. stylosa (521 stands ha⁻¹) (Table 4). A. marina and R. mucronata were found in all subdistricts, whereas A. alba was found only in Pajarakan, and R. stylosa was dominant in Pajarakan and absent in Kademangan, Mayangan, and Sumberasih. Tongas exhibited the highest sapling species richness, whereas S. caseolaris was the leas abundant species overall (10 stands ha⁻¹).

The pole-stage stand density was consistently lower than the sapling density across all subdistricts. R. mucronata dominated the pole stage (485 stands ha⁻¹), followed by A. marina (364 stands ha⁻¹) and A. alba (280 stands ha⁻¹). R. mucronata was found in most subdistricts but not in Pajarakan, A. marina was found in all subdistricts, and A. alba was found only in Pajarakan and Tongas. Other species were found in several subdistricts, whereas R. apiculata (33 stands ha⁻¹), B. gymnorrhiza, and X. granatum were found only in Kraksaan (15 stands ha⁻¹) and Tongas (19 stands ha⁻¹).

The tree stage had the lowest species density in all subdistricts, mainly in Tongas and Sumberasih, where no tree stands were found (Table 4). In the tree stage, S. alba was the most dominant species (293 stands ha⁻¹), followed by A. marina (118 stands ha⁻¹), and R. mucronata (48 stands ha⁻¹). Overall, the tree density results showed that the dominant species was Rhizophora with a high diversity density in each subdistrict.

3.4. Important Value Index (IVI)

Figure 5 shows the importance value index (IVI) of mangrove species across various subdistricts for the sapling, pole, and tree growth stages. During the sapling stage, R. mucronata consistently exhibited the highest IVI values across five subdistricts, followed by A. marina (Figure 4). This suggests that this species has a strong regeneration potential.

At the pole stage, IVI values were varied among species. R. mucronata had the highest IVI values in Gending (118.7), Kademangan (120.3), and Sumberasih (180.7), whereas A. marina had the highest IVI in Pajarakan (141.3) and Dringu (181.5). Furthermore, A. alba, S. alba, and X. granatum exhibited the highest IVI values in Mayangan (165.7), Kraksaan (80.0), and Tongas (118.5), respectively. This reflects a widespread distribution and competitive ability in the early-to-intermediate growth stages, which potentially brings diverse species to Probolinggo Regency’s mangrove forests. Conversely, species such as X. granatum, A. corniculatum, and E. agallocha were localized, with lower IVI values restricted primarily to Tongas and specific growth stages. These species likely play minor ecological roles or are constrained by site-specific environmental conditions. At the tree stage, S. alba had the highest IVI in most subdistricts, followed by A. marina (Figure 5).

3.5. Species Diversity, Evenness, and Richness Index

Table 6. Species diversity (H’), richness (R), evenness (E), richness, and dominance (C) indices in all subdistricts of Probolinggo Regency.

Subdistrict	H’	R	E	C
Kraksaan	1.8 (medium)	1.2 (low)	0.9 (high)	0.2 (low)
Pajarakan	1.5 (medium)	1.1 (low)	0.8 (high)	0.3 (low)
Gending	1.4 (medium)	1.2 (low)	0.7 (high)	0.3 (low)
Dringu	1.4 (medium)	0.9 (low)	0.8 (high)	0.3 (low)
Kademangan	1.5 (medium)	0.8 (low)	0.9 (high)	0.2 (low)
Mayangan	1.0 (low)	0.4 (low)	0.9 (high)	0.4 (low)
Sumberasih	0.9 (low)	0.4 (low)	0.8 (high)	0.5 (low)
Tongas	1.6 (medium)	1.5 (low)	0.7 (high)	0.3 (low)
Total	1.7 (medium)	1.5 (low)	0.7 (high)	0.2 (low)

provides ecological indices—species diversity (H’), richness (R), evenness (E), and dominance (C)—for mangrove communities across eight subdistricts in Probolinggo Regency. These indices provide a comprehensive overview of the ecological complexity and balance of the mangrove ecosystems in each area. Overall, species diversity (H’) ranges from 0.9 to 1.8, classifying most subdistricts in the medium diversity category. Kraksaan exhibited the highest diversity (1.8), indicating a balanced and variable species composition. In contrast, Mayangan and Sumberasih showed the lowest diversity (1.0 and 0.9, respectively), suggesting lower ecological heterogeneity, likely owing to the dominance of one or a few species.

