With the rapid advancement of urbanization and industrialization, the contradiction between the social economy and resources and the environment has become increasingly prominent. On the basis of limited land resources, the way to promote multi-objective comprehensive development such as economic, social development and ecological and environmental protection through structure and layout regulation, so as to maximize regional comprehensive benefits, is an important task of current land spatial planning. Our aim is to obtain land-use-change data in the study area using remote-sensing data inversion and multiple-model simulation. Based on land suitability evaluation, we predict and optimize the land use structure of the study area in 2030 and evaluate and compare ecosystem services. Based on remote-sensing images and eco-environmental data from 1985 to 2014 in the study area, land use/land cover change (LUCC) and future simulation data were obtained by using supervised classification, landscape metrics and the CA-Markov model. The ecosystem services were evaluated by the InVEST model. The analytic hierarchy process (AHP) method was used to evaluate the land suitability for LUCC. Finally, the LUCC in 2030 under two different scenarios, Scenario_1 (prediction) and Scenario_2 (optimization), were evaluated, and the ecosystem service functions were compared. In the last 30 years, the landscape in the study area has gradually fragmented, and the built-up land has expanded rapidly, increased by one-third, mainly at the cost of cropland, orchards and wasteland. According to the suitability evaluation, giving priority to the land use types with higher environmental requirements will ensure the study area has a higher ecosystem service value. The rapid development of urbanization has a far-reaching impact on regional LUCC. Intensive land resources need reasonable and scientific land use planning, and land use planning should be based on the suitability evaluation of land resources, which can improve the regional ecosystem service function.

The variability of leaf stoichiometry has been studied at different taxonomic levels across various geographic ranges. However, the intraspecific variations in leaf stoichiometry of widely distributed species are poorly understood. We characterize the biogeographical patterns and environmental controls of leaf nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), and sulfur (S) concentrations of Quercus variabilis Blume, a widely distributed tree species of significant economic and ecological value in China. The stoichiometry of Q. variabilis leaves exhibited substantial variation, which was strongly affected by climatic factors and respective concentrations of soil nutrients but had little association with leaf mass per area. Climate was the dominant driver, apart from P and Ca, which were also strongly related to soil P and Ca, respectively. Concentrations of leaf N, P, K, and Mg decreased significantly with mean annual temperature and increased with aridity, albeit at different magnitudes, resulting in positive latitudinal trends of all elements except for Ca and S. The results indicate that Q. variabilis leaf stoichiometry shows a relevant degree of flexibility and that alterations in climatic factors and soil nutrient availability have diverse influences on patterns of the different elements. Our findings provide an important contribution toward an understanding of how widespread species regulate their stoichiometry to adapt to heterogeneous environments.