Soil-Based Emissions and Context-Specific Climate Change Planning to Support the United Nations (UN) Sustainable Development Goal (SDG) on Climate Action: A Case Study of Georgia (USA)

Abstract

Soil-based emissions from land conversions are often overlooked in climate planning. The objectives of this study were to use quantitative data on soil-based greenhouse gas (GHG) emissions for the state of Georgia (GA) (USA) to examine context-specific (temporal, biophysical, economic, and social) climate planning and legal options to deal with these emissions. Currently, 30% of the land in GA has experienced anthropogenic land degradation (LD) primarily due to agriculture (64%). All seven soil orders were subject to various degrees of anthropogenic LD. Increases in overall LD between 2001 and 2021 indicate a lack of land degradation neutrality (LDN) in GA. Besides agricultural LD, there was also LD caused by increased development through urbanization, with 15,197.1 km² developed, causing midpoint losses of 1.2 × 10¹¹ kg of total soil carbon (TSC) with a corresponding midpoint social cost from carbon dioxide (CO₂) emissions (SC-CO₂) of USD $20.4B (where B = billion = 10⁹, $ = U.S. dollars (USD)). Most developments occurred in the Metro Atlanta and Coastal Economic Development Regions, which indicates reverse climate change adaptation (RCCA). Soil consumption from developments is an important issue because it limits future soil or forest carbon (C) sequestration potential in these areas. Soil-based emissions should be included in GA’s carbon footprint. Understanding the geospatial and temporal context of land conversion decisions, as well as the social and economic costs, could be used to create incentives for land management that limit soil-based GHG emissions in a local context with implications for relevant United Nations (UN) initiatives.

1. Introduction

Climate change affects many facets of society (e.g., social, economic, etc.) and requires context-specific climate planning (Figure 1). In general, “context is defined as the interrelated conditions in which something exists or occurs” [1]. For example, soil-based emissions occur because of economic activity and biophysical changes from land conversions leading to damages, which can be described in terms of societal costs (e.g., social costs of CO₂ emissions, SC-CO₂ [2]) (Figure 1). Most states in the United States of America (USA) do not have climate change preparation and adaptation plans, and the very few states that have plans often overlook soil-based emissions (https://www.georgetownclimate.org/adaptation/plans.html (accessed on 15 March 2024)) [3]. The omission of soil-based emissions can lead to the underestimation of a state’s carbon footprint and can harm overall climate change mitigation efforts. Understanding emissions patterns provides important geospatial and temporal information about land and soil consumption patterns. Soil consumption from developments is an important issue because it limits future soil or forest C sequestration potential in these areas. Understanding the context of land conversion decisions, as well as the social and economic costs, could be used to create mechanisms to incentivize land use decisions that limit soil-based greenhouse gas (GHG) emissions within a local context [4].

The state of Georgia (GA) currently does not have climate change preparation and adaptation plans. However, GA conducted research for the state’s climate action using an approach developed specifically for GA, which is called “Drawdown GA” (https://www.drawdownga.org/carbon-reduction-visualizer/ (accessed on 16 August 2024)) [5,6,7]. This GHG reduction framework evaluates the baseline emissions for GA and identifies and examines possible emission reduction options [6]. This research evaluated 20 “high impact” carbon reduction strategies but assumed there was no change in soil-based C sequestration [7]. A companion interactive website, “Drawdown GA,” further explores the impact of the proposed reductions and includes the concept of “Climate Smart Agriculture,” which can use agronomic conservation practices to increase C sequestration, as well as the assumption that land is only a sink of GHG emissions. Soil-based emissions because of land conversions are not accounted for in the “Drawdown GA” framework [5]. Brown et al. (2021) [7] stress the importance of “place” and “context” in developing climate action plans. In addition to these GA research initiatives, on July 14, 2023, the EPA granted the state of GA $3 million ($, USD) to develop its first-ever climate plan as a part of the United States (US) Congressional Inflation Reduction Act (IRA) of 2022 [8,9,10].

The omission of soil-based emissions from land conversions in GA climate change preparation and adaptation plans can lead to the underestimation of emissions from the state as well as an inability to reduce future potential emissions through sustainable land and soil management. The soil-based emissions potential from land conversions is dependent on many factors, including the inherent soil quality of soil types found in GA (Figure 2). The inherent SQ of GA is dominated by strongly weathered Ultisols (77%) with lower SQ status (Figure 2) [11]. All other soil orders have limited presence in the state (

Table 1. Distribution of inherent soil quality and soil carbon regulating ecosystem services in the state of Georgia (GA) (USA) by soil order (photos courtesy of USDA/NRCS [19]).

Soil Regulating Ecosystem Services in the State of Georgia (USA)
Degree of Weathering and Soil Development (Inherent Soil Quality)
Slight (17%)			Moderate (3%)		Strong (80%)
Entisols	Inceptisols	Histosols	Alfisols	Mollisols	Spodosols	Ultisols
8%	8%	1%	3%	<1%	3%	77%
Midpoint storage and social cost of soil organic carbon (SOC): 1.3 × 1012 kg C, $220.4B
9.9 × 1010 kg	1.0 × 1011 kg	2.2 × 1011 kg	2.8 × 1010 kg	3.8 × 107 kg	6.1 × 1010 kg	8.0 × 1011 kg
$16.8B	$17.0B	$36.6B	$4.7B	$0.6B	$10.2B	$135.1B
8%	8%	17%	2%	<1%	5%	61%
Midpoint storage and social cost of soil inorganic carbon (SIC): 1.4 × 1011 kg C, $23.8B
6.0 × 1010 kg	5.8 × 1010 kg	3.7 × 109 kg	1.6 × 1010 kg	3.2 × 107 kg	3.0 × 109 kg	0
$10.2B	$9.8B	$0.6B	$2.7B	$5.4M	$0.5B	$0
43%	41%	3%	11%	<1%	2%	0%
Midpoint storage and social cost of total soil carbon (TSC): 1.4 × 1012 kg C, $244.2B
1.6 × 1011 kg	1.6 × 1011 kg	2.2 × 1011 kg	4.4 × 1010 kg	7.0 × 107 kg	6.4 × 1010 kg	8.0 × 1011 kg
$26.9B	$26.8B	$37.2B	$7.4B	$12M	$10.7B	$135.1B
11%	11%	15%	3%	<1%	4%	55%
Sensitivity to climate change
Low	Low	High	High	High	Low	Low
SOC and SIC sequestration (recarbonization) potential
Low	Low	Low	Low	Low	Low	Low

Note: Entisols, Inceptisols, Alfisols, Mollisols, Spodosols, and Ultisols are mineral soils. Histosols are mostly organic soils. M = million = 10⁶; B = billion = 10⁹; $ = U.S. dollars (USD). See Supplementary Materials Table S2 for minimum and maximum values.

