Multi‐model comparison highlights consistency in predicted effect of warming on a semi‐arid shrub

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi‐model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi‐model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.     

Targeted subfield switchgrass integration could improve the farm economy,water quality,and bioenergy feedstock production

Progress on reducing nutrient loss from annual croplands has been hampered by perceived conflicts between short‐term profitability and long‐term stewardship, but these may be overcome through strategic integration of perennial crops. Perennial biomass crops like switchgrass can mitigate nitrate‐nitrogen (NO₃‐N) leaching, address bioenergy feedstock targets, and – as a lower‐cost management alternative to annual crops (i.e., corn, soybeans) – may also improve farm profitability. We analyzed publicly available environmental, agronomic, and economic data with two integrated models: a subfield agroecosystem management model, Landscape Environmental Assessment Framework (LEAF), and a process‐based biogeochemical model, DeNitrification‐DeComposition (DNDC). We constructed a factorial combination of profitability and NO₃‐N leaching thresholds and simulated targeted switchgrass integration into corn/soybean cropland in the agricultural state of Iowa, USA. For each combination, we modeled (i) area converted to switchgrass, (ii) switchgrass biomass production, and (iii) NO₃‐N leaching reduction. We spatially analyzed two scenarios: converting to switchgrass corn/soybean cropland losing >US$ 100 ha^?1 and leaching >50 kg ha^?1 (‘conservative’ scenario) or losing >US$ 0 ha^?1 and leaching >20 kg ha^?1 (‘nutrient reduction’ scenario). Compared to baseline, the ‘conservative’ scenario resulted in 12% of cropland converted to switchgrass, which produced 11 million Mg of biomass and reduced leached NO₃‐N 18% statewide. The ‘nutrient reduction’ scenario converted 37% of cropland to switchgrass, producing 34 million Mg biomass and reducing leached NO₃‐N 38% statewide. The opportunity to meet joint goals was greatest within watersheds with undulating topography and lower corn/soybean productivity. Our approach bridges the scales at which NO₃‐N loss and profitability are usually considered, and is informed by both mechanistic and empirical understanding. Though approximated, our analysis supports development of farm‐level tools that can identify locations where both farm profitability and water quality improvement can be achieved through the strategic integration of perennial vegetation.     

The Beauty is a beast: Does leachate from the invasive terrestrial plant Impatiens glandulifera affect aquatic food webs?

Invasive alien species are a major threat to ecosystems. Invasive terrestrial plants can produce allelochemicals which suppress native terrestrial biodiversity. However, it is not known if leached allelochemicals from invasive plants growing in riparian zones, such as Impatiens glandulifera, also affect freshwater ecosystems. We used mesocosms and laboratory experiments to test the impact of I. glandulifera on a simplified freshwater food web. Our mesocosm experiments show that leachate from I. glandulifera significantly reduced population growth rate of the water flea Daphnia magna and the green alga Acutodesmus obliquus, both keystone species of lakes and ponds. Laboratory experiments using the main allelochemical released by I. glandulifera, 2‐methoxy‐1,4‐naphthoquinone, revealed negative fitness effects in D. magna and A. obliquus. Our findings show that allelochemicals from I. glandulifera not only reduce biodiversity in terrestrial habitats but also pose a threat to freshwater ecosystems, highlighting the necessity to incorporate cross‐ecosystem effects in the risk assessment of invasive species.     

Statistical method for prediction of gait kinematics with Gaussian process regression

We propose a novel methodology for predicting human gait pattern kinematics based on a statistical and stochastic approach using a method called Gaussian process regression (GPR). We selected 14 body parameters that significantly affect the gait pattern and 14 joint motions that represent gait kinematics. The body parameter and gait kinematics data were recorded from 113 subjects by anthropometric measurements and a motion capture system. We generated a regression model with GPR for gait pattern prediction and built a stochastic function mapping from body parameters to gait kinematics based on the database and GPR, and validated the model with a cross validation method. The function can not only produce trajectories for the joint motions associated with gait kinematics, but can also estimate the associated uncertainties. Our approach results in a novel, low-cost and subject-specific method for predicting gait kinematics with only the subject's body parameters as the necessary input, and also enables a comprehensive understanding of the correlation and uncertainty between body parameters and gait kinematics.     

