Carbon Sequestration Policies Research Articles

Farmers’ Willingness to Participate in a Carbon Sequestration Program – A Discrete Choice Experiment

Farmers can counteract global warming by drawing carbon dioxide from the air into agricultural soils by building up humus. Humus programs were developed to motivate farmers for even more humus formation (= carbon sequestration) through an additional financial incentive. These programs are still at an early stage of development, which is why the number of participating farmers and research work is still low. This study is the first to analyze the willingness of German farmers to participate in hypothetical humus programs. The results of a discrete choice experiment show that a (higher) threshold for the payout of the premium, regional (rather than field-specific) reference values, and the risk of repayment clearly discourage farmers from participating. Program providers must more than double the premium (set at around 240 € per hectare and 0.1% humus increase) to maintain farmers’ willingness to participate despite a payout threshold. Regional reference values and an additional premium/repayment system would lead to an increase in the premium of around 20 € per hectare in order to keep the willingness to participate at the same level. The motivation to build up humus, the desire to maximize subsidies, and a higher livestock density have a positive influence on farmers’ decision to participate. Farm size and risk attitude have an impact on farmers’ preferences for program design. The study is relevant for policymakers and non-governmental organizations concerned with carbon management, as our findings highlight pathways for efficient, targeted designs of humus programs and carbon sequestration policies.

Synergistic Application of Multiple Machine Learning Algorithms and Hyperparameter Optimization Strategies for Net Ecosystem Productivity Prediction in Southeast Asia

The spatiotemporal patterns and shifts of net ecosystem productivity (NEP) play a pivotal role in ecological conservation and addressing climate change. For example, by quantifying the NEP information within ecosystems, we can achieve the protection and restoration of natural ecological balance. Monitoring the changes in NEP enables a more profound understanding and prediction of ecosystem alterations caused by global warming, thereby providing a scientific basis for formulating policies aimed at mitigating and adapting to climate change. The accurate prediction of NEP sheds light on the ecosystem’s response to climatic variations and aids in formulating targeted carbon sequestration policies. While traditional ecological process models provide a comprehensive approach to predicting NEP, they often require extensive experimental and empirical data, increasing research costs. In contrast, machine-learning models offer a cost-effective alternative for NEP prediction; however, the delicate balance in algorithm selection and hyperparameter tuning is frequently overlooked. In our quest for the optimal prediction model, we examined a combination of four mainstream machine-learning algorithms with four hyperparameter-optimization techniques. Our analysis identified that the backpropagation neural network combined with Bayesian optimization yielded the best performance, with an R2 of 0.68 and an MSE of 1.43. Additionally, deep-learning models showcased promising potential in NEP prediction. Selecting appropriate algorithms and executing precise hyperparameter-optimization strategies are crucial for enhancing the accuracy of NEP predictions. This approach not only improves model performance but also provides us with new tools for a deeper understanding of and response to ecosystem changes induced by climate change.

The fate of vegetation carbon stocks of India: Insights from a remote-sensed evaluation of carbon use efficiency

