武汉地区硅质磷片金藻的初步研究

1986年11月,在武汉植物所的3个池塘及东湖附近的池塘内采集的标本中,含有大量的具硅质磷片的金藻,共11种,分别隶属于Spiniferomonas, Paraphysomonas, Chrysosphaevella, Mallomonas和Synura 5个属。本文提供了这些藻的硅质磷片、刺及毛的电镜照片。这些藻在中国研究得很少,许多种都是第一次报道,它们中的大多数在世界上其它一些地区也是普遍出现的,有些则毫无疑问地属于世界性分布。     

Signs of stabilisation and stable coexistence

Many empirical studies motivated by an interest in stable coexistence have quantified negative density dependence, negative frequency dependence, or negative plant–soil feedback, but the links between these empirical results and ecological theory are not straightforward. Here, we relate these analyses to theoretical conditions for stabilisation and stable coexistence in classical competition models. By stabilisation, we mean an excess of intraspecific competition relative to interspecific competition that inherently slows or even prevents competitive exclusion. We show that most, though not all, tests demonstrating negative density dependence, negative frequency dependence, and negative plant–soil feedback constitute sufficient conditions for stabilisation of two‐species interactions if applied to data for per capita population growth rates of pairs of species, but none are necessary or sufficient conditions for stable coexistence of two species. Potential inferences are even more limited when communities involve more than two species, and when performance is measured at a single life stage or vital rate. We then discuss two approaches that enable stronger tests for stable coexistence‐invasibility experiments and model parameterisation. The model parameterisation approach can be applied to typical density‐dependence, frequency‐dependence, and plant–soil feedback data sets, and generally enables better links with mechanisms and greater insights, as demonstrated by recent studies.     

Weather-induced changes in moth activity bias measurement of long-term population dynamics from light trap samples

Interpretation of light trap catches of moths is complicated by daily variation in weather that alters flight activity and numbers caught. Light trap efficiency is also modified by wind and fog, and daily weather may effect absolute abundance (numbers actually present). However, actograph experiments and other sampling methods suggest that changes in daily activity are large by comparison to changes in absolute abundance. Daily variation in weather (other than wind and fog) is therefore a form of sampling error in absolute abundance estimates. We investigated the extent of this sampling bias in 26 years of population dynamics from 133 moth species. In a subset of 20 noctuid and geometrid species, daily numbers caught were positively correlated with temperature in 14 species, and negatively correlated with rainfall in 11 species. The strength of correlations varied between species, making it difficult to standardize catches to constant conditions. We overcame this by establishing how weather variation changed with time and duration of the flight period. Species flying later in the summer and for shorter periods experienced more variable temperatures, making sampling error greater for these species. Of the 133 moth species, those with shorter flight periods had greater population variability and more showed significant temporal density dependence. However, these effects were weak, which is encouraging because it suggests that population analyses of light trap data largely reflect factors other than sampling error.     

Producing and scrounging can have stabilizing effects at multiple levels of organization

This study shows, for the first time, that the evolution of a simple behavior, scrounging, at the individual level can have effects on populations, food chains, and community structure. In particular, the addition of scrounging in consumer populations can allow multiple consumers to coexist while exploiting a single prey. Also, scrounging in the top predator of a tritrophic food chain can stabilize interactions between the top predator, its prey, and its prey's prey. This occurs because the payoffs to scrounging for food in a population are negative frequency dependent, allowing scroungers to invade a population and to coexist with producers at a frequency which is density‐dependent. The presence of scroungers, who do not search for resources but simply use those found by others (producers) reduces the total amount of resource acquired by the group. As scrounging increases with group size, this leads to less resource acquired per individual as the group grows. Ultimately, this limits the size of the group, its impact on its prey, and its ability to outcompete other species. These effects can promote stability and thus increase species diversity. I will further suggest that prey may alter their spatial distribution such that scrounging will be profitable among their predators thus reducing predation rate on the prey.     

