Using relatedness networks to infer contemporary dispersal: Application to the endangered mammal Galemys pyrenaicus

Information about the degree of contemporary dispersal is important when trying to understand how populations interchange individuals and identify the specific barriers that prevent these movements. In the case of endangered species, this can represent crucial information when designing appropriate conservation strategies. Here we analyse relatedness between individuals from different localities and use these data to infer whether dispersal occurred in recent generations. We applied this approach to the Pyrenean desman (Galemys pyrenaicus), a semiaquatic and endangered species endemic to the Iberian Peninsula. We studied this species in four primary rivers in the Iberian Range, where two ancient mitochondrial lineages are separated by a strict contact zone, suggesting the existence of complex dispersal patterns. Using next‐generation sequencing, we obtained 912 SNPs from each specimen and estimated relatedness values between them. While relatedness networks were dense within each river, we found surprisingly few relationships between individuals from different rivers despite their close proximity in some cases, indicating much lower dispersal between rivers compared to dispersal within a single river. In agreement with this result, the degree of inbreeding was exceedingly high in most individuals. These data show that relatedness information can be crucial to understand the contemporary dispersal patterns and conservation status of specific populations of endangered species.     

The geography of spatial synchrony

Spatial synchrony, defined as correlated temporal fluctuations among populations, is a fundamental feature of population dynamics, but many aspects of synchrony remain poorly understood. Few studies have examined detailed geographical patterns of synchrony; instead most focus on how synchrony declines with increasing linear distance between locations, making the simplifying assumption that distance decay is isotropic. By synthesising and extending prior work, we show how geography of synchrony, a term which we use to refer to detailed spatial variation in patterns of synchrony, can be leveraged to understand ecological processes including identification of drivers of synchrony, a long‐standing challenge. We focus on three main objectives: (1) showing conceptually and theoretically four mechanisms that can generate geographies of synchrony; (2) documenting complex and pronounced geographies of synchrony in two important study systems; and (3) demonstrating a variety of methods capable of revealing the geography of synchrony and, through it, underlying organism ecology. For example, we introduce a new type of network, the synchrony network, the structure of which provides ecological insight. By documenting the importance of geographies of synchrony, advancing conceptual frameworks, and demonstrating powerful methods, we aim to help elevate the geography of synchrony into a mainstream area of study and application.     

Habitat patch size alters the importance of dispersal for species diversity in an experimental freshwater community

Increased dispersal of individuals among discrete habitat patches should increase the average number of species present in each local habitat patch. However, experimental studies have found variable effects of dispersal on local species richness. Priority effects, predators, and habitat heterogeneity have been proposed as mechanisms that limit the effect of dispersal on species richness. However, the size of a habitat patch could affect how dispersal regulates the number of species able to persist. We investigated whether habitat size interacted with dispersal rate to affect the number of species present in local habitats. We hypothesized that increased dispersal rates would positively affect local species richness more in small habitats than in large habitats, because rare species would be protected from demographic extinction. To test the interaction between dispersal rate and habitat size, we factorially manipulated the size of experimental ponds and dispersal rates, using a model community of freshwater zooplankton. We found that high‐dispersal rates enhanced local species richness in small experimental ponds, but had no effect in large experimental ponds. Our results suggest that there is a trade‐off between patch connectivity (a mediator of dispersal rates) and patch size, providing context for understanding the variability observed in dispersal effects among natural communities, as well as for developing conservation and management plans in an increasingly fragmented world.     

Rotifers,the jelly plankton of freshwater

Jelly plankton (gelata) is a rather fuzzy concept that I attempt to redefine and expand: gelata should have no exo or endoskeleton, have a water content of 92–98%, and should usually be somewhat transparent. Although gelata are usually considered as part of the plankton, there are many cases in which they lead a benthic life, permanently or during part of their life. Gelatinous material can be part of the body, or can be secreted to form a sheath around it, especially in freshwater. Size is not a criterion: gelata individuals or colonies can be from 50 μm to 30 m and more in size. Early development stages (eggs and embryos) shed freely in the environment are not considered true gelata, even if enveloped in jelly. Under these conditions, jelly plankton in freshwater is represented by 20–40 species of cnidarians, by a few rhabdocoelid flatworms, and by up to 200 rotifer species (600+ if the periphytic and benthic species are included, and almost 1,500 species if males are included). Contrary to the ocean, where overfishing will benefit gelata, overfishing in freshwater will favor planktonic crustaceans, and these, in turn competitively suppress rotifers. Guest editors: S. S. S. Sarma, R. D. Gulati, R. L. Wallace, S. Nandini, H. J. Dumont and R. Rico-Martínez Advances in Rotifer Research     