Vegetation carbon use efficiency (CUE), defined as the ratio of the net primary productivity (NPP) to gross primary productivity (GPP), is a critical metric for assessing the extent of sequestration of atmospheric carbon by vegetation into biomass. Evaluating CUE is essential for policymakers to devise carbon sequestration policies and also identify hotspots of carbon storage loss. Indian ecosystems face variable weather conditions across the year. However, the roles of weather variability, spatial patterns, and temporal dynamics are poorly understood, as much as the resilience to hydroclimatic perturbations that may influence CUE in Indian terrestrial ecosystems, particularly at sub-annual scales. The lack of sub-annual NPP datasets hinders remote sensing-based sub-annual CUE assessments. However, this study derived an 8-day scale NPP dataset through an empirical formulation on moderate-resolution imaging spectroradiometer (MODIS) products. This study assessed CUE dynamics for India across its six homogeneous meteorological regions (HMRs) including the major biomes of each HMR, encompassing croplands, forests, and grasslands, through a fine-scale remote sensing approach for 2000–2021. The results show pronounced variability of CUE across spatiotemporal scales governed by the water availability and temperature interplay, with hilly 0.59±0.01 and northwestern 0.33±0.02 regions exhibiting the highest and lowest CUE on an annual scale. Distinct patterns have been observed among the biomes, depending on the HMRs dictated by the land management practices of the regions. Similar pronounced CUE variability has been observed on seasonal scales. The study also derived sustainability maps of carbon stocks for India from the trend-persistence interplay of CUE, revealing alarming concerns across most HMRs, with peninsular India exhibiting a persistent decrease in CUE for 82% of its cropland area. A widespread loss of resilience of carbon stocks was observed, primarily caused by increased precipitation and warming under meteorological drivers, along with aridity induced by soil and atmospheric conditions. Overall, this study highlights the critical role of CUE in assessing the carbon sequestration potential of Indian ecosystems and the need for a better understanding of the factors that influence it to develop effective carbon sequestration policies.

Spatiotemporal Pattern and Driving Factors of Carbon Emissions in Guangxi Based on Geographic Detectors

Analysis of the spatiotemporal distribution pattern and driving factors of carbon emissions has been a focus of research in recent years. However, at the county level, analyses of the driving factors of carbon emissions are still relatively few. This study selected the Guangxi Zhuang Autonomous Region as the research subject, selecting the normalized difference vegetation index (NDVI), nighttime light index (NLI), gross domestic product (GDP), and population density (POP) as driving factors. Based on the geographic detector method, the spatiotemporal distribution pattern and driving factors of carbon emissions at the county level in Guangxi were investigated. The results show the following: (1) There are significant regional differences in the degree of change in carbon emissions. From 2005 to 2020, the total carbon emissions in Guangxi show an upward trend, presenting a “high in the south and low in the north” distribution characteristic, gradually forming a high-level region in the capital city of Nanning, the city of Liuzhou, and some coastal cities (such as the cities of Qinzhou, Beihai, and Fangchenggang) as the core of carbon emissions; (2) NDVI, NLI, GDP, and POP have a relatively high impact on the carbon emission pattern in Guangxi, and the impact of human activity intensity on carbon emissions is higher than that of the influencing factors of NDVI; (3) The interaction between NDVI, NLI, GDP, and POP has a significant impact on the carbon emission pattern. The aforementioned results can provide decision-making suggestions for the social and economic development of Guangxi, as well as the formulation of carbon sequestration policies.

Spatio-Temporal Variation of Carbon Sources and Sinks in the Loess Plateau under Different Climatic Conditions and Land Use Types

The carbon balance of terrestrial ecosystems is intertwined with climate and changes in land use. Over the past 30 years, the Loess Plateau (LP) has experienced temperature increases and an expansion of forest and grassland. The net ecosystem productivity (NEP) underlying these changes is worth investigating. Using three periods (i.e., 1990–2000, 2000–2010, and 2010–2019) of annual average NEP and climatic, topographic, and land use data, we analyzed changes in the spatial distribution of carbon sources and sinks of the LP. Using an optimal parameter-based geographical detector model to discuss the driving factors of carbon sources and sinks, we found that: (1) The area of carbon sinks has been increasing continuously, and that the distributions of both of these elements are zonal. The carbon sinks show a downward trend from south to north, which is mainly driven by climate and land use type. (2) Carbon sources are mainly concentrated in the middle temperate zone, and they are mainly linked to impervious land, unused land, and grassland. The carbon sinks are mainly concentrated in the south temperate zone and plateau climatic zone, and they are mainly linked to forest, grassland, and cultivated land. Additionally, the southern temperate zone has been the most green, due to its superior hydrothermal conditions that sustain carbon sinks. (3) It is not uncommon for some forests, grasslands, and cultivated land to transition between being carbon sources and carbon sinks, especially when affected by human intervention and inadequate management measures. (4) NEP was primarily influenced by CO2 concentration, temperature, and precipitation, and the interaction of these factors greatly influenced the dynamics of carbon sources and sinks, while terrain exerted insignificant impacts on the NEP. This study highlights the importance of the carbon balance in terrestrial ecosystems and can be used to guide the creation of vegetation-based carbon sequestration policies.