). Citizens of GA have selected the State Soil as Tifton (soil order: Ultisols) because it is among the most extensive soils in the state [12]. Soils of GA provide a wide range of ecosystem services (ES) (cultural, provisioning, regulation/maintenance) to the economic development regions for GA (Figure 2, Table S1) [11]. Regulating ES provided by GA soils is particularly relevant to the state’s climate change planning, especially concerning soil C storage and the potential for C loss because of disturbance, which results in the oxidation of soil organic matter (SOM) and subsequent release of carbon dioxide gas (CO₂) [11]. The knowledge of soil C stocks is relevant to the GA climate change plan; however, it should be noted that this stock was already significantly depleted during the state’s land and soil use history [13]. As of 2021, the remaining estimated total mid-point storage for TSC for GA was 1.4 × 10¹² kg C with an estimated total mid-point monetary value of $244.2B (i.e., $244.2B billion U.S. dollars (USD), where B = billion = 10⁹ in social costs of C (SC-CO₂) [2] (Table 1)). From these total estimates, SOC was 60% of the total value (1.3 × 10¹² kg C, $220.4B), and SIC represented 40% of the total value (1.4 × 10¹¹ kg C, $23.8B). We have previously reported that the state of GA ranked 15th for SOC [14], 34th for SIC [15], and 26th for TSC [16] for the SC-CO₂ values among the 48 contiguous US states. Soil orders with the highest midpoint monetary value and storage for TSC were Ultisols (8.0 × 10¹¹ kg C, $135.1B), Histosols (2.2 × 10¹¹ kg C, $37.2B), and Entisols (1.6 × 10¹¹ kg C, $26.9B) (Table 1). Counties in GA having the highest midpoint TSC values included Charlton (1.1 × 10¹¹ kg C, $18.6B), Ware (1.1 × 10¹¹ kg C, $18.6B), and Clinch (3.5 × 10¹⁰ kg C, $5.9B) (Table 1). Estimated values of the remaining TSC storage and its social costs estimate the potential C footprint of GA soils upon disturbance with its variability (minimum, midpoint, and maximum) reported in the Supplemental Materials (Table S2).

Previously, Brown et al. (2021) [7] claimed that GA lands serve as a sink for GHG emissions with only the potential to increase GHG sequestration and not as a contributor to emissions. However, this assumption does not consider past, current, and future soil-based emissions from land conversions. This study hypothesizes that it is possible to quantitatively evaluate soil-based greenhouse gas (GHG) emissions for the state of GA within temporal, biophysical, economic, and social contexts to enable climate planning and to help use either existing or new legal strategies to limit and provide greater responsibility and accountability for damages from these emissions.

The primary objectives of this study were to use satellite-based remote sensing (Multi-Resolution Land Characteristics Consortium (MRLC) [20]) and soil spatial databases (Soil Survey Geographic Database (SSURGO) [17,21], and the State Soil Geographic Database, (STATSGO) [22]) to examine soil-based emissions from land conversions in GA in biophysical, economic, and social contexts. Sub-objectives include: (1) quantifying the total area of anthropogenic land degradation (LD) and potential land for nature-based solutions (NBS) disaggregated by type of LD and soil type; (2) quantifying the total area of past (prior to and through 2021) and recent (2001-2021) developments in GA by soil type; (3) quantifying the total soil C loss as a result of the past and recent developments based on information provided by Guo et al. (2006) [23]; (4) estimating the social cost of C [2] loss from past and recent developments; (5) presenting results in both tabular and spatial formats (e.g., maps) to identify emission hotspots for climate change planning and (6) discussing the use of existing or novel legal strategies to provide greater accountability for emission damages in GA and worldwide.

2. Materials and Methods

This study used an accounting framework (Table S3) to examine soil-based emissions in biophysical, economic, and social contexts and their temporal changes in GA. The biophysical analyses involved calculating soil organic, inorganic, and total carbon stocks (kg), the area (km²), and proportion (%) of LD and LDN by soil type, land cover type, and administrative unit (state, county). Land cover analysis using classified satellite remote sensing data (30-m) provided by the Multi-Resolution Land Characteristics Consortium (MRLC) [20] allowed the evaluation of LD based on NLCD class legend and descriptions between 2001 and 2021 (Figure S1). To combine the land cover data with high-resolution soil spatial layers (SSURGO) [21], the data were converted to vector from the original raster format and then unioned with the soil data. This combined dataset of land cover and soil information was analyzed using ArcGIS Pro 2.6 [24] to examine the soil types associated with various land cover types and changes.

The economic analysis focused on calculating monetary damages from LD within various administrative units. The soil spatial analysis was combined with values provided by Guo et al. (2006) [23] to estimate soil C contents for SOC, SIC, and TSC (kg m⁻²) by administrative unit (e.g., county) and soil order (Table S3, Table S4). For the economic analysis, these calculated soil contents were used to calculate the C that was likely lost through CO₂ emissions as the social cost of carbon (SC-CO₂) (Table S4) in monetary terms. These calculations relied on the EPA SC-CO₂ valuation of $46 per metric ton of CO₂, which serves as a damage estimate from CO₂ release but underestimates the true costs and impacts associated with climate change damage [2]. Monetary values ($ m⁻²) were determined for each area using Equation (1), while totals were calculated by summing within the polygon boundary (with SC = soil carbon and a metric tonne equal to 1 megagram (Mg) or 1000 kilograms (kg)):

$${\displaystyle \frac{\mathrm{\$} \mathrm{U}\mathrm{S}\mathrm{D}\hspace{0.33em}}{{\mathrm{m}}^2}}=\hspace{0.33em}\left(\mathrm{S}\mathrm{C} \mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t},{\displaystyle \frac{\mathrm{k}\mathrm{g}}{{\mathrm{m}}^2}}\right)\hspace{0.33em}\times \hspace{0.33em}{\displaystyle \frac{1 \mathrm{M}\mathrm{g}}{{10}^3 \mathrm{k}\mathrm{g}}}\hspace{0.33em}\times \hspace{0.33em}{\displaystyle \frac{44 \mathrm{M}\mathrm{g} \mathrm{C}{\mathrm{O}}_2}{12 \mathrm{M}\mathrm{g} \mathrm{S}\mathrm{C}}}\times {\displaystyle \frac{\mathrm{\$}46 \mathrm{U}\mathrm{S}\mathrm{D}}{\mathrm{M}\mathrm{g} {\mathrm{C}\mathrm{O}}_2}} \hspace{0.33em}$$

(1)

As a calculation example for areas with Alfisols soil order, Guo et al. (2006) [23] provided a midpoint estimate of 7.5 kg m⁻² for SOC content (2-m soil depth; Table S4). This reported soil content is then used in Equation (1) to calculate an area-normalized SOC value of $1.27 m⁻² (Table S4). The SOC content with its area-normalized value for that area is subsequently multiplied by the area of Alfisols within GA (3699.0 km²) to create an SOC stock estimate of 2.8 × 10¹⁰ kg and a $4.7B monetary value of SC-CO₂.

3. Results

3.1. Biophysical Context

3.1.1. Total Area of Anthropogenic Land Degradation (LD) and Potential Land for Nature-Based Solutions (NBS) Disaggregated by Type of LD and Soil Type

As of 2021, almost 30% of the land in GA experienced anthropogenic land degradation (LD) primarily due to agriculture (64%) (Figure 3,

Table 2. Land use/land cover (LULC) by soil order in Georgia (GA) (USA) in 2021.

