• Energy Research

The protection and expansion of forest carbon sinks are critical to achieving climate-change mitigation targets. Yet, the increasing frequency and severity of forest disturbances challenge the sustainable provision of forest services. We investigated patterns of forest disturbances’ impacts on carbon sinks by combining spatial datasets of forest carbon sequestration from biomass growth and emissions from fire and bark beetle damage in the western United States (U.S.) and valued the social costs of forest carbon losses. We also examined potential future trends of forest carbon sinks under two climate-change projections using a global vegetation model. We found that forest carbon losses from bark-beetle damage were larger than emissions from fires between 2003 and 2012. The cumulative social costs of forest carbon losses ranged from USD 7 billion to USD 72 billion, depending on the severity of global warming and the discount rate. Forest carbon stocks could increase around 5% under Representative Concentration Pathway (RCP) 4.5 or 7% under RCP 8.5 by 2091 relative to 2011 levels, mostly in forests with high net primary productivity. These results indicate that spatially explicit management of forest disturbances may increase forest carbon sinks, thereby improving opportunities to achieve critical climate-change mitigation goals.

As one of the countries which has been experiencing a forest transition, China provides important insights into and theoretical and empirical knowledge of forest transition. In this study, through the framework of Sustainable Livelihood Analysis (SLA) and questionnaire surveys, we examined forest transition, farmers’ land-use activities and livelihood changes in Chicheng county, a typical mountainous area in Northern China, during 1975–2018. Most villages of Chicheng county experienced forest transition during the period of 2003–2005, but some villages experienced forest transition in 2010–2015. Forest transition variation over time was influenced by land use and livelihood changes. Livelihood resources, policy and institutional constraints and livelihood strategies had significant influences on land use and then caused variation in forest transition characteristics. The process of “livelihood–land use–forest transition” was the key to achieving and maintaining forest transition, and the interaction between livelihood and land use was a negative feedback relationship between society and ecology. The dominant path of forest transition in Chicheng county was the “economic development path”. Moreover, the “intensive agriculture path of small-scale farmers” enhanced the “economic development path”, and the “forest scarcity path” promoted both of the above two paths. This implies that the feedback and interactions between society and ecology should be taken into account so as to achieve a sustainable human and environmental system.

Abstract Livestock production is an integral part of the global food system and the livelihoods of local people, but it also raises questions of environmental sustainability due to issues such as greenhouse gas (GHG) emissions, biodiversity decline, land degradation, and water use. Further challenges to extensive livestock systems may arise from changes in climate and the global economy (particularly variation in prices for livestock and carbon). However, significant potential exists for both mitigating these impacts and adapting to change via altering stocking rates, managing fire, and supplementing cattle diets to reduce methane emissions. We developed an integrated, spatio-temporal modelling approach to assess the effectiveness of these options for land management in northern Australia’s tropical savanna under different global change scenarios. Performance was measured against a range of sustainability indicators, including environmental (GHG emissions, biodiversity, water intake, and land condition) and agricultural (profit, beef production) outcomes. Our model shows that maintaining historical stocking rates is not environmentally sustainable due to the accelerated land degradation exacerbated by a changing climate. However, planned early dry season burning substantially reduced emissions, and in our simulations was profitable under all global change scenarios that included a carbon price. Overall, the balance between production and environmental outcomes could be improved by stocking below modelled carrying capacity and implementing fire management. This management scenario was the most profitable (more than double the profit from maintaining historical stocking rates), prevented land degradation, and reduced GHG emissions by 23%. By integrating the cumulative impacts of climate change, external economic drivers, and management actions across a range of sustainability indicators, we show that the future of rangelands in Australia’s savannas has the potential to balance livestock production and environmental outcomes.

Abstract Globally, the development of the unconventional natural gas (UNG) industry is expected to continue as gas consumption increases in the transition to cleaner energy sources. However, social and regulatory factors may constrain UNG activity at regional scales. Robust impact assessments of the effects of the UNG industry at different phases of development could help reduce trade-offs of energy policy and promote overall welfare improvements. We assessed if the early phases of the coal seam gas (CSG, a type of UNG) industry in New South Wales, Australia produced regional economic changes between 2001 and 2011. We combined spatial econometrics, genetic matching algorithms and seemingly unrelated regressions with instrumental variables to control for multiple factors influencing regional economic patterns (e.g., climate, human capital) to estimate the effect of the CSG industry on local income and employment. Results show that regions with CSG activity had 7% (±5%, 95% C.I.) higher family income than regions without CSG mining. No statistical evidence of indirect employment multiplier effects from CSG activity were found. The analysis can inform social license and regulatory decisions related to the CSG industry that impact competing social priorities such as energy and water security, economic growth and environmental health.