Exploring the inter-decadal variability of soil organic carbon in China

Spatiotemporal variability in soil organic carbon (SOC) plays key roles in ecosystem stability and terrestrial carbon cycling. However, the inter-decadal characteristics of SOC variability and its climate drivers in China from the 1980s to 2010s remain unclear. In this study, a modeling framework for combining spatiotemporal prediction models was proposed. Within this model, soil samples from each of the two periods were combined and calibrated to obtain three models, and their prediction outputs were selectively combined to obtain SOC maps for the different inter-decadal periods. A total of 8473 soil samples from three periods (1980s, 2000s and 2010s) were used for model validation. The results suggested that the SOC prediction accuracy in the top 0–20 cm of soil (SOC020) was better than that of the first meter of soil (SOC0100), and the predicted spatial patterns shared characteristics with findings from previous studies. Predictions for the 1990s exhibited relatively high uncertainty, especially in the Tibetan Plateau, Tien Shan, and Northeast China. Both individual and coupled climatic factors exerted scale- and location-specific effects on the SOC. Coupled climatic factors accounted for more than 65% of the SOC variability in both soil layers. The regional SOC in North and Northeast China exhibited inter-decadal decline. Soil in China functioned as carbon sinks from the 1980s to 2010s at a national scale, with SOC020 increasing from 30.40 Pg to 33.97 Pg and SOC0100 from 79.29 Pg to 82.26 Pg. Overall, our results provide reliable baseline data for optimizing carbon cycle models of terrestrial ecosystems, and to guide future carbon sequestration policies.

Optical assessment of the spatial variation in total soil carbon using laser-induced breakdown spectroscopy

Soil carbon storage is a substantial factor in the global carbon cycle. Carbon sequestration in agricultural soils, and the assessment and validation of soil carbon storage, are crucial for the mitigation of agricultural greenhouse gas emissions and for steering towards sustainable farming practices. Enforcement and verification of carbon sequestration policies, methods, and models require extensive soil carbon monitoring capability. However, current conventional laboratory-based methods for soil carbon estimation are laborious, expensive, and time-consuming. In this work, we have developed a compact, robust, and field-capable experimental device based on laser-induced breakdown spectroscopy (LIBS) for the rapid assessment of total soil carbon content and its spatial distribution in mineral soils. The carbon content quantification was performed using a spectral line of carbon at a wavelength of 193.1 nm emitted from the laser-induced plasma plume. The LIBS measurements were performed on soil samples collected from 28 different locations and various depths (up to 1 m) of a test field cultivated with a forage legume (red clover - Trifolium pratense, L.) and grass (Timothy - Phleum pratense, L.) mixture in eastern Finland. A calibration model was established based on a limited and randomly chosen sample set and validated by comparing soil carbon estimates obtained from various locations in the test field using the dry combustion (LECO) method. Further, we demonstrate here the usefulness of LIBS methodology for mapping three-dimensional carbon distribution at the test field. We emphasize here that the calibration model can be generalized to other sample areas under similar soil type with a relative error of less than 10 % and possesses potential for fast on-site determination of spatial variation in total soil carbon, reducing substantially the need of time-consuming sample processing in laboratory. Therefore, LIBS enables frequent and extensive spatial and temporal soil carbon mapping and has the potential to become part of the future carbon monitoring network.