NLCD Land Cover Classes (LULC), Soil Health Continuum	2021 Total Area by LULC (km2)	Degree of Weathering and Soil Development (Inherent Soil Quality)
		Slight			Moderate		Strong
		Entisols	Inceptisols	Histosols	Alfisols	Mollisols	Spodosols	Ultisols
		2021 Area by Soil Order (km2)
Woody wetlands	24073.8	5009.2	4143.2	1515.0	662.3	0.3	857.7	11886.1
Shrub/Scrub	6051.0	408.2	176.4	0.4	174.3	0.1	604.7	4686.8
Mixed forest	9544.6	610.0	1175.9	0.1	279.3	0.6	11.1	7467.8
Deciduous forest	18518.2	879.4	2795.8	0.0	503.6	0.4	6.1	14332.9
Herbaceous	6579.4	487.6	182.0	1.5	173.9	0.2	348.8	5385.5
Evergreen forest	35692.0	1824.6	1321.5	4.1	1124.0	0.5	2414.6	29002.7
Emergent herbaceous wetlands	2561.1	1561.6	143.3	31.3	30.8	0.0	78.6	715.6
Hay/Pasture	10192.7	451.6	534.2	0.1	376.0	0.5	96.0	8734.3
Cultivated crops	17879.5	447.1	207.8	0.0	65.1	0.2	83.7	17075.6
Developed, open space	7992.8	369.0	410.9	0.9	168.6	0.0	235.6	6807.8
Developed, low intensity	4629.3	192.1	162.9	0.2	85.2	0.0	133.5	4055.3
Developed, medium intensity	1899.9	96.3	74.7	0.1	34.5	0.0	49.4	1644.8
Developed, high intensity	675.0	39.3	26.0	0.0	12.7	0.0	14.3	582.8
Barren land	309.4	55.3	13.4	0.0	8.9	0.0	14.0	217.8
Totals	146,598.9	12,431.4	11,367.9	1553.8	3699.0	2.8	4948.0	112,596.0

Note: Entisols, Inceptisols, Alfisols, Mollisols, Spodosols, and Ultisols are mineral soils. Histosols are most often organic soils.

, Figure S2). All seven soil orders were subject to varying degrees of anthropogenic soil degradation and LD: Ultisols (35%), Mollisols (30%), Alfisols (20%), Entisols (13%), Spodosols (13%), Inceptisols (13%), and Histosols (0.1%). Increases in soil and LD between 2001 and 2021 (+3.7%) indicated a lack of land degradation neutrality (LDN) in GA (

Table 3. Anthropogenic land degradation status and potential land for nature-based solutions by soil order for the state of Georgia (GA) in the United States of America (USA) in 2021. Percent changes in area from 2001 to 2021 are shown in parentheses. Reported values have been rounded; therefore, calculated sums and percentages may exhibit minor discrepancies.

Soil Order	Total Area		Anthropogenically Degraded Land	Types of Anthropogenic Degradation			Potential Land for Nature-Based Solutions
				Barren	Developed	Agriculture
	(km2)	(%)	(km2)	(km2)	(km2)	(km2)	(km2)
Slightly Weathered Soils
	25,353	17.3	3082 (+5.9)	68 (−3.4)	1372 (+24.7)	1641 (−5.7)	1325 (+5.3)
Entisols	12,431	8.5	1651 (+5.9)	55 (−0.2)	697 (+22.2)	899 (−3.8)	951 (+9.2)
Inceptisols	11,368	7.8	1430 (+5.8)	13 (−14.7)	674 (+27.4)	742 (−7.9)	372 (−3.9)
Histosols	1554	1.1	1 (+22.9)	0 (0)	1 (+20.4)	0 (0)	2 (+151.6)
Moderately Weathered Soils
	3701	2.5	752 (+2.4)	9 (−4.4)	301 (+25.1)	442 (−8.8)	357 (+9.2)
Alfisols	3699	2.5	751 (+2.4)	9 (−4.5)	301 (+25.1)	441 (−8.8)	357 (+9.2)
Mollisols	3	0	1(+6.1)	0 (0)	0 (0)	1 (+5.0)	0 (0)
Strongly Weathered Soils
	117,544	80.2	39,745 (+3.3)	232 (−10.6)	13,524 (+26.6)	25,990 (−5.3)	11,258 (+19.8)
Spodosols	4948	3.4	626 (+27.6)	14 (+93.2)	433 (+16.7)	180 (+59.5)	967 (+24.0)
Ultisols	112,596	76.8	39,118 (+3.3)	218 (−13.5)	13,091 (+26.9)	25,810 (−5.5)	10,290 (+19.4)
All Soils
Totals	146,599	100.0	43,579 (+3.7)	309 (−8.9)	15,197 (+26.4)	28,072 (−5.3)	12,940 (+17.8)

Note: Entisols, Inceptisols, Mollisols, Spodosols, Ultisols, and Alfisols are mineral soils. Histosols are mostly organic soils. Anthropogenically degraded land was calculated as a sum of degraded land from agriculture (hay/pasture, and cultivated crops), from development (developed, open space; developed, low intensity; developed, medium intensity; developed, high intensity), and barren land. Developed land includes categories: developed, open space; developed, low intensity; developed, medium intensity; developed, high intensity. Agriculture includes categories: hay/pasture; and cultivated crops. Potential land for nature-based solutions (NBS) is limited to barren land, shrub/scrub, and herbaceous land cover classes, to provide potential land areas without impacting current land uses. Change in the area was calculated as follows: ((2021 Area − 2001 Area) / 2001 Area) × 100%.

). Almost 44% of GA is covered by mixed, deciduous, and evergreen forests, which are primarily found in soils classified as Ultisols because of their high susceptibility to soil erosion and leaching [12]. Land degradation in GA has a long history since European settlers changed the natural soils in GA with various agricultural uses (e.g., corn, cotton, tobacco, soybeans, etc.), and these soils now require modern technologies to support their fertility status because the underlying material of these soils has low native fertility [25]. Only 8.8% of the land in GA is potentially available for NBS (Figures S3 and S4), the availability of which is further complicated by the high amount of private land ownership (90.3%) in the state [26]. Most of the potential land for NBS belonged to the soil order of Ultisols (79.5%) with inherently low SQ and high susceptibility to erosion (Table 3).

3.1.2. Biophysical Losses and Damages to Ecosystem Services

Anthropogenic LD is a dynamic process that causes various damages to ecosystem services (ES) (cultural, regulation/maintenance, provisioning), which need to be quantified both spatially and temporally.

Table 4. Land use/land cover (LULC) change (%) by soil order in Georgia (USA) from 2001 to 2021.

NLCD Land Cover Classes (LULC), Soil Health Continuum	Change in Area, 2001–2021 (%)	Degree of Weathering and Soil Development (Inherent Soil Quality)
		Slight			Moderate		Strong
		Entisols	Inceptisols	Histosols	Alfisols	Mollisols	Spodosols	Ultisols
		Change in Area, 2001–2021 (%)
Woody wetlands	0.7	1.1	0.8	1.3	0.9	1.9	2.3	0.2
Shrub/Scrub	55.9	24.4	3.9	44.6	45.0	400.0	97.4	58.5
Mixed forest	−4.0	−9.2	0.2	−32.9	−1.9	−3.0	−44.5	−4.1
Deciduous forest	−13.2	−15.5	−3.8	−51.0	−12.0	−7.9	−83.3	−14.6
Herbaceous	−2.7	0.1	−9.6	218.9	−12.0	100.0	−25.3	−0.4
Evergreen forest	−2.3	−0.8	−2.4	−18.6	1.0	−27.2	−11.6	−1.7
Emergent herbaceous wetlands	14.8	1.7	22.6	−28.2	41.6	52.9	33.4	57.4
Hay/Pasture	−11.3	−8.0	−11.5	29.8	−11.2	−6.6	121.6	−12.1
Cultivated crops	−1.5	1.0	2.7	71.4	7.8	42.6	20.7	−1.8
Developed, open space	5.0	−0.1	9.8	6.1	4.3	−28.9	−5.6	5.4
Developed, low intensity	37.7	38.2	39.2	73.6	42.7	−6.3	35.6	37.6
Developed, medium intensity	154.4	129.2	171.9	126.0	159.1	1000.0	192.3	154.2
Developed, high intensity	122.6	99.2	144.9	150.0	118.0	0.0	143.1	123.1
Barren land	−8.9	−0.2	−14.7	216.7	−4.5	0.0	93.2	−13.5

