Length‐based assessment of larval lamprey population structure at differing spatial scales

1. Perspectives on lamprey management contrast between pest control in the US Great Lakes and species conservation in the Pacific Northwest, New Zealand, and Europe. Five lamprey species are listed in the European Union (EU) Habitats Directive (HD) as requiring conservation measures. Assessments of HD ‘conservation status’ for these lampreys mainly target the larval (ammocoete) stage.
2. Larval lamprey populations can be assessed by evaluating presence or absence, density and demographic structure in riverine samples. Demographic structure has typically been described from length–frequency data using qualitative approaches and the statistical assignment of age classes. Length‐based indicators (LBIs) may provide a more rapid and flexible framework.
3. The demographic structure of a fish population can be described by univariate length metrics: length range (L_RANGE) and 90^th percentile of length (L₉₀). This study used a pooled data set from seven Irish catchments to estimate a reference point (RP) value for each metric corresponding to a healthy larval lamprey population. Two LBIs were then derived that can be estimated for an observed (OBS) population as LBI_RANGE = L_{RANGE_OBS}/L_{RANGE_RP} and LBI₉₀ = L_{90_OBS}/L_{90_RP}.
4. Simulated lamprey population length structures, representing a range of status values, were used to develop a reference gradient (RG) to support population assessment using LBIs. The assessment framework was applied to each of the seven Irish catchments, and also to subcatchment and sampling‐site scales within the Barrow system. The LBIs and RG suggested that most catchments had favourable conservation status overall, whereas smaller assessment scales revealed a spread of status values.
5. The proposed framework allows the rapid assessment of demographic structure and comparison across systems. There is potential to track states across sampling sites, events, and legislative reporting cycles, and to interpret change in relation to the local environment. The general approach may be adaptable for other fish species monitored during juvenile stages.

     

参考作物蒸散量对气象要素的敏感性分析

为了研究参考作物蒸散量(ET_0)对气象要素的敏感性,利用新乡地区1951―2003年逐日气象资料,由Penman-Manteith公式计算参考作物蒸散量,采用敏感曲线和敏感系数方法分析了参考作物蒸散量对气象要素的敏感性。结果表明,温度、风速和日照时间3种气象要素与ET_0正相关,相对湿度与ET_0负相关。1―12月,相对湿度和风速的敏感系数表现为"先减小后增大"趋势,而日照时间和温度敏感系数表现为"先增大后减小"趋势。在全年中,ET_0对气象要素的敏感程度表现为相对湿度风速日照时间温度;第一、四季度各气象要素在季尺度中的敏感性均为相对湿度风速日照时间温度,第二季度表现为相对湿度日照时间风速温度,第三季度表现为相对湿度日照时间温度风速;冬小麦生育期典型时段内各气象要素敏感性在1、3、10月份均表现为相对湿度风速日照时间温度,5月则表现为相对湿度日照时间风速温度。     

岭南四园造园特色及其对兰州园林化建设的借鉴意义

岭南私家园林是中国私家园林的独特流派,有其显著的风格特点.选取岭南私家园林的代表佛山梁园、东莞可园、番禺余荫山房、顺德清晖园,对其造园历史、园主思想、园景特点和造园特色进行梳理探讨,总结精髓,以启发更深研究和借鉴运用.     

荒漠草原不同时间尺度下垫面水分消耗与气象植被因子的关系

利用大型称重式蒸渗仪2012—2018年连续观测数据，系统解析了希拉穆仁荒漠草原植物生长季（4—10月）不同时间尺度蒸散发（ET)与气象植被因子之间的关系。研究表明：（1）小时、日和月尺度上，始终与ET保持高度相关的气象植被因子包括风速（P<0.01）、空气温度（P<0.01）和降水量（P<0.01）；（2）结合不同时间尺度主控因子，利用多元回归定量表征了小时、日、月尺度的下垫面ET变化特征，经验方程决定系数分别为0.94（P<0.01）、0.42（P<0.01）、0.82（P<0.01），小时和月尺度上的经验方程可较好地反映希拉穆仁荒漠草原下垫面耗水特征；（3）ET与降水差值显示，2012—2018年希拉穆仁荒漠草原植物生长季（4—10月）水汽交换以下垫面水分消耗为主，8月份发生干旱事件的概率最大。     

Investigation of crop evapotranspiration and irrigation water requirement in the lower Amu Darya River Basin,Central Asia

