Oxygen and carbon isoscapes for the Baltic Sea: Testing their applicability in fish migration studies

Conventional tags applied to individuals have been used to investigate animal movement, but these methods require tagged individuals be recaptured. Maps of regional isotopic variability known as “isoscapes” offer potential for various applications in migration research without tagging wherein isotope values of tissues are compared to environmental isotope values. In this study, we present the spatial variability in oxygen () and dissolved inorganic carbon (δ¹³C_DIC) isotope values of Baltic Sea water. We also provide an example of how these isoscapes can reveal locations of individual animal via spatial probability surface maps, using the high‐resolution salmon otolith isotope data from salmon during their sea‐feeding phase in the Baltic Sea. A clear latitudinal and vertical gradient was found for both and δ¹³C_DIC values. The difference between summer and winter in the Baltic Sea values was only slight, whereas δ¹³C_DIC values exhibited substantial seasonal variability related to algal productivity. Salmon otolith δ¹⁸O_oto and δ¹³C_oto values showed clear differences between feeding areas and seasons. Our example demonstrates that dual isotope approach offers great potential for estimating probable fish habitats once issues in model parameterization have been resolved.     

Contemporary effective population and metapopulation size (Ne and meta‐Ne): comparison among three salmonids inhabiting a fragmented system and differing in gene flow and its asymmetries

We estimated local and metapopulation effective sizes ( and meta‐) for three coexisting salmonid species (Salmo salar, Salvelinus fontinalis, Salvelinus alpinus) inhabiting a freshwater system comprising seven interconnected lakes. First, we hypothesized that might be inversely related to within‐species population divergence as reported in an earlier study (i.e., F_ST: S. salar> S. fontinalis> S. alpinus). Using the approximate Bayesian computation method implemented in ONeSAMP, we found significant differences in () between species, consistent with a hierarchy of adult population sizes (). Using another method based on a measure of linkage disequilibrium (LDNE: ), we found more finite values for S. salar than for the other two salmonids, in line with the results above that indicate that S. salar exhibits the lowest among the three species. Considering subpopulations as open to migration (i.e., removing putative immigrants) led to only marginal and non‐significant changes in , suggesting that migration may be at equilibrium between genetically similar sources. Second, we hypothesized that meta‐ might be significantly smaller than the sum of local s (null model) if gene flow is asymmetric, varies among subpopulations, and is driven by common landscape features such as waterfalls. One ‘bottom‐up’ or numerical approach that explicitly incorporates variable and asymmetric migration rates showed this very pattern, while a number of analytical models provided meta‐ estimates that were not significantly different from the null model or from each other. Our study of three species inhabiting a shared environment highlights the importance and utility of differentiating species‐specific and landscape effects, not only on dispersal but also in the demography of wild populations as assessed through local s and meta‐s and their relevance in ecology, evolution and conservation.     

Estimators for QST and coalescence times

Comparisons of to can provide insights into the evolutionary processes that lead to differentiation, or lack thereof, among the phenotypes of different groups (e.g., populations, species), and these comparisons have been performed on a variety of taxa, including humans. Here, I show that for neutrally evolving (i.e., by genetic drift, mutation, and gene flow alone) quantitative characters, the two commonly used estimators have somewhat different interpretations in terms of coalescence times, particularly when the number of groups that have been sampled is small. A similar situation occurs for estimators. Consequently, when observations come from only a small number of groups, which is not an unusual situation, it is important to match estimators appropriately when comparing to .     

