Atlantic Bluefin Tuna in the Gulf of Maine, I: Estimation of Seasonal Abundance Accounting for Movement, School and School-Aggregation Behaviour

Direct assessment of the abundance of highly migratory pelagic species, such as tuna, is rarely available and most indices are based on catch information. We estimate the seasonal abundance of North Atlantic bluefin tuna, Thunnus thynnus, in the Gulf of Maine (GOM) from a 3-year aerial survey conducted with commercial spotter pilots, while also utilizing findings from analyses of tracking and tagging data. We apply statistical correction and calibration to seasonal abundance estimates accounting for measured changes in horizontal and vertical movement behaviour, size, shape and aggregation of bluefin tuna schools. Our approach relies on ecological knowledge of bluefin tuna to extrapolate survey observations across areas not sampled by correcting survey abundance estimates based on range of movement search pattern and depth preference. We demonstrate how separate findings obtained through the analysis of data collected across different spatial and temporal scales can be integrated to correct and calibrate estimates of population abundance. We obtain fitted estimates of seasonal abundance of bluefin tuna in the GOM during 1994–1996 in the range of 45,000–51,000 individuals. If tuna behaviour is not accounted for, we estimate that the base or residual survey precision would be 4–7% determined from analysis of recent spotter survey data in the study region. We estimate the precision in estimating seasonal abundance accounting for tuna behaviour to lie within a range of 1,301–3,302%. Under hypothetical future improvements in survey design that achieve a precision of 20% in transect length and placement, we calculate net-precision to lie within a range of 82–93%. This calculation assumes reducible uncertainty in school size estimation and irreducible uncertainty in movement and school-aggregation behaviour. We infer that survey precision could be further reduced by 43–32% to attain 10–50% in which a 3–8 years adaptive survey design may reliably detect a seasonal abundance trend.     

Statistical error in isothermal titration calorimetry: variance function estimation from generalized least squares

The method of generalized least squares (GLS) is used to assess the variance function for isothermal titration calorimetry (ITC) data collected for the 1:1 complexation of Ba(2+) with 18-crown-6 ether. In the GLS method, the least squares (LS) residuals from the data fit are themselves fitted to a variance function, with iterative adjustment of the weighting function in the data analysis to produce consistency. The data are treated in a pooled fashion, providing 321 fitted residuals from 35 data sets in the final analysis. Heteroscedasticity (nonconstant variance) is clearly indicated. Data error terms proportional to q(i) and q(i)/v are well defined statistically, where q(i) is the heat from the ith injection of titrant and v is the injected volume. The statistical significance of the variance function parameters is confirmed through Monte Carlo calculations that mimic the actual data set. For the data in question, which fall mostly in the range of q(i)=100-2000 microcal, the contributions to the data variance from the terms in q(i)(2) typically exceed the background constant term for q(i)>300 microcal and v<10 microl. Conversely, this means that in reactions with q(i) much less than this, heteroscedasticity is not a significant problem. Accordingly, in such cases the standard unweighted fitting procedures provide reliable results for the key parameters, K and DeltaH(degrees) and their statistical errors. These results also support an important earlier finding: in most ITC work on 1:1 binding processes, the optimal number of injections is 7-10, which is a factor of 3 smaller than the current norm. For high-q reactions, where weighting is needed for optimal LS analysis, tips are given for using the weighting option in the commercial software commonly employed to process ITC data.     

