Projecting future habitat quality of three midwestern reservoir fishes under warming conditions

Rising temperatures caused by climate change are likely to affect cool‐water and warm‐water fishes differently. Yet, forecasts of anticipated temperature effects on fishes of different thermal guilds are lacking, especially in freshwater ecosystems. Towards this end, we used spatially explicit, growth rate potential (GRP) models to project changes in seasonal habitat quality for a warm‐water piscivore (largemouth bass Micropterus salmoides), a cool‐water piscivore (walleye Sander vitreus) and a hybrid piscivore (saugeye S. vitreus × S. canadensis) in two Midwestern reservoirs. We assessed habitat quality for two periods (early and middle 21st century) under two realistic greenhouse gas emission scenarios (a mid‐century emissions peak and a rapid continuous increase in emissions). Largemouth bass were projected to experience enhanced or slightly reduced habitat during all seasons, and throughout the mid‐21st century. By contrast, walleye habitat was projected to decline with anticipated warming, except during the spring in the smaller of our two study reservoirs and during the fall in the larger of our two study reservoirs. Saugeye habitat was projected to either increase modestly or decline slightly during the spring and fall and declines in habitat quality and quantity that were smaller than those for walleye were identified during summer. Collectively, our findings indicate that climate warming will differentially alter habitat suitability for reservoir piscivores, favouring warm‐water species over cool‐water species. We expect these changes in habitat quality to impact the dynamics of reservoir fish populations to varying degrees necessitating the consideration of climate when making future management decisions.     

Impact of climate change on maize yield in China from 1979 to 2016

Climate change severely impacts agricultural production, which jeopardizes food security. China is the second largest maize producer in the world and also the largest consumer of maize. Analyzing the impact of climate change on maize yields can provide effective guidance to national and international economics and politics. Panel models are unable to determine the group-wise heteroscedasticity, cross-sectional correlation and autocorrelation of datasets, therefore we adopted the feasible generalized least square(FGLS) model to evaluate the impact of climate change on maize yields in China from 1979–2016 and got the following results:(1) During the 1979–2016 period, increases in temperature negatively impacted the maize yield of China. For every 1°C increase in temperature, the maize yield was reduced by 5.19 kg 667 m–2(1.7%). Precipitation increased only marginally during this time, and therefore its impact on the maize yield was negligible. For every 1 mm increase in precipitation, the maize yield increased by an insignificant amount of 0.043 kg 667 m–2(0.014%).(2) The impacts of climate change on maize yield differ spatially, with more significant impacts experienced in southern China. In this region, a 1°C increase in temperature resulted in a 7.49 kg 667 m–2 decrease in the maize yield, while the impact of temperature on the maize yield in northern China was insignificant. For every 1 mm increase in precipitation, the maize yield increased by 0.013 kg 667 m–2 in southern China and 0.066 kg 667 m–2 in northern China.(3) The resilience of the maize crop to climate change is strong. The marginal effect of temperature in both southern and northern China during the 1990–2016 period was smaller than that for the 1979–2016 period.     

气候变化对藏药独一味适生区分布格局的影响

本研究通过实地调查，运用最大熵（MaxEnt）模型和环境气候数据模拟未来气候变化对青藏高原地区藏药独一味（Lamiophlomis rotata（Benth.）Kudo）适生区空间分布格局的影响，探索其适生区变迁规律。通过ArcGIS和SPSS对模拟结果分析显示，当前气候条件下独一味最适宜生长地区主要分布于青藏高原地区的四川与西藏，甘肃与青海交界处，占青藏高原总面积的24.87%，其中西藏自治区适生区面积最大，其次是四川和青海，甘肃和云南占比最小；未来气候变化使适生区几何中心向西南方向迁移97.1 km，且海拔上升267 m；气候变化带来的适生区扩大面积约为退化面积的2倍，各省适生区面积均呈现增加，西藏增加最多，其次是四川，青海略有增加，云南和甘肃变化不大；如果气候变暖持续发生，人工引种驯化应选择海拔相对较高区域，而低海拔地区由于退化风险，应作为物种保护区域重点监测。本研究将为气候敏感地区野生濒危药用植物的引种驯化及资源保护提供参考依据。     