Soil moisture variations affect short‐term plant‐microbial competition for ammonium,glycine, and glutamate

We tested whether the presence of plant roots would impair the uptake of ammonium (), glycine, and glutamate by microorganisms in a deciduous forest soil exposed to constant or variable moisture in a short‐term (24‐h) experiment. The uptake of ¹⁵NH₄ and dual labeled amino acids by the grass Festuca gigantea L. and soil microorganisms was determined in planted and unplanted soils maintained at 60% WHC (water holding capacity) or subject to drying and rewetting. The experiment used a design by which competition was tested in soils that were primed by plant roots to the same extent in the planted and unplanted treatments. Festuca gigantea had no effect on microbial N uptake in the constant moist soil, but its presence doubled the microbial uptake in the dried and rewetted soil compared with the constant moist. The drying and rewetting reduced by half or more the uptake by F. gigantea, despite more than 60% increase in the soil concentration of . At the same time, the amino acid and ‐ N became equally valued in the plant uptake, suggesting that plants used amino acids to compensate for the lower acquisition. Our results demonstrate the flexibility in plant‐microbial use of different N sources in response to soil moisture fluctuations and emphasize the importance of including transient soil conditions in experiments on resource competition between plants and soil microorganisms. Competition between plants and microorganisms for N is demonstrated by a combination of removal of one of the potential competitors, the plant, and subsequent observations of the uptake of N in the organisms in soils that differ only in the physical presence and absence of the plant during a short assay. Those conditions are necessary to unequivocally test for competition.     

Exploring a Pool‐seq‐only approach for gaining population genomic insights in nonmodel species

Developing genomic insights is challenging in nonmodel species for which resources are often scarce and prohibitively costly. Here, we explore the potential of a recently established approach using Pool‐seq data to generate a de novo genome assembly for mining exons, upon which Pool‐seq data are used to estimate population divergence and diversity. We do this for two pairs of sympatric populations of brown trout (Salmo trutta): one naturally sympatric set of populations and another pair of populations introduced to a common environment. We validate our approach by comparing the results to those from markers previously used to describe the populations (allozymes and individual‐based single nucleotide polymorphisms [SNPs]) and from mapping the Pool‐seq data to a reference genome of the closely related Atlantic salmon (Salmo salar). We find that genomic differentiation (F_ST) between the two introduced populations exceeds that of the naturally sympatric populations (F_ST = 0.13 and 0.03 between the introduced and the naturally sympatric populations, respectively), in concordance with estimates from the previously used SNPs. The same level of population divergence is found for the two genome assemblies, but estimates of average nucleotide diversity differ ( ≈ 0.002 and  ≈ 0.001 when mapping to S. trutta and S. salar, respectively), although the relationships between population values are largely consistent. This discrepancy might be attributed to biases when mapping to a haploid condensed assembly made of highly fragmented read data compared to using a high‐quality reference assembly from a divergent species. We conclude that the Pool‐seq‐only approach can be suitable for detecting and quantifying genome‐wide population differentiation, and for comparing genomic diversity in populations of nonmodel species where reference genomes are lacking.     

Estimating animal behavior and residency from movement data

We present a process‐based approach to estimate residency and behavior from uncertain and temporally correlated movement data collected with electronic tags. The estimation problem is formulated as a hidden Markov model (HMM) on a spatial grid in continuous time, which allows straightforward implementation of barriers to movement. Using the grid to explicitly resolve space, location estimation can be supplemented by or based entirely on environmental data (e.g. temperature, daylight). The HMM method can therefore analyze any type of electronic tag data. The HMM computes the joint posterior probability distribution of location and behavior at each point in time. With this, the behavioral state of the animal can be associated to regions in space, thus revealing migration corridors and residence areas. We demonstrate the inferential potential of the method by analyzing satellite‐linked archival tag data from a southern bluefin tuna Thunnus maccoyii where longitudinal coordinates inferred from daylight are supplemented by latitudinal information in recorded sea surface temperatures.     

Fine‐scale frequency differentiation along a herbivory gradient in the trichome dimorphism of a wild Arabidopsis

