Economic land use, ecosystem services and microfounded species dynamics

In an integrated economy–ecosystem model humans choose their land use and leave the residual land as habitat for three species forming a food chain. The size of habitat determines the diversity and abundance of species. That biodiversity generates, in turn, a flow of ecosystem services with public-good characteristics for human consumption. The ecosystem submodel yields (rather than assumes!) population growth functions with each species’ growth depending on the size of habitat. First the relationship between habitat and species growth (sustenance, decline and extinction) is explored. The laissez-faire economy is shown to result in an underprovision of habitat making the case for land use restrictions for nature protection. The optimal land use policy is characterized with full regard of ecosystem dynamics. Finally, labor-augmenting technical change is introduced to generate ever increasing pressure towards further habitat reductions. In the laissez-faire economy the habitat is consequently squeezed to zero in the long-run so that all species are doomed. Social optimality demands, however, to refrain from using all land for economic purposes despite ever growing labor productivity.     

Response of ecological storage and conservation to land use transformation: A case study of a mining town in China

Rapid land use transformation shaped by agriculture, industrialization and population urbanization has a great influence on ecological environment. Based on theory of ecosystem service functions, this study aims at revealing the response of ecological storage and conservation to each unit area of land use transformation. Taking Cishan Town, a mining town in China, as a case study, this paper estimates the “past-present-future” ecological storage impacted by the process, result and possibility of land use transformation. The local land use and industrial distribution show that the active areas of land use transformation are also the areas of concentration of human (industrial) activities. Ecological storage shows the different responses to land use ways. And then this study combines the ecological storage indices with the indices of ecosystem pattern and land condition into the“5A” framework (active state, active degree, active possibility, active balance and active condition) for grading ecological conservation, and then assigns all regions of Cishan Town into different grades through membership functions for complex mapping of ecological conservation. The research results show that the ecological conservation in Cishan goes toward two extreme grades (best grade and worst grade). Uneven and unbalanced land use transformation is the main cause of that. Hence, rational and timely reflection of impact of land use transformation on ecological storage and conservation can assist land use planners and local government in adjusting land use ways and balancing regional ecology and economy.     

黄土小流域水沙输移过程对土地利用/覆被变化的响应

以甘肃定西安家沟小流域为典型研究区,基于TM、ALOS遥感影像解译和地面长期水文数据,深入分析了1997至2010年间流域土地利用变化特征及其产流产沙效应。结果显示,（1）14年间,流域林灌草面积分别增加160.23%、176.33%和80.75%;坡耕地、居民地、裸地和梯田面积分别减少25.57%、0.16%、48.45%和21.52%。以2005年为时间节点,发现前期灌草增加较多、裸地减少明显,后期则是乔木增加比例和坡耕地减少比例更为显著,彰显出不同历史阶段植被恢复的策略变化。（2）流域出口多年平均径流量和输沙量分别由前期的18 249 m3和6 383 kg锐减至后期的2 292 m3和2 267 kg,流域土地利用/覆被有效增加是其主要驱动。（3）春冬季节,由于降雨稀少、径流泥沙的本底值很低,前后两个阶段的水沙输移量差异较小,土地利用/覆被变化的影响相对尚不显著。但在夏秋季节,随着降雨事件增多,土地利用/覆被变化减水减沙的效应趋于显性化。     

Land‐use history as a guide for forest conservation and management

Conservation efforts to protect forested landscapes are challenged by climate projections that suggest substantial restructuring of vegetation and disturbance regimes in the future. In this regard, paleoecological records that describe ecosystem responses to past variations in climate, fire, and human activity offer critical information for assessing present landscape conditions and future landscape vulnerability. We illustrate this point drawing on 8 sites in the northwestern United States, New Zealand, Patagonia, and central and southern Europe that have undergone different levels of climate and land‐use change. These sites fall along a gradient of landscape conditions that range from nearly pristine (i.e., vegetation and disturbance shaped primarily by past climate and biophysical constraints) to highly altered (i.e., landscapes that have been intensely modified by past human activity). Position on this gradient has implications for understanding the role of natural and anthropogenic disturbance in shaping ecosystem dynamics and assessments of present biodiversity, including recognizing missing or overrepresented species. Dramatic vegetation reorganization occurred at all study sites as a result of postglacial climate variations. In nearly pristine landscapes, such as those in Yellowstone National Park, climate has remained the primary driver of ecosystem change up to the present day. In Europe, natural vegetation–climate–fire linkages were broken 6000–8000 years ago with the onset of Neolithic farming, and in New Zealand, natural linkages were first lost about 700 years ago with arrival of the Maori people. In the U.S. Northwest and Patagonia, the greatest landscape alteration occurred in the last 150 years with Euro‐American settlement. Paleoecology is sometimes the best and only tool for evaluating the degree of landscape alteration and the extent to which landscapes retain natural components. Information on landscape‐level history thus helps assess current ecological change, clarify management objectives, and define conservation strategies that seek to protect both natural and cultural elements.     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.