Cytochemical and molecular characteristics of the process of cornification during feather morphogenesis

Feathers are the most complex epidermal derivatives among vertebrates. The present review deals with the origin of feathers from archosaurian reptiles, the cellular and molecular aspects of feather morphogenesis, and focus on the synthesis of keratins and associated proteins. Feathers consist of different proteins among which exists a specialized group of small proteins called beta-keratins. Genes encoding these proteins in the chick genome are distributed in different chromosomes, and most genes encode for feather keratins. The latter are here recognized as proteins associated with the keratins of intermediate filaments, and functionally correspond to keratin-associated proteins of hairs, nails and horns in mammals. These small proteins possess unique properties, including resistance and scarce elasticity, and were inherited and modified in feathers from ancestral proteins present in the scales of archosaurian progenitors of birds. The proteins share a common structural motif, the core box, which was present in the proteins of the reptilian ancestors of birds. The core box allows the formation of filaments with a different molecular mechanism of polymerization from that of alpha-keratins. Feathers evolved after the establishment of a special morphogenetic mechanism gave rise to barb ridges. During development, the epidermal layers of feathers fold to produce barb ridges that produce the ramified structure of feathers. Among barb ridge cells, those of barb and barbules initially accumulate small amounts of alpha-keratins that are rapidly replaced by a small protein indicated as “feather keratin”. This 10 kDa protein becomes the predominant form of corneous material of feathers. The main characteristics of feather keratins, their gene organization and biosynthesis are similar to those of their reptilian ancestors. Feather keratins allow elongation of feather cells among supportive cells that later degenerate and leave the ramified microstructure of barbs. In downfeathers, barbs are initially independent and form plumulaceous feathers that rest inside a follicle. Stem cells remain in the follicle and are responsible for the regeneration of pennaceous feathers. New barb ridges are produced and they merge to produce a rachis and a flat vane. The modulation of the growth pattern of barb ridges and their fusion into a rachis give rise to a broad variety of feather types, including asymmetric feathers for flight. Feather morphogenesis suggests possible stages for feather evolution and diversification from hair-like outgrowths of the skin found in fossils of pro-avian archosaurians.     

不同空间尺度下的ALMANAC模型验证

ALMANAC模型最早作为EPIC模型的一部分,用于模拟土壤侵蚀导致的土地生产力的下降．它将试验数据的统计过程和作物生长的机理过程结合起来,是一种典型的基于过程模拟的应用型作物生长模型．如能在不同的空间尺度上验证模型的适用性,无疑会大大扩展模型的应用范围．从这一目的出发,利用美国得克萨斯州19个试验田和9个县的玉米和高粱产量资料及其相关的作物、土壤、田问管理等数据,模拟了1998年田间尺度,1989～1998年县级尺度的平均作物产量．模拟结果表明,ALMANAC模型能够很好地模拟两种不同空间尺度的作物产量,其相对误差在田问尺度上分别为8．9％(高粱)和9．4％(玉米),在县级尺度上分别达到2．6％(玉米)和—0．6％(高粱)．该模型在进行产量预测、掌握作物生长动态,指导农业生产管理和土地利用等方面具有很好的应用前景．     

Testing for density dependence

Summary The robustness and sensitivity of a test for density dependence in an animal population against departures from the assumed null and alternative model is assessed via simulation. The test is shown to be nonrobust and insensitive to departures from the assumed models.     

Trap‐shyness subsidence is a threshold function of mark–recapture interval in brown mudfish Neochanna apoda populations

The influence of capture interval on trap shyness, and temperature, rainfall and drought on capture probability (p) in 827 brown mudfish Neochanna apoda was quantified using mark–recapture models. In particular, it was hypothesized that the loss of trapping memory in marked N. apoda would lead to a capture‐interval threshold required to minimize trap shyness. Neochanna apoda trap shyness approximated a threshold response to capture interval, declining rapidly with increasing capture intervals up to 16·5 days, after which p remained constant. Tests for detecting trap‐dependent capture probability in Cormack–Jolly–Seber models failed to detect trap shyness in N. apoda capture histories with capture intervals averaging 16 days. This confirmed the applicability of the 16 day capture‐interval threshold for mark–recapture studies. Instead, N. apoda p was positively influenced by water temperature and rainfall during capture. These results imply that a threshold capture interval is required to minimize the trade‐off between the competing assumptions of population closure and p homogeneity between capture occasions in closed mark–recapture models. Moreover, environmental factors that influence behaviour could potentially confound abundance indices, and consequently abundance trends should be interpreted with caution in the face of long‐term climate change, such as with global warming.     