Spatiotemporal Changes in Supply–Demand Patterns of Carbon Sequestration Services in an Urban Agglomeration under China’s Rapid Urbanization

Quantifying the urban supply and demand of carbon sequestration services is an important prerequisite for achieving global carbon neutrality goals. However, the spatiotemporal patterns for balancing the supply and demand of carbon sequestration services in urban agglomerations remain unclear. In this study, NPP/VIIRS nighttime light data were used to identify the carbon sequestration service demand and were then combined with the carbon sequestration service supply to analyze the spatiotemporal patterns of supply and demand for carbon sequestration services in the Harbin-Changchun urban agglomeration (HCUA) in Northeast China. Our results indicate that both the supply and demand of carbon sequestration services showed increasing trends from 2012 to 2020 in the HCUA. The regions with increasing supply and demand trends were mainly located in the eastern mountainous and western urban areas, respectively. The total supply and demand of carbon sequestration services in the HCUA were 2080.3 Mt·C yr−1 and 433.6 Mt·C yr−1, respectively. Carbon surpluses (supply > demand) were found in most areas (98%), although particularly in the southeastern mountainous region. However, with rapid urbanization, in most cities, the supply–demand ratio decreased from 2012 to 2020, and the proportion of carbon deficit regions showed a continuous increase, which was mainly distributed in newly developed urban areas. The low supply–high demand (L-H) pattern showed significant spatial mismatching for supply and demand in the HCUA. The proportion of regions with the L-H pattern also showed a rapidly increasing trend from 2012 to 2020, indicating a more obvious carbon deficit trend in the future. This study provides important guidelines for formulating effective policies for energy consumption and carbon sequestration to combat global warming under China’s rapid urbanization.

The preferential preservation of both different minerals and polyethylene microplastics on aromatic or aliphatic carbon fractions within low or high pyrolysis temperature biochar under mineralization

The effects of soil minerals and microplastics on the stability of biochar (BC) have not been clearly clarified. Here, the mineralization of BC produced at low and high temperatures (L-BC and H-BC) and their artificial soils made of quartz, smectite and kaolinite, respectively, was investigated. BC and BC artificial soils were incubated with or without polyethylene (PE) over 180 d, and the CO2 emission, molecular composition and microbial community structure were assessed. Minerals, especially quartz, had relatively more protection to H-BC than to L-BC. Moreover, smectite preserved aliphatic C of L-BC, and kaolinite protected its aromatic C and aliphatic C. Smectite and kaolinite likely had comparable ability to protect BCs. Quartz protected the aromatic C of H–BCs by adsorbing the hydrophobic aromatic C. Minerals also led to the shift of the dominant bacteria from r-strategists to K-strategists, which alleviated degradation of labile carbon and reduced the CO2 emissions. PE decreased the CO2 emissions of L-BC as well as its artificial soils and the opposite effect was observed for H-BC. PE enhanced the aromatic C associated with minerals within H-BC artificial soils, and inhibited the mineralization of H-BC. PE degradation by fungi (Aspergillus) could be largely responsible for the rise in CO2 emissions of H-BC artificial soils. This study addressed the different effect of minerals and PE in the process of BC mineralization and provided the basis for elucidating the stability mechanism of BC in soil, which would be helpful for establishment of BC carbon sequestration policy.

Decoupling Relationship between Urbanization and Carbon Sequestration in the Pearl River Delta from 2000 to 2020

Rapid urbanization has a significant impact on the ecological environment. Net primary productivity (NPP) can effectively reflect the growth of urban vegetation and the carbon sequestration capacity of an ecosystem. Taking the rapidly growing Pearl River Delta (PRD) as our study area, the relative contributions of human activities and climate change to NPP were analyzed using an improved two-step method based on residual trend analysis. The decoupling index was used to compare the coordinated development of socioeconomic factors and the NPP in different time periods. This study lays the foundation for formulating comprehensive and reasonable urban low-carbon development measures. The results showed that (1) NPP decreased significantly before 2010, but by 2019, NPP in most regions of the PRD showed a slight increase. The NPP of new urban land was better than that of original urban land. (2) The negative contribution of climatic factors to NPP was clearer than that of human activities, and human activities contributed positively to NPP outside urban land. (3) The decoupling status of socioeconomic factors and NPP is improving, and the degree of decoupling in 2010–2019 was higher than that in 2000–2010. In conclusion, as the first forest urban agglomeration in China, the PRD has shown a good implementation of carbon sequestration policies, which can provide a reference for the coordinated development of urbanization and carbon sequestration.

