Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale.

Ajaz Ahmed MA ，Abd-Elrahman A ，Escobedo FJ ，Cropper WP Jr ，Martin TA ，Timilsina N ... -  《-》

Modeling the spatially heterogeneous relationships between tradeoffs and synergies among ecosystem services and potential drivers considering geographic scale in Bairin Left Banner, China.

Understanding the complex relationships of tradeoffs and synergies among ecosystem services (ESs) is essential to achieve a comprehensive, coordinated, and sustainable development for human well-being. However, the quantitative measurement for the properties and intensities within these relationships as well as the deeper exploration of its formation mechanism from a spatial-explicit perspective is still a challenge. In this study, a comprehensive and general methodology was developed to quantitatively illustrate the intensities of tradeoffs/synergies among pairwise ESs and explore the spatially heterogeneous relationships between these relations and several socio-ecological drivers, integrating InVEST, geographical detector and multi-scale geographically weighted regression (MGWR) methods. The results indicated that (1) the properties and intensities of tradeoffs/synergies among various ESs varied greatly over space and presented significant clustered distribution patterns; (2) different relations between ESs were dominated by diverse drivers and the combined effects from multiple factors were stronger than any single one within this process. The tradeoffs/synergies between soil conservation and other ESs were mainly affected by geomorphological drivers including elevation and slope, while relations involved habitat quality could be attributed to vegetation and climate drivers such as precipitation and vegetation fractional cover. The relationships among ESs were more susceptible to topographic and anthropogenic drivers when concerning the carbon storage service; (3) compared to global ordinary least squares and local geographically weighted regression (GWR), the MGWR obtained better performance in explaining relationships between tradeoffs/synergies among ESs and potential drivers by operating different spatial scales. Accordingly, several spatially targeted ecological measures were proposed and recommended to reduce ESs tradeoffs and ultimately achieve better synergies. This research could enrich the methods in revealing the complex evolvement mechanism behind the tradeoffs/synergies among ESs and the proposed framework also provided a new perspective in the field of ESs tradeoffs/synergies studies and might be valuable guidance for other regions worldwide.

Xue C ，Chen X ，Xue L ，Zhang H ，Chen J ，Li D ... -  《-》

Quantifying the biophysical and socioeconomic drivers of changes in forest and agricultural land in South and Southeast Asia.

South and Southeast Asia (SSEA) has been a hotspot for land use and land cover change (LULCC) in the past few decades. The identification and quantification of the drivers of LULCC are crucial for improving our understanding of LULCC trends. So far, the biophysical and socioeconomic drivers of forest change have not been quantified at the regional scale, particularly for SSEA. In this study, we quantify the biophysical and socioeconomic drivers of forest change on a country-by-country basis in SSEA using an integrated quantitative methodology, which systematically accounts for previously published driver information and regional datasets. We synthesize more than 200 publications to identify the drivers of the forest change at different spatial scales in SSEA. Subsequently, we collect spatially explicit proxy data to represent the identified drivers. We quantify the dynamics of forest and agricultural land from 1992 to 2015 using the Climate Change Initiative (CCI) land cover data developed by the European Space Agency (ESA). A geographically weighted regression method is employed to quantify the spatially heterogeneous drivers of forest change. Our results show that socioeconomic drivers are more important than biophysical drivers for the conversion of forest to agricultural land in South Asia and maritime Southeast Asia. In contrast, biophysical drivers are more important than socioeconomic drivers for the conversion of agricultural land to forest in maritime Southeast Asia and less important in South Asia. Both biophysical and socioeconomic drivers contribute approximately equally to both changes in the mainland Southeast Asia region. By quantifying the dynamics of forest and agricultural land and the spatially explicit drivers of their changes in SSEA, this study provides a solid foundation for LULCC modeling and projection.

Xu X ，Jain AK ，Calvin KV 《-》

Scenarios reveal pathways to sustain future ecosystem services in an agricultural landscape.

