Quantification of Carbon Flux Patterns in Ecosystems: A Case Study of Prince Edward Island

Abstract

Mitigating climate change by reducing heat-trapping greenhouse gas (GHG) emissions in the Earth’s atmosphere is a critical global challenge. In response to this urgency, the Canadian government has set a target of achieving zero emissions by 2050. The Government of Prince Edward Island (PEI) has committed to becoming Canada’s first net-zero province by 2040. Achieving this goal requires an extensive knowledge of emissions arising from ecosystem dynamics in PEI. Therefore, this study aims to quantify the carbon fluxes of these ecosystems, offering insights into their role in GHG emissions and removals. Through an extensive literature review and analysis, this research provides a detailed assessment of the potential carbon flux contributions from various ecosystems across PEI. High-resolution maps for carbon emissions, removals, and flux for the years 2010 and 2020 were developed, highlighting key findings on carbon dynamics. Additionally, a web-based tool was developed to allow decision makers and the general public to explore these carbon flux maps interactively. This work aims to inform policy decisions and enhance strategies for effective climate change mitigation in PEI.

1. Introduction

Greenhouse gas (GHG) emissions from different land use and management practices contribute to almost twenty-five percent of human-caused global emissions [1,2]. Carbon dioxide (CO₂) emissions within this sector arise from different agricultural and natural ecosystems, often due to land conversion activities such as farming, deforestation, and peatland drainage [3,4,5]. These activities have been responsible for approximately 4–5 Gt of CO₂ annually in recent years, according to [6]. Recognized by both the Intergovernmental Panel on Climate Change (IPCC) reports and the Paris Agreement, the role of forests and other natural ecosystems in mitigating climate change is indispensable. Carbon flux refers to the movement of carbon in and out of various carbon reservoirs within an ecosystem, including the atmosphere, soil, vegetation, and water bodies. It quantifies the rate at which carbon is exchanged between these reservoirs, often measured in units of mass per area per time (e.g., grams of carbon per square meter per year). Understanding carbon flux is essential for assessing the carbon balance of ecosystems and their role in mitigating climate change. However, accurately monitoring the levels of atmospheric greenhouse gases (GHGs) presents a significant challenge [7]. A study by Yadav et al. (2022) assessed C storage and CO₂ fluxes in the tropical dry deciduous forests of southern Haryana, India, calculating above- and below-ground biomass and soil carbon storage [8]. The results revealed forests showing a high potential of 3.55 to 4.35 MgCha⁻¹ y⁻¹ for atmospheric CO₂ reduction. Were et al. (2021) investigated CO₂ and CH₄ fluxes in a Ugandan freshwater wetland under different vegetation communities during dry and wet seasons [9]. Water level was the main factor affecting gas fluxes, with annual emissions estimated at 159.5 to 180.2 million tonnes of CO₂ and 2.8 to 3.6 million tonnes of CH₄ from Uganda’s wetlands. These natural ecosystems can act as both sources and sinks of GHGs; for example, by emitting carbon through processes such as deforestation and absorbing it via photosynthesis [10,11,12].

This duality of roles means that they can simultaneously contribute to both the increase and decrease in atmospheric GHG levels depending on the balance of emissions and removals within a given area [13]. This balance is influenced by various factors, including the occurrence of natural disturbances, management practices, and land use dynamics, all of which can vary significantly across different regions and over time [14,15,16,17]. The influence of these factors is often more dynamic and occurs on finer spatiotemporal scales [18]. Local-scale climate change mitigation initiatives are essential to reach the global net-zero targets [19]. Changes in land use and land cover (LULC) have an impact on how various ecosystems participate in the carbon cycle [20,21]. In 2018, PEI’s legislative assembly adopted a GHG reduction target. To attain the net zero emission targets by 2040, PEI’s government must specifically recognize how distinct ecosystems contribute to the province’s overall GHG emissions [22]. Prince Edward Island (PEI) experienced an increase of 2.8% in GHG emissions in 2021 compared to the previous year (Government of PEI, 2003 [23]). As a result, a thorough understanding of carbon pathways over time and the factors influencing the resilience and carbon sequestration capacity of various ecosystems must be established. The gap in spatiotemporal information on GHG measurement over PEI is one of the major climate mitigation targets [24].

This is considered one of the current gaps in PEI since there is inadequate information about carbon emissions for the province’s ecosystems. Addressing these gaps, however, is critical for understanding carbon dynamics at the local level, which informs effective policy and management strategies. The main objectives of this research are to (i) quantify the emission and removal factors for each different ecosystem and (ii) develop high-resolution carbon emission, removal, and flux maps over PEI. The anticipated results of this project will assist the PEI provincial government in better understanding GHG emissions and establishing adaptation measures considering climate change.

2. Data and Methods

2.1. Study Area

PEI is Canada’s smallest province, located on the east coast of Canada in the Gulf of St. Lawrence between latitudes 45°57′ and 47°04′ N and longitudes 61°55′ and 64°25′ W [25] (Figure 1). PEI has a total population of 158,000 people and a total area of 5620 km² [26,27]. The LULC types in PEI are generally dominated by cropland and mixed forest, covering 45% and 39% of the total land area, respectively (Government of PEI, 2003, [23]). In this research, ecosystems are classified into three different groups, including (i) forest, with a total area of 2500 km², (ii) wetlands (sand dunes, seasonally flooded flat, meadows, brackish marsh, salt marsh, deep marsh, wooded swamp, shrub swamp, and bog), 395 km², and (iii) grass and shrubs, 216 km². Forest trees in PEI are abundant and account for around 43 different species, with Red Maple (33%) and White Spruce (17%) being the most prevalent trees growing here. Similarly, salt marshes (16%) and bogs (16%) are the primary types of wetlands; meanwhile, grass (95%) is far more predominant than shrubs (5%). PEI experiences a temperate climate that ranges from moderate to humid that is significantly influenced by winds, air masses, and weather systems traveling eastward from the mainland [27]. The average temperatures in January and July are −7 °C and 18.7 °C, respectively, and the island receives an average annual precipitation of 1100 mm, a quarter of which falls as snow. The number of days without frost ranges from 100 to 160, enabling the growth of a diverse array of crops [28].