Carbon sequestration in French agricultural soils: A spatial economic evaluation

AbstractSoil organic carbon sequestration measures entail costs to farmers with different individual characteristics and located in different areas. A cost‐effective analysis taking into account these heterogeneities is crucial for developing effective public policy aimed at increasing carbon sequestration. We undertake such an analysis focusing on three soil organic carbon sequestration measures: no‐till, extension of temporary grasslands, and hedgerows. Through an optimization model applied to France, our results show that only extension of temporary grasslands can store carbon at low cost, though their potential for carbon sequestration is also low. For an ambitious carbon sequestration target, no‐till and hedgerows are needed. Because of heterogeneities among farmers, we show that economic incentives are more cost effective than command and control measures. Furthermore, we highlight that the carbon sequestration policy tested here is unable to totally neutralize agricultural greenhouse gas emissions and that a combination of agricultural and environmental policies is essential for tackling climate change.

Forest Resource Management and Its Climate-Change Mitigation Policies in Taiwan

Based on high carbon emissions in recent years (i.e., about 11 metric tons in 2018) per capita in terms of carbon dioxide equivalents, Taiwan has actively development greenhouse gas (GHG) reduction action plans. One of the action plans has been to promote afforestation and reforestation in non-forested lands for carbon sequestration. Thus, this paper aims to address the forest resources in Taiwan by using the latest national survey, reporting on an interactive analysis of forest carbon sequestration, GHG emissions, and climate-change mitigation policies. In this regard, the methodology is based on the official websites of forest resources, GHG emissions, and carbon sequestration from the yearbooks, national statistics, and regulations relevant to the mitigation policies in the forestry sector. It is found that Taiwan’s forest area is estimated to be 2.197 million hectares, which corresponds to a total forest stock volume of about 502.0 million cubic meters. During the period of 1990–2018, the change in total carbon sequestration did not vary much (with the exception of 2009), decreasing from 23.4 million metric tons in 1990 to 21.4 million metric tons in 2018. Compared to the total carbon dioxide emissions (i.e., 102.4 million metric tons in 1990 and 282.8 million metric tons in 2018), the contribution to GHG mitigation in the forestry sector shows a declining trend. However, biomass (i.e., wood) carbon sequestration indicates a slight increase from 20.4 million metric tons in 2010 to 20.7 million metric tons in 2018 due to the afforestation policy. Obviously, regulatory policies, based on the Forestry Act and the Greenhouse Gas Reduction & Management Act in 2015, play a vital role in mitigating GHG emissions in Taiwan. The discussion on the regulations is further addressed to highlight climate-change mitigation policies in Taiwan’s forestry sector.

Investigating the spatio-temporal variability of soil organic carbon stocks in different ecosystems of China

Soil organic carbon (SOC) significantly influences soil fertility, soil water holding capacity, and plant productivity. In this study, we applied two boosted regression tree (BRT) models to map SOC stocks across China in the 1980s and the 2010s. The models incorporated nine environmental variables (climate, topography, and biology) and 8897 (in the 1980s) and 4534 (in the 2010s) topsoil (0–20 cm) samples. During the two study periods, 20% of the soil samples were randomly selected for model testing, and the remaining samples were used as a training set to construct the models. The verification results showed that incorporating climate environment variables significantly improved the model prediction in both study periods. Mean annual temperature, mean annual precipitation, elevation, and the normalized difference vegetation index were the dominant environmental factors affecting the spatial distribution of SOC stocks. The full-variable model predicted similar spatial distributions of SOC stocks for the 1980s and the 2010s. SOC stocks in China showed an increasing trend over the past 30 years, from 3.9 kg m−2 in the 1980s to 4.6 kg m−2 in the 2010s. In both periods, topsoil SOC stocks were mainly stored in agroecosystems, forests, and grasslands in the 1980s, with values of 9.5, 12.0, and 11.4 Pg C, respectively. Our study provides reliable information on Chain's carbon distribution, which can be used by land managers and the national government to formulate relevant land use and carbon sequestration policies.