Testing the ability of species distribution models to infer variable importance

Models of species’ distributions and niches are frequently used to infer the importance of range- and niche-defining variables. However, the degree to which these models can reliably identify important variables and quantify their influence remains unknown. Here we use a series of simulations to explore how well models can 1) discriminate between variables with different influence and 2) calibrate the magnitude of influence relative to an ‘omniscient’ model. To quantify variable importance, we trained generalized additive models (GAMs), Maxent and boosted regression trees (BRTs) on simulated data and tested their sensitivity to permutations in each predictor. Importance was inferred by calculating the correlation between permuted and unpermuted predictions, and by comparing predictive accuracy of permuted and unpermuted predictions using AUC and the continuous Boyce index. In scenarios with one influential and one uninfluential variable, models failed to discriminate reliably between variables when training occurrences were < 8–64, prevalence was > 0.5, spatial extent was small, environmental data had coarse resolution and spatial autocorrelation was low, or when pairwise correlation between environmental variables was |r| > 0.7. When two variables influenced the distribution equally, importance was underestimated when species had narrow or intermediate niche breadth. Interactions between variables in how they shaped the niche did not affect inferences about their importance. When variables acted unequally, the effect of the stronger variable was overestimated. GAMs and Maxent discriminated between variables more reliably than BRTs, but no algorithm was consistently well-calibrated vis-à-vis the omniscient model. Algorithm-specific measures of importance like Maxent's change-in-gain metric were less robust than the permutation test. Overall, high predictive accuracy did not connote robust inferential capacity. As a result, requirements for reliably measuring variable importance are likely more stringent than for creating models with high predictive accuracy.     

The importance of plankton to Cassin's auklets during breeding

The breeding chronology, food habits, growth and reproductivesuccess of Cassin's Auklets, Ptychoramphus aleuticus, were investigatedon Triangle Island, British Columbia. The breeding of Cassin'sAuklets coincides with the plankton bloom in the eastern NorthPacific. Cassin's Auklets in British Columbia feed their youngmostly large copepods, Calanus cristatus, and euphausiids, chieflyThysanoessa spinifera, but fish was an important food item inone summer. Chicks which hatched early, grew and survived betterthan late-hatched chicks and this may relate to food availability.Adults and chicks on Triangle Island were heavier than thoseon South Farallon Island, California. The heavier weight andgreater numbers of Cassin's Auklets in British Columbia as comparedwith regions to the south may relate to Calanus cristatus availabilityand abundance in northern areas.     

Fitness-dependent dispersal in metapopulations and its consequences for persistence and synchrony

1. We present a novel metapopulation model where dispersal is fitness dependent: the strength of migration from a site is dependent on the expected reproductive fitness of individuals there. Furthermore, individuals continue to migrate until they reach a suitable habitat where their expected fitness is above a threshold value.
2. Fitness-dependent dispersal has a very strong stabilizing effect on population dynamics, even when the intrinsic dynamics of populations in the absence of dispersal exhibit complex high-amplitude oscillations. This stabilizing effect is much stronger than that of the density-independent dispersal normally considered in metapopulation models.
3. Even when fitness-dependent dispersal does not stabilize the dynamics in a formal sense, it generally leads to simplification, with complex or even chaotic fluctuations being reduced to simple cycles.
4. This form of dispersal also has a strong tendency to synchronize local population dynamics across the spatial extent of the metapopulation.
5. These conclusions are robust to the addition of strong stochasticity in the migration threshold.     

Viruses in the plankton of freshwater and saline Antarctic lakes

1. Virus‐like particle (VLP) abundances in nine freshwater to saline lakes in the Vestfold Hills, Eastern Antarctica (68° S) were determined in December 1999. In the ultra‐oligotrophic to oligotrophic freshwater lakes, VLP abundances ranged from 1.01 to 3.28 × 10⁶ mL^–1 in the top 6 m of the water column. In the saline lakes the range was between 6.76 and 36.5 × 10⁶ mL^–1. The lowest value was found in meromictic Ace Lake and the highest value in hypersaline Lake Williams. Virus to bacteria ratios (VBR) were lowest in the freshwater lakes and highest in the saline lakes, with a maximum of 23.4 in the former and 50.3 in the latter. 2. A range of morphologies among VLP was observed, including phages with short (Podoviridae) and long tails, icosahedric viruses of up to 300 nm and star‐like particles of about 80 nm diameter. 3. In these microbially dominated ecosystems there was no correlation between VLP and either bacterial numbers or chlorophyll a. There was a significant correlation between VLP abundances and dissolved organic carbon concentration (r=0.845, P < 0.01). 4. The data suggested that viruses probably attack a spectrum of bacteria and protozoan species. Virus‐like particle numbers in the freshwater lakes were lower than values reported for lower latitude systems. Those in the saline lakes were comparable with abundances reported from other Antarctic lakes, and were higher than most values published for lower latitude lakes and many marine systems. Across the salinity spectrum from freshwater through brackish to hypersaline, VLP concentrations increased roughly in relation to increasing trophy. 5. Given that Antarctic lakes have a plankton almost entirely made up of bacteria and protists, and that VLP abundances are high, it is likely that viruses play a pivotal role in carbon cycling in these extreme ecosystems.     