基于复合叶片特征的计算机植物识别方法

该文探讨如何根据植物的叶片特征,利用图像处理和机器学习的方法对植物进行分类。鉴于现有的叶片分类系统多采用单一的特征,如几何和纹理等,仅能在小规模数据库上得到较好的结果。然而,随着样本种类的增多,单一特征在不同种类叶片之间的相似性非常明显,致使分类正确率降低。该研究使用多种复合特征,并提出了原创的预处理方法以及宽度、叶缘频率特征,较传统的几何特征更为详尽。研究结果显示,复合特征可以有效避免算法过拟合问题,使之适用于更大的数据库。通过提取21类植物的叶片宽度、颜色、叶缘和纹理共292维特征,对1 915张数字图像进行了分类,正确率达到93%,并分析了各类特征对分类结果的影响。研究结果表明,在不影响分类正确率前提下,可将特征减少到约100维。     

Improved E. coli erythromycin A production through the application of metabolic and bioprocess engineering

In this report, small-scale culture and bioreactor experiments were used to compare and improve the heterologous production of the antibiotic erythromycin A across a series of engineered prototype Escherichia coli strains. The original strain, termed BAP1(pBPJW130, pBPJW144, pHZT1, pHZT2, pHZT4, pGro7), was designed to allow full erythromycin A biosynthesis from the exogenous addition of propionate. This strain was then compared against two alternatives hypothesized to increase final product titer. Strain TB3(pBPJW130, pBPJW144, pHZT1, pHZT2, pHZT4, pGro7) is a derivative of BAP1 designed to increase biosynthetic pathway carbon flow as a result of a ygfH deletion; whereas, strain TB3(pBPJW130, pBPJW144, pHZT1, pHZT2, pHZT4-2, pGro7) provided an extra copy of a key deoxysugar glycosyltransferase gene. Production was compared across the three strains with TB3(pBPJW130, pBPJW144, pHZT1, pHZT2, pHZT4, pGro7) showing significant improvement in erythronolide B (EB), 3-mycarosylerythronolide B (MEB), and erythromycin A titers. This strain was further tested in the context of batch bioreactor production experiments with time-course titers leveling at 4 mg/L, representing an approximately sevenfold increase in final erythromycin A titer.     

Environmental restoration effects of Ranunculus sceleratus L. in a eutrophic sewage system

This study investigated the environmental restoration effects of Ranunculus sceleratus in a sewage system microcosm trial, including the removal of pollutants and algal inhibition. We compared the removal of pollutants by R. sceleratus in a eutrophic sewage system in the presence and the absence of algae. The rate of removal without algae was 16.2–20.5% of that with algae. ${\text{NH}}_4^{+}–\text{N}$ was removed most readily by R. sceleratus. The effects of R. sceleratus on the growth of Microcystis aeruginosa were also investigated in two allelopathic modes. The level of algal inhibition after the addition of an extract of Ranunculus scleratus was 57.1–78.9% greater than that in a co-culture test. To understand the role of allelopathy interference with algal development, we also determined the total flavonoid contents of plants, which ranged from 3.57 g to 20.19 g per plant. The cell density of Microcystis aeruginosa was negatively correlated with the total flavonoids in R. sceleratus, although aquatic macrophytes may contain other allelochemicals involved with algal inhibition in addition to flavonoid compounds. The environmental effects of R. sceleratus were significantly correlated with its growth stage (or water retention time), plant height, and biomass. This study suggests that R. sceleratus has potential for the low-effort and sustainable management of freshwaters, particularly the removal of nutrient pollutants and the reduction of excessive algal growth, which may be attributable to allelochemicals such as flavonoids. The in situ environmental restoration effects of R. sceleratus require further investigation at the ecosystem level.     