Evaluation of the Potential for Soil Organic Carbon Content Monitoring With Farmers

Increasing soil organic carbon (SOC) content is crucial for soil quality and climate change mitigation. SOC monitoring is indispensable to the corresponding policies and should provide results at farm scale to allow for incentives. In Switzerland farmers perform mandatory analyses of the SOC content of the 0-20 cm topsoil of every field, based on a composite sample, at least every ten years. The corresponding results are stored in a database in canton of Geneva. These data may be relevant for topsoil SOC monitoring, in particular for carbon sequestration policies, provided that they show appropriate quality, which is analyzed in this study. The minimum detectable change (MDC) of past results calculated based on the observed SOC changes was 0.013 % g g-1 at canton scale (2700 fields). Based on extended sampling of three representative fields different sampling strategies were simulated to determine the best future sampling guidelines for farmers. Collecting 20 aliquots with a gouge on the field diagonals was considered the best sampling compromise with field MDC of about 0.1 % g g-1 and a sampling duration of 20 mn. Compared to this procedure, former farmers’ sampling was not biased in average but showed a variance of 0.22% g g-1 due to smaller number of aliquots and varying sampling depths. Based on the best sampling results and assumptions on farm-scale SOC variance or SOC differences, the MDCs at farm scale ranged from 0.21 to 0.12 % g g-1 (5 fields) and 0.09 to 0.05 % g g-1 (30 fields), respectively. These MDCs are small compared to published monitoring networks MDCs, and allow determining SOC change rates at farm scale, thus offering perspectives for inexpensive and efficient monitoring in the frame of soil quality or climate mitigation incentives. For the latter, however, additional information with equivalent soil mass and deeper layers carbon content would be necessary.

Slow-growing trees sequester more carbon

Tree Demography Dendrochronology—the study of tree growth patterns through the analysis of annual growth rings—is a powerful tool for studying the past but may also help to inform the future. Through tree-ring analysis of living and dead conifers from highland ecosystems in Spain and Russia, Buntgen et al. show that longest-lived individuals are those with the slowest juvenile growth rates. This means that higher levels of carbon accumulation are achieved in communities of slow-growing species, which indicates potential limits to the effectiveness of policies for carbon sequestration that rely on fast-growing tree plantations to mitigate the effects of global warming. Nat. Commun. 10 , 2171 (2019).

Potential complementarity between forest carbon sequestration incentives and biomass energy expansion

There is a growing literature on the potential contributions the global forest sector could make toward long-term climate action goals through increased carbon sequestration and the provision of biomass for energy generation. However, little work to date has explored possible interactions between carbon sequestration incentives and bioenergy expansion policies in forestry. This study develops a simple conceptual model for evaluating whether carbon sequestration and biomass energy policies are carbon complements or substitutes. Then, we apply a dynamic structural model of the global forest sector to assess terrestrial carbon changes under different combinations of carbon sequestration price incentives and forest bioenergy expansion. Our results show that forest bioenergy expansion can complement carbon sequestration policies in the near- and medium-term, reducing marginal abatement costs and increasing mitigation potential. By the end of the century these policies become substitutes, with forest bioenergy expansion increasing the costs of carbon sequestration. This switch is driven by relatively high demand and price growth for pulpwood under scenarios with forest bioenergy expansion, which incentivizes management changes in the near- and medium-term that are carbon beneficial (e.g., afforestation and intensive margin shifts), but requires sustained increases in pulpwood harvest levels over the long-term.