Species richness (R), which reflects the number of species present regardless of their abundance, varied across sites. The species richness index was low in all subdistricts (Table 6). Tongas had the highest richness value (1.5), indicating the presence of a relatively large number of species. Mayangan (0.4) and Sumberasih (0.4) had the lowest species richness, further supporting their low biodiversity status.

Evenness (E), representing the distribution of individuals among species, showed moderate variation among subdistricts. Most subdistricts had evenness values between 0.7 and 0.9. Gending and Tongas had the lowest evenness values (0.7), whereas Kraksaan, Kademangan, and Mayangan exhibited the highest values (0.9). This suggests that, despite differences in species richness, individuals were generally evenly distributed among species.

Notably, the dominance index (C) remained consistently low across all subdistricts (0.2–0.5), indicating that no single species overwhelmingly dominated the communities. However, Mayangan (0.4) and Sumberasih (0.5) still showed relatively higher dominance despite low diversity, which is consistent with the observed dominance of A. marina in these areas.

3.6. Estimation of Biomass and Carbon Stock

Table 7. Estimation of biomass and carbon stock of above- and belowground biomass in each subdistrict of Probolinggo Regency. Abbreviations: Aboveground biomass (AGB), belowground biomass (BGB), aboveground carbon stock (AGC), belowground carbon stock (BGC).

Site	AGB			BGB			Total Biomass			AGC			BGC			Total Carbon			Total CO2
	(Mg ha−1)			(Mg ha−1)			(Mg ha−1)			(Mg ha−1)			(Mg C ha−1)			(Mg C ha−1)			(Mg CO2 ha−1)
Kraksaan	579.8	±	168	320.5	±	89.7	900.3	±	257.8	278.3	±	80.7	125.0	±	35.0	403.3	±	115.7	1480.1	±	424.5
Pajarakan	732.5	±	224	343.2	±	132.4	1075.7	±	350.7	270.6	±	64.4	100.2	±	32.1	370.8	±	92.1	1360.8	±	337.9
Gending	595.1	±	178	325.0	±	92.6	920.2	±	270.4	285.7	±	85.4	126.8	±	36.1	412.4	±	121.5	1513.6	±	445.8
Dringu	749.0	±	251	380.9	±	116.5	1129.9	±	367.5	359.5	±	120.6	148.6	±	45.4	508.1	±	165.9	1864.7	±	609.0
Kademangan	273.4	±	136	158.8	±	63.8	432.1	±	199.7	131.2	±	65.2	61.9	±	24.9	193.1	±	90.1	708.8	±	330.7
Mayangan	302.3	±	114	178.1	±	64.7	480.4	±	178.3	145.1	±	54.7	69.5	±	25.2	214.6	±	79.8	787.5	±	292.8
Sumberasih	200.1	±	75.5	131.3	±	46.8	331.4	±	122.2	96.0	±	36.2	51.2	±	18.2	147.2	±	54.5	540.4	±	199.9
Tongas	92.7	±	30.4	63.1	±	20.6	155.8	±	51.0	44.5	±	14.6	24.6	±	8.0	69.1	±	22.6	253.7	±	83.0
All	440.6	±	89.6	237.6	±	41.8	678.2	±	131.1	201.4	±	39.3	88.5	±	15.3	289.8	±	54.5	1063.7	±	199.9

summarizes the aboveground biomass (AGB), belowground biomass (BGB), total biomass, and the corresponding carbon stock and carbon dioxide (CO₂) equivalents across various subdistricts in Probolinggo Regency. These metrics are essential for evaluating the role of mangrove forests in carbon sequestration and climate change mitigation.