2.2. Data Sources

LULC data for 2010 and 2020 were obtained from the Department of Environment, Energy & Climate Action (EECA). In particular, the LULC from 2010 is accessible via the Government of Prince Edward Island’s Open Data Portal (https://data.princeedwardisland.ca, accessed on 10 January 2024); however, the LULC in 2020 was internally granted by the EECA, given that it was not publicized during the time of conducting this research. Other datasets, such as emission and removal information, were derived from various sources.

2.3. Emission and Removal Factors

Table 1. Estimated emission and removal factors for different ecosystems in PEI.

Land Cover	Emission Factor (tCO2eha−1yr−1)	Removal Factor (tCO2eha−1yr−1)
Forest [29]
Alder	1.01	10.05
Austrian Pine	4.35	7.17
Aspen Provenance	0.00	11.14
Black Ash	1.09	10.18
Beech	0.79	10.89
Balsam Fir	2.32	10.10
Black Spruce	2.51	9.82
Clear Cut	8.55	5.65
Cedar	4.22	8.68
Corsican Pine	0.61	3.67
Douglas Fir	4.38	8.67
Dead Tree	15.39	3.85
European Birch	0.00	11.23
European Larch	0.69	7.12
Elm	0.65	10.83
Grey Birch	1.13	8.16
Hemlock	1.98	10.50
Hybrid Poplar	0.00	10.05
Hybrid Spruce	3.75	8.23
Japanese Larch	1.06	7.14
Jack Pine	2.75	10.52
Eastern Larch	2.64	9.46
Linden	0.00	9.09
Lodgepole Pine	3.62	10.45
Larch Provenance	0.00	6.72
Apple	0.71	10.78
Norway Spruce	1.70	6.08
Others	0.78	6.35
Pin Cherry	3.09	7.27
Poplar	1.93	9.90
Red Maple	1.91	10.08
Red Oak	8.87	6.31
Red Pine	2.69	8.32
Red Spruce	3.65	9.85
Sugar Maple	1.11	10.71
Scots Pine	3.62	10.45
White Ash	2.84	8.84
White Birch	2.31	9.05
Willow	0.00	10.88
White Pine	3.47	7.65
White Spruce	3.27	9.61
Yellow Birch	2.13	10.33
Yugoslavian Pine	5.48	6.73
Wetlands [30,31,32,33,34,35,36,37,38,39,40,41,42]
Bog	1.67	11.70
Brackish Marsh	4.10	7.30
Deep Marsh	0.06	5.87
Seasonally Flooded Flat	4.01	4.76
Meadows	1.22	2.59
Salt Marsh	3.48	5.19
Sand Dunes	0.00	0.23
Wooded Swamp	15.16	14.97
Shrub Swamp	1.89	7.40
Grass and Shrubs [43,44,45]
Grass	13.09	20.62
Shrubs	5.75	6.70

shows the estimated emission and removal factors for the three main ecosystems in PEI, including forest, wetlands, and grass and shrubs. These factors were primarily obtained from literature reviews and converted into carbon dioxide equivalent emissions per hectare per year (tCO₂eha⁻¹yr⁻¹). The next subsections will further provide information on the emission and removal factors of the studied ecosystems.

2.4. Forest

In this study, the carbon and removal factors for forests were derived from the Global Forest Watch (GFW) map (https://www.globalforestwatch.org, accessed on 10 January 2024) provided by [29] in 30 m resolution for the years 2001 to 2022. Because the GFW data provide a gross estimate for twenty-two years, the emissions and removals data were divided by twenty-two to estimate the annual average. As illustrated in Figure 2, which presents the flow chart to estimate the emission and removal factors for forest species in PEI, the GFW data were aggregated with PEI’s LULC inventory for 2010 and 2020, allowing the estimated emission and removal factors to be extracted for each forest species in PEI using ArcGIS Pro software, version 3.2.0. These factors, estimated in 2010, were later used to determine the net emissions and removals for PEI’s forest species due to their coverage in relation to the PEI context. This can be accomplished by multiplying the estimated emission and removal factors by the corresponding areas of each forest species in two different years, 2010 and 2020. Hence, the total carbon flux was estimated by subtracting the total removals from the total emissions for each forest species. Negative values represent the carbon sink forest areas, while positive values represent the carbon source forest areas. Overall, it is evident that these species act as a net carbon sink over PEI, except for clear-cut and red oak. The clear-cut is typically considered a net carbon source rather than a carbon sink [46,47]. Meanwhile, oak species could serve as a net carbon source depending on changing climate conditions [48].