High water consumption and inefficient irrigation management in the agriculture sector of the middle and lower reaches of the Amu Darya River Basin(ADRB)have significantly influenced the gradual shrinking of the Aral Sea and its ecosystem.In this study,we investigated the crop water consumption in the growing seasons and the irrigation water requirement for different crop types in the lower ADRB during 2004–2017.We applied the FAO Penman–Monteith method to estimate reference evapotranspiration(ET0)based on daily climatic data collected from four meteorological stations.Crop evapotranspiration(ETc)of specific crop types was calculated by the crop coefficient.Then,we analyzed the net irrigation requirement(NIR)based on the effective precipitation with crop water requirements.The results indicated that the lowest monthly ET0 values in the lower ADRB were found in December(18.2 mm)and January(16.0 mm),and the highest monthly ET0 values were found in June and July,with similar values of 211.6 mm.The annual ETc reached to 887.2,1002.1,and 492.0 mm for cotton,rice,and wheat,respectively.The average regional NIR ranged from 514.9 to 715.0 mm in the 10 Irrigation System Management Organizations(UISs)in the study area,while the total required irrigation volume for the whole region ranged from 4.2×109 to 11.6×109 m3 during 2004–2017.The percentages of NIR in SIW(surface irrigation water)ranged from 46.4%to 65.2%during the study period,with the exceptions of the drought years of 2008 and 2011,in which there was a significantly less runoff in the Amu Darya River.This study provides an overview for local water authorities to achieve optimal regional water allocation in the study area.     

旱作覆膜玉米生长和水分利用对气候变化的响应

基于3 a连续冬小麦-夏玉米覆膜轮作试验校准和验证AquaCrop模型的适用性,模拟研究了气候变化对夏玉米生长、产量和水分利用的影响,分析了覆膜措施对气候变化的应对效果。结果表明:关中地区(以武功、宝鸡和西安地区为例)年平均温度呈逐年递增趋势,温度增加幅度由高到低依次为宝鸡、西安和武功,增温速率分别为0.20、0.12℃·10a~(-1)和0.09℃·10a~(-1);降雨量呈逐年递减趋势,减少幅度大小依次为西安、宝鸡和武功,减小量分别为3.59、3.23 mm·10a~(-1)和2.64 mm·10a~(-1)。AquaCrop模型在关中地区表现出了良好的适用性,可以较好地模拟连续覆膜条件下作物的产量指标、水分利用和生长的动态变化,冠层覆盖度模拟值和实测值之间的均方根误差(RMSE)介于1.1%～15.3%,生物量模拟值和实测值之间的RMSE介于0.626～2.540 t·hm~(-2),土壤贮水量模拟值和实测值之间的RMSE介于12.6～47.4 mm。模拟研究表明,上世纪60年代以来,随着气温不断升高,武功、宝鸡和西安地区的夏玉米生育期均呈逐年缩短趋势,特别是1980s以来,减少幅度达2.76、4.82 d·10a~(-1)和5.94 d·10a~(-1);在不同的降水年型下,覆膜处理产量均高于裸地处理,且其变异系数较小;在干旱气候条件下,覆膜处理依然可以获得一定的籽粒产量,与裸地处理相比,覆膜处理表现出了较好的稳产效应。同时,覆膜处理有效减少了玉米苗期土壤表层蒸发(平均减少7.6 mm),从而在土壤中保蓄更多的降雨;覆膜处理虽然增加了土壤耗水量,但其通过保蓄土壤水分,稳定作物产量,有效提高了玉米的水分利用效率。因此,关中地区旱作覆膜可以有效适应当地气候变化,在一定程度上应对干旱气候,具有较好的增产稳产效应。     

GFDL-ESM2M气候模式下京津冀地区未来潜在蒸散量时空变化

为探究未来潜在蒸散量时空变化特征,该研究以京津冀地区为例,基于美国GFDL提供的GFDL-ESM2M全球气候模式,得到京津冀地区92个格点2000-2050年的平均气温、最高气温、最低气温、太阳总辐射、平均相对湿度和近地面平均风速,应用Penman-Monteith公式计算京津冀地区未来92个格点的逐日潜在蒸散量(ET0),分析其时空分布特征及其与气象要素的相关关系。结果表明:未来年ET0总体呈增加趋势,RCP8.5情景下ET0上升速度最快,且随着时间推移增幅越来越大。夏季ET0增长速度最快,其次为春季、秋季与冬季,意味着未来ET0季节差异将愈加明显,可能出现更为严重的季节性干旱。ET0空间分布呈由西南向东北逐渐递减趋势,其中中部地区增速最快,增长趋势由中部向南北递减。不同气候情景下平均气温均呈逐年上升趋势,风速、太阳总辐射略微上升,而相对湿度下降。ET0与太阳总辐射的相关系数最大,呈由东北向西南递增趋势,其次为最高气温,呈由西北向东南递增趋势。ET0与相对湿度变化呈显著负相关,相关系数绝对值呈东北向西南递增趋势,ET0与风速相关度不明显。该研究可为农业需水预测与灌溉管理、科学应对气候变化提供基础支撑。     