资源型城市土地利用转型及其对生境质量的影响——以乌海市为例

资源型城市前期发展导致了生境丧失或退化,实现高质量转型需要深入理解城市转型与生态环境质量之间的关系,土地利用转型特征及其对生境质量的影响规律研究为此提供依据与支撑。以资源型城市--乌海市为研究区,通过地学信息图谱和InVEST模型探究2005-2018年乌海市土地利用转型特征、生境质量时空变化及土地利用转型对生境质量的影响。结果表明：（1）2005-2018年乌海市土地利用变化趋势发生改变,土地利用转型明显,土地利用变化图谱单元数量逐渐增加78.14%,分布范围逐渐广泛。主要表现为草地与建设用地、采矿用地之间的相互转化,第一阶段（2005-2015年）草地大面积减少,建设用地和采矿用地大面积增加,第二阶段（2015-2018年）趋势相反。（2）乌海市生境质量变化呈现先强退化后弱提升趋势。2005-2015年乌海市18.75%的区域生境质量退化,提升面积较小;2015-2018年生境质量提升面积略大于退化面积。（3）2005-2015年草地向采矿用地、建设用地转化是区域生境质量降低的主要原因,2015-2018年区域生境质量提升的主导因素是采矿用地和建设用地向草地转化。研究结果揭示了资源型城市土地利用转型过程中生境质量的响应规律,可为资源型城市土地利用转型决策提供参考。     

流域生态系统服务簇变化及影响因素——以大清河流域为例

生态系统服务簇是多种生态系统服务的组合,是生态系统多功能性中的主导功能表征。识别生态系统服务簇的空间和功能变化及影响因素,可为基于主导功能实施分区管理策略、统筹土地多功能性,进而为整体提升区域生态系统服务提供参考。本研究以大清河流域为例,选取6种生态系统服务（水资源供给服务、粮食供给服务、水源涵养服务、水质净化服务、土壤保持服务、固碳服务）,在乡镇尺度上探讨了生态系统服务簇的变化特征,研究了影响其变化的主要因素。结果表明：（1）依据主导的生态系统服务类型,大清流域可以分为3个生态系统服务簇,生态调节服务簇（B1）,农产品供给服务簇（B2）和人居环境簇（B3）;（2）2000-2015年,生态调节服务簇的空间格局变幅最大,乡镇变化率为19.6%,而农产品供给服务簇和人居环境簇的空间稳定性较强,变化率小于5.0%;生态系统服务簇类型发生转化的区域主要位于服务簇交界处;（3）尽管服务簇在空间上有变化,但生态调节服务簇、农产品供给服务簇和人居环境簇的生态系统服务呈增长趋势,平均增幅高达8.62%;（4）自然本底条件和生态保护政策是驱动生态调节服务簇变化的主要因素,农产品供给和建设用地面积的变化分别是驱动农产品供给服务簇和人居环境簇时空变化的主要因素。该案例研究结果为管理土地多功能属性、整体提升国土空间功能提供了有效的途径。     

卧龙自然保护区典型生态系统服务时空变化研究

自然保护区作为生态系统服务的产生区和生物多样性保护的重点区,评估其关键生态系统服务,对提高保护区管理水平和生态保护与建设效率有重要意义。利用CASA模型、RUSLE模型、InVEST模型及水量平衡原理等方法分别定量评估了卧龙自然保护区2000年和2015年碳固定（NPP）、土壤保持、生境质量和水源涵养4种生态系统服务并分析了其时空分布及其变化特征,揭示了不同地形位梯度和土地利用类型上生态系统服务的差异,识别了生态系统服务的热点区域。研究结果揭示了2000-2015年4种生态系统服务及其变化的时空异质性：1）研究期间保护区4种生态系统服务供给量均有所增加,且增益面积大于减损面积;2）空间上,NPP、土壤保持和生境质量3种服务表现为东南高、西北低,水源涵养空间分布无明显规律,4种服务的空间分布特征均变化不大且保持相对稳定;3）4种生态系统服务空间分布及变化与地形位和土地利用类型有关。4种服务的高值和增益的优势分布区均位于较低地形位指数梯度上,以保护区东南部最为突出;林地和草地是对保护区生态系统服务贡献较大的土地利用类型,尤以林地突出;4）热点分析表明保护区东南部是主要的生态系统服务供给热点区,研究期间Ⅳ类热点区面积显著增加。结合研究区域生态系统特征和生态恢复与管理政策,探讨分析了目标生态系统服务时空变化的自然生态和社会经济驱动力,为本区域生态系统恢复和生物多样性保护提供依据和建议。