2.5. Sand Dunes

Sand dunes, often overlooked in carbon sequestration discussions, can capture atmospheric CO₂ by stabilizing organic material and promoting vegetation growth [49]. The process involves the colonization of dunes by plants, which, through photosynthesis, convert CO₂ into organic matter that becomes trapped within the sand. This helps reduce the atmospheric concentrations of CO₂ and stabilizes the dunes, preventing soil erosion and promoting ecosystem health. Various studies have estimated the carbon sequestration factors for different sand dune classes [38,39,50]. Based on PEI’s landscape characteristics, dune areas often have embryo, mobile, and fixed dunes, as [39] reported. Hence, it is necessary to consider the average sequestration factors for these types of dunes in the context of PEI, which is equivalent to 0.23 tCO₂eha⁻¹yr⁻¹. Notably, the carbon emissions from sand dunes often occur when they are eroded or destroyed by various natural disasters or human activities, which can be observed as a loss in sequestration capacity.

2.6. Seasonally Flooded Flat

Seasonally flooded flats are mainly located on riverbanks or estuaries, where the flooding and drought seasons alternate. Because of the different morphological zone conditions on PEI, it is appropriate to regard flooded flats as tidal flats, since they are widely dispersed in the tidal-controlled rivers, estuaries, and low-lying coastal plains across the island. According to specific studies [51,52], salt marshes are commonly found in tidal flats. Given the hydrodynamic conditions on PEI’s tidal flats, where no substantial freshwater stream flows emerge and tides are dominating control forces, saltwater should be regarded as the primary component of the water body flooding the tidal flats rather than fresh or mixed water. We refer to a study conducted on the Scheldt estuary’s tidal flat in Belgium and the Netherlands, which found a larger emission factor in the freshwater zone and a lower one in the mixed zone. Assuming a higher salinity (about 30 ppt) in the seawater-dominated area, the factor following the present pattern could be smaller, estimated at 25 ppt in this study, or equivalent to 4.015 tCO₂eha⁻¹yr⁻¹ in PEI. In terms of carbon sequestration, relevant research reports that the average carbon accumulation factor of global tidal flats is 4.76 tCO₂eha⁻¹yr⁻¹. This value was previously estimated on the North China coasts [34], where the geographical conditions are comparable.

2.7. Meadows

Meadows in the low-lying coastal plain of PEI are mostly Eelgrass (Zostera marina) meadows, which are common along the island’s coastline (Environment and Climate Change Canada, 2022 [53]). The emissions from eelgrass meadows vary depending on the geographical conditions of the studied area [35]. According to comprehensive studies on the GHG emissions of CO₂, CH₄, and N₂O throughout coastal Australia [54], the factor ranges for CH₄ and N₂O are significantly broader than those for CO₂. As higher temperatures limit the carbon storage capacity of seagrass meadows [20], we regard the study area of Australia as having higher emission factors than the study area of PEI. As a result, we use the sum of the Australian study’s minimal emission factors for CO₂, CH₄ (CO₂e), and N₂O (CO₂e) in the estimation for PEI, which is 1.22 tCO₂eha⁻¹yr⁻¹ total. Regarding sequestration, studies in New England and the US about the carbon accumulation rates for eelgrass meadows [36] can be considered for PEI due to their relatively close distance. Given that New England’s and the US’s coastal landscape has more consolidated textures, higher elevations, and more complicated geological conditions, we assume that meadows will grow more easily on PEI’s low-lying sedimentary coastline. As a result, the average maximum sequestration factor of all New England sites, 2.59 tCO₂eha⁻¹yr⁻¹, was used in the estimation for PEI.

2.8. Brackish Marsh

Brackish marshes are significant for their role in the global carbon cycle but can also be a sink as well as a source [55]. The vegetation in these marshes, such as salt-tolerant grasses and sedges, captures CO₂ from the atmosphere and stores it in biomass and underground in their root systems [56]. On the other hand, brackish marshes can emit CO₂ through the decomposition of organic matter and respiration processes of microbial and plant communities. According to [32], freshwater and brackish marshes have annual methane emissions of 62.3 gCH₄m²yr⁻¹ and 13.8 gCH₄m²yr⁻¹, respectively. It is reported that well-maintained brackish marshes would act as a net radiative sink, which is less than half the soil carbon accumulation rate of 4.1 tCO₂eha⁻¹yr⁻¹ after subtracting methane emissions. This is presuming that natural marshes sequester approximately 200 gC⁻¹m²yr⁻¹ (7.3 tCO₂eha⁻¹yr⁻¹) of soil carbon annually over the long term [32].

2.9. Salt Marsh

Coastal salt marshes and mangrove ecosystems are especially susceptible to variations in atmospheric CO₂ levels and related climate changes a long time ago [57], including those induced by climate shifts [58]. A salt marsh’s carbon emission rate was observed to range from 13 to 28 mmoles CO₂m⁻²hr⁻¹ (50.1 to 107.9 tCO₂ehayr⁻¹) in research in New Brunswick [37]. The salt marsh sequestration factors for Malpeue Bay, Brackley Bay, and Rustico Bay were initially reported to be 5.9 molCm⁻² yr⁻¹, 7.4 molCm⁻²yr⁻¹, and 10.4 molCm⁻²yr⁻¹ [59]. Thus, we take the average of the three CO₂ emission factors for the PEI, equivalent to 3.48 tCO₂eha⁻¹yr⁻¹. Regarding the sequestration factor, [38] disclosed that the salt marsh sequestration factor could vary from 2.35 to 8.04 tCO₂eha⁻¹yr⁻¹. Similarly, the average of these two values, which is equivalent to 5.19 tCO₂eha⁻¹yr⁻¹, was then used for PEI.

