Spatio-temporal Population Dynamics Research Articles

Inter- and intra-host sequence diversity reveal the emergence of viral variants during an overwintering epidemic caused by dengue virus serotype 2 in southern Taiwan.

Purifying selection during dengue viral infection has been suggested as the driving force of viral evolution and the higher complexity of the intra-host quasi-species is thought to offer an adaptive advantage for arboviruses as they cycle between arthropod and vertebrate hosts. However, very few studies have been performed to investigate the viral genetic changes within (intra-host) and between (inter-host) humans in a spatio-temporal scale. Viruses of different serotypes from various countries imported to Taiwan cause annual outbreaks. During 2001–2003, two consecutive outbreaks were caused by dengue virus serotype 2 (DENV-2) and resulted in a larger-scale epidemic with more severe dengue cases in the following year. Phylogenetic analyses showed that the viruses from both events were similar and related to the 2001 DENV-2 isolate from the Philippines. We comprehensively analyzed viral sequences from representative dengue patients and identified three consensus genetic variants, group Ia, Ib and II, with different spatio-temporal population dynamics. The phylodynamic analysis suggested group Ib variants, characterized by lower genetic diversity, transmission rate, and intra-host variant numbers, might play the role of maintenance variants. The residential locations among the patients infected by group Ib variants were in the outer rim of case clusters throughout the 2001–2003 period whereas group Ia and II variants were located in the centers of case clusters, suggesting that group Ib viruses might serve as “sheltered overwintering” variants in an undefined ecological niche. Further deep sequencing of the viral envelope (E) gene directly from individual patient serum samples confirmed the emergence of variants belonging to three quasi-species (group Ia, Ib, and II) and the ancestral role of the viral variants in the latter phase of the 2001 outbreak contributed to the later, larger-scale epidemic beginning in 2002. These findings enhanced our understanding of increasing epidemic severity over time in the same epidemic area. It also highlights the importance of combining phylodynamic and deep sequencing analysis as surveillance tools for detecting dynamic changes in viral variants, particularly searching for and monitoring any specific viral subpopulation. Such subpopulations might have selection advantages in both fitness and transmissibility leading to increased epidemic severity.

Spatiotemporal dynamics of Lutzomyia longipalpis and macro-habitat characterization using satellite images in a leishmaniasis-endemic city in Argentina.

The spatiotemporal population dynamics of Lutzomyia longipalpis (Lutz & Neiva, 1912) (Diptera: Psychodidae) were evaluated in a city in Argentina in which visceral leishmaniasis is endemic. Over 14 sampling sessions, 5244 specimens of five species of Phlebotominae (Diptera: Psychodidae) were captured, of which 2458 (46.87%) specimens were L. longipalpis. Generalized linear models were constructed to evaluate the associations between L. longipalpis abundance and explanatory variables derived from satellite images. The spatial variable 'stratum' and the temporal variable 'season' were also included in the models. Three variables were found to have significant associations: the normalized difference vegetation index; land surface temperature, and low urban coverage. The last two of these were associated with L. longipalpis abundance only during summer and winter, respectively. This variation between seasons supports the development of models that include temporal variables because models of distributions of the abundance of a species may show different critical variables according to the climatic period of the year. Abundance decreased gradually towards the downtown area, which suggests that L. longipalpis responds to a meta-population structure, in which rural-periurban source populations that persist over time may colonize adjacent areas. This information allows for a spatiotemporal stratification of risk, which provides public health authorities with a valuable tool to help optimize prevention measures against visceral leishmaniasis.

Analysis of land use/land cover spatio-temporal metrics and population dynamics for urban growth characterization

Promoting sustainable urbanization and limiting land consumption is a local and regional priority policy target in Europe. Monitoring and quantifying urban growth supports decision-making processes for the prevention of ecological and socio-economic consequences. In this work, we present a methodology based on spatio-temporal metrics and a new index (PUGI), that quantifies the inequality of growth between population and urban areas, to analyze and compare urban growth patterns at different levels. We computed an exhaustive set of spatio-temporal metrics at local level in a testing sample of six urban areas from the Urban Atlas database, then uncorrelated metrics were selected and the data were interpreted at various levels. Results allow for a differentiation of growing patterns, discriminating between compact and sprawl trends. The index proposed complements the analysis by including demographic dynamics, being also useful for assessing the growing imbalance between the progression on residential areas and the population change at local level. The analysis at various levels contributes to a better understanding of urban growth patterns and its relation to sustainable policies not only within urban areas, but also for the comparison across Europe.