Note: Entisols, Inceptisols, Alfisols, Mollisols, Spodosols, and Ultisols are mineral soils. Histosols are most often organic soils. Change in the area was calculated as follows: ((2021 LULC Area − 2001 LULC Area) / 2001 LULC Area) * 100%.

shows anthropogenic LD trends by soil type in GA from 2001 to 2021, which demonstrates an increase in developments in place of more land-conserving LULC (e.g., mixed forest, deciduous forest, etc.). As an example, developments within the state of GA caused loss and damage (L&D) to regulating ES because of the loss of land that could potentially be used for soil carbon (C) sequestration with a sum of 15,197.1 km² of land area converted to developments before and through 2021 (Table 3). The largest area losses from developments were found in Gwinnett (741.7 km²), Cobb (577.9 km²), and Fulton (441.2 km²) counties (Table S5). Between 2001 and 2021, new developments led to a total of 3564.9 km² of land being converted to developments (Table S5). The areas with the largest losses from development were found in Gwinnett (208.8 km²), Fulton (149.1 km²), and Henry (117.0 km²) counties (Table S5). Most developments occurred adjacent to the Atlanta urban area and came at the expense of cultivated and forest areas (Figure 4). This analysis determined that between 2001 and 2021, land developments mainly occurred near existing urban and coastal areas. Georgia is dominated by the soil order of Ultisols, which have inherently low C sequestration potential. Projected urbanization increases will likely cause a future reduction in land available for C sequestration. Another example of L&D is from soil carbon (C) loss and the associated emissions from the land conversion process to create developments in GA (USA) (Figure 5). These losses that occurred before and up to 2021 resulted in an estimated midpoint total of 1.2 × 10¹¹ kg of C losses (Table S6). The largest soil C losses were seen in Gwinnett (5.8 × 10⁹ kg C), Cobb (4.3 × 10⁹ kg C), and Fulton (3.4 × 10⁹ kg C) counties (Table S5). All these counties are in proximity to the urban center of Atlanta. New development activity between 2001 and 2021 caused a total of 6.5 × 10¹⁰ kg in C losses (Table S7). The highest soil C losses were seen in Gwinnett (5.3 × 10⁹ kg C), Fulton (3.4 × 10⁹ kg C), and Chatham (2.2 × 10⁹ kg C) counties (Figure 5, Table S5).

3.2. Economic Context

3.2.1. Anthropogenic Land Degradation (LD) as a Proxy for Economic Development

Anthropogenic LD in GA is closely associated with past and current economic activities in the state, with a high degree of spatial variability between counties and economic development regions (

Table 5. Land degradation (LD) status and trends in economic development regions of Georgia (GA) (USA). Percent changes in area from 2001 to 2021 are shown in parentheses. Reported values have been rounded; therefore, calculated sums and percentages may exhibit minor discrepancies. This table shows anthropogenic LD status in 2021 but likely does not account for historical anthropogenic LD as well as most inherent LD.

Georgia Economic Development Regions	Land Degradation (through 2021)
	Area (Change from 2001 to 2021) (km2, %)	Proportion from Total Region Area (%)
Metro Atlanta	3665.5 (+18.3)	42.5
Northwest	3728.4 (+3.3)	28.5
Southeast	5162.5 (+4.3)	30.9
Coastal	2299.6 (+11.0)	23.1
Northeast	2606.8 (+7.8)	22.0
South	4700.9 (+0.1)	25.6
East Central	3045.0 (+1.9)	25.8
East	3054.1 (-0.7)	31.9
Southwest	7116.2 (+0.9)	48.5
Middle	2143.2 (+4.5)	27.7
West Central	2345.5 (+0.3)	23.7
West	3711.0 (+1.0)	25.9
Overall State Total	43,578.7 (+3.7)	29.7 (State)

, Figure 6). There were 68 counties below the value of 29.7% anthropogenic LD for the state as a whole and 91 counties at or above this value. Southwest (48.5%) and Metro Atlanta (42.5%) economic development regions had the highest proportions of anthropogenic LD in the state (Table 5) compared to 29.7% of anthropogenic LD for the whole state. Table 5 shows anthropogenic LD status in 2021 but likely does not account for historical anthropogenic LD or most inherent LD. Metro Atlanta (+18.3%) and Coastal (+11.0%) economic development regions experienced the highest increase in development between 2001 and 2021. Among GA counties, Cobb (71.8%), Gwinnett (71.6%), and Clayton (65.4%) had the highest anthropogenic LD proportions. All three counties are in the Metro Atlanta economic development region. Counties with the lowest anthropogenic LD were McIntosh (5.1%) (in the Coastal economic region), Charlton (5.2%), and Clinch (6.5%) (both in the Southeast economic development region).

It should be noted that 29.7% of the current level of anthropogenic LD does not account for historic anthropogenic LD, where as much as 95% of the forests in GA were removed by the 1920s for agriculture and had to be subsequently reforested after agricultural uses collapsed [27]. The rapid development of the area in and around Atlanta has led to the rapid loss and fragmentation of forests [28] in concert with the increase in LD. This loss of forest habitat has likely caused a range of ecological and habitat damages [28], as well as loss of above-ground C with forest removal. A study by Obata et al. (2020) [29] examined forest disturbance between 1987 and 2016 and found that 29.2% of the state was disturbed, noting the difference between forestry cycles and urbanization.

3.2.2. Global Social Cost of Soil-Based Emissions Associated with Economic Development

Loss and damage from land conversions associated with developments extend beyond the boundaries of GA, which can be quantified as the “realized” social costs of soil carbon (C) (SC-CO₂) [2] released from land conversion because of soil organic matter decomposition and other disturbances [11]. The SC-CO₂ is a fixed, non-market-based value intended to monetize damages to society from a metric tonne of CO₂ emissions [30], which is often used only for government purposes. The SC-CO₂ from land conversions to developments before and into 2021 within the state of GA (USA) results in a total midpoint value of $20.4B SC-CO₂ (Table S6). The highest social costs were found in Gwinnett ($983.8M), Cobb ($732.7M), and Fulton ($580.4M) counties, which are all located in the Metro Atlanta economic development region. From 2001 to 2021, new developments caused $11.0B in SC-CO₂. The highest costs were found in Gwinnett ($904.2M) and Fulton ($582.7M), which are also located in the Metro Atlanta region and Chatham ($375.9M) in the Coastal economic development region (Figure 7). For economic development regions, the highest “past” and “recent” SC-CO₂ values were associated with Metro Atlanta (past: $3.9B; recent: $3.1B), Northwest ($2.3B; $1.7B), and Coastal ($1.8B; $1.3B) economic development regions (

Table 6. Past and recent loss and damages (L&D) from developments by economic development regions, Georgia (GA) (USA).