An Integrated Population Model for Harvest Management of Atlantic Brant

Atlantic brant (Branta bernicla hrota) are important game birds in the Atlantic Flyway and several long-term monitoring data sets could assist with harvest management, including a count-based survey and demographic data. Considering their relative strengths and weaknesses, integrated analysis to these data would likely improve harvest management, but tools for integration have not yet been developed. Managers currently use an aerial count survey on the wintering grounds, the mid-winter survey, to set harvest regulations. We developed an integrated population model (IPM) for Atlantic brant that uses multiple data sources to simultaneously estimate population abundance, survival, and productivity. The IPM abundance estimates for data from 1975–2018 were less variable than annual mid-winter survey counts or Lincoln estimates, presumably reflecting better accounting for observer error and incorporation of demographic estimates by the IPM. Posterior estimates of adult survival were high (0.77–0.87), and harvest rates of adults and juveniles were positively correlated with more liberal hunting regulations (i.e., hunting days and the daily bag limit). Productivity was variable, with the percent of juveniles in the winter population ranging from 1% to >40%. We found no evidence for environmental relationships with productivity. Using IPM-predicted population abundances rather than mid-winter survey counts alone would have meant fewer annual changes to hunting regulations since 2004. Use of the IPM could improve harvest management for Atlantic brant by providing the ability to predict abundance before annual hunting regulations are set, and by providing more stable hunting regulations, with fewer annual changes. © 2021 The Wildlife Society.     

Toward Reliable Estimates of Abundance: Comparing Index Methods to Assess the Abundance of a Mammalian Predator

Due to time and financial constraints indices are often used to obtain landscape-scale estimates of relative species abundance. Using two different field methods and comparing the results can help to detect possible bias or a non monotonic relationship between the index and the true abundance, providing more reliable results. We used data obtained from camera traps and feces counts to independently estimate relative abundance of red foxes in the Black Forest, a forested landscape in southern Germany. Applying negative binomial regression models, we identified landscape parameters that influence red fox abundance, which we then used to predict relative red fox abundance. We compared the estimated regression coefficients of the landscape parameters and the predicted abundance of the two methods. Further, we compared the costs and the precision of the two field methods. The predicted relative abundances were similar between the two methods, suggesting that the two indices were closely related to the true abundance of red foxes. For both methods, landscape diversity and edge density best described differences in the indices and had positive estimated effects on the relative fox abundance. In our study the costs of each method were of similar magnitude, but the sample size obtained from the feces counts (262 transects) was larger than the camera trap sample size (88 camera locations). The precision of the camera traps was lower than the precision of the feces counts. The approach we applied can be used as a framework to compare and combine the results of two or more different field methods to estimate abundance and by this enhance the reliability of the result.     

Strengths and weaknesses of museum and national survey data sets for predicting regional species richness: comparative and combined approaches

We compiled three independent data sets of bird species occurrences in northeastern Colorado to test how predicted species richness compared to a combined analysis using all the data. The first data set was a georeferenced regional museum data set from two major repositories — the Denver Museum of Nature, and the Science and University of Colorado Museum. The two national survey data sets were the Breeding Bird Survey (summer), and the Great Backyard Bird Count (winter). Resulting analyses show that the museum data sets give richness estimates closest to the combined data set while exhibiting a skewed abundance distribution, whereas survey data sets do not accurately estimate overall richness even though they contain far more records. The combined data set allows the strengths of one data set to augment weaknesses in others. It is likely some museum data sets display skewed abundance distributions due to collectors’ potentially self‐selecting under‐represented species over common ones.     

Population Indices Versus Correlated Density Estimates of Black-Footed Ferret Abundance

ABSTRACT Estimating abundance of carnivore populations is problematic because individuals typically are elusive, nocturnal, and dispersed across the landscape. Rare or endangered carnivore populations are even more difficult to estimate because of small sample sizes. Considering behavioral ecology of the target species can drastically improve survey efficiency and effectiveness. Previously, abundance of the black-footed ferret (Mustela nigripes) was monitored by spotlighting and generating indices of relative abundance because reintroduced populations were slow to establish. Indices, however, lack variance estimates and are costly to generate for the black-footed ferret. We therefore used spotlight surveys and live-trapping in conjunction with a robust mark-recapture estimator to improve abundance monitoring for the black-footed ferret, one of North America's most endangered carnivores. We estimated abundance of the black-footed ferret at Shirley Basin, Wyoming, USA, using correlated density estimates and Program MARK. We compared our results to 2 indices of relative abundance, minimum number alive and predicted number of ferrets from litter counts. The correlated density estimate for the black-footed ferret (N̂_R = 229; 95% CI = 161–298) was similar to minimum number alive (N̂_R = 192) and predicted number of ferrets from litter counts (N̂_R= 235). The efficiency and effectiveness of survey methods we used for the black-footed ferret were high by carnivoran standards. Our results suggest that the sampling approach we utilized can be implemented for a fraction of the cost and effort required to generate 2 indices of relative abundance for the black-footed ferret. Although we recommend managers implement a similar survey approach to monitor abundance of reintroduced populations of the black-footed ferret, analysis with sparse data sets will be problematic. Until the black-footed ferret becomes widespread and abundant at a reintroduction site, spotlighting will remain preferable as a means to generate indices of distribution and relative abundance for the black-footed ferret.     