Dringu exhibited the highest total biomass (1129.9 Mg ha⁻¹), comprising 749.0 Mg ha⁻¹ AGB and 380.9 Mg ha⁻¹ BGB. Consequently, Dringu had the highest total carbon stock (508.1 Mg C ha⁻¹) and CO₂ equivalent (1864.7 Mg CO₂ ha⁻¹), highlighting its critical role in carbon storage. Pajarakan and Gending also exhibited high biomass and carbon stocks. Pajarakan exhibited a total biomass of 1075.7 Mg ha⁻¹ and stores of 370.8 Mg C ha⁻¹, equivalent to 1360.8 Mg CO₂ ha⁻¹. Gending followed with 920.2 Mg ha⁻¹ biomass and the second-highest carbon stock (412.4 Mg C ha⁻¹), corresponding to 1513.6 Mg CO₂ ha⁻¹. In contrast, Tongas and Sumberasih had the lowest biomass and carbon stock values. Tongas had the lowest total biomass (155.8 Mg ha⁻¹), resulting in a modest carbon stock of 69.1 Mg C ha⁻¹ and 253.7 Mg CO₂ ha⁻¹, while Sumberasih has slightly higher values at 331.4 Mg ha⁻¹, 147.2 Mg C ha⁻¹, and 540.4 Mg CO₂ ha⁻¹. Across all subdistricts the average total biomass was 678.2 Mg ha⁻¹, compromising 440.6 Mg ha⁻¹ AGB and 237.6 Mg ha⁻¹ BGB. This corresponds to an average total carbon stock of 289.8 Mg C ha⁻¹ and an estimated 1063.7 Mg CO₂ ha⁻¹ sequestered.

Although the total biomass and carbon stocks showed varied values among subdistricts, these differences were not statistically significant (p total biomass = 0.21; p total carbon stock = 0.16) (see: Supplementary Materials S2). This indicates that the similarity of species composition and degradation history plays an important role in accumulating the total biomass and carbon stocks among subdistricts.

4. Discussion

The study indicated that mangrove species diversity in Probolinggo Regency is relatively low to moderate, with abundance varying across subdistricts. A. marina and R. mucronata consistently exhibited the highest IVI, emphasizing their dominance and underscoring the need for species enrichment across the subdistricts. Although Probolinggo Regency has considerable blue carbon potential, its mangrove carbon stock remains within the lower range of national estimates (average 289.8 Mg C ha⁻¹).

4.1. Ecological Significance and Species Dominance

Mangrove communities of Probolinggo Regency are largely structured by the dominance of A. marina and R. mucronata. Their dominance defines the current structure of these natural mangrove forests and reflects a transitional stage of succession along the northern coast of Java. Similar dominance patterns have been reported in neighboring regions such as Pasuruan and Madura [26,27,28,29], suggesting that this composition is characteristic of East Java’s coastal ecology. The prevalence of these two genera underscores their superior adaptability to dynamic coastal conditions, including high tides, strong currents, and variable soil textures.

This dominance pattern aligns with classical mangrove zonation and succession frameworks [1,26], in which Avicennia spp. typically colonize open, saline, and sandy substrates, followed by Rhizophora which settles in more protected and fine-grained sediments. The widespread abundance of A. marina, reaching up to 2534 stands ha⁻¹, demonstrates its tolerance to salinity, desiccation, and wave exposure. Such adaptability allows the species to thrive in physically demanding coastal settings, which is consistent with reports from arid or semi-arid mangrove systems in Indonesia, Pakistan, and China [30,31,32,33,34].

Beyond its ecological role, A. marina also has socioeconomic value. Its roots harbor nitrogen-fixing bacteria, which enhance nutrient availability and support interspecific growth [35,36,37,38,39]. The seeds are locally used as flour, reflecting cultural adaptation to mangrove resources and providing an alternative income source for the community. Meanwhile, R. mucronata and R. stylosa, with respective densities of 1903 and 521 stands ha⁻¹, are frequently prioritized for rehabilitation in the area owing to their stilt-root systems, which effectively trap sediments and stabilize muddy substrates [40,41].

Collectively, Avicennia and Rhizophora spp. likely played important roles in early mangrove forest development, with Avicennia acting as a pioneer and Rhizophora as a structural consolidator. Therefore, both genera should be incorporated into restoration programs, with species selection tailored to site-specific conditions and socioeconomic needs. However, to enhance habitat heterogeneity and future resource potential, planting other taxa that are found in the Probolinggo Regency, such as X. granatum, A. corniculatum, E. agallocha, and C. tagal is recommended for medicinal and industrial applications [42,43,44,45,46].