Spatio-temporal dynamics of Codium populations along the rocky shores of N and NW Spain

The green alga Codium fragile ssp. fragile (hereafter C. fragile) has long been assumed to outcompete and displace its native congeners via cryptic invasion. We analysed the population dynamics of the exotic C. fragile and native congeners and their relative abundance on intertidal shores in N-NW Spain. Our results did not support the existence of current competitive displacement by the exotic species. The presence of C. fragile was clearly seasonal, while the native C. tomentosum was more persistent throughout the year, due to a higher frequency of frond sprouting from perennial basal fragments. However, our results also indicated an increase in the proportion of C. fragile relative to native species towards inner areas of the Bay of Biscay, which was correlated with environmental gradients. The greater tolerance of C. fragile to environmental stress and its opportunistic abilities may favour establishment and spread of the species under a warming scenario.

Population and evolutionary dynamics in spatially structured seasonally varying environments.

ABSTRACTIncreasingly imperative objectives in ecology are to understand and forecast population dynamic and evolutionary responses to seasonal environmental variation and change. Such population and evolutionary dynamics result from immediate and lagged responses of all key life‐history traits, and resulting demographic rates that affect population growth rate, to seasonal environmental conditions and population density. However, existing population dynamic and eco‐evolutionary theory and models have not yet fully encompassed within‐individual and among‐individual variation, covariation, structure and heterogeneity, and ongoing evolution, in a critical life‐history trait that allows individuals to respond to seasonal environmental conditions: seasonal migration. Meanwhile, empirical studies aided by new animal‐tracking technologies are increasingly demonstrating substantial within‐population variation in the occurrence and form of migration versus year‐round residence, generating diverse forms of ‘partial migration’ spanning diverse species, habitats and spatial scales. Such partially migratory systems form a continuum between the extreme scenarios of full migration and full year‐round residence, and are commonplace in nature.Here, we first review basic scenarios of partial migration and associated models designed to identify conditions that facilitate the maintenance of migratory polymorphism. We highlight that such models have been fundamental to the development of partial migration theory, but are spatially and demographically simplistic compared to the rich bodies of population dynamic theory and models that consider spatially structured populations with dispersal but no migration, or consider populations experiencing strong seasonality and full obligate migration. Second, to provide an overarching conceptual framework for spatio‐temporal population dynamics, we define a ‘partially migratory meta‐population’ system as a spatially structured set of locations that can be occupied by different sets of resident and migrant individuals in different seasons, and where locations that can support reproduction can also be linked by dispersal. We outline key forms of within‐individual and among‐individual variation and structure in migration that could arise within such systems and interact with variation in individual survival, reproduction and dispersal to create complex population dynamics and evolutionary responses across locations, seasons, years and generations. Third, we review approaches by which population dynamic and eco‐evolutionary models could be developed to test hypotheses regarding the dynamics and persistence of partially migratory meta‐populations given diverse forms of seasonal environmental variation and change, and to forecast system‐specific dynamics. To demonstrate one such approach, we use an evolutionary individual‐based model to illustrate that multiple forms of partial migration can readily co‐exist in a simple spatially structured landscape. Finally, we summarise recent empirical studies that demonstrate key components of demographic structure in partial migration, and demonstrate diverse associations with reproduction and survival. We thereby identify key theoretical and empirical knowledge gaps that remain, and consider multiple complementary approaches by which these gaps can be filled in order to elucidate population dynamic and eco‐evolutionary responses to spatio‐temporal seasonal environmental variation and change.

Bayesian spatiotemporal dynamic models for regional dynamics of avian populations

The spatiotemporal dynamics of multiple animal populations may exhibit the hierarchical dynamic patterns including regional common trends or spatial synchrony and local variability. Environmental drivers such as climatic variability, operating on large spatial scales, have been proposed to be a driver of the spatial synchrony of avian and mammalian populations (i.e., the Moran effect). On the other hand, demographic responses to heterogeneous, local environments may result in substantial local population variability (i.e., variance across multiple populations). This study used the Bayesian hierarchical spatiotemporal dynamic model to determine the spatiotemporal dynamic patterns of 27 eastern wild turkey (Meleagris gallopavo silvestris) populations scattered across Mississippi, USA, from 1994 to 2005. The regional effects of seasonal climate and relative amount of forest in habitats were also evaluated to test the Moran effect. Twenty seven wild turkey populations had a spatial synchrony with the strength and spatial scale similar to those of other avian populations in North America. Warming spring or spring-autumn climate appeared to reduce wild turkey relative abundance; however, winter climate did not influence the dynamics of wild turkey populations in Mississippi. Average proportion of forest affected the average relative abundance of wild turkeys in a nonlinear manner, with its positive effects switching to a lessened constant effect beyond the threshold of 60% forest cover. However, regional climatic variability was unlikely to synchronize wild turkey populations in Mississippi. This study proposed a hypothesis concerning regional habitat quality degradation, which may cause regional population declines and synchronize the dynamics of animal populations.