秦岭太白山弃耕地植物群落演替的生态学研究 Ⅱ演替系列的群落α多样性特征

应用物种丰富度、Ｓｉｍｐｓｏｎ指数、Ｓｈａｎｎｏｎ－Ｗｉｅｎｅｒ指数、Ｐｉｅｌｏｕ均匀度指数、Ａｌａｔａｌｏ均匀度指数研究了太白山弃耕地植物群落次生演替过程中的群落α多样性动态特征,结果表明,群落在由一年生草本植物群落阶段向多年生草本植物群落、灌丛、混交林阶段的演替过程中,群落多样性指数逐渐上升,至混交林阶段达到最高值。若以分布在这一垂直地带的代表性森林群落锐齿栎林为演替进一步发展的方向,则由多样性指数在锐齿栎混交林、锐齿栎林阶段呈下降趋势。不同演替阶段不同生长型的多样性指数变化规律为：在演替的初期,草本层多样性指数＞灌木层＞乔木层;在混交林阶段,这３个不同生长型的多样性指数相差无几,乔木生长型稍占优势;在锐齿栎混交林和锐齿栎林阶段,灌木生长型的物种多样性最大,草本次之,乔木生长型的物种多样性则迅速降低。首次利用群落各生长型的叶层相对厚度和相对盖度作为加权参数,对群落总体的物种多样性指数进行了测度,结果表明,这种加权处理是比较合理的。     

ProVal: a protein-scoring function for the selection of native and near-native folds

A low-resolution scoring function for the selection of native and near-native structures from a set of predicted structures for a given protein sequence has been developed. The scoring function, ProVal (Protein Validate), used several variables that describe an aspect of protein structure for which the proximity to the native structure can be assessed quantitatively. Among the parameters included are a packing estimate, surface areas, and the contact order. A partial least squares for latent variables (PLS) model was built for each candidate set of the 28 decoy sets of structures generated for 22 different proteins using the described parameters as independent variables. The C(alpha) RMS of the candidate structures versus the experimental structure was used as the dependent variable. The final generalized scoring function was an average of all models derived, ensuring that the function was not optimized for specific fold classes or method of structure generation of the candidate folds. The results show that the crystal structure was scored best in 64% of the 28 test sets and was clearly separated from the decoys in many examples. In all the other cases in which the crystal structure did not rank first, it ranked within the top 10%. Thus, although ProVal could not distinguish between predicted structures that were similar overall in fold quality due to its inherently low resolution, it can clearly be used as a primary filter to eliminate approximately 90% of fold candidates generated by current prediction methods from all-atom modeling and further evaluation. The correlation between the predicted and actual C(alpha) RMS values varies considerably between the candidate fold sets.     

Performance of Baited Underwater Video: Does It Underestimate Abundance at High Population Densities?