Georgia Economic Development Regions	Past Developments (through 2021)			Recent Developments (2001-2021)
	Area (km2)	Midpoint TSC loss (kg)	Midpoint SC-CO2 ($, USD)	Area (km2)	Midpoint TSC loss (kg)	Midpoint SC-CO2 ($, USD)
Metro Atlanta	3025.6	2.3 × 1010	$3.9B	871.1	1.8 × 1010	$3.1B
Northwest	1634.0	1.4 × 1010	$2.3B	433.1	1.0 × 1010	$1.7B
Southeast	1257.1	1.1 × 1010	$1.8B	193.3	2.8 × 109	$478.1M
Coastal	1120.7	1.1 × 1010	$1.8B	349.8	7.4 × 109	$1.3B
Northeast	1345.1	1.0 × 1010	$1.7B	352.5	5.8 × 109	$980.4M
South	1160.8	9.0 × 109	$1.5B	138.8	2.0 × 109	$335.1M
East Central	1133.8	8.4 × 109	$1.4B	321.5	5.0 × 109	$849.3M
East	915.0	7.0 × 109	$1.2B	160.5	2.3 × 109	$382.9M
Southwest	980.1	7.2 × 109	$1.2B	137.2	1.9 × 109	$316.8M
Middle	829.5	6.5 × 109	$1.1B	215.4	3.1 × 109	$522.1M
West Central	880.6	6.5 × 109	$1.1B	221.3	3.5 × 109	$595.3M
West	908.6	7.0 × 109	$1.2B	170.4	2.8 × 109	$467.1M
Overall State Total	15,190.8	1.2 × 1011	$20.4B	3564.9	6.5 × 1010	$11.0B

Note: TSC = total soil carbon; SC-CO₂ = social costs of carbon dioxide emissions; M = million = 10⁶; B = billion = 10⁹; $ = U.S. dollars (USD).

). It should be pointed out that SC-CO₂ values are calculated from the developed areas and soil types within these areas, and values of SC-CO₂ can be quite different even if the developed areas are the same in size because of the variability in soil C content between soil types (Table 6). For example, even though the Coastal economic development region has a smaller area (km²) than the Northeast economic development region, it has more SC-CO₂ from developments because of the higher soil C content in soils for these developed areas (Table 6). Potential solutions to negative externalities associated with damages from developments can include market-based payments in proportion to these damages [31].

3.2.3. Reverse Climate Change Adaptation (RCCA) Linked to Economic Development

Increased GHG emissions in GA and worldwide have contributed to sea level rise which threatens the GA coast. Eleven out of GA’s 159 counties are potentially impacted by projected sea level rise (Figure 8, Table 7). All these 11 counties experienced increases in development between 2001 and 2021 (Table 7), resulting in loss of land for C sequestration and RCCA.

Sea level rise (3.2 cm per decade) is already occurring along the GA coast and appears to be 30% higher than global averages [32,33] because of the regional land subsidence of the GA coastal plain [34]. Future flood modeling predicts increases in coastal flooding for GA, with an increase to more than 8 days of flooding within approximately 125 events each year by 2060 [32]. The largest economic impact from flooding caused by extreme weather events is seen in the GA coastal communities because coastal buildings and infrastructure have high risks from sea level rise and proximity to storm surges [35]. The economic impact of these extreme weather events is exacerbated by the 300% increase in coastal property value between 1980 and 2000 [36], which has likely continued to increase to the present day. While a recent study has found some reduced property value (3.1%) for homes at high flood risk [37], this is nearly insignificant when looking at the overall value of coastal property subject to risk from these natural disasters. Therefore, there are few negative incentives for coastal development (e.g., increased insurance cost or even uninsurability) that could serve to disincentivize development that caused LD and the associated social costs while also putting additional homeowners at risk from climate-change-related extreme weather events. Government-supported insurance for coastal developments may further aggravate the problem of RCCA by providing incentives that result in increased development in these hazard-prone areas [38]. An unanswered question is what the economic cost would be of relocation of property and people who currently live in coastal areas, which will not be habitable because of the increasing disaster risk. It should be noted that flooding risk in GA is not only limited to the coastal areas, but other parts of the state as well. Ferguson and Ashley (2017) [39] conducted a spatiotemporal analysis of residential flood risk in the Atlanta metropolitan area and concluded that an increase in developments contributes to greater flood risks.

Table 7. Selected county area changes in the developed area (2001-2021) and county area loss (%) due to sea rise in the state of Georgia (GA) (USA) (based on original ArcGIS Pro 2.6 [24] analysis of data from the National Oceanic and Atmospheric Administration (NOAA) [40]).

Counties (Affected by Sea Rise)	Change in Developed Area (2001-2021) (km2, %)	County Area Loss due to Sea Rise (%)
		1 foot	3 feet	6 feet	9 feet
Brantley	8.3 (+14.5)	0.0	0.0	0.1	0.3
Bryan	20.2 (+31.5)	0.0	0.0	14.6	18.7
Camden	21.0 (+22.7)	21.4	28.8	34.4	44.6
Charlton	5.0 (+9.3)	1.0	1.9	3.9	6.2
Chatham	81.2 (+55.8)	37.3	43.2	50.4	60.3
Effingham	35.3 (+46.9)	2.7	3.2	3.8	4.4
Glynn	27.0 (+25.0)	27.7	35.1	48.1	63.0
Liberty	21.1 (+25.4)	14.0	17.9	21.8	26.3
Long	9.2 (+20.1)	0.0	0.0	0.0	0.1
McIntosh	3.8 (+9.2)	34.2	39.6	46.5	54.7
Wayne	10.2 (+9.3)	0.0	0.0	0.3	0.7

Note: 11 out of Georgia’s (USA) 159 counties are potentially affected by the projected sea level rise. 1 foot = 0.3048 meters.

Table 7. Selected county area changes in the developed area (2001-2021) and county area loss (%) due to sea rise in the state of Georgia (GA) (USA) (based on original ArcGIS Pro 2.6 [24] analysis of data from the National Oceanic and Atmospheric Administration (NOAA) [40]).

Counties (Affected by Sea Rise)	Change in Developed Area (2001-2021) (km2, %)	County Area Loss due to Sea Rise (%)
		1 foot	3 feet	6 feet	9 feet
Brantley	8.3 (+14.5)	0.0	0.0	0.1	0.3
Bryan	20.2 (+31.5)	0.0	0.0	14.6	18.7
Camden	21.0 (+22.7)	21.4	28.8	34.4	44.6
Charlton	5.0 (+9.3)	1.0	1.9	3.9	6.2
Chatham	81.2 (+55.8)	37.3	43.2	50.4	60.3
Effingham	35.3 (+46.9)	2.7	3.2	3.8	4.4
Glynn	27.0 (+25.0)	27.7	35.1	48.1	63.0
Liberty	21.1 (+25.4)	14.0	17.9	21.8	26.3
Long	9.2 (+20.1)	0.0	0.0	0.0	0.1
McIntosh	3.8 (+9.2)	34.2	39.6	46.5	54.7
Wayne	10.2 (+9.3)	0.0	0.0	0.3	0.7

Note: 11 out of Georgia’s (USA) 159 counties are potentially affected by the projected sea level rise. 1 foot = 0.3048 meters.