气候变化情景下流苏香竹潜在分布区预测

流苏香竹（Chimonocalamus fimbriatus）是云南特有珍稀竹种，主要分布于云南西南部。文章以野外调查获取的流苏香竹分布信息为主，运用最大熵模型（MaxEnt）同时结合地理信息系统（ArcGIS），基于19个气候因子，预测其在当前及未来气候变化情景下的潜在分布区。结果表明：当前流苏香竹的高适生区和中适生区主要分布于德宏州、保山市和临沧市等地，除迪庆州、丽江市和昭通市外，云南其他区域均有低适生区零星分布。在未来2050s和2070s的2个时间段，基于2种不同共享社会经济路径（SSP1-2.6和SSP5-8.5），流苏香竹的高适生区面积呈减少的趋势，尤其是SSP5-8.5路径下，高适生区面积仅为当前的12.51%（2050s）和18.63%（2070s）；中、低适生区在SSP1-2.6路径下，显著扩张（2050s）或略微扩张（2070s），在SSP5-8.5路径下，则大幅收缩。流苏香竹野外实际分布区及其潜在分布区均以斑块状为主，可能与云南特殊的地形、地貌有关。影响流苏香竹分布的主导气候因子为最湿月份降水量、最暖月份最高温度、最干季度降水量和平均气温日较差。流苏香竹对气候变化比较敏感，根据其野外分布状况，建议以就地保护为主、迁地保护为辅，在其潜在适生区内适当引种栽培。     

Cotton Image Segmentation Algorithm Based on Fusion Method of Markov Random Field and Quantum Particle Swarm Cluster

[Objective] The aim of this study was to improve the cotton image segmentation accuracy in a picking robot image processing system. [Method] An image segmentation algorithm based on a fusion method of Markov random field and quantum particle swarm optimization clustering was proposed. The process of the proposed algorithm is as follows: first, transform the RGB (red, green, blue) images into grayscale; second, use it to segment these images; finally, the threshold of the connected area is set on the basis of the segmented image to obtain the target area. Then, the cotton front image and the cotton side image are selected from the images collected from different angles. The segmentation experiment was carried out by using this algorithm, and compared with the Otsu algorithm, the fuzzy C-means algorithm, the quantum particle swarm image segmentation algorithm and the Markov random field image segmentation algorithm. [Result] The results showed that the segmentation accuracy and peak signal to noise ratio of the proposed algorithm were 98.94% and 77.48 dB. When compared with the Otsu algorithm, fuzzy C-means algorithm, quantum particle swarm optimization algorithm and Markov random field algorithm, the average segmentation accuracy and peak signal to noise ratio of the proposed algorithm increased by 2.47%–4.56%, and 9.81–13.11 dB, respectively. [Conclusion] The proposed algorithm had higher segmentation accuracy and higher peak signal to noise ratio than the other algorithms tested.     

黔东南州打造全域森林公园的可行性研究

指出了建设全域森林公园是经济和社会发展的必然要求。在对黔东南州发展全域森林公园进行必要性和打造条件后认为:黔东南州在打造全域森林公园方面具有明显的政策优势,有着优良的森林生态环境资源,以及良好的林业产业基础等优势条件。通过不断完善相关的配套服务体系,已具备了打造全域森林公园的可行性。     

基于GODAS资料的南海上层海洋热状态气候变化特征分析

为了深入了解南海上层海洋热力状态的变化规律,利用1980—2015年共36年GODAS月平均海温资料,将5~366 m的垂直平均海温表征南海地区海洋上层的热含量,分析了南海海洋上层热状态的水平和垂直分布特征以及季节和年际变化特征。结果表明：年平均南海热含量水平分布表现为东高西低的形势,垂直纬向平均分布表现为暖水厚度和温跃层深度东厚（深）西薄（浅）,垂直经向平均表现为暖水厚度南厚北薄,温跃层深度中间浅两边深;南海地区海温变化幅度在75~200 m处最大,不同深度海温距平均具有明显的年际和年代际变化特征;南海区域平均热含量在秋季最高,春夏次之,冬季最低,其年际变化明显,且在1998年之后出现明显的突变,由负值转变为正值,表现出明显的增温趋势;热含量季节EOF主模态空间分布形势表现为东高西低的特征,对应的时间序列在20世纪90年代末存在年代际转折,由主要为负值转化为主要为正值,表现在空间分布上,则为南海地区热含量由西高东低型转化为东高西低型。     

二氧化碳浓度升高对茶树生理代谢的影响及应对技术

大气中的二氧化碳(CO2)浓度升高是工业革命以来全球范围内最重要的生态变化之一,将直接影响植物的生长发育和代谢过程。尽管CO2浓度升高对粮食作物的影响已经得到了广泛的研究,但其对茶树等重要经济作物的影响却很少受到关注。本文回顾和总结了CO2浓度升高对茶树的初级代谢(包括光合作用、呼吸作用和碳氮代谢)和次级代谢的影响,并探讨了CO2浓度升高环境下茶叶生产过程中的应对技术,旨在为CO2浓度升高背景下茶树优质高产栽培提供一定的理论基础和科学依据。