Video survey techniques are now commonly used to estimate animal abundance under the assumption that estimates relate to true abundance, a key property needed to make video a valid survey tool. Using the spiny lobster Palinurus elephas as our model organism, we evaluate the effectiveness of baited underwater video (BUV) for estimating abundance in areas with widely different population density. We test three BUV abundance metrics and compare the results with an independently obtained abundance index from trammel-net surveys (Trammel). Video metrics used to estimate relative abundance include a value for total number of individuals per recording (TotN), the traditional maximum number of fish observed in a single video frame (MaxN), and the recently suggested alternative, the average of the mean MaxN from 5-minute periods throughout the duration of the recording (MeanN). This is the first video study of a wild population to include an estimate for TotN. Comparison of TotN with the other two BUV relative abundance metrics demonstrates that both of the latter lack resolution at high population densities. In spite of this, the three BUV metrics tested, as well as the independent estimate Trammel, distinguished high density areas from low density areas. Thus they could all be used to identify areas of differing population density, but MaxN and MeanN would not be appropriate metrics for studies aimed at documenting increases in abundance, such as those conducted to assess marine protected area effectiveness, as they are prone to sampling saturation. We also demonstrate that time of first arrival (T1) is highly correlated with all of the abundance indices; suggesting T1 may be a potentially useful index of abundance. However, these relationships require further investigation as our data suggests T1 may not adequately represent lobster abundance in areas of high density.     

Analysis of spatial patterns at a geographical scale over north-western Europe from point-referenced aphid count data

The spatial analysis by distance indices (SADIE) technique was developed to evaluate the spatial pattern of point-referenced count data as well as the spatial association between two sets of data sharing the same point locations. This paper presents an analysis of spatial patterns in aphid count data and the association of these data with climate across north-west Europe. The paper tests the applicability of the technique to large geographical areas. Aggregation and cluster indices were calculated for the total annual abundance of the peach-potato aphid Myzus persicae (Sulzer) and for the annual mean rainfall and temperature at aphid monitoring sites. Association indices demonstrated the stability in time of aphid spatial structures and the correlation between aphid density and climate patterns. Groups of relatively large numbers of aphids, termed patches, and groups of relatively small numbers of aphids, termed gaps, were located and their mean size estimated. The aphid patterns were quite stable in time and the spatial patterns of temperature and rainfall were weakly associated with M. persicae annual abundance. Similarities were observed between the results of SADIE and those from the more widely used technique of spatial autocorrelation (SAC). However, the SADIE association index has the advantage of quantifying the possible associations between aphid data and the factors that determine population distribution. Thus, high temperature and low rainfall were identified as environmental factors that were positively associated with aphid abundance across north-west Europe.     

Evaluation of an Aerial Survey to Estimate Abundance of Wintering Ducks in Mississippi

Abstract: Researchers have successfully designed aerial surveys that provided precise estimates of wintering populations of ducks over large physiographic regions, yet few conservation agencies have adopted these probability-based sampling designs for their surveys. We designed and evaluated an aerial survey to estimate abundance of wintering mallards (Anas platyrhynchos), dabbling ducks (tribe Anatini) other than mallards, diving ducks (tribes Aythini, Mergini, and Oxyurini), and total ducks in western Mississippi, USA. We used design-based sampling of fixed width transects to estimate population indices (Ǐ), and we used model-based methods to correct population indices for visibility bias and estimate population abundance (Ň) for 14 surveys during winters 2002–2004. Correcting for bias increased estimates of mallards, other dabbling ducks, and diving ducks by an average of 40–48% among all surveys and contributed 48–61% of the estimated variance of Ň. However, mean-squared errors were consistently less for Ň than Ǐ. Estimates of Ň met our goals for precision (CV ≤ 15%) in 7 of 14 surveys for mallards, 5 surveys for other dabbling ducks, no surveys for diving ducks, and 10 surveys for total ducks. Generally, we estimated more mallards and other dabbling ducks in mid- and late winter (Jan-Feb) than early winter (Nov-Dec) and determined that population indices from the late 1980s were nearly 3 times greater than those from our study. We developed a method to display relative densities of ducks spatially as an additional application of survey data. Our study advanced methods of estimating abundance of wintering waterfowl, and we recommend this design for continued monitoring of wintering ducks in western Mississippi and similar physiographic regions.     

