Economic development and ecological restoration guided by policies has had a profound impact on the relationship between ecosystem service supply and consumption in the past few decades. Exploring the relationship in specific study areas is necessary to support regional planning for sustainability. In this study, we analyzed the equilibrium relationship between ecosystem service supply and consumption driven by economic development and ecological restoration from 1995 to 2018 in Northeast China. We quantified the supply and consumption of three critical ecosystem services, food production, water yield and atmospheric regulation, and identified the main areas for supply and consumption of ecosystem services. We measured the quantity and spatial equilibrium relationship between ecosystem service supply and consumption driven by economic development and ecological restoration at economic megaregion scale. We found the new industrial structure shaped by regional economic development policies formed the new ecosystem service consumer demand. The development of agricultural industry not only resulted in the increase of water consumption, but also the scope of water consumption was expanded in Northeast China. The development of tertiary industry causes the change of atmospheric regulation consumption in urban agglomeration. What’s more, economic development exacerbated imbalances in the supply and consumption of ecosystem services. The unbalanced areas where food supply was less than consumption were in the clusters of Harbin, Changchun, Shenyang, and coastal cities. Since food products can circulate freely through the market, this imbalance will not fundamentally affect regional food security, but will improve the level of agricultural industrialization and scale. The implementation of the grain economic policy caused the rapid expansion of unbalanced areas where water supply was less than consumption. The incredible space mismatch between the supply and consumption of ecosystem services still exists for a long time. However, the implementation of the ecological restoration didn’t effectively solve the problem of insatiable ecosystem service consumption. The ecosystem service consumption brought by economic development need to be given the utmost attention when formulating ecological restoration policies and economic development policies. The results can provide insights for enhancing economic sustainability in northeast china, as well other economic megaregion with similar characteristics throughout the world.

Stem taper function is an important concept in forest growth and yield modeling, and forest management. However, the additivity of the function and the inherent correlations between stem components (diameter outside bark—dob, diameter inside bark—dib, and double-bark thickness—dbt) are seldom considered. In this paper, a total disaggregation model (TDM) structure was developed based on the well-known Kozak (2004) model to ensure the additivity of the stem components. The reconstructed model was fitted with the data of 1281 felled Dahurian larch trees from three regions of Daxing’anling Mountains in Northeast China. The results from TDM were compared with other additive model structures including adjustment in proportion (AP), non-additive taper models (NAM), and three logical structures of NSUR (AMO, SMI, SMB). The results showed that the difference was significant among the three regions. The performance of TDM was slightly better than those of other model structures. Therefore, TDM was considered as another optimal additive system to estimate stem, bark thickness, and volume predicting for Dahurian larch in Northeast China besides NSUR, a method widely used in calculating additive volume or biomass throughout the world. We believe this work is cutting-edge, and that this methodology can be applied to other tree species.

Accuracy estimation of forest stand volume with stem taper function is an important subject in the field of forestry study. For decreasing the time-intensive and labor-cost fieldwork in traditional forest science, how to select an optimal sampling strategy to precisely estimate stand volume is a focusing question for forest scientists. To deal with forementioned challenges and ensure the precision and reliability of stand volume estimation, we utilized portable Lidar data from 50 conifers to extract the accurate trunk models to build accuracy estimation models of stand volumes with two sampling strategies (the uniform sampling of trunk(UST), the segmented uniform sampling of trunk delineated by breast height diameter (SUST)) and two integration methods (the cumulative summation model(CMM), the Gauss-Legendre numerical integral model(GNIM)),and these were compared with results of stem taper functions and stand volume models constructed with field-measured data.The results showed that: (1) There was no discernible difference between the measured trunk lumber volume and the estimation results of lumber volume in the whole-trunk uniform segmentation and the cumulative accumulation of upper and lower trunk segments bounded by the diameter at breast height (DBH) when the trunk segments were 8 and 6, respectively. (2)when trunks were divided into 8 segments with the UST strategy and 6 segments with the SUST strategy, the fitting accuracies of the corresponding stem taper functions were 0.9512 and 0.9637. Furthermore, by stem taper function and the GNIM method, the estimation accuracies of stand volumes were 0.9137 and 0.9360, respectively. Additionally,the analysis of variance and confidence intervals indicated that two models of estimating stand volume,based on two sampling strategies, demonstrated reliability and consistency. (3)given that the number of trunk segments was smaller and the accuracy of stand volume estimation was higher, the SUST strategy was optimal for those. The strategy can also provide an important reference for forestry research and timber consumption.