Geographic variation is commonly observed in plant resistance traits, where plant species might experience different selection pressure across a heterogeneous landscape. Arabidopsis halleri subsp. gemmifera is dimorphic for trichome production, generating two morphs, trichome‐producing (hairy) and trichomeless (glabrous) plants. Trichomes of A. halleri are known to confer resistance against the white butterfly, cabbage sawfly, and brassica leaf beetle, but not against flea beetles. We combined leaf damage, microclimate, and microsatellite loci data of 26 A. halleri populations in central Japan, to explore factors responsible for fine‐scale geographic variation in the morph frequency. We found that hairy plants were less damaged than glabrous plants within populations, but the among‐site variation was the most significant source of variation in the individual‐level damage. Fixation index () of a putative trichome locus exhibited a significant divergence along population‐level damage with an exception of an outlier population, inferring the local adaptation to herbivory. Notably, this outlier was a population wherein our previous study reported a balancing role of the brassica leaf beetle Phaedon brassicae on the morph frequency. This differentiation of the trichome locus was unrelated to neutral genetic differentiation (evaluated by of microsatellite loci) and meteorological factors (including temperature and solar radiation). The present findings, combined with those of our previous work, provide suggestive evidence that herbivore‐driven divergence and occasional outbreak of a specific herbivore have jointly contributed to the ecogeographic pattern in the frequency of two morphs.     

American marten and fisher do not segregate in space and time during winter in a mixed‐forest system

Understanding the mechanisms of coexistence between ecologically similar species is an important issue in ecology. Carnivore coexistence may be facilitated by spatial segregation, temporal avoidance, and differential habitat selection. American martens Martes americana and fishers Pekania pennanti are medium‐sized mustelids that occur sympatrically across portions of North America, yet mechanisms of coexistence between the two species are not fully understood. We assessed spatial and temporal partitioning in martens and fishers in the Upper Peninsula of Michigan, USA, using camera trap data collected during winter 2013–2015. To investigate spatial segregation, we used a dynamic occupancy model to estimate species’ occupancy probabilities and probabilities of persistence and colonization as a function of covariates and yearly occupancy probability for the other species. Temporal segregation was assessed by estimating diel activity overlap between species. We found weak evidence of spatial or temporal niche partitioning of martens and fishers. There was high overlap in forest cover selection, and both marten and fisher occupancy were positively correlated with deciduous forests (excluding aspen [Populus tremuloides]). There was strong temporal overlap (; CI = 0.79–0.82) with both species exhibiting largely crepuscular activity patterns. Co‐occurrence of martens and fishers appears to be facilitated by mechanisms not investigated in this study, such as partitioning of snow features or diet. Our results add additional insights into resource partitioning of mesocarnivores, but further research is required to enhance our understanding of mechanisms that facilitate marten and fisher coexistence.     

CopyMap: localization and calling of copy number variation by joint analysis of hybridization data from multiple individuals

SUMMARY: The program package CopyMap identifies copy number variation from oligo-hybridization and CGH data. Using a time-dependent hidden Markov model to combine evidence of copy number variants (CNVs) across multiple carriers, CopyMap is substantially more accurate than standard hidden Markov methods in identifying CNVs and calling CNV-carriers. Moreover, CopyMap provides more precise estimates of CNV-boundaries. AVAILABILITY: The C-source code and detailed documentation for the program CopyMap is available on the Internet at http://www.sph.umich.edu/csg/szoellner/     

Paleoecological evidence for decadal increase in phytoplankton biomass off northwestern Australia in response to climate change

Ocean warming can modify the phytoplankton biomass on decadal scales. Significant increases in sea surface temperature (SST) and rainfall in the northwest of Australia over recent decades are attributed to climate change. Here, we used four biomarker proxies (TEX₈₆ index, long‐chain n‐alkanes, brassicasterol, and dinosterol) to reconstruct approximately 60‐year variations of SST, terrestrial input, and diatom and dinoflagellate biomass in the coastal waters of the remote Kimberley region. The results showed that the most significant increases in SST and terrestrial input occurred since 1997, accompanied by an abrupt increase in diatom and dinoflagellate biomasses. Compared with the results before 1997, the average temperature during 1997–2011 increased approximately 1°C, rainfall increased 248.2 mm, brassicasterol and dinosterol contents increased 8.5 and 1.7 times. Principal component analysis indicated that the warming SST played a more important role in the phytoplankton increase than increased rainfall and river discharge.     