2.10. Deep Marsh

Deep marsh has a standing water depth of more than six inches. Deep marshes are significant carbon sinks as they capture CO₂ from the atmosphere through photosynthesis and store it in plant biomass and sediment, potentially locking it away for centuries. This makes deep marshes important components in strategies aimed at mitigating climate change. Phillips and Beeri (2008) reported that the emission factor for deep marsh species in the Prairie Pothole Region, Canada, is 1778.4 kgkm⁻²d⁻¹, equivalent to 0.06 tCO₂eha⁻¹yr⁻¹ [38]. Meanwhile, another Australian study found that the deep marsh’s sequestration factor can be estimated at 1.6 MgC_orgha⁻¹yr⁻¹ or equal to 5.87 tCO₂eha⁻¹yr⁻¹ [60]. It is important to note that the study did not include any factors for PEI due to the limitation of shallow marsh information.

2.11. Wooded Swamp

Swamps are nutrient-rich soil wetlands with significant seasonal variations in water levels. In the example study of Kejimkujik National Park in Nova Scotia, researchers determined that the CO₂ emissions from wooded/treed swamps are 18.63 tCO₂eha⁻¹yr⁻¹ and 11.69 tCO₂eha⁻¹yr⁻¹, respectively, for an average of 15.16 tCO₂eha⁻¹yr⁻¹ [60]. Previous studies found that forested swamps sequester 12.59 tCO₂eha⁻¹yr⁻¹ in the Katewe’katik Wilderness region in Nova Scotia [41] and 17.35 tCO₂eha⁻¹yr⁻¹ for the wooded swamps [60]. These investigations led us to an average sequestration rate of 14.97 tCO₂eha⁻¹yr⁻¹, slightly less than the carbon emission rate.

2.12. Shrub Swamp

Shrub swamps are wetland ecosystems characterized by woody vegetation and waterlogged soils that are typically found in temperate regions. These ecosystems play a complex role in global GHG dynamics, as they are sources of both CO₂ and CH₄, yet also serve as significant carbon sinks. A long-term monitoring study of shrub swamps categorized by species and degrees of peat decomposition yields GHG emission rates. According to Inisheva and Golovchenko (2022), the transit profile with dwarf shrub species emitted 1.89 tCO₂eha⁻¹yr⁻¹ in the most recent year [42]. Meanwhile, Bernal et al. (2012) reported that these shrub swamps could sequester 7.4 tCO₂eha⁻¹yr⁻¹. This is further confirmed by shrub swamps serving as significant carbon sinks [45].

2.13. Bog

Peatlands are altered by extraction (for horticulture) and draining (for land use purposes), which emits CO₂ emissions. For instance, Artz et al. (2022) [43] estimated that an eroding Atlantic blanket bog emits from 1.06 to 1.91 tCO₂eha⁻¹yr⁻¹. Wilson et al. (2015) showed that the peatland managed for extraction emits 1.64 tCO₂eha⁻¹yr⁻¹ for domestic and 1.7 tCO₂eha⁻¹yr⁻¹ for industrial sites [30]. Ultimately, an average of these values (1.6 tCO₂eha⁻¹yr⁻¹) was then used for this research. In general, bogs have a substantially greater carbon sequestration rate than emission rates, making them the most effective carbon sink among all wetlands. For instance, Lunt et al. (2019) [31] found that blanket bogs sequester 11.7 tCO₂eha⁻¹yr⁻¹. Blanket bogs are a unique form of ombrotrophic peatland that thrives in regions with high rainfall and cold climates and are most commonly found near the coast [61]. Because the bogs have similar hydroclimatic and topographical conditions, these values were applied to PEI.

2.14. Grass

Grass ecosystems, which are not subject to land use activities like tillage or agricultural conversion, often preserve the carbon they store without disrupting or releasing it into the atmosphere. This stability indicates that grass serves as a carbon sink. Researchers have studied the emissions from grass in different types of wetland ecosystems [62]. They examined grass in both ombrotrophic bogs and minerotrophic fens. The carbon emission rate for the grass was then obtained from the average of these above ecosystems (13.09 tCO₂eha⁻¹yr⁻¹). Rees et al. (2005) also showed that the carbon sequestration factor for grass was 20.62 tCO₂eha⁻¹yr⁻¹; this value was used in this study [63].

2.15. Shrubs

Shrubs are essential in the PEI landscape and are found along the coast, in woodlands, and in open areas. In addition to their ecological importance, shrubs contribute to carbon cycling on PEI. While they release CO₂ through respiration and breakdown, they also absorb CO₂ through photosynthesis and store it in their stems and roots. According to Pasalodos-Tato et al. (2015), shrubs’ average carbon emission factor is about 5.75 tCO₂eha⁻¹yr⁻¹ [44]. On the other hand, a relevant study conducted in [45] found that the carbon sequestration factor for shrubs could be about 6.7 tCO₂eha⁻¹yr⁻¹. These emission and sequestration factors were used in this study to quantify the net flux of shrubs in PEI.

2.16. Data Processing

Carbon emissions and removals were calculated for each type of ecosystem based on the PEI LULC data from 2010 and 2020 using ArcGIS Pro, version 3.2.0. Before applying to LULC data, emission and removal factors were converted into tCO₂eha⁻¹yr⁻¹ units. Figure 3 shows the flow chart to estimate the carbon flux for forest, wetlands, and shrubs and grass. The total carbon emissions and carbon removals from each studied ecosystem were also calculated.

$$\sum C_{emission}=EF\times Area$$

(1)

$$\sum C_{removal}=RF\times Area$$

(2)

where $C_{emission}$ and $C_{removal}$ are carbon emissions and removals, respectively, and EF and RF are the emission and removal factors, respectively.