4.2. Presumable Gradient Pattern and Environmental Drivers

Distinct east–west ecological gradients were observed along the Probolinggo coastline. The western subdistricts tended to exhibit higher species richness (Tongas) but lower tree density (Tongas, Sumberasih, Mayangan, and Kademangan), whereas the eastern subdistricts (Dringu, Gending, Pajarakan, and Kraksaan) supported taller, denser stands with greater biomass. This pattern is likely driven by environmental filtering associated with coarse sandy sediments in the west and fine riverine clay sediments in the east, consistent with findings from East Java and broader Southeast Asia [47,48,49].

Sandy soils in the western subdistricts, often derived from the volcanic materials of Mount Bromo and reworked by monsoonal runoff [26], promote species turnover but restrict root anchorage and seedling survival. This results in low tree density and high species richness. In contrast, clay-rich eastern subdistricts foster more favorable hydrology and nutrient retention, resulting in denser stands and higher aboveground biomass. Although this study did not directly assess soil substrate differences among subdistricts, future research should explicitly evaluate substrate characteristics and the effect of land conversion adjacent to mangrove forests. Our findings demonstrate the disturbance–succession continuum [50], in which varying exposure to hydrodynamic and anthropogenic stress produces different successional outcomes.

Anthropogenic pressure further accentuates these patterns. Western and urban subdistricts such as Mayangan and Kademangan exhibited lower tree density and diversity (H’ ≤ 1.0), likely owing to domestic and industrial waste discharge, which alter sediment chemistry and nutrient balance [1]. In contrast, the eastern subdistricts exhibited moderate diversity (H’ = 1.4–1.8) and greater biomass, suggesting ecological recovery toward more stable community states.

As in many coastal regions of Indonesia, mangroves in Probolinggo Regency face increasing pressure from land conversion for aquaculture. These activities alter hydrology, reduce sediment supply, and enhance erosion and pollution, leading to poor regeneration and soil degradation [51,52]. The conditions observed in Tongas, where species richness remained high but regeneration was weak, were consistent with such disturbances. This underscores the need for long-term monitoring of soil–vegetation dynamics and the influence of neighboring intact mangrove forests.

4.3. Evidence of Early Successional and Degraded Structure

The demographic structure of the observed stands provided strong evidence of early- to mid-successional stages. Saplings comprised more than 80% of the total individuals, whereas mature trees accounted for less than 10%. This imbalance has been widely reported as a hallmark of mangrove regeneration after disturbances, such as logging, hydrological alteration, or sediment stress [53]. The absence of mature trees limits essential ecological functions for shoreline protection, carbon sequestration, and faunal habitat provisioning, and reflects ongoing stress from anthropogenic activities in urbanized western subdistricts.

Therefore, classifying these mangroves as being “in a potential of ecologically degraded condition” is justified. The dominance of juvenile stands and their low structural diversity indicate heightened vulnerability to further degradation. Although species richness was low, evenness remained relatively high (E = 0.7–0.9), suggesting community homogenization and reduced functional diversity—conditions that increase sensitivity to climate-related stressors such as sea-level rise and storm surges [3,4].

Important Value Index (IVI) patterns support these findings. A. marina and R. mucronata consistently exhibited the highest IVI values across growth stages, reflecting their resilience to fluctuating salinity and sediment regimes. In contrast, other species such as B. gymnorrhiza, X. granatum, and C. tagal maintained moderate and uniform IVIs across subdistricts [51,54]. The prevalence of saplings with high IVI values further demonstrated an active but incomplete regeneration process, emphasizing the need for restoration in degraded western zones and conservation activities in all existing natural mangrove forests.

4.4. Carbon Stock and Implications for Blue Carbon Frameworks

Despite these structural constraints, mangrove forests in Probolinggo Regency possess considerable blue carbon potential. Mean total carbon stock was 289.8 Mg C ha⁻¹, with the highest value recorded in Dringu (508.1 Mg C ha⁻¹) and the lowest in Tongas (69.1 Mg C ha⁻¹). These values fall within the global ranges for Indo-Pacific mangroves [7] and the lower bound of national estimates for Indonesian mangroves (360–450 Mg C ha⁻¹) [55]. Spatial variation in carbon stocks reflects differences in forest maturity and substrate conditions, with higher proportions of mature trees in Dringu and Pajarakan corresponding to greater biomass accumulation and carbon storage [56].