Sea scallops exhibit strong local spatiotemporal structure associated with seabed stability and high flows

AbstractSea scallops (Placopecten magellanicus) live along the Northwest Atlantic continental shelf and are aggregated over a broad range of spatial scales (m2–105 km2). However, little is known about the spatial distribution of local scallop neighborhoods, the scale at which spawning, intra‐specific competition, and predator–prey interactions occur. We surveyed 30,995 km2 of Georges Bank and the Great South Channel annually from 2003 to 2010 counting the number of scallops in 54,016 locally replicated 3.24‐m2 quadrats with underwater video. There were about 4 billion scallops occupying 11,200 km2 of the study area in concentrations from 1 to 41 scallops per scallop. Scallop spatial distribution switched from dispersed to aggregated at a concentration of 3–4 scallops in every year. High concentrations (>3) occurred in 11% but were only persistent in 4% (449 km2) of scallop habitat. There were 13 persistent high‐concentration aggregations (7–217 km2), and all but two occurred on gravel‐dominated sediments left by prehistoric glacial retreat. Model‐derived benthic boundary shear stresses in the persistent aggregations averaged two times higher than in scallop habitat, but the seabed was about two times more stable because it had significantly less sand and more granule–pebble and cobble sediment. The area occupied by scallops each year varied little (9%) despite a 49% increase in total scallop abundance between 2005 and 2007, suggesting Georges Bank scallops have a proportional density population structure. Most scallops occurred alone or at low concentrations (≤2) where fertilization success is probably poor. The persistent high‐concentration aggregations we identified may be critical for successful reproduction and sustainable harvest. Observing organisms at scales corresponding to their individual interactions reveals important processes shaping their landscape‐scale spatiotemporal distributions. These processes are obscured by the methods typically employed to estimate abundances of commercial fishery species. The spatiotemporal structure of sea scallop distribution has important implications for the design of abundance surveys and the assumptions underlying stock assessment methods. These should be investigated. Finally, this work suggests that natural disturbance (sediment stability) may play a substantial role in shaping spatiotemporal distributions and dynamics of benthic marine populations.

Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records

AbstractUnderstanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time‐series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log‐linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub‐district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation.

Density-independent and density-dependent factors affecting spatio-temporal dynamics of Atlantic cod (Gadus morhua) distribution in the Gulf of Maine

Abstract Due to strong spatial interplays between intraspecific interactions and environmental forcing, both density-dependent and density-independent processes can affect spatio-temporal dynamics of fish populations in a spatially explicit fashion. To this end, this study investigated the underlying mechanisms of spatio-temporal dynamics of Atlantic cod (Gadus morhua) in the Gulf of Maine (GoM). Based on the data from the Northeast Fisheries Science Center (NEFSC) bottom-trawl surveys in spring and fall from 1982 to 2013, empirical cumulative distribution function (ECDF) curves and geographic distribution indices were used to examine the species–environment and abundance–occupancy relationship, respectively. Then, a variable-coefficient generalized additive model was constructed to quantify the simultaneous effects of environmental variables and population size on the spatio-temporal dynamics of cod distribution. Area occupied remained relatively high through the late 1990s, but underwent a pronounced contraction into the western GoM (WGoM) for the reminder of the time-series. The model results suggest that the spatio-temporal dynamics of GoM cod have been driven by complex interactions of density-dependent and density-independent factors over the past three decades. Better knowledge of these dynamics can improve our understanding of the causality of abundance–occupancy and species–environment relationships and help to reduce error estimates for survey-based indices.