Carbon flux was then determined by subtracting the total carbon removals from the carbon emissions for all studied ecosystems in PEI, as described in Equation (3).

$$\sum C_{flux}=\sum C_{emission}-\sum C_{removal}$$

(3)

where $C_{flux}$ is carbon flux.

3. Results and Discussions

3.1. Quantification of Forest Carbon Flux in PEI Ecosystem

Forests typically serve as carbon sinks by absorbing CO₂ from the atmosphere. The results estimate that the forest has a net carbon sink over PEI in 2010 and 2020. Figure 4 shows that Charlottetown and Summerside had some gaps, while the areas near Miminegash, Poplar Grove, Wood Islands, and Clear Springs in PEI had higher net carbon flux flow rates. In 2010, the forest’s net carbon emissions were 683 KtCO₂e, while net carbon removal was 2381 KtCO₂e in PEI. This leads to a carbon sink in forests with a net carbon flux of −1698 KtCO₂e. In 2020, the net carbon emissions were 634 KtCO₂e, while net carbon removal was 2360 KtCO₂e, for a total net carbon flux of −1726 KtCO₂e. The increased net carbon flux in 2020 was because of the reduction in clear-cut areas. In 2010, PEI had 18,784 ha of clearcut, which had been reduced to 13,241 ha by 2020. Clear-cutting produces some of the highest carbon emissions in forest ecosystems.

Table 2. Total carbon emissions, removals, and flux from forest in PEI.

Cover Name	2010			2020
	Emissions (tCO2e)	Removals (tCO2e)	Flux (tCO2e)	Emissions (tCO2e)	Removals (tCO2e)	Flux (tCO2e)
Alder	11,759.66	117,596.57	−105,836.91	7281.42	73,542.36	−66,260.94
Apple	3.62	55.80	−52.19	7.72	119.08	−111.36
Aspen Provenance	0.00	2.97	−2.97	0.00	0.00	0.00
Austrian Pine	130.60	218.67	−88.08	83.29	139.47	−56.17
Balsam Fir	24,140.96	106,010.30	−81,869.34	34,061.32	149,573.62	−115,512.30
Beech	141.31	1925.37	−1784.06	126.50	1723.59	−1597.09
Black Ash	8.83	81.86	−73.03	0.74	6.86	−6.12
Black Spruce	57,788.58	226,531.24	−168,742.66	57,065.73	223,697.65	−166,631.92
Cedar	551.39	1142.16	−590.77	2386.07	4942.56	−2556.50
Clear Cut	161,544.08	105,191.49	56,352.58	113,877.88	74,153.03	39,724.84
Corsican Pine	0.72	4.45	−3.73	0.72	4.45	−3.73
Dead Tree	4570.00	1157.34	3412.66	2036.14	515.65	1520.50
Douglas Fir	54.65	108.05	−53.41	65.70	129.91	−64.21
Eastern Larch	19,723.61	72,067.04	−52,343.43	24,335.14	88,916.86	−64,581.72
Elm	0.66	10.15	−9.50	6.27	96.73	−90.46
European Birch	0.00	12.50	−12.50	0.00	42.39	−42.39
European Larch	35.77	362.83	−327.06	72.94	739.81	−666.87
Grey Birch	150.72	1123.51	−972.80	3650.58	27,213.39	−23,562.82
Hemlock	86.28	452.98	−366.70	99.28	521.23	−421.95
Hybrid Poplar	0.00	89.02	−89.02	0.00	100.93	−100.93
Hybrid Spruce	15.64	34.65	−19.02	14.57	32.28	−17.72
Jack Pine	355.36	1381.97	−1026.61	220.60	857.90	−637.30
Japanese Larch	436.21	2815.56	−2379.35	414.12	2672.98	−2258.86
Larch Provenance	0.00	50.79	−50.79	0.00	49.81	−49.81
Linden	0.00	9.69	−9.69	0.00	5.41	−5.41
Lodgepole Pine	11.22	32.42	−21.20	0.00	0.00	0.00
Norway Spruce	1493.49	5358.98	−3865.49	1427.48	5122.12	−3694.64
Others	39.40	310.28	−270.88	0.00	0.00	0.00
Pin Cherry	1950.24	4592.50	−2642.26	1024.81	2413.26	−1388.45
Poplar	40,885.27	213,033.77	−17,2148.50	35,160.36	183,203.98	−148,043.62
Red Maple	155,462.11	826,403.85	−670,941.74	165,619.36	880,397.64	−714,778.28
Red Oak	314.16	222.38	91.78	349.51	247.40	102.10
Red Pine	6361.62	19,556.09	−13,194.47	5887.49	18,098.57	−12,211.08
Red Spruce	11,311.81	29,961.02	−18,649.21	6147.09	16,281.49	−10,134.40
Scots Pine	231.76	669.53	−437.77	220.20	636.13	−415.93
Sugar Maple	13,173.50	128,142.25	−114,968.75	11,807.18	114,851.62	−103,044.44
White Ash	28.13	88.42	−60.29	33.92	106.62	−72.69
White Birch	22,314.46	87,317.47	−65,003.00	24,313.58	95,140.08	−70,826.50
White Pine	6412.29	14,107.05	−7694.75	6703.62	14,747.97	−8044.35
White Spruce	141,020.64	410,241.86	−269,221.22	128,046.70	372,499.49	−244,452.79
Willow	0.00	36.11	−36.11	0.00	247.22	−247.22
Yellow Birch	641.99	3148.80	−2506.81	1377.28	6755.21	−5377.93
Yugoslavian Pine	2.80	3.41	−0.61	8.75	10.66	−1.91

shows the carbon emissions, removals, and flux from different forest covers in 2010 and 2020. Forest cover types, such as Black Spruce, Balsam Fir, and Eastern Larch, exhibit dynamic carbon cycling characterized by significant CO₂ emissions and removals. These forests act as carbon sinks, sequestering atmospheric CO₂ through photosynthesis and storing it within biomass and soils. However, they also release CO₂ through processes like respiration, decomposition, and disturbances such as wildfires or logging activities. Deciduous and broadleaf cover types, including Sugar Maple and Yellow Birch, contribute to effective carbon sequestration, with high rates of CO₂ removal relative to emissions. Their dense foliage and efficient photosynthetic processes enable them to absorb and store carbon efficiently. In contrast, mixed and clear-cut areas experience temporary increases in emissions following disturbance events like logging, as the carbon stored in vegetation and soils is released into the atmosphere.