3.3. Social Context

3.3.1. Significance of the Results for Georgia’s Soil Health Legislation

Georgia passed a soil health-related Bill No. 391-1-6 (https://rules.sos.ga.gov/gac/391-1-6?urlRedirected=yes&data=admin&lookingfor=391-1-6 (accessed on 8 July 2024) [41]. This bill, “Georgia Conservation Tax Credit Program,” provides income tax credits for land that is accepted into the program in return for agreeing to a permanent conservation of various types of lands. This includes the protection of streams, lakes, wetlands or rivers, wildlife habitats, cultural sites, and lands used for outdoor recreation. Additionally, this program can be used to protect prime forestry or agricultural lands, with a stipulation requiring the use of forestry or agricultural best management practices (BMPs). For agricultural lands, the program requires the use of the Georgia Soil and Water Commission BMPs [42], which encourage but do not require the use of conservation tillage, which can improve soil organic matter (SOM), as well as various practices that can reduce soil erosion. While this program can protect land from development, it is not specifically focused on improving soil health and C sequestration. Another program in GA also incentivizes maintaining forest, agricultural, and environmentally sensitive areas by reducing the tax rate on lands in the Conservation Use Valuation Assessment (CUVA) system [43]. This reduces the property taxes for land that is maintained in the specified land uses (forest, agricultural, and environmentally sensitive areas) for ten years, with financial penalties for breaking the conservation agreement. This CUVA program has been extensively used in north Georgia [44] and likely serves to reduce some development but does not require soil conservation or improvement. While these types of programs may reduce LD and the associated social cost of emissions, they may not be the most efficient approach because they do not directly target incentives to prevent LD or GHG emissions that land use conversions cause (e.g., soil-based emissions from land development), which vary based on the type of disturbance and soil type.

3.3.2. Importance of the Results for Georgia’s Climate Change

Despite the ongoing impacts of climate change on GA, there are no completed state-led climate change preparation and adaptation plans (https://www.georgetownclimate.org/adaptation/plans.html (accessed on 8 August 2024) [3]. Georgia has been experiencing a variety of impacts from climate change: rising atmospheric temperatures [45,46] and precipitation, more severe floods [46] and droughts, sea level rise [32,33] and sinking coastline [34], and many others [47]. Droughts often decrease soil available water, making soils drier in most of GA, which can result in reduced agricultural output and forest cover [47]. Our study shows that GA had an increase (+13.3%) in developments associated with impervious surfaces, which will only aggravate the problem of flooding and urban heat islands [48].

Results of our study show that the state of GA experienced LD and associated GHG emissions, which can be mapped and quantified using geospatial techniques. These GHG emissions go beyond the state of GA boundaries and should be accounted for (e.g., “polluter-pays-principle” [49], etc.) in the global loss and damage (L&D) accounting. Increases in developments in coastal counties of GA between 2001 and 2021 most likely indicate reverse climate change adaptation with potentially detrimental consequences to property and human life (Table 7). These coastal developments should not be further incentivized by providing federal assistance to support property insurance or repair and recovery of properties in coastal areas at high risk from future climate risks.

3.4. Temporal Context

Temporal context plays an important role in climate change planning. Our study likely underestimates soil-based emissions from past land conversions because of the history of deforestation and subsequent agriculture that was prevalent in GA and the Southeast region of the US in the 19^th century, which has now largely returned to forest cover in many areas. This LD caused gullies due to soil erosion, with the most extreme example being evident at Providence Canyon State Park, also known as Georgia’s “Little Grand Canyon,” where historic LD (Figure 9a) is still evident after reforestation (Figure 9b) [50]. Government intervention was necessary for land restoration and the resulting economic hardship caused by failed agricultural activity [51], and it is unknown if the reforestation efforts were sufficient to compensate for the past GHG emissions caused by the combination of deforestation and agriculture.

The present context is demonstrated by our study, which documents patterns of ongoing LD and development very often following historic patterns of past LD and development (“business as usual”). Technological advances, including the advent of soil spatial data and satellite-based LULC analysis, allow us to quantify spatial patterns and trends in emissions. Also, the realization that GHG emissions contribute to climate change damages with real social costs necessitates new methods to understand and track the physical and economic impacts of anthropogenic land conversions.

In terms of future context, our study offers a methodology to quantify and understand how the impact of land management decisions can be modeled so that governments can provide incentives that minimize LD and emissions by optimizing the decision-making process. Future advances in high-resolution remote sensing technologies, combined with automated artificial intelligence classification and prediction techniques, will track land conversions and predict future potential LULC changes [52] that cause LD and soil GHG emissions. This may help optimize land planning by providing the opportunity to disincentivize developments with significant negative impacts.

Figure 9. Degraded land caused by human activity in the Providence Canyon State Park, Stewart County, Georgia (USA) (https://gastateparks.org/ProvidenceCanyon) (accessed on 16 August 2024) [53]: (a) an oblique photo of eroded soil in 1937 from the Library of Congress (control number: 2017775702) [54], and (b) a modern aerial photo showing these erosion features (from 2023 National Agriculture Imagery Program (NAIP) aerial photography [55]).

Figure 9. Degraded land caused by human activity in the Providence Canyon State Park, Stewart County, Georgia (USA) (https://gastateparks.org/ProvidenceCanyon) (accessed on 16 August 2024) [53]: (a) an oblique photo of eroded soil in 1937 from the Library of Congress (control number: 2017775702) [54], and (b) a modern aerial photo showing these erosion features (from 2023 National Agriculture Imagery Program (NAIP) aerial photography [55]).

3.5. Legal Context

In the legal literature, an important distinction exists between the “law as written” and the “law in context.” The distinction is between the law as written in a statute or court decision, on the one hand, and the law as actually applied in an actual society, on the other [56]. According to Selznick (2003) [56]: “[T]he phrase ‘law in context’ points to the many ways legal norms and institutions are conditioned by culture and social organization.” That is, “[w]e see … how much the authority and self-confidence of legal institutions depend on underlying realities of class and power; how legal rules fit into broader contexts of custom and morality”. Indeed a whole movement has developed that recognizes the importance of understanding the law as it exists within a society’s specific economic and moral context. The founding principle of the Law and Society movement, with its Law and Society Association, is that identical written laws could lead to fundamentally different outcomes in societies with different conditions. This contextual approach has become commonplace in the teaching and application of law [57].

Legal scholars have recognized that the societal context is vitally important to whether a state or country will successfully address climate change. According to Osofsky (2003) [58], first, the success of a state’s efforts to control climate change will depend on pressures from above and below: “vertical pressures from ‘above’ (international negotiations for the post-2012 regime) and ‘below’ (state and local efforts)”. An important influence from above would be the United Nations. Success will also depend on horizontal influences, “namely climate change litigation and executive policy, as well as advocacy efforts by a range of nongovernmental actors” [58]. For example, studies of household-level adaptation to flooding indicate the profound impacts of the context of prior experience with flooding, “the influence of the media or the behavior of others, and demographic factors such as age or education” [59].

Whether our results will prove fruitful in contributing to appropriate measures to address climate change in GA will require both understanding the local context in which such efforts will occur and also working to influence that context [60]. Georgia has traditionally been a conservative state with powerful agricultural and business interests. Efforts to address climate change in GA must recognize this context and propose measures that align with it. First, the context can be altered by distributing the information from our paper that land disturbance can be a major source of GHG; a main reason why GA has not taken measures to address this danger is that most people do not know about it.