Using ancient DNA and coalescent-based methods to infer extinction

DNA sequences extracted from preserved remains can add considerable resolution to inference of past population dynamics. For example, coalescent-based methods have been used to correlate declines in some arctic megafauna populations with habitat fragmentation during the last ice age. These methods, however, often fail to detect population declines preceding extinction, most likely owing to a combination of sparse sampling, uninformative genetic markers, and models that cannot account for the increasingly structured nature of populations as habitats decline. As ancient DNA research expands to include full-genome analyses, these data will provide greater resolution of the genomic consequences of environmental change and the genetic signatures of extinction.     

Using approximate Bayesian computation to infer photosynthesis model parameters

We developed a method, namely Adaptive Population Monte Carlo Approximate Bayesian Computation (APMC), to estimate the parameters of Farquhar photosynthesis model. Treating the canopy as a big leaf, we applied this method to derive the parameters at canopy scale. Validations against observational data showed that parameters estimated based on the APMC optimization are un-biased for predicting the photosynthesis rate. We conclude that APMC has greater advantages in estimating the model parameters than those of the conventional nonlinear regression models.     

Multifaceted aspects of synchrony between freshwater prokaryotes and protists

Community composition of freshwater prokaryotes and protists varies through time. Few studies contemporarily investigate temporal variation of these freshwater communities for more than 1 year. We compared the temporal patterns of prokaryotes and protists in three distinct habitats for 4 years (2014–2017) in Lake Tovel, a cold‐water lake. This lake showed a marked temperature increase in 2017 linked to altered precipitation patterns. We investigated whether microbial communities reflected this change across habitats and whether changes occurred at the same time and to the same extent. Furthermore, we tested the concept of hydrological year emphasizing the ecological effect of water renewal on communities for its explanatory power of community changes. Microbe diversity was assessed by Illumina sequencing of the V3–V4 hypervariable region of the 16S rRNA gene and 18S rRNA gene, and we applied co‐inertia analysis and asymmetric eigenvector maps modelling to infer synchrony and temporal patterns of prokaryotes and protists. When considering community composition, microbes were invariable in synchrony across habitats and indicated a temporal gradient linked to decreasing precipitation; however, when looking at temporal patterns, the extent of synchrony was reduced. Small‐scale patterns were similar across habitats and microbes and linked to seasonally varying environmental variables, while large‐scale patterns were different and partially linked to an ecosystem change as indicated by increasing water transparency and temperature and decreasing dissolved oxygen. Our advanced statistical approach outlined the multifaceted aspect of synchrony when linked to community composition and temporal patterns.     

Using biological assemblage composition to infer the values of covarying environmental factors

1. Observations of different organisms can often be used to infer environmental conditions at a site. These inferences may be useful for diagnosing the causes of degradation in streams and rivers. 2. When used for diagnosis, biological inferences must not only provide accurate, unbiased predictions of environmental conditions, but also pairs of inferred environmental variables must covary no more strongly than actual measurements of those same environmental variables. 3. Mathematical analysis of the relationship between the measured and inferred values of different environmental variables provides an approach for comparing the covariance between measurements with the covariance between inferences. Then, simulated and field‐collected data are used to assess the performance of weighted average and maximum likelihood inference methods. 4. Weighted average inferences became less accurate as covariance in the calibration data increased, whereas maximum likelihood inferences were unaffected by covariance in the calibration data. In contrast, the accuracy of weighted average inferences was unaffected by changes in measurement error, whilst the accuracy of maximum likelihood inferences decreased as measurement error increased. Weighted average inferences artificially increased the covariance of environmental variables beyond what was expected from measurements, whereas maximum likelihood inference methods more accurately reproduced the expected covariances. 5. Multivariate maximum likelihood inference methods can potentially provide more useful diagnostic information than single variable inference models.     