Additionally, non-forest cover types like Apple orchards and Hybrid Poplar plantations exhibit lower carbon dynamics, reflecting smaller carbon pools and turnover rates compared to natural forests. Comparing between 2010 and 2020, the data reveal changes in carbon dynamics across different forest cover types over time in PEI. While some land cover types, such as Black Spruce and Balsam Fir, show relatively consistent patterns of emissions and removals over the decade, others exhibit notable shifts. For instance, areas subject to clear-cutting may experience temporary spikes in emissions in 2010, followed by a gradual recovery as vegetation regrows and carbon sequestration resumes by 2020. Similarly, forested areas like Sugar Maple and Yellow Birch may show increases in removals over the decade, reflecting the maturation of forests and enhanced carbon sequestration capacity. These comparisons underscore the dynamic nature of carbon cycling in terrestrial ecosystems and highlight the importance of long-term monitoring to assess carbon budgets and inform climate change mitigation strategies accurately.

3.2. Quantification of Wetland Carbon Flux in PEI Ecosystem

In PEI, wetlands can be combined from different ecosystems, such as sand dunes, seasonally flooded flats, meadows, brackish marshes, salt marshes, deep marshes, wooded swamps, shrub swamps, and bogs. Figure 5 presents PEI’s wetland carbon emissions, removals, and flux for 2010 and 2020. The results showed a significant increase in the net carbon emissions of different wetlands in PEI from 139,987 tCO₂e to 159,200 tCO₂e from 2010 to 2020, especially from meadows, wooded swap, and shrub swamp in the West Devon, Partage, and Cardcross areas. The results suggest a decrease in grass ecosystem net carbon removal, from 177,050 tCO₂e to 959,904 tCO₂e. Since the net carbon removal was higher than the emissions, the overall net carbon flux decreased from −98,752 tCO₂e to −98,064 tCO₂e.

Table 3. Total carbon emissions, removals, and flux from wetlands in PEI.

Cover Name	2010			2020
	Emissions (tCO2e)	Removals (tCO2e)	Flux (tCO2e)	Emissions (tCO2e)	Removals (tCO2e)	Flux (tCO2e)
Bog	10,111	73,941	−63,829	9300	68,007	−58,707
Brackish Marsh	5109	9097	−3988	4703	8375	−3617
Deep Marsh	234	6263	−6028	154	4115	−3961
Seasonally Flooded Flat	49	58	−12	63	75	−15
Meadows	2788	5913	−3125	5178	10,982	−5804
Salt Marsh	22,471	35,513	11,041	22,957	34,238	11,280
Sand Dunes	0	772	−772	0	682	−682
Wooded Swamp	87,788	86,688	1302	103,927	102,65	1100
Shrub Swamp	11,437	44,778	−33,341	12,918	50,576	−37,658

shows the carbon dynamics of different wetlands in PEI in 2010 and 2020. Comparing the carbon dynamics of various cover types in wetland types between 2010 and 2020 reveals nuanced shifts influenced by a multitude of factors. Notably, emissions from bogs decreased in 2020, alongside reduced removals and a consequent decline in net flux as compared to 2010.

This trend aligns with potential changes in land use or management practices aimed at mitigating carbon loss. Similarly, brackish marshes and deep marshes experienced decreases in emissions and removals, potentially reflecting alterations in hydrological regimes or vegetation composition over the decade. Conversely, meadows exhibited substantial increases in emissions and removals in the study period, suggesting changes in agricultural practices or land management that could enhance carbon sequestration. Salt marshes, despite a slight rise in emissions in 2020, saw a decrease in removals, possibly due to habitat degradation or sea level rises impacting marsh health. Natural sand dunes are unlikely to be a source of net carbon emissions. Because sand dunes’ net emissions are very small in PEI, net carbon flux is considered as removals for sand dunes. However, they experienced a decrease in removals, likely influenced by natural factors such as shifting sand dynamics. Wooded swamps demonstrated notable increases in emissions and removals, indicative of shifts in forest dynamics or land use patterns favouring carbon storage. Shrub swamps, while experiencing emission increases in 2020, also showed a rise in removals, possibly due to restoration efforts or natural succession processes. Overall, these trends underscore the complex interplay between ecological processes, land management strategies, and external stressors like climate change, highlighting the need for targeted conservation and restoration measures to sustainably manage carbon dynamics in diverse ecosystems.

3.3. Quantification of Grass and Shrubs’ Carbon Flux in PEI’s Ecosystem

Figure 6 illustrates PEI’s carbon emissions, removal, and flux for grass and shrubs in 2010 and 2020. The results showed a significant intensification in net carbon emissions of grass and shrubs from 590,514 tCO₂eyr⁻¹ to 611,882 tCO₂eyr⁻¹ from 2010 to 2020. The results suggest an increase in the grass ecosystem net carbon removal as oscillating from 925,937 tCO₂eyr⁻¹ to 959,904 tCO₂eyr⁻¹. Since the net carbon removal was higher than the emissions, the overall net carbon flux also increased from −335,440 tCO₂eyr⁻¹ to −348,020 tCO₂eyr⁻¹.