Assessing the skill of yes/no predictions

Summary Should healthy, middle‐aged women receive precautionary mammograms? Should trauma surgeons use the popular TRISS score to predict the likelihood of patient survival? These are examples of questions confronting us when we decide whether to use a yes/no prediction. In order to trust a prediction we must show that it is more valuable than would be our best guess of the future in the absence of the prediction. Calculating value means identifying our loss should the prediction err and examining the past performance of the prediction with respect to that loss. A statistical test to do this is developed. Predictions that pass this test are said to have skill. Only skillful predictions should be used. Graphical and numerical methods to identify skill will be demonstrated. The usefulness of mammograms is explored.     

Status,trends, and equilibrium abundance estimates of the translocated sea otter population in Washington State

Sea otters (Enhydra lutris kenyoni) historically occurred in Washington State, USA, until their local extinction in the early 1900s as a result of the maritime fur trade. Following their extirpation, 59 sea otters were translocated from Amchitka Island, Alaska, USA, to the coast of Washington, with 29 released at Point Grenville in 1969 and 30 released at La Push in 1970. The Washington Department of Fish and Wildlife has outlined 2 main objectives for sea otter recovery: a target population level and a target geographic distribution. Recovery criteria are based on estimates of population abundance, equilibrium abundance (K), and geographic distribution; therefore, estimates of these parameters have important management implications. We compiled available survey data for sea otters in Washington State since their translocation (1977–2019) and fit a Bayesian state-space model to estimate past and current abundance, and equilibrium abundance at multiple spatial scales. We then used forward projections of population dynamics to explore potential scenarios of range recolonization and as the basis of a sensitivity analysis to evaluate the relative influence of movement behavior, frontal wave speed, intrinsic growth, and equilibrium density on future population recovery potential. Our model improves upon previous analyses of sea otter population dynamics in Washington by partitioning and quantifying sources of estimation error to estimate population dynamics, by providing robust estimates of K, and by simulating long-term population growth and range expansion under a range of realistic parameter values. Our model resulted in predictions of population abundance that closely matched observed counts. At the range-wide scale, the population size in our model increased from an average of 21 independent sea otters (95% CI = 13–29) in 1977 to 2,336 independent sea otters (95% CI = 1,467–3,359) in 2019. The average estimated annual growth rate was 12.42% and varied at a sub-regional scale from 6.42–14.92%. The overall estimated mean K density of sea otters in Washington was 1.71 ± 0.90 (SD) independent sea otters/km² of habitat (1.96 ± 1.04 sea otters/km², including pups), and estimated densities within the current range correspond on average to 87% of mean sub-regional equilibrium values (range = 66–111%). The projected value of K for all of Washington was 5,287 independent sea otters (95% CI = 2,488–8,086) and 6,080 sea otters including pups (95% CI = 2,861–9,300), assuming a similar range of equilibrium densities in currently un-occupied habitats. Sensitivity analysis of simulations of sea otter population growth and range expansion suggested that mean K density estimates in currently occupied sub-regions had the largest impact on predicted future population growth (r² = 0.52), followed by the rate of southward range expansion (r² = 0.26) and the mean K density estimate of currently unoccupied sub-regions to the south of the current range (r² = 0.04). Our estimates of abundance and sensitivity analysis of simulations of future population abundance and geographic range help determine population status in relation to population recovery targets and identify the most influential parameters affecting future population growth and range expansion for sea otters in Washington State.