Larval dispersal of intertidal organisms and the influence of coastline geography

The dispersal stages of organisms with sessile adults must be able to select habitats with suitable environmental conditions for establishment and survival, and also must be able to reach those locations. For marine planktonic larvae, movement due to currents is often orders of magnitude greater than movement due to swimming behaviour. Current patterns are determined by interactions between underlying geography and tidal forces, modified by meteorological conditions. These linkages impose an area‐specific focus to connectivity studies. Yet, how geographical features and meteorological forcing combine to produce specific current patterns and resultant connectivity among populations remains unclear. In this study of a complex fjordic region (the Firth of Lorn, Scotland), we followed tracks of generic particles driven by modelled hydrodynamic currents to investigate how connectivity between evenly spaced habitat sites varies in relation to coastal topography. We studied a range of larval durations (1–28 d), and two different but typical meteorological forcing scenarios. Particles released from regions of high current velocity, open coastline and low local habitat availability travelled furthest but were less likely to disperse successfully to other coastal sites. Extensive natal habitat in the vicinity of a site generally had a positive impact on the number of arriving particles, as did low current velocities. However, relationships between numbers of arriving particles and local geographical indices were complex, particularly at longer larval durations. Local geography alone explained up to 50% of the variance in success of particles released and closer to 10% of the variation in the number of particles arriving at each site. General patterns are evident, but coastline properties fall short of predicting dispersal measures for particular locations. The study shows that meteorological variation and broad scale current patterns interact strongly with local geography to determine connectivity in coastal areas.     

The plankton of a large oligotrophic freshwater Antarctic lake

The planktonic community of Crooked Lake, a large freshwaterlake in the Vestfold Hills, Antarctica was investigated duringthe austral summer in 1990. Very low levels of chlorophyll aranging between mean values of 0 29 and 1.8 µl^–1were recorded. The phytoplankton was largely made up of colouredflagellates, including single species of Chlamydomonas, Ochromonasand Pendimum, which occurred in low concentrations (23.8x 10²–47.3x10² l^–1). Heterotrophic colourless flagellates, includingParaphysomonas vestita, were also relatively sparse (2.1x 10²–21.3x10²l^–1). Ciliated protozoans were particularly poorly represented.Only three species occurred reaching densities of 1001^–1,and among them the mixotrophic species Strombidium vinde wasthe most common. A single species of heliozoan Actinosphaeriumand relatively large numbers of naked amoebae were the sarcodinerepresentatives The protistan community and the bacteria wereconcentrated into microbial consortia associated with floesof paniculate organic matter probably derived from the benthicalgal mat. Of the two microcrustacean zooplankters recordedfrom the lake only Daphniopsis studeri was found breeding inthe plankton in very low numbers. The behavioural and physiologicaladaptations of the organisms inhabiting this extremely oligotrophicenvironment are discussed.     

A new hypothesis for the importance of seed dispersal in time

Most studies on seed dispersal in time have focused on seed dormancy and the physiological triggers for germination. However, seed dispersed by animals with low metabolic and moving rates, and long gut-passage times such as terrestrial turtles, could be considered another type of dispersal in time. This study tests the hypothesis that seeds dispersed in time may lower predation rates. We predicted that seeds deposited below parent trees after fruiting fall has finished is advantageous to minimize seed predators and should show higher survival rates. Four Amazonian plant species, Dicranostyles ampla, Oenocarpus bataua, Guatteria atabapensis and Ocotea floribunda, were tested for seed survival probabilities in two periods: during fruiting and 10-21 days after fruiting. Experiments were carried out in two biological stations located in the Colombian Amazon (Caparú and Zafire Biological Stations). Seed predation was high and mainly caused by non-vertebrates. Out of the four plant species tested, only Guatteria atabapensis supported the time escape hypothesis. For this species, seed predation by vertebrates after the fruiting period increased (from 4.1% to 9.2%) while seed predation by non-vertebrates decreased (from 54.0% to 40.2%). In contrast, seed predation by vertebrates and by non-vertebrates after the fruiting period in D. ampla increased (from 7.9% to 22.8% and from 40.4% to 50.6%, respectively), suggesting predator satiation. Results suggest that for some species dispersal in time could be advantageous to avoid some type of seed predators. Escape in time could be an additional dimension in which seeds may reach adequate sites for recruitment. Thus, future studies should be address to better understand the survival advantages given by an endozoochory time-dispersal process.     

Using genome scans of DNA polymorphism to infer adaptive population divergence

Elucidating the genetic basis of adaptive population divergence is a goal of central importance in evolutionary biology. In principle, it should be possible to identify chromosomal regions involved in adaptive divergence by screening genome-wide patterns of DNA polymorphism to detect the locus-specific signature of positive directional selection. In the case of spatially separated populations that inhabit different environments or sympatric populations that exploit different ecological niches, it is possible to identify loci that underlie divergently selected traits by comparing relative levels of differentiation among large numbers of unlinked markers. In this review I first address the question of whether diversifying selection on polygenic traits can be expected to produce predictable patterns of allelic variation at the underlying quantitative trait loci (QTL), and whether the locus-specific effects of selection can be reliably detected against the genome-wide backdrop of stochastic variability. I then review different approaches that have been developed to identify loci involved in adaptive population divergence and I discuss the relative merits of model-based approaches that rely on assumptions about population structure vs. model-free approaches that are based on empirical distributions of summary statistics. Finally, I consider the evolutionary and functional insights that might be gained by conducting genome scans for loci involved in adaptive population divergence.