Multiple-stand forest management under fire risk: Analytical characterization of stationary rotation ages and optimal carbon sequestration policy

This paper focuses on the characterization of stationary states for a multiple-stand forest that is subject to forest fires and managed by a producer who has expected utility preferences. An analytical and tractable characterization of the stationary rotation age is established on the basis of Karush–Kuhn–Tucker conditions. The rotation age is shown to be unique and to depend on the risk probability but not on producer's risk preferences. A numerical application, using these analytical findings and based on the forestry of maritime pine in southwestern France is conducted. This numerical application consists in designing an optimal carbon sequestration policy based on financial incentives aiming at extending forest rotation ages. Results show that forest fire probability has a significant decreasing impact on sequestration costs.

Payments for Carbon Sequestration to Alleviate Development Pressure in a Rapidly Urbanizing Region

The purpose of this study was to determine individuals' willingness to enroll in voluntary payments for carbon sequestration programs through the use of a discrete choice experiment delivered to forest owners living in the rapidly urbanizing region surrounding Charlotte, North Carolina. We examined forest owners' willingness to enroll in payments for carbon sequestration policies under different levels of financial incentives (annual revenue), different contract lengths, and different program administrators (e.g., private companies versus a state or federal agency). We also examined the influence forest owners' sense of place had on their willingness to enroll in hypothetical programs. Our results showed a high level of ambivalence toward participating in payments for carbon sequestration programs. However, both financial incentives and contract lengths significantly influenced forest owners' intent to enroll. Neither program administration nor forest owners' sense of place influenced intent to enroll. Although our analyses indicated that payments from carbon sequestration programs are not currently competitive with the monetary returns expected from timber harvest or property sales, certain forest owners might see payments for carbon sequestration programs as a viable option for offsetting increasing tax costs as development encroaches and property values rise.

Spatial autocorrelation reduces model precision and predictive power in deforestation analyses

AbstractGeneralized linear models are often used to identify covariates of landscape processes and to model land‐use change. Generalized linear models however, overlook the spatial component of land‐use data, and its effects on statistical inference. Spatial autocorrelation may artificially reduce variance in observations, and inflate the effect size of covariates. To uncover the consequences of overlooking this spatial component, we tested both spatially explicit and non‐spatial models of deforestation for Colombia. Parameter estimates, analyses of residual spatial autocorrelation, and Bayesian posterior predictive checks were used to compare model performance. Significant residual correlation showed that non‐spatial models failed to adequately explain the spatial structure of the data. Posterior predictive checks revealed that spatially explicit models had strong predictive power for the entire range of the response variable and only failed to predict outliers, in contrast with non‐spatial models, which lacked predictive power for all response values. The predictive power of non‐spatial models was especially low in regions away from Colombia's center, where about half the observations were clustered. While all analyses consistently identified a core of important covariates of deforestation rates, predictive modeling requires parameter estimates informed by the spatial structure of the data. To inform increasingly important forest and carbon sequestration policy, land‐use models must account for spatial autocorrelation.

Forest Carbon Sequestration Subsidy and Carbon Tax as Part of China’s Forestry Policies

Forestry is an effective strategy for climate change mitigation. However, forestry activities not only sequester carbon but also release CO2. It is therefore important to formulate carbon subsidy and carbon taxation policies on the basis of the price of carbon. In this study, a forestry-based Computable General Equilibrium (CGE) model was built by using input-output data of China in 2014 to construct a Social Accounting Matrix (SAM). The model simulates different carbon price scenarios and was used to explore the effects of carbon subsidy and carbon taxation policies on the forestry economy. The main results can be summarized as follows: When the carbon price is low, the implementation of the policy increases forestry output and causes forest product prices to rise. When the carbon price is high, the carbon tax will produce an inhibitory effect, and output and prices will decline. With the constant rise of the carbon price, value addition will decrease, with flow to other industries. For the carbon sequestration policy, there is a reasonable carbon price range bound. In light of these results, relevant policies are proposed.