A test of male mating and hunting success in the kestrel: the advantages of smallness?

We tested female choice for male wing and tarsus length and body mass in the kestrel (Falco tinnunculus), a species in which males average about 10% smaller than females. We also studied how male characters are related to their hunting success. In the laboratory, females preferred lighter males with shorter tarsi as mates, if the difference in those characters between competing males was larger than average. Lighter and shorter-winged males seemed to be better hunters than heavier and longer-winged males. Field observations in a year in which voles were scarce suggested that shorter-winged males were also better food providers in courtship feeding than longer-winged males,although in good vole years such a relationship was not found. We argue that females may prefer to pair with smaller males, because they have higher flight performance and better hunting success than heavier males. By doing so, females may gain direct breeding advantages. We conclude that both female choosiness and the hunting efficiency of males well contribute to reversed sexual size dimorphism (RSD, females larger than males) in the kestrel. Received: 18 July 1995/Accepted after revision: 17 August 1996     

Bayesian estimation of age-specific bird nest survival rates with categorical covariates

The populations of many North American landbirds are showing signs of declining. Gathering information on breeding productivity allows critical assessment of population performance and helps identify good habitat-management practices. He (Biometrics (2003) 59 962–973) proposed a Bayesian model to estimate the age-specific nest survival rates. The model allows irregular visiting schedule under the assumption that the observed nests have homogeneous nest survival. Because nest survival studies are often conducted in different sites and time periods, it is not realistic to assume homogeneous nest survival. In this paper, we extend He’s model by incorporating these factors as categorical covariates. The simulation results show that the Bayesian hierarchical model can produce satisfactory estimates on nest survival and capture different factor effects. Finally the model is applied to a Missouri red-winged blackbird data set.     

Socioecological influences on the reproductive success of female mountain gorillas (<Emphasis Type="Italic">Gorilla beringei beringei</Emphasis>)

Over the past few decades, socioecological models have been developed to explain the relationships between the ecological conditions, social systems, and reproductive success of primates. Feeding competition, predation pressures, and risk of infanticide are predicted to influence how female reproductive success (FRS) depends upon their dominance rank, group size, and mate choices. This paper examines how those factors affected the reproductive success of female mountain gorillas (Gorilla beringei beringei) of the Virunga Volcanoes, Rwanda from 1967–2004. Reproductive success was measured through analyses of interbirth intervals, infant survival, and surviving infant birth rates using data from 214 infants born to 67 females. Mountain gorillas were predicted to have “within-group scramble” feeding competition, but we found no evidence of lower FRS in larger groups, even as those groups became two to five times larger than the population average. The gorillas are considered to have negligible “within-group contest” competition, yet higher ranked mothers had shorter interbirth intervals. Infant survival was higher in multimale groups, which was expected because infanticide occurs when the male dies in a one-male group. The combination of those results led to higher surviving birth rates for higher ranking females in multimale groups. Overall, however, the socioecological factors accounted for a relatively small portion of the variance in FRS, as expected for a species that feeds on abundant, evenly distributed foliage.     

基于MODIS数据的河南省冬小麦产量遥感估算模型

小麦是世界上最重要的粮食作物,小麦生产对中国的粮食保障起着十分重要的作用,及时、准确、大范围对小麦产量进行监测预报,对于农学经济发展和粮食政策制定具有极为重要的现实意义。对作物产量进行遥感监测的原理是建立在其遥感特征基础之上的,通过建立作物长势指标与遥感信息的定量关系,可实现对作物产量的监测预报。文章基于2009年MODIS遥感数据和气象数据,利用Arcgis和ENVI提取纯小麦像元,并提取纯小麦像元对应的NDVI、NPP和LAI,获取分县NDVI、NPP和LAI均值,利用统计软件对产量数据和分县遥感参数均值进行数据整理和分析,建立了河南省冬小麦产量估算模型。以往研究多采用遥感图像上某像元和地面调查点进行研究,具有很大的不确定性,文章以县为单位,对冬小麦平均单产和县域内冬小麦种植像元遥感参数的均值进行相关研究,提高了模型模拟精度。同时文章选用多种遥感参数和多项气象因子建立估产模型,避免了针对一个参数进行估产的局限性。在最佳时相的选择上,根据冯美辰（2010）以往的研究结果,从4月以后,5月8日和4月20Et植被指数和产量相关性最大,4月份之前冬小麦处于返青到拔节期,对产量来说还有很多不确定闪素,因此文章选用5月8El和4月20日进行冬小麦估产研究。结果表明,5月8日的估产模型优于4月20日,加入气象冈子的遥感气象估产模型优于只采用遥感参数进行估产的遥感模型。利用2010年产量数据对模型精度进行检验,遥感气象模型预测精度在70．2％N99．7％之间,平均精度为90．7％;遥感模型预测精度在68．1％到95．5％之间,平均精度为83．9％。表明遥感气象模型模拟精度更高,其精度可以满足大面积估产要求,可以对产量预报提供科学参考。