基于估计准度和调查费用的渔业资源调查采样设计优化

合理的调查采样设计及优化可以降低调查费用,确保调查数据的准确性,实现调查采样效益的最大化。本研究量化了调查费用,在考虑估计准确度基础上,将调查费用作为评价指标加入到采样设计优化中,应用计算机模拟重抽样方法和模拟退火算法进行航线规划。基于2013—2015年春、秋季海州湾渔业资源底拖网调查数据,使用克里金插值法模拟了该海域星康吉鳗(Conger myriaster)、方氏云鳚(Enedrias fangi)和大泷六线鱼(Hexagrammos otakii)在春、秋季的相对资源量分布,作为其分布的“真值”。应用分层随机抽样模拟不同样本量下的调查采样,估计各目标鱼种的资源量指数,以相对偏差(RB)的绝对值来评价目标鱼种资源量指数估计的准确度,以调查费用、超标概率作为费用评价指标,以综合评价指标(IEI)作为衡量准确度和费用的综合指标。结果表明: 各鱼种资源量指数估计的RB值随样本量增加而降低,但各鱼种的RB值不同。不同评价指标确定的最优站位数不同,按RB值确定的最优站位数较高,调查费用超过预算;按调查费用确定的站位数较低,但无法有效保证资源量指数估计的准确性;按IEI确定的最优站位数处于中间水平,能兼顾调查费用和资源量指数估计准度。综合考虑调查费用和航线规划的采样设计不仅能确定最优站位数,还可以确定调查设计的站位空间位置、站位调查顺序和调查费用。调查者可以根据实际费用预算,从模拟方案中选择费用低、RB低的理想采样设计方案开展调查。     

Estimation of a Nonlinear Density-Dependence Parameter for Wild Turkey

Abstract: Although previous research and theory has suggested that wild turkey (Meleagris gallopavo) populations may be subject to some form of density dependence, there has been no effort to estimate and incorporate a density-dependence parameter into wild turkey population models. To estimate a functional relationship for density dependence in wild turkey, we analyzed a set of harvest-index time series from 11 state wildlife agencies. We tested for lagged correlations between annual harvest indices using partial autocorrelation analysis. We assessed the ability of the density-dependent theta-Ricker model to explain harvest indices over time relative to exponential or random walk growth models. We tested the homogeneity of the density-dependence parameter estimates (θ) from 3 different harvest indices (spring harvest no. reported harvest/effort, survey harvest/effort) and calculated a weighted average based on each estimate's variance and its estimated covariance with the other indices. To estimate the potential bias in parameter estimates from measurement error, we conducted a simulation study using the theta-Ricker with known values and lognormally distributed measurement error. Partial autocorrelation function analysis indicated that harvest indices were significantly correlated only with their value at the previous time step. The theta-Ricker model performed better than the exponential growth or random walk models for all 3 indices. Simulation of known parameters and measurement error indicated a strong positive upward bias in the density-dependent parameter estimate, with increasing measurement error. The average density-dependence estimate, corrected for measurement error ranged 0.25 ≤ θC ≤ 0.49, depending on the amount of measurement error and assumed spring harvest rate. We infer that density dependence is nonlinear in wild turkey, where growth rates are maximized at 39-42% of carrying capacity. The annual yield produced by density-dependent population growth will tend to be less than that caused by extrinsic environmental factors. This study indicates that both density-dependent and density-independent processes are important to wild turkey population growth, and we make initial suggestions on incorporating both into harvest management strategies.     

Aerial survey as a tool to estimate whale shark abundance trends

Aerial surveys have been used to estimate population abundance of both terrestrial and marine species; in the marine environment this has largely been used for air-breathing species that spend time regularly at the surface. Whale sharks spend a large proportion of their time close to the surface and so are amenable to aerial survey techniques. This study presents the results of six years of synoptic aerial belt-surveys done nearly daily during the peak whale shark season around the island of Mahe, Seychelles. A total of 580 survey flights were flown providing 699.7 hours of survey record. A seasonal peak of shark sightings per hour was recorded in September or October in most years with the maximum on a single survey of 28.4 h^- 1 in October 2006. The aerial survey data were used to generate an estimate of relative population abundance indicating that highest mean annual relative population estimate was also in 2006, with an estimate of 38, while the lowest mean estimate was 11 in 2004. These estimates were then compared to weekly capture-mark-recapture estimates of abundance based on unique individual identification data. The results indicate that the use of aerial survey data alone may give an acceptable indication of instantaneous relative population abundance but further refinement is necessary to estimate absolute regional abundance.     