Prévoir les futurs changements fonciers est crucial pour anticiper les impacts sociétaux et environnementaux et informer les réponses à différentes échelles. Nous avons conçu un modèle intégré de changement de territoire à haute résolution et avons prévu le changement de territoire de l'Australie pour les années 2020, 2025 et 2030 pour les utilisations des terres cultivées, des forêts, des prairies et des terres bâties à l'aide d'un calcul basé sur le cloud et à haute performance. Un ensemble spatialement explicite de facteurs a été introduit dans un classificateur forestier aléatoire pour générer des couches d'adéquation de 30 m par classe pour le pays, qui ont ensuite été utilisées pour allouer l'utilisation des terres. Le modèle a été validé par rapport aux données de 2015, puis l'utilisation des terres a été projetée jusqu'en 2030. La précision au niveau national était d'environ94 %. Les prévisions ont montré des augmentations dans les prairies et les zones bâties et des diminutions dans les forêts et les terres cultivées. Notre cadre de modélisation élargit les capacités actuelles des modèles de changement de terre à grande échelle et fournit des prévisions foncières multi-classes uniques en leur genre pour l'Australie qui peuvent éclairer la politique foncière à plusieurs échelles en Australie. Predecir el cambio futuro de la tierra es crucial para anticipar los impactos sociales y ambientales e informar las respuestas a diferentes escalas. Diseñamos un modelo integrado de cambio de tierras de alta resolución y pronosticamos el cambio de tierras de Australia para los años 2020, 2025 y 2030 para los usos de tierras de cultivo, bosques, pastizales y construcciones utilizando computación basada en la nube y de alto rendimiento. Se introdujo un conjunto espacialmente explícito de impulsores en un clasificador forestal aleatorio para generar capas de idoneidad de 30 m por clase para el país, que luego se utilizaron para asignar el uso de la tierra. El modelo se validó con datos de 2015, luego se proyectó el uso de la tierra hasta 2030. La precisión a nivel nacional fue de ~94%. Los pronósticos mostraron aumentos en pastizales y áreas edificadas y disminuciones en bosques y tierras de cultivo. Nuestro marco de modelado amplía las capacidades actuales de los modelos de cambio de tierras a gran escala y proporciona un pronóstico de tierras multiclase único en su tipo para Australia que puede informar la política de tierras a múltiples escalas en Australia. Predicting future land change is crucial in anticipating societal and environmental impacts and informing responses at different scales. We designed an integrated, high-resolution, land-change model and forecasted Australia's land change for the years 2020, 2025 and 2030 for Cropland, Forest, Grassland, and Built-up land-uses using cloud-based and high-performance computing. A spatially explicit set of drivers was fed into a random forest classifier to generate 30-m per-class suitability layers for the country, which were then used for allocating land-use. The model was validated against 2015 data, then land-use was projected until 2030. Accuracy at the national level was ∼94%. Forecasts showed increases in Grassland and Built-up areas and decreases in Forest and Cropland. Our modelling framework expands the current capabilities of large-scale land-change models and provides a first-of-its-kind multiclass land forecast for Australia that can inform land policy at multiple scales in Australia. يعد التنبؤ بتغير الأراضي في المستقبل أمرًا بالغ الأهمية في توقع الآثار المجتمعية والبيئية وإبلاغ الاستجابات على مستويات مختلفة. لقد صممنا نموذجًا متكاملًا وعالي الدقة لتغيير الأراضي وتوقعنا تغيير الأراضي في أستراليا للأعوام 2020 و 2025 و 2030 للأراضي الزراعية والغابات والمراعي واستخدامات الأراضي المبنية باستخدام الحوسبة القائمة على السحابة والأداء العالي. تم إدخال مجموعة واضحة مكانيًا من المحركات في مصنف عشوائي للغابات لتوليد طبقات ملاءمة 30 مترًا لكل فئة للبلد، والتي تم استخدامها بعد ذلك لتخصيص استخدام الأراضي. تم التحقق من صحة النموذج مقابل بيانات عام 2015، ثم تم توقع استخدام الأراضي حتى عام 2030. بلغت الدقة على المستوى الوطني 94 ٪. أظهرت التوقعات زيادات في الأراضي العشبية والمناطق المبنية وانخفاضات في الغابات والأراضي الزراعية. يوسع إطار النمذجة لدينا القدرات الحالية لنماذج تغيير الأراضي واسعة النطاق ويوفر توقعات الأراضي متعددة الطبقات الأولى من نوعها لأستراليا والتي يمكن أن تسترشد بها سياسة الأراضي على نطاقات متعددة في أستراليا.

Abstract Forest cover gains and losses occur in response to complex environmental and anthropogenic pressures. Yet the impact of forest gains and losses on the provision of ecosystem services differs markedly. Here we investigate the social costs of potential forest carbon change in Australia’s intensive agricultural region from 2015 to 2050 using spatial forest cover change and forest carbon models combined with climate and socioeconomic projections. More than 24,000 possible scenarios were used to identify the trend and lower and upper bounds of forest cover/carbon change. Net deforestation (3.5 million hectares, Mha) under the lower bound forest cover (LBFC) projection was around one-third less than net reforestation (4.8 Mha) under the upper bound forest cover (UBFC) projection by 2030. However, the CO2 emissions (1.3 Gigatons of CO2, GtCO2) from deforestation were more than double the sequestration (0.5 GtCO2) from reforestation. The social costs (up to 134 billion dollars) of the LBFC were almost five times the benefits of the UBFC (up to 28 billion dollars). The asymmetry decreased over time but persisted to 2050. This shows the markedly different social costs of potential forest carbon losses and gains under global change, evidence which can be useful to policymakers, stakeholders, and practitioners.

Abstract The achievement of several sustainable development goals and the Paris Climate Agreement depends on rapid progress towards sustainable food and land systems in all countries. We have built a flexible, collaborative modeling framework to foster the development of national pathways by local research teams and their integration up to global scale. Local researchers independently customize national models to explore mid-century pathways of the food and land use system transformation in collaboration with stakeholders. An online platform connects the national models, iteratively balances global exports and imports, and aggregates results to the global level. Our results show that actions toward greater sustainability in countries could sum up to 1 Mha net forest gain per year, 950 Mha net gain in the land where natural processes predominate, and an increased CO2 sink of 3.7 GtCO2e yr−1 over the period 2020–2050 compared to current trends, while average food consumption per capita remains above the adequate food requirements in all countries. We show examples of how the global linkage impacts national results and how different assumptions in national pathways impact global results. This modeling setup acknowledges the broad heterogeneity of socio-ecological contexts and the fact that people who live in these different contexts should be empowered to design the future they want. But it also demonstrates to local decision-makers the interconnectedness of our food and land use system and the urgent need for more collaboration to converge local and global priorities.