Presence of a Fibronectin Type III Domain in a Plant Protein

A hidden Markov model (HMM) approach was used to identify potential candidates in sequence databases for fibronectin type III domains in plants, a kingdom heretofore bereft of these structures. Fortuitously, one of the proteins uncovered had already had a crystal structure published, allowing direct structural confirmation of the existence of this domain in plants. Received: 19 December 1997 / Accepted: 23 December 1997     

Generalizing HMMs to Continuous Time for Fast Kinetics: Hidden Markov Jump Processes

The hidden Markov model (HMM) is a framework for time series analysis widely applied to single-molecule experiments. Although initially developed for applications outside the natural sciences, the HMM has traditionally been used to interpret signals generated by physical systems, such as single molecules, evolving in a discrete state space observed at discrete time levels dictated by the data acquisition rate. Within the HMM framework, transitions between states are modeled as occurring at the end of each data acquisition period and are described using transition probabilities. Yet, whereas measurements are often performed at discrete time levels in the natural sciences, physical systems evolve in continuous time according to transition rates. It then follows that the modeling assumptions underlying the HMM are justified if the transition rates of a physical process from state to state are small as compared to the data acquisition rate. In other words, HMMs apply to slow kinetics. The problem is, because the transition rates are unknown in principle, it is unclear, a priori, whether the HMM applies to a particular system. For this reason, we must generalize HMMs for physical systems, such as single molecules, because these switch between discrete states in “continuous time”. We do so by exploiting recent mathematical tools developed in the context of inferring Markov jump processes and propose the hidden Markov jump process. We explicitly show in what limit the hidden Markov jump process reduces to the HMM. Resolving the discrete time discrepancy of the HMM has clear implications: we no longer need to assume that processes, such as molecular events, must occur on timescales slower than data acquisition and can learn transition rates even if these are on the same timescale or otherwise exceed data acquisition rates.     

Pyric‐carnivory: Raptor use of prescribed fires

Fire is a process that shaped and maintained most terrestrial ecosystems worldwide. Changes in land use and patterns of human settlement have altered fire regimes and led to fire suppression resulting in numerous undesirable consequences spanning individual species and entire ecosystems. Many obvious and direct consequences of fire suppression have been well studied, but several, albeit less obvious, costs of alteration to fire regimes on wildlife are unknown. One such phenomenon is the response of carnivores to fire events—something we refer to as pyric‐carnivory. To investigate the prevalence of pyric‐carnivory in raptors, we monitored 25 prescribed fires occurring during two different seasons and across two different locations in tallgrass prairie of the central United States. We used paired point counts occurring before and during prescribed fires to quantify the use of fires by raptors. We found a strong attraction to fires with average maximum abundance nearly seven times greater during fires than prior to ignitions (before:  = 2.90, SE = 0.42; during:  = 20.20; SE = 3.29) and an average difference between fire events and immediately before fires of 15.2 (±2.69) raptors. This result was driven by Swainson's hawks (Buteo swainsoni), which were the most abundant (n = 346) of the nine species we observed using fires. Our results illustrate the importance of fire as integral disturbance process that effects wildlife behavior through multiple mechanisms that are often overshadowed by the predominant view of fire as a tool used for vegetation management.     

Classifying movement behaviour in relation to environmental conditions using hidden Markov models

1.  Linking the movement and behaviour of animals to their environment is a central problem in ecology. Through the use of electronic tagging and tracking (ETT), collection of in situ data from free-roaming animals is now commonplace, yet statistical approaches enabling direct relation of movement observations to environmental conditions are still in development.
2.  In this study, we examine the hidden Markov model (HMM) for behavioural analysis of tracking data. HMMs allow for prediction of latent behavioural states while directly accounting for the serial dependence prevalent in ETT data. Updating the probability of behavioural switches with tag or remote-sensing data provides a statistical method that links environmental data to behaviour in a direct and integrated manner.
3.  It is important to assess the reliability of state categorization over the range of time-series lengths typically collected from field instruments and when movement behaviours are similar between movement states. Simulation with varying lengths of times series data and contrast between average movements within each state was used to test the HMMs ability to estimate movement parameters.
4.  To demonstrate the methods in a realistic setting, the HMMs were used to categorize resident and migratory phases and the relationship between movement behaviour and ocean temperature using electronic tagging data from southern bluefin tuna ( Thunnus maccoyii ). Diagnostic tools to evaluate the suitability of different models and inferential methods for investigating differences in behaviour between individuals are also demonstrated.     