MONITORING THE TREND OF HARBOR SEALS IN PRINCE WILLIAM SOUND,ALASKA, AFTER THE EXXON VALDEZ OIL SPILL

We used aerial counts to monitor the trend in numbers of harbor seals, Phoca vitulina richardsi, in Prince William Sound, Alaska, following the 1989 Exxon Valdez oil spill. Repetitive counts were made at 25 haul-out sites during the annual molt period each year from 1990 through 1997. A generalized linear model indicated that time of day, date, and time relative to low tide significantly affected seal counts. When Poisson regression was used to adjust counts to a standardized set of survey conditions, results showed a highly significant decline of 4.6% per year. Unadjusted counts indicated a slight, but not statistically significant, decline in the number of seals. The number of harbor seals on the trend-count route in eastern and central PWS has been declining since at least 1984, with an overall population reduction of 63% through 1997. Programs to monitor long-term changes in animal population sizes should account for factors that can cause short-term variations in indices of abundance. The inclusion of such factors as covariates in models can improve the accuracy of monitoring programs.     

Application of Diversity Indices to Appraise Plant Availability in the Traditional Medicinal Markets of Johannesburg,South Africa

The lack of scientific rigour in analysing ethnobotanical surveys has prompted researchers to investigate ways of quantitatively describing their data, including the use of ecological diversity indices. There are numerous indices and measures available to describe sample diversity. Twenty-two measures of species richness, diversity and evenness were reviewed using six sets of ethnomedicinal data derived from 50 formal muti shop traders (of different ethnicities) and 100 informal street traders of traditional medicine in Johannesburg, South Africa, and a seventh data set from traders on the western boundary of the Kruger National Park, South Africa. The diversity measures were coupled with species accumulation curves to construct cumulative diversity curves used to determine the minimum viable sample size on which a diversity index should be based, and to better understand the differences in the relative diversities of the samples. Distinct differences in the relative abundance and diversity of plants sold by street traders and shop traders were evident. Species diversity and evenness was found to be higher in shops, thus resulting in a lower dominance in the sale of certain plant species compared to the street traders. A survey of an informal market should include no less than 35 research participants compared to no less than 20 for the muti shops. The use of selected indices of species richness (Margalef's), diversity (Shannon, Simpson's, Fisher's alpha, Hill's numbers) and evenness are recommended as a means of describing patterns exhibited within ethnobotanical data.     

The population status of Capercaillie Tetrao urogallus in Scotland during winter 2015–16

Capsule: The population size of Western Capercaillie Tetrao urogallus in Scotland was estimated at 1114 individuals with 95% confidence intervals (CIs) of 805–1505.

Aim: To produce an updated estimate of Capercaillie population size in Scotland, with improved precision from, but retaining comparability with, previous surveys.

Methods: A random sample of 2?km long line transects was surveyed throughout the current range of the Capercaillie, during winter 2015–16, with sampling in three separate strata. Multi-covariate distance sampling was used to fit detection functions to the Capercaillie data, deriving national, regional and sex-specific estimates of density and abundance.

Results: Across 741 transects, 136 Capercaillie were recorded in 120 separate encounters, giving rise to a population estimate of 1114 individuals (95% CIs: 805–1505). This estimate is 13% lower than that from the previous survey in 2009–10 but the difference is not statistically significant. Most of the population (83%) was estimated to occur in Strathspey, with much smaller numbers in the rest of the range.

Conclusion: The Capercaillie population in Scotland remains at a critically low level. Further evidence of decline in edge of range subpopulations raises serious concern over the viability of Capercaillie in these areas, whereas numbers appear stable in the core of the range in Strathspey. The use of a revised survey design, with greater sampling in the core of the range, improved estimate precision.     

