Endangered Cape Sable Seaside Sparrow Survival

ABSTRACT We investigated survival for male, female, and first-year Cape Sable seaside sparrows (Ammodramus maritimus mirabilis, hereafter sparrows), a federally endangered bird restricted to the Florida Everglades, USA. Accurate estimates of survival are critical to improve management decisions and population estimates for this and other threatened species. We used Program MARK to evaluate effects of age, sex, population membership, temporal variation, and ground-water levels on annual survival from mark-recapture data collected across 3 sparrow populations from 1997 to 2007. We found little evidence that annual survival rates differed between the populations or across ground-water levels, but we found high variability between years for both adult and juvenile survival. Our results revealed female sparrows experienced 14–19% lower survival than males. Sparrows experienced much lower survival during their first year of life and were short-lived (2–3 yr). Our results highlight sparrows' susceptibility to population declines and suggest that management actions aimed at increasing survival may be effective for this species' management.     

Influence of water depth on nest success of the endangered Cape Sable seaside sparrow in the Florida Everglades

The restoration of the Florida Everglades rests largely on the ability of managers to re-create a more natural hydrologic regime throughout the remaining natural areas. The Cape Sable seaside sparrow, an endangered subspecies endemic to the freshwater marl prairies of the Everglades, has suffered from changes in the depth and the timing of water flows through its habitat. However, it remains unclear what temporal and spatial aspects of water inputs (both managed and natural) affect nesting success. We monitored 429 nests in two of the six extant sparrow subpopulations over 10 breeding seasons and a variety of water levels. Using an information-theoretic approach, we find that nests initiated early in the breeding season experience substantially higher success rates than those initiated later. We suggest that this seasonal effect is due to a change in predator abundance or activity levels as the season progresses, which are tied to the increase in water levels that accompany the onset of the wet season. In addition, nest success is influenced to a lesser degree by where sparrows choose to nest across the landscape, the height of base water levels within the sparrow's breeding season and the height of water levels when nests are active. Our observation of extreme variability in nest success over the span of a single season suggests that successful late-season breeding, although shown to be important for population recovery, is a rare event. Management actions that maximize the success of late-season broods or increase the number of early broods are warranted, but the ecosystem implications of such actions are poorly understood.     

Bayesian interval mapping of count trait loci based on zero-inflated generalized Poisson regression model

Count phenotypes with excessive zeros are often observed in the biological world. Researchers have studied many statistical methods for mapping the quantitative trait loci (QTLs) of zero-inflated count phenotypes. However, most of the existing methods consist of finding the approximate positions of the QTLs on the chromosome by genome-wide scanning. Additionally, most of the existing methods use the EM algorithm for parameter estimation. In this paper, we propose a Bayesian interval mapping scheme of QTLs for zero-inflated count data. The method takes advantage of a zero-inflated generalized Poisson (ZIGP) regression model to study the influence of QTLs on the zero-inflated count phenotype. The MCMC algorithm is used to estimate the effects and position parameters of QTLs. We use the Haldane map function to realize the conversion between recombination rate and map distance. Monte Carlo simulations are conducted to test the applicability and advantage of the proposed method. The effects of QTLs on the formation of mouse cholesterol gallstones were demonstrated by analyzing an mouse data set.     

应用混合模型和分位数回归分析东黄海小黄鱼肥满度空间异质性

基于2008-2010年黄海南部近海(SYS)、东海北部外海(NECS)和东海中部近海(MECS)小黄鱼体长和体质量数据,采用均值回归和分位数回归模型,解析了小黄鱼幼鱼和成鱼群体体长-体质量关系的空间变异.结果表明: 协方差模型和线性混合模型的残差标准误基本一致,线性模型残差标准误最高.从线性混合模型对特定区域和总体区域平均体质量计算的相对比值来看,SYS和NECS幼鱼群体的平均体质量高于总体平均值,但MECS低于总体平均值;成鱼群体则为NECS平均体质量高于总体平均值,MECS和SYS低于总体平均值.分位回归估计的肥满度和异速生长指数结果显示,幼鱼群体在不同分位的估计参数呈显著变化,SYS异速生长指数均值为2.85,在0.1~0.95分位的估计值变化范围为2.63~2.96.MECS和NECS参数估计值和置信区间在各分位数呈异质性变化,低分位时,NECS估计值在3个调查区域中最低,MECS最高;高分位时,MECS和NECS均高于SYS.对低分位0.25、中分位0.5和高分位0.75分位数的异速体长体质量关系的方差分析结果显示,低分位和高分位数之间体长 体质量关系极为显著(0.25∶0.75,F=6.38,df=1737,P<0.01),低分位数和中分位数之间为显著(0.25∶0.5,F=2.35,df=1737,P=0.039),中分位数和高分位数之间接近显著(0.5∶0.75,F=2.21,df=1737,P=0.051).成鱼群体SYS异速生长指数均值为3.01,在0.1~0.95分位的估计值变化范围为2.77~3.10.低分位和高分位数之间体长 体质量关系差异达到显著水平(0.25∶0.75,F=3.31,df=2793,P=0.01),低分位和中分位之间差异不显著(0.25∶0.5,F=0.98,df=2793,P=0.43),而高分位和中分位之间则差异极显著(0.5∶0.75,F=3.56,df=2793,P<0.01).     

A method of determining rooting depth from a terrestrial biosphere model and its impacts on the global water and carbon cycle

We outline a method of inferring rooting depth from a Terrestrial Biosphere Model by maximizing the benefit of the vegetation within the model. This corresponds to the evolutionary principle that vegetation has adapted to make best use of its local environment. We demonstrate this method with a simple coupled biosphere/soil hydrology model and find that deep rooted vegetation is predicted in most parts of the tropics. Even with a simple model like the one we use, it is possible to reproduce biome averages of observations fairly well. By using the optimized rooting depths global Annual Net Primary Production (and transpiration) increases substantially compared to a standard rooting depth of one meter, especially in tropical regions that have a dry season. The decreased river discharge due to the enhanced evaporation complies better with observations. We also found that the optimization process is primarily driven by the water deficit/surplus during the dry/wet season for humid and arid regions, respectively. Climate variability further enhances rooting depth estimates. In a sensitivity analysis where we simulate changes in the water use efficiency of the vegetation we find that vegetation with an optimized rooting depth is less vulnerable to variations in the forcing. We see the main application of this method in the modelling communities of land surface schemes of General Circulation Models and of global Terrestrial Biosphere Models. We conclude that in these models, the increased soil water storage is likely to have a significant impact on the simulated climate and the carbon budget, respectively. Also, effects of land use change like tropical deforestation are likely to be larger than previously thought.