Western subdistricts exhibited lower carbon stocks, aligning with the dominance of saplings and limited presence of mature trees. Similar patterns have been reported in other East Java regions such as Lamongan [57] and Pasuruan [58]. Nonetheless, even partially degraded mangroves retain a significant carbon storage capacity, supporting Indonesia’s carbon mitigation goals under the Paris Agreement [25] and emphasizing the importance of maintaining existing mangroves. Restoring degraded stands, especially in the western coastal areas, may enhance biomass and carbon stock up to 73% of intact forest values ~20 years after planting [59].

4.5. Regional and Theoretical Synthesis

In a broader context, the mangrove forests of Probolinggo Regency exemplify the ecological homogenization observed along Java’s northern coast, where recurrent disturbances simplify the community structure while maintaining moderate species diversity [60]. This trade-off between persistence and specialization under anthropogenic pressure has also been observed in other tropical mangrove systems [2,4,61,62]. The soil substrate is likely a key driver of species diversity and limited regeneration; however, its influence requires explicit evaluation, particularly in relation to the effect of neighboring intact mangrove areas. By integrating species-level diversity metrics with carbon estimates, this study bridges the gap between structural and functional ecology by showing how recovering mangroves play a role in climate regulation and shoreline stability. These insights contribute to the regional discourse on nature-based solutions and blue carbon management in Southeast Asia.

This study suggests that restoration and management should be site specific. Eastern subdistricts with more mature stands and higher biomass should prioritize conservation and assisted natural regeneration. In contrast, western subdistricts experiencing greater degradation require active restoration interventions to restore structural complexity and ecological resilience [46]. At the policy level, integrating these ecological findings into Indonesia’s National Mangrove Rehabilitation Plan (2021–2024) and the Blue Carbon Initiative could yield measurable progress toward Sustainable Development Goals 13, 14, and 15. The dataset presented in this study provides a robust baseline for tracking restoration success, carbon accounting, and biodiversity recovery along the Java coastline and beyond.

Overall, the mangrove forests of Probolinggo Regency represent ecosystems in transitional recovery from past degradation, yet they retain significant ecological and climatic importance. Integrating structural and functional data clarifies how soil texture, disturbance history, and species adaptability influence regeneration pathways. By connecting local patterns to regional succession theory and global blue carbon frameworks, this study enhances our understanding of mangrove resilience and reinforces the urgency for evidence-based, community-engaged restoration strategies. These implications extend beyond Probolinggo, offering insights into the recovery pathways of semi-arid mangroves across Java’s northern coast and comparable Indo-Pacific regions. This study is limited by its reliance on a single temporal snapshot and the use of allometric equations to estimate above- and belowground carbon stocks, excluding soil organic carbon and other belowground components, which may lead to underestimation of total carbon stocks in the ecosystem.

5. Conclusions

Natural mangrove forests in Probolinggo Regency exhibit pronounced spatial variation in species composition, stand structure, and ecosystem function. Several species were present in only one subdistrict, and only two species were dominant in all subdistricts, indicating the need for targeted species-enrichment planting. Mangrove stands were generally dominated by saplings, suggesting active natural regeneration and historical degradation. A restoration program with intensive monitoring and evaluation is recommended to ensure forest maturity and high productivity rates. This is also crucial for improving the substantial variation in carbon stock estimation among subdistricts, mainly Kademangan and Tongas (western subdistricts), which have the lowest biomass and carbon stock values. This study is limited to single-time survey, allometric biomass and carbon stock estimations, and no soil organic carbon has been included. Therefore, it is highly recommended to conduct more frequent vegetation surveys to assess regeneration rates and the success of restoration programs on carbon stock regain. Overall, the integrated assessment of species diversity, composition, biomass, and carbon stocks highlight the significant ecological value of Probolinggo’s natural mangrove forests, while also demonstrating the need for more intensive management practices to improve the conservation and restoration success rate.