Density‐dependent space use affects interpretation of camera trap detection rates

Camera traps (CTs) are an increasingly popular tool for wildlife survey and monitoring. Estimating relative abundance in unmarked species is often done using detection rate as an index of relative abundance, which assumes that detection rate has a positive linear relationship with true abundance. This assumption may be violated if movement behavior varies with density, but the degree to which movement behavior is density‐dependent across taxa is unclear. The potential confounding of population‐level relative abundance indices by movement would depend on how regularly, and by what magnitude, movement rate and home‐range size vary with density. We conducted a systematic review and meta‐analysis to quantify relationships between movement rate, home‐range size, and density, across terrestrial mammalian taxa. We then simulated animal movements and CT sampling to test the effect of contrasting movement scenarios on CT detection rate indices. Overall, movement rate and home‐range size were negatively correlated with density and positively correlated with one another. The strength of the relationships varied significantly between taxa and populations. In simulations, detection rates were related to true abundance but underestimated change, particularly for slower moving species with small home ranges. In situations where animal space use changes markedly with density, we estimate that up to thirty percent of a true change in relative abundance may be missed due to the confounding effect of movement, making trend estimation more difficult. The common assumption that movement remains constant across densities is therefore violated across a wide range of mammal species. When studying unmarked species using CT detection rates, researchers and managers should explicitly consider that such indices of relative abundance reflect both density and movement. Practitioners interpreting changes in camera detection rates should be aware that observed differences may be biased low relative to true changes in abundance. Further information on animal movement, or methods that do not depend on assumptions of density‐independent movement, may be required to make robust inferences on population trends.     

Spatial dynamics in breeding performance of a predator: the connection to prey availability

Using nationwide long-term data on goshawk and grouse populations in Finland we study the spatial dynamics of the numbers of breeding northern goshawk ( Accipiter gentilis ) pairs, goshawk brood size and offspring sex ratio and their connection to the abundance of grouse. Our first large-scale data comprise of observations on goshawk nests during 1986–2001 pooled to 21 different regions. The second set are annual (1989–1998) observations of brood size and offspring sex ratio (females over the sum of females and males) in goshawk nests all over the country, aggregated to 50 km grid level (n=28 grid units). The third set comprises counts (1989–2001) of four species of woodland grouse, split to adults and juveniles, also given in the same 50 km grid units. Using these data, we show that the annual numbers of northern goshawk nests in the different regions fluctuate in synchrony. Synchrony is also found in long-term fluctuations of northern goshawk brood size and offspring sex ratio. Moreover, synchrony is found in annual numbers of grouse juveniles and adults, the main prey for the northern goshawk. In the brood size and offspring sex ratio of the goshawk, as well as in the annual numbers of grouse juveniles and adults the degree of synchrony falls off with increasing distance. However, only in sex ratios and in grouse dynamics are the slopes of synchrony vs distance roughly matching. We also found that sex ratio either vs grouse juveniles or grouse adults has a more matching spatial dimension (50 km radius) that sex ratio vs brood size. These observation lend support to the hypothesis that goshawk offspring sex ratio and grouse abundance are interconnected. Despite the reason, consequences of spatial coupling in sex ratio could have repercussions on other life history events.     

pime: A package for discovery of novel differences among microbial communities

The data used for profiling microbial communities is usually sparse with some microbes having high abundance in a few samples and being nearly absent in others. However, current bioinformatics tools able to deal with this sparsity are lacking. pime (Prevalence Interval for Microbiome Evaluation) was designed to remove those taxa that may be high in relative abundance in just a few samples but have a low prevalence overall. The reliability and robustness of pime were compared against existing methods and tested using 16S rRNA independent data sets. pime filters microbial taxa not shared in a per treatment prevalence interval started at 5% prevalence with increasing increments of 5% at each filtering step. For each prevalence interval, hundreds of decision trees were calculated to predict the likelihood of detecting differences in treatments. The best prevalence‐filtered data set was user‐selected by choosing the prevalence interval that kept a large portion of the 16S rRNA sequences in the data set while also showing the lowest error rate. To obtain the likelihood of introducing type I error while building prevalence‐filtered data sets, an error detection step based was also included. A pime reanalysis of published data sets uncovered other expected microbial associations than previously reported, which may be masked when only relative abundance was considered.