Table 4. Total carbon emissions, removals, and flux from grass and shrubs in PEI.

Cover Name	2010			2020
	Emissions (tCO2e)	Removals (tCO2e)	Flux (tCO2e)	Emissions (tCO2e)	Removals (tCO2e)	Flux (tCO2e)
Grass	580,147	913,857	−333,728	602,217	948,642	−346,424
Shrubs	10,367	12,080	−1712	9665	11,262	−1596

shows the carbon emission, removal, and flux in PEI over the study period. In comparing the emissions, removals, and flux of grass and shrub areas between 2010 and 2020, several noteworthy trends emerge. Firstly, both grass and shrubs exhibit a decrease in emissions over the decade, albeit to varying degrees. This reduction in emissions could be attributed to various factors, such as changes in land management practices, improvements in agricultural techniques, or shifts in vegetation cover. Interestingly, despite the decrease in emissions, both grass and shrubs saw an increase in removals over the same period. This suggests that these ecosystems have become more effective at sequestering carbon dioxide or other greenhouse gases from the atmosphere. Potential reasons for this could include enhanced vegetation growth, improved soil carbon storage, or natural regeneration processes. When considering the overall flux, which represents the net change in greenhouse gas levels, both grass and shrubs continued to act as carbon sinks, although with varying intensities. Despite this decrease, both ecosystems maintained a net removal of greenhouse gases from the atmosphere, underscoring their importance in mitigating climate change. These shifts in emissions, removals, and flux highlight the dynamic nature of terrestrial ecosystems and their role in the global carbon cycle.

Understanding these changes is crucial for effective climate change mitigation and informing sustainable land management strategies in the future. Figure 7 depicts variations of net carbon flux for various ecosystems (e.g., forests, wetlands, and grass and shrubs) between 2010 and 2020. Negative values indicate increased carbon sequestration, while positive values indicate that the ecosystem emits more GHG. The results reveal insignificant changes in carbon flux in the last decade, regardless of changes in the LULC. The altering sediment transport induced by coastal erosion has significantly resulted in changing sand dune flux in 2020 compared to 2010. Since forests cover the majority of PEI, their variances are more significant than those of other ecosystems. Overall, the findings indicate that most ecosystems in PEI sequester GHGs rather than emit them.

3.4. Carbon Flux Mapping

The carbon flux maps of PEI can be explored on the PEI Ecosystem Carbon Flux App (CARBON: https://carbon.peiclimate.ca, accessed on 5 September 2024). This platform aims to provide a comprehensive GIS- and web-based tool that enables the general public and decision makers to explore the spatial and temporal patterns of carbon emissions, removals, and fluxes across various ecosystems in PEI (Figure 8). This user-friendly interface allows visitors to navigate through various map layers, soil types, and land uses, enabling a deeper understanding of how these factors influence carbon dynamics within the province. Users can interact with the platform by selecting specific years, such as 2010 and 2020, and various ecosystem types, including forests, wetlands, sand dunes, and grasslands. This feature is important for evaluating how environmental policies and land management practices affect carbon storage and emissions in PEI ecosystems. The tool is a valuable resource for developing climate action strategies, helping decision makers create informed, data-driven environmental policies.

4. Ecosystem Management and Planning

Ecosystem management efforts should focus on minimizing the extent and intensity of land-use change, preserving natural habitats, and promoting sustainable land management practices. This study underscores the importance of preserving and restoring forests, which play a critical role in carbon sequestration in PEI. Forest species such as black spruce, balsam fir, and eastern larch demonstrate significant CO₂ removals, highlighting their potential as carbon sinks. Ecosystem management strategies should prioritize the protection of these forests from deforestation, degradation, and disturbance. Implementing sustainable forestry practices, such as selective logging and reforestation, can help maintain carbon stocks and promote ecosystem resilience. Additionally, the data highlight the impacts of land-use change on carbon dynamics, particularly in areas subject to clear-cutting and land conversion. Clear-cut areas exhibit temporary spikes in CO₂ emissions, followed by gradual recovery as vegetation regrows. Integrating agroforestry systems, where trees are planted alongside crops, can maximize land use efficiency. This method not only increases carbon sinks but also provides additional income sources for farmers and improves soil health. We recommend targeted reforestation initiatives that focus on planting native species adapted to local conditions, which can effectively increase carbon sequestration while also enhancing habitat for wildlife.