Sustaining food production, water quality, soil retention, flood, and climate regulation in agricultural landscapes is a pressing global challenge given accelerating environmental changes. Scenarios are stories about plausible futures, and scenarios can be integrated with biophysical simulation models to explore quantitatively how the future might unfold. However, few studies have incorporated a wide range of drivers (e.g., climate, land-use, management, population, human diet) in spatially explicit, process-based models to investigate spatial-temporal dynamics and relationships of a portfolio of ecosystem services. Here, we simulated nine ecosystem services (three provisioning and six regulating services) at 220 × 220 m from 2010 to 2070 under four contrasting scenarios in the 1,345-km2 Yahara Watershed (Wisconsin, USA) using Agro-IBIS, a dynamic model of terrestrial ecosystem processes, biogeochemistry, water, and energy balance. We asked (1) How does ecosystem service supply vary among alternative future scenarios? (2) Where on the landscape is the provision of ecosystem services most susceptible to future social-ecological changes? (3) Among alternative future scenarios, are relationships (i.e., trade-offs, synergies) among food production, water, and biogeochemical services consistent over time? Our results showed that food production varied substantially with future land-use choices and management, and its trade-offs with water quality and soil retention persisted under most scenarios. However, pathways to mitigate or even reverse such trade-offs through technological advances and sustainable agricultural practices were apparent. Consistent relationships among regulating services were identified across scenarios (e.g., trade-offs of freshwater supply vs. flood and climate regulation, and synergies among water quality, soil retention, and climate regulation), suggesting opportunities and challenges to sustaining these services. In particular, proactive land-use changes and management may buffer water quality against undesirable future climate changes, but changing climate may overwhelm management efforts to sustain freshwater supply and flood regulation. Spatially, changes in ecosystem services were heterogeneous across the landscape, underscoring the power of local actions and fine-scale management. Our research highlights the value of embracing spatial and temporal perspectives in managing ecosystem services and their complex interactions, and provides a system-level understanding for achieving sustainability of the food-water-climate nexus in agricultural landscapes.

Qiu J ，Carpenter SR ，Booth EG ，Motew M ，Zipper SC ，Kucharik CJ ，Chen X ，Loheide SP 2nd ，Seifert J ，Turner MG ... -  《ECOLOGICAL APPLICATIONS》

Predicting the responses of forest distribution and aboveground biomass to climate change under RCP scenarios in southern China.

In the past three decades, our global climate has been experiencing unprecedented warming. This warming has and will continue to significantly influence the structure and function of forest ecosystems. While studies have been conducted to explore the possible responses of forest landscapes to future climate change, the representative concentration pathways (RCPs) scenarios under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5) have not been widely used in quantitative modeling research of forest landscapes. We used LANDIS-II, a forest dynamic landscape model, coupled with a forest ecosystem process model (PnET-II), to simulate spatial interactions and ecological succession processes under RCP scenarios, RCP2.6, RCP4.5 and RCP8.5, respectively. We also modeled a control scenario of extrapolating current climate conditions to examine changes in distribution and aboveground biomass (AGB) among five different forest types for the period of 2010-2100 in Taihe County in southern China, where subtropical coniferous plantations dominate. The results of the simulation show that climate change will significantly influence forest distribution and AGB. (i) Evergreen broad-leaved forests will expand into Chinese fir and Chinese weeping cypress forests. The area percentages of evergreen broad-leaved forests under RCP2.6, RCP4.5, RCP8.5 and the control scenarios account for 18.25%, 18.71%, 18.85% and 17.46% of total forest area, respectively. (ii) The total AGB under RCP4.5 will reach its highest level by the year 2100. Compared with the control scenarios, the total AGB under RCP2.6, RCP4.5 and RCP8.5 increases by 24.1%, 64.2% and 29.8%, respectively. (iii) The forest total AGB increases rapidly at first and then decreases slowly on the temporal dimension. (iv) Even though the fluctuation patterns of total AGB will remain consistent under various future climatic scenarios, there will be certain responsive differences among various forest types.

Dai E ，Wu Z ，Ge Q ，Xi W ，Wang X ... -  《-》