Second, as much as possible, measures to address excessive land disturbance and climate change should be crafted to align contextually with existing interests and preferences. In the contexts of other states, it might be sufficient to motivate change by invoking the dangers of increases in sea levels. In these other states, reports or agreements from the UN or other groups might prove persuasive. In contrast, in a proudly independent state such as GA, change in the state’s context might be presented as promoting business and agricultural interests: limiting land disturbance not only reduces climate change but also reduces soil erosion.

4. Significance of Results in a Broader Context

The methodology used by the UNCCD leverages Trends.Earth 2.1.17 cloud-based software to evaluate LD by using a range of datasets at various spatial resolutions to evaluate the SDG 15.3.1 sub-indicators of land productivity (LP), land cover (LC) change and SOC stocks [61]. A recent study evaluated this methodology to identify LD in the European Union and found that degraded land that was identified using the Trends.Earth software had poor agreement with low C and highly eroded soils, which is an alternative way to identify areas with LD [62]. Recommendations for improving the accuracy of LD analysis included identifying a baseline of prior LD status, increasing the spatial resolution of datasets to better contextualize changes in LC and LP, and incorporating local-scale datasets, including soil surveys, to better understand the relationship between LC change and LD [62]. The present study for the state of GA is innovative because it uses higher resolution (30 m) classified imagery than the UNCCD standard method to more accurately identify LC to developments. Zimba et al. (2024) [63] found that using 30-m Landsat-derived land cover maps was much more accurate, particularly in the development and cropping categories, than the standard land cover maps used in the Trends.Earth analysis, which has a spatial resolution of 300 m. This study is also innovative in its use of high-resolution soil survey maps to link LC change to soil types to better link soil capacity and soil C contents to land conversions for LD analysis. High-resolution soil survey data (e.g., SSURGO) is likely the most accurate way to account for landscape soil C, because it is unrealistic to obtain the density and coverage of soil samples necessary to accurately characterize impacts for land cover change over large areas [64]. There is a realization that higher-resolution data are needed to properly understand LD [65]; however, this study and related studies do not incorporate detailed soil spatial data to help contextualize LD. Econometric models can link practices to CO₂ emissions on a global scale [66]; however, they do not typically provide the spatial information necessary to understand the local context and impact of land use change. Also, we account for TSC because there are potential CO₂ emissions from both SOC and SIC from land development.

This study’s relevance to multiple UN initiatives includes Sustainable Development Goals (SDGs), adopted in 2015 [67], and many other UN initiatives (e.g., UN Convention to Combat Desertification [68,69]; UN Convention on Biological Diversity [70]; UN Kunming-Montreal Global Biodiversity Framework [71]; Ramsar Convention on Wetlands [72,73,74,75], etc.) because GA is a state in the contiguous US. The UN suggests disaggregating indicators whenever possible. Therefore, this study linked soil and land use relationships to UN SDGs to better direct land management to meet UN SDGs, because country-level analysis can easily mask differences within states and regions [67]. This study’s results are essential for UN initiatives and goals for the following reasons:

• There was an overall decrease in cultivated crops (−1.5%) and hay/pasture (−11.3%) between 2001 and 2021 in GA (Table 5). This may indicate a reduction in available farmlands overall, as well as the conversion of hay/pasture to more destructive land uses. (Relevant for UN SDG 2: Zero Hunger);
• For the state of GA, this study found a spatial link between high soil-based GHG emissions areas and likely vulnerability to climate change. The projected GA land losses from expected sea level rise (Table 7) will impact several highly populated areas as well as areas with high-value real estate, causing potential human displacement and damage to infrastructure and buildings. Table 7 also shows an increase in developments in the GA counties impacted by the rising sea level, which can be an indication of reverse climate change adaptation (RCCA). (Relevant for UN SDG 11: Sustainable Cities and Communities);
• Land conversions that occurred across all of the seven soil orders found in GA were caused by land development at the expense of mixed (−4.0%), deciduous (−13.2%), and evergreen (−2.3%) forests (Table 5). Land development occurred on soils with high agricultural productivity (e.g., Alfisols and Mollisols), while C-rich Histolsols were also developed in place of mixed forest (−32.9%), deciduous forest (−51.0%) and evergreen forest (−18.6%) (Table 5). This shows that C-sequestering and productive soils were impacted by land development. (Relevant for UN SDG 12: Responsible Consumption and Production);
• No climate change plans for GA’s preparation and adaptation have been completed (https://www.georgetownclimate.org/adaptation/plans.html (accessed on 8 August 2024) [3]. The state of GA was awarded a $3 million noncompetitive planning grant to develop a climate action plan, which intends to generate a Priority Climate Action Plan (PCAP) by March 1, 2024, a Comprehensive Climate Action Plan (CCAP) by June 30, 2025, and a status report, due at the close of the 4-year grant period, which ends in 2027 [8,9]. Data from this study that estimates soil-based GHG emissions from land developments can support the development of a future plan. This study’s quantitative soil-based GHG emissions estimates are from both past and recent land conversions and the resulting monetary social C cost (SC-CO₂) values. Also, this research quantified the area no longer available for C sequestration in GA. Prior to and before 2021, GA lost an area of 15,197.1 km² to developments with a midpoint of 1.2 × 10¹¹ of total soil carbon (TSC) losses and midpoint values of $20.4B (where B = billion = 10⁹, $ = U.S. dollars (USD)) in SC-CO₂. “New” land developments (3564.9 km²) that occurred from 2001 to 2021 likely caused a loss of midpoint 6.5 × 10¹⁰ kg of TSC, causing a midpoint of $11.0B SC-CO₂. There is very little land (8.8% of total land area) available for nature-based C sequestration (e.g., 0.2% barren land, 4.1% shrub/scrub, 4.5% herbaceous) (Table 2). Georgia’s soils typically have low inherent potential for C sequestration because they are dominated by low-fertility and highly leached Ultisols. Projected levels of sea level rise and expected urbanization will likely reduce land availability for C sequestration further. (Addressing UN SDG 13: Climate Action);
• Nearly 30% of GA’s land area has had anthropogenic LD, mainly due to agriculture (64%) before and through 2021. All seven soil orders received varying degrees of anthropogenic LD: Ultisols (35%), Inceptisols (13%), Mollisols (30%), Entisols (13%), Spodosols (13%), Alfisols (20%), and Histosols (0.1%). Recent trends (2001-2021) showed a +3.7% increase in anthropogenic LD and an increase of +26.4% in the developed type of LD in the state, which was not balanced by the potential NBS land. Development has resulted in a reduction of soil resources because of LULC change between 2001 and 2021 for nearly all 159 counties and 12 economic development regions in GA (Table 3, Table S5). There were decreases in the total areas of deciduous (−13.2%), mixed (−4.0%), and evergreen (−2.3%) forests, hay/pasture (−11.3%), herbaceous (−2.7%) land covers needed for atmospheric pollution reduction and C sequestration (Table 5). (Addressing UN SDG 15: Life on Land; UN Convention to Combat Desertification; UN Convention on Biological Diversity; UN Kunming-Montreal Global Biodiversity Framework);
• At the international level, there is renewed attention on preserving ecosystem resilience and integrity, as shown by the agreement from the UN’s fifteenth meeting of the conference of the parties (COP 15), which adopted the UN Kunming-Montreal Global Biodiversity Framework [71]. This framework includes the goal (Goal A) of maintaining, enhancing, and restoring the resilience, connectivity, and integrity of all ecosystems and includes the target (Target 11) to both restore as well as maintain and enhance ecosystem functions and services (e.g., air, water, soil health, and regulation of climate). This study shows that GA did not reach LDN between 2001 and 2021, with developments occurring in all soil orders, including the agriculturally important soil orders of Alfisols and Mollisols and the C-rich Histosols soil order. The creation of these new developments likely decreased biodiversity through the loss of pedodiversity (soil diversity). This study’s techniques can guide decision-making by providing methods to create the best possible data, which supports Target 21, which focuses on the importance of data development to support equitable governance. (Relevant to UN Kunming-Montreal Global Biodiversity Framework).
• The Ramsar Convention on Wetlands was adopted in 1971 with a focus on the conservation of wetlands, especially as they relate to habitat for waterfowl [72,73,74]. The United States joined the Ramsar Convention on Wetlands in 1986 and currently has 41 designated Ramsar sites that contain critical wetlands areas, including the Okefenokee National Wildlife Refuge (designated as a wetland of international importance), which is both in the states of GA and Florida (FL) [75]. As part of the agreement, the United States supports the Wetlands for the Future (WFF) initiative, which funds training and is focused on wetland management and conservation as part of the development process [72]. Key to the Ramsar Convention is the concept of the “wise use” of wetlands to maintain the “ecological character (of wetlands) … within the context of sustainable development.” This convention also obligates the US to work to conserve all wetlands, including those wetlands outside of the designated sites [73]. Initiatives from the U.S. government in 1989 and 1993 promoted the concept of no net loss of wetlands [73]. A more recent resolution from the Ramsar Convention noted the significance of some wetland types for C storage in relation to climate change [74]. Our study leverages satellite change analysis, combined with soil spatial databases, to identify changes in LULC related to wetlands (e.g., emergent herbaceous wetlands) and related soil types (e.g., Histosols) in GA. One way to evaluate if wetland areas had no net loss is to use satellite land cover data over time. Table 5 shows this analysis for the state of GA between 2001 and 2021, which indicates that there was a net gain in overall wetlands. However, further analysis reveals that there was a loss within Histosols (-28.2%) in wetland areas, which indicates the loss of C-rich soils and wetlands to development or other LULC conversions. Future analysis should use soil spatial data to help understand and disaggregate LULC analysis to quantify wetland change. Changes in wetland areas that contain Histosols can have a much larger impact on soil C emissions because of their much higher C contents compared to other soil types.
  Histosols account for only 1% of soils in GA, but these soils are a significant source (“hotspot”) of SOC (17% of the total SOC of GA) and TSC (15% of the total TSC of GA) (Table 1). There was an overall reduction in Histosols in the state of GA of -28.2% between 2001 and 2021 (Table 5). In this period of time, 0.2 km² of Histosols were converted to developments, which resulted in the loss of 29.4M kg of TSC and corresponding SC-CO₂ in the amount of $5.0M USD. This type of analysis can aid the recent resolution from a Ramsar Convention to quantify wetland changes in C storage in relation to climate change. In addition, in the case of GA (USA), the counties that contain the Okefenokee National Wildlife Refuge [74] saw reductions between 2001 and 2021 in the amount of emergent herbaceous wetlands: Charlton (-9.5%), Clinch (-3.2%), and Ware (-16.7%). Furthermore, this analysis can provide additional details concerning which soils were impacted at the county level and showed a reduction in Histosols within the emergent herbaceous wetlands LULC: Charlton (-10.49%), Clinch (-77.46%), and Ware (-17.48%). Histosols are C-rich soils commonly associated with wetlands. There were also large increases in development in these three counties: Charlton (+9.3%), Clinch (+4.1%), and Ware (+9.9%), which is likely related to the wetland and Histosols identified losses. Methods used in our study can also estimate the CO₂ release and SC-CO₂ associated with the development of Histosols in wetlands, which demonstrates why it is important to preserve wetlands and protect these C-rich soils. (Relevant to Ramsar Convention on Wetlands).
• The Revised World Soil Charter, which was endorsed by member states of the Food and Agriculture Organization (FAO), provides guidelines to ensure that “soils are managed sustainably and that degraded soils are rehabilitated or restored” [76]. This Charter calls for the limiting of soil degradation to preserve soil ecosystem services and support LDN. Our study shows that the state of GA has experienced an increase in both LD and soil degradation, as indicated in Table 4, with an overall +3.7% increase in LD between 2001 and 2021. Land and soil degradation occurred across all soil types during this study period primarily due to the rise in developments. The state of GA was not LD neutral, as indicated by the data in Table 4. This case study in GA is an important contribution to the ongoing research on climate governance [77], which should include soil governance as well [78,79,80]. (Relevant to The Revised World Soil Charter).

5. Conclusions

This study reveals that the current assumption that land and soil in GA only serve as a GHG emissions sink is unlikely to be true. Our results show that the state of GA (USA) experienced significant historical and present LD and soil degradation, which are (were) accompanied by GHG emissions with corresponding social costs, which are (were) not accounted for in the business activities responsible for these LD and soil degradation. This research most likely underestimated the GHG emissions because only areas subjected to developments were considered, and it was not possible to calculate emissions from agriculture and other non-development-related land cover changes. This is an important finding because past and future land use decisions have impacted and will impact soil-based GHG emissions. Also, the social costs calculated likely underestimate the true impact of soil-based emissions, both because agricultural and other land use conversions were not considered and because the social costs were calculated using standard methods that are based on fixed, non-market values. Study limitations include potential errors associated with satellite image classification. However, the resolution of remote sensing data used for this study (30 m) is higher than the land cover data used for most LD analyses. Also, our study compared land cover data over twenty years (2001 to 2021), which only documented the overall change and not the yearly change and other LULC cycles that occurred within those dates (e.g., forestry and agricultural practices). Future studies could leverage yearly or even more fine-scaled land cover data to more quickly identify critical changes and relationships.

Despite the limitations of our study, the results are useful for future climate planning efforts in GA (USA) because they provide a technique to monitor LULC changes and to account for soil-based emissions from the rapid development of GA. The analysis has several direct benefits for the planning process, including spatial analysis of soil type-specific emissions from developments, which also show development patterns, including areas that are susceptible to sea level rise leading to reverse climate change adaptation. Also, soil-based emissions were driven by developments linked to high-value economic development regions, including Metro Atlanta and Coastal economic development regions. Considering that the state of GA is in the process of using context-specific climate change planning, these soil-based emissions can also be examined using a context-specific framework, which could be used to develop regulatory or incentive-based methods to account for the past soil-based emissions and reduce future soil-based emissions tied to LD and soil degradation. Our study demonstrated how soil-based emissions can be understood in temporal, biophysical, economic, and social contexts, which can be used for existing or novel legal strategies to provide greater responsibility and accountability for emissions damages in the state of GA (USA) and worldwide. Potential solutions to negative externalities associated with damages from developments can include market-based payments in proportion to damages from LD and developments. To achieve success in GA, new policies must recognize GA’s specific context. Accordingly, policies should be crafted to appeal not just to the broad worldwide virtues of addressing climate change but also to the benefits of such policies to GA itself.