基于气象-生理的夏玉米作物系数及蒸散估算

准确估算作物系数对预测作物实际蒸散量和制定精准的灌溉计划至关重要。为反映作物逐日作物系数变化,综合考虑气象和生物因子对作物生长的共同影响,采用五道沟水文实验站大型蒸渗仪夏玉米实测蒸散及气象数据,基于地温及叶面积指数建立了气象-生理双函数乘法模型,并结合梯度下降法对模型进行了精度优化。结果表明,在整个玉米生长期中,作物系数实测值和计算值平均绝对误差为0.12,均方根误差为0.15,相关性为0.91,蒸散量实测值与计算值平均绝对误差为1.0 mm/d,均方根误差为4.5 mm/d,相关性为0.75。该模型计算的全生育期蒸散量准确率(误差在2～3 mm/d以内)相比使用联合国粮农组织(FAO)推荐的作物系数计算所得准确率提高了3倍以上,可更精确用于作物系数及蒸散量计算。     

中国大陆地区基于太阳辐射经验值计算ET0的适用性研究

太阳辐射是利用FAO推荐的Penman-Monteith(PM)公式计算参考作物需水量(ET_0)的必要参数。为了探究PM公式在辐射数据缺失的条件下,利用FAO推荐的公式及参数获得太阳辐射值(R_(s_c))替代观测值(R_(s_o))在中国大陆地区的适用性,本研究选用了中国大陆112个站点至少15 a的多年月平均观测数据,通过逐点计算分析了R_(s_c)和R_(s_o)的时空差异及二者分别输入PM公式获得的参考作物需水量ET_(0_c)和ET_(0_o)的时空差异。结果表明,R_(s_c)与R_(s_o)存在显著的时空差异性,二者相对差值范围为-2.86～4.41 MJ·m~(-2)·d~(-1),且在4—8月份差异较大;大致以"胡焕庸线"为界,线西北区域R_(s_c)与R_(s_o)的时空差异相对较小,且稳定,线东南区域的时空差异较大,且不稳定。但是,基于二者计算的ET_(0_c)和ET_(0_o)时空差异却不显著,平均只有0.06～0.26 mm·d~(-1)的误差;"胡焕庸线"西北地区的ET_(0_c)和ET_(0_o)绝对差值常年稳定在0.00～0.25 mm·d~(-1),"胡焕庸线"线东南地区则随季节而变化,夏季差异相对较大。在实际的应用中,西北地区全年和北方地区春、秋、冬三季以及长江、珠江流域所覆盖的南方地区在1、2、10、11、12月使用R_(s_c)替代R_(s_o)获得ET_0具有较好的适用性,北方地区的夏季、南方地区的3—9月份使用R_(s_c)计算ET_0则必须研究相应的方法对结果进行矫正,否则会有误差,且偏大。     

Uncertainty assessment of soya bean yield gaps using DSSAT‐CSM‐CROPGRO‐Soybean calibrated by cultivar maturity groups

Soya bean yield gap can be caused by different factors resulting in uncertainties when the objective is to use such information for farm decision‐making and reference yield determination. Thus, this study aimed to quantify the soya bean yield gap for four sites, located in Southern and Midwestern Brazil, as well as the uncertainties of that related to cultivars, sowing dates, soil types and reference yields. The crop simulation model DSSAT‐CSM‐CROPGRO‐Soybean was calibrated for cultivars with similar maturity groups, based on the data obtained from the best farmers at the county level. The yield gap by water deficit (YG_WD) was obtained through the difference between potential and attainable yields, and that one caused by sub‐optimum crop management (YG_CM) by subtracting actual yield of each county, obtained from official statistics between 1989/90 and 2014/15 growing seasons, from the estimated attainable yield. The yield was simulated using four sowing dates, three soil types and two soya bean maturity groups by county. The reference yield uncertainty was quantified using yield reference from crop model and regional winners of the soya bean yield context, conducted by CESB (Brazilian Soybean Strategic Committee), for the growing seasons from 2013/14 to 2015/16. The crop model showed a good agreement between measured and simulated crop development and growth using calibration by maturity group, with low root mean square error (347 kg/ha). Southern sites had a mean YG_WD of 1,047 kg/ha, while in the Midwest, it was lower than 100 kg/ha. The YG_CM was 1,067, 528, 984 and 848 kg/ha, respectively, for Castro, PR, Mamborê, PR, Montividiu, GO and Primavera do Leste, MT, representing the opportunity for yield gain when having the best farmers as reference. The maturity groups, sowing dates and soil types showed to be an important source of uncertainty for yield gap determination, being recommended to investigate the farms in detail for an appropriate quantification. The reference yield showed expressive uncertainties, with some farmers presenting conditions to increase their soya bean yields by more than 3,000 kg/ha, when considering as reference the yields obtained by the winners’ farmers. These results show that uncertainties must be reduced when assessing farm yield gaps, in order to ensure that expected rate of soya bean yield growth could be reached by adopting the same technologies from CESB winners and best farmers in the county as a reference.