Important role of genetic drift in rapid polygenic adaptation

We analyzed a model to determine the factors that facilitate or limit rapid polygenic adaptation. This model includes population genetic terms of mutation and both directional and stabilizing selection on a highly polygenic trait in a diploid population of finite size. First, we derived the equilibrium distribution of the allele frequencies of the multilocus model by diffusion approximation. This formula describing the equilibrium allele frequencies as a mutation‐selection‐drift balance was examined by computer simulation using parameter values inferred for human height, a well‐studied polygenic trait. Second, assuming that a sudden environmental shift of the fitness optimum occurs while the population is in equilibrium, we analyzed the adaptation of the trait to the new optimum. The speed at which the trait mean approaches the new optimum increases with the equilibrium genetic variance. Thus, large population size and/or large mutation rate may facilitate rapid adaptation. Third, the contribution of an individual locus i to polygenic adaptation depends on the compound parameter , where is the effect size, the equilibrium frequency of the trait‐increasing allele of this locus, and . Thus, only loci with large values of this parameter contribute coherently to polygenic adaptation. Given that mutation rates are relatively small, this is more likely in large populations, in which the effects of drift are limited.     

Optimizing reduced-space sequence analysis

MOTIVATION: Dynamic programming is the core algorithm of sequence comparison, alignment and linear hidden Markov model (HMM) training. For a pair of sequence lengths m and n, the problem can be solved readily in O(mn)time and O(mn)space. The checkpoint algorithm introduced by Grice et al. (CABIOS, 13, 45--53, 1997) runs in O(Lmn)time and O(Lm(L) square root of n)space, where L is a positive integer determined by m, n, and the amount of available workspace. The algorithm is appropriate for many string comparison problems, including all-paths and single-best-path hidden Markov model training, and is readily parallelizable. The checkpoint algorithm has a diagonal version that can solve the single-best-path alignment problem in O(mn)time and O(m + n)space. RESULTS: In this work, we improve performance by analyzing optimal checkpoint placement. The improved row checkpoint algorithm performs up to one half the computation of the original algorithm. The improved diagonal checkpoint algorithm performs up to 35% fewer computational steps than the original. We modified the SAM hidden Markov modeling package to use the improved row checkpoint algorithm. For a fixed sequence length, the new version is up to 33% faster for all-paths and 56% faster for single-best-path HMM training, depending on sequence length and allocated memory. Over a typical set of protein sequence lengths, the improvement is approximately 10%.     

Animal movement tools (amt): R package for managing tracking data and conducting habitat selection analyses

Advances in tracking technology have led to an exponential increase in animal location data, greatly enhancing our ability to address interesting questions in movement ecology, but also presenting new challenges related to data management and analysis. Step‐selection functions (SSFs) are commonly used to link environmental covariates to animal location data collected at fine temporal resolution. SSFs are estimated by comparing observed steps connecting successive animal locations to random steps, using a likelihood equivalent of a Cox proportional hazards model. By using common statistical distributions to model step length and turn angle distributions, and including habitat‐ and movement‐related covariates (functions of distances between points, angular deviations), it is possible to make inference regarding habitat selection and movement processes or to control one process while investigating the other. The fitted model can also be used to estimate utilization distributions and mechanistic home ranges. Here, we present the R package amt (animal movement tools) that allows users to fit SSFs to data and to simulate space use of animals from fitted models. The amt package also provides tools for managing telemetry data. Using fisher (Pekania pennanti) data as a case study, we illustrate a four‐step approach to the analysis of animal movement data, consisting of data management, exploratory data analysis, fitting of models, and simulating from fitted models.