For effective management of wetlands as a carbon reduction tool, it is essential to rigorously monitor their net ecosystem carbon balance, consistently accounting for aquatic exchanges and inland restoration. We recommend implementing restoration techniques that focus on re-establishing natural hydrology and native vegetation. This includes creating controlled water levels to support diverse plant species, which can enhance the wetland’s ability to sequester carbon. Establishing buffer zones around wetlands can help reduce nutrient runoff and protect these areas from development pressures. These zones should be planted with native vegetation to increase biodiversity and improve carbon storage. However, regular monitoring of wetland health and carbon storage capacity is essential. This can involve using remote sensing technologies to assess changes over time and adapt management practices accordingly. Understanding these dynamics is crucial for developing effective management strategies tailored to each ecosystem type. For instance, ecosystems like bogs and marshes, which exhibited decreases in emissions, may benefit from conservation efforts aimed at preserving their hydrological integrity and vegetation composition. Conversely, ecosystems experiencing increases in emissions, such as meadows and wooded swamps, may require targeted interventions to enhance carbon sequestration, such as reforestation or sustainable land management practices. Land managers can enhance carbon storage while providing additional co-benefits such as biodiversity conservation and flood mitigation by prioritizing the protection and restoration of high-carbon ecosystems like salt marshes and wooded swamps. Incorporating wetlands into climate change mitigation strategies presents challenges because their impact on GHG emissions is inconsistent and sensitive to land use or climate change [64]. Despite these fluctuations, preserving and restoring wetlands remains a crucial natural approach to climate mitigation, as their degradation inevitably results in GHG emissions. Grass and shrubs play a critical role in carbon sequestration, as evidenced by their negative carbon flux values, indicating a net carbon removal of greenhouse gases from the atmosphere. Therefore, preserving existing grasslands and shrubs areas and restoring degraded areas can enhance their capacity to reduce carbon and mitigate climate change. Adopting sustainable land management practices such as afforestation, reforestation, and agroforestry can increase carbon sequestration while providing additional benefits such as habitat restoration and soil conservation. Encouraging the use of cover crops during off-seasons can improve soil health and increase organic matter, leading to greater carbon sequestration in the soil. Further, implementing reduced tillage practices minimizes soil disturbance, which helps maintain soil structure and carbon content. Developing comprehensive nutrient management plans that optimize fertilizer use can reduce emissions and enhance soil carbon storage. Similarly, promoting sustainable grazing practices in grasslands and shrublands can help maintain ecosystem health while minimizing carbon emissions from livestock. Effective ecosystem management and planning require a holistic approach that considers the interconnection of ecological, social, and economic factors. While this study utilizes data from the existing literature to estimate carbon emissions and removals in ecosystems, there are inherent uncertainties in these estimates. These uncertainties arise from variations in data collection methods, temporal changes in ecosystems, and differences in the assumptions made by various studies. For example, carbon flux estimates often depend on the climatic conditions, land-use patterns, and ecological dynamics, all of which may introduce variability. Moreover, the accuracy of the satellite imagery and remote sensing data used in carbon mapping can be influenced by weather conditions and the resolution of the imagery. To mitigate these uncertainties, the study employed high-resolution mapping and cross-validated data from multiple sources. However, it is important to acknowledge that, despite these efforts, some level of uncertainty remains.

In comparison to previous studies on carbon flux in ecosystems, this work offers more detailed high-resolution maps specific to Prince Edward Island (PEI), providing a localized understanding of carbon emissions and removals. While past studies have provided broad estimates at national or regional levels, this research provides a finer scale of analysis that is crucial for decision making at the provincial level. Previous research has often focused on specific ecosystem types, whereas this study integrates data across various ecosystems, offering a more comprehensive view. Additionally, the web-based tool developed here provides a unique interactive feature not found in prior literature, enabling real-time exploration of carbon dynamics for decision makers and the public. By integrating scientific data, stakeholder engagement, and adaptive governance principles, researchers can develop resilient ecosystems that provide essential services for both the present and future generations while mitigating the impacts of climate change.

The impact of land use change and management practices on carbon fluxes is critical in understanding ecosystem dynamics. Human activities such as agriculture and deforestation play significant roles in altering carbon storage and emissions. Different farming methods can greatly influence carbon fluxes. For example, conventional tillage often leads to soil degradation and increased carbon emissions, while no-tillage practices have been shown to enhance soil carbon storage. The adoption of cover crops can significantly improve soil health and contribute to carbon sequestration. The conversion of forests for agricultural use or urban development results in substantial carbon emissions due to the loss of carbon stocks. Deforestation not only releases stored carbon but also disrupts local ecosystems and their capacity to sequester carbon in the future. To address these challenges, it is essential to promote sustainable land management practices. Policies that incentivize agroforestry, reforestation, and sustainable agricultural methods can enhance carbon sequestration and mitigate emissions effectively.

Future studies could focus on carbon balance shifts in weather patterns due to climate change, comparing novel mitigation measures aimed at reducing GHG emissions like wetland restoration, reforestation of degraded areas, reduced impact lodging, or the introduction of plant species with high carbon sequestration potential [65]. Additionally, there could be an emphasis on the socio-economic impacts of climate change solutions, using an ecosystem-based approach to integrate environmental sustainability with human well-being [64]. Research in this area could investigate how local communities can be engaged in climate action through ecosystem conservation and restoration projects that offer co-benefits such as livelihood opportunities, flood regulation, and biodiversity conservation [66].

5. Conclusions

This study carried out a comprehensive literature review to quantify carbon flux for diverse ecosystems on PEI between 2010 and 2020. Potential carbon emission, removal, and flux maps were then developed to represent the changes in PEI’s ecosystems. The results show that all the studied ecosystems act as carbon sinks in PEI in both studied years except for wooded swamps. Some areas, such as PEI’s eastern and western parts, served as the more effective carbon sinks compared to the central region. The findings of this study underscore the importance of considering both carbon flux dynamics in different ecosystems to comprehensively assess their role in PEI’s carbon cycle. It is important to acknowledge that the findings of this study are based on the literature review, which is solely dependent on data availability and may not fully capture the intricate interactions within ecosystems that influence carbon flux, such as interspecies relationships, soil dynamics, and microclimatic effects. Moreover, the impact of human activities and different management practices on carbon flux is a complicated socio-ecological issue that may need to be thoroughly understood. For future improvement, the study recommends incorporating in situ approaches to reduce uncertainty in GHG estimation.