Spatiotemporal dynamics of mesocarnivore populations

Mammalian mesocarnivores play critical roles in ecosystems via trophic interactions. The fluctuation of mesocarnivore abundance may cause trophic cascading throughout the ecosystems. However, little was known about density dependence and spatiotemporal dynamics of mesocarnivore populations. Northern raccoon Procyon lotor is a common mammalian mesocarnivore in North America, and is the host of many human infectious diseases. Few studies have investigated density dependence and hierarchical spatiotemporal dynamics of raccoon populations. We used 23‐year time series of raccoon relative abundance from 14 wildlife management areas in Mississippi, USA, to test for spatial synchrony of raccoon populations with nonparametric correlation functions. We developed non‐Gaussian state space models to detect density dependence of raccoon populations, and also used dynamic factor analysis (DFA) to determine the structure of the spatiotemporal dynamics of raccoon populations. The 14 raccoon populations lacked common trends, and were not synchronized. Strength of density dependence varied among raccoon populations, but was not related to the amount of hardwood forests. Differences in the structure of density dependence probably prevented populations from being synchronize by climatic variability. The raccoon populations exhibited greater local or idiosyncratic variability than regional variability in Mississippi. Northern raccoons have plastic life history traits permitting their population dynamics to closely track local variations in resource availability.

Modelling the effects of habitat and hosts on tick invasions

AbstractMany tick species are invading new areas because of anthropogenic changes in the landscape, shifting climatic variables and increasing populations of suitable host species and tick habitat. However, the relative influences of habitat and hosts in tick dispersal and tick population establishment remain in question. A spatially explicit agent-based model was developed to explore the spatio-temporal dynamics of a generic tick population in the years immediately following the introduction of ticks into a novel environment. The general model was then adapted to investigate a case study of two recent tick species invasions into the Mid-Atlantic United States. The recent simultaneous range expansions of two ixodid tick species, Ixodes affinis and Amblyomma maculatum, provided an opportunity to determine if invasion patterns observed in the field could be replicated in silico on a small scale. The models presented here indicated that for generalist parasites, habitat connectivity is a better indicator tha...

Investigating population continuity with ancient DNA under a spatially explicit simulation framework

BackgroundRecent advances in sequencing technologies have allowed for the retrieval of ancient DNA data (aDNA) from skeletal remains, providing direct genetic snapshots from diverse periods of human prehistory. Comparing samples taken in the same region but at different times, hereafter called “serial samples”, may indicate whether there is continuity in the peopling history of that area or whether an immigration of a genetically different population has occurred between the two sampling times. However, the exploration of genetic relationships between serial samples generally ignores their geographical locations and the spatiotemporal dynamics of populations. Here, we present a new coalescent-based, spatially explicit modelling approach to investigate population continuity using aDNA, which includes two fundamental elements neglected in previous methods: population structure and migration. The approach also considers the extensive temporal and geographical variance that is commonly found in aDNA population samples.ResultsWe first showed that our spatially explicit approach is more conservative than the previous (panmictic) approach and should be preferred to test for population continuity, especially when small and isolated populations are considered. We then applied our method to two mitochondrial datasets from Germany and France, both including modern and ancient lineages dating from the early Neolithic. The results clearly reject population continuity for the maternal line over the last 7500 years for the German dataset but not for the French dataset, suggesting regional heterogeneity in post-Neolithic migratory processes.ConclusionsHere, we demonstrate the benefits of using a spatially explicit method when investigating population continuity with aDNA. It constitutes an improvement over panmictic methods by considering the spatiotemporal dynamics of genetic lineages and the precise location of ancient samples. The method can be used to investigate population continuity between any pair of serial samples (ancient-ancient or ancient-modern) and to investigate more complex evolutionary scenarios. Although we based our study on mitochondrial DNA sequences, diploid molecular markers of different types (DNA, SNP, STR) can also be simulated with our approach. It thus constitutes a promising tool for the analysis of the numerous aDNA datasets being produced, including genome wide data, in humans but also in many other species.

Quantitative label-free single cell tracking in 3D biomimetic matrices

Live cell imaging enables an observation of cell behavior over a period of time and is a growing field in modern cell biology. Quantitative analysis of the spatio-temporal dynamics of heterogeneous cell populations in three-dimensional (3D) microenvironments contributes a better understanding of cell-cell and cell-matrix interactions for many biomedical questions of physiological and pathological processes. However, current live cell imaging and analysis techniques are frequently limited by non-physiological 2D settings. Furthermore, they often rely on cell labelling by fluorescent dyes or expression of fluorescent proteins to enhance contrast of cells, which frequently affects cell viability and behavior of cells. In this work, we present a quantitative, label-free 3D single cell tracking technique using standard bright-field microscopy and affordable computational resources for data analysis. We demonstrate the efficacy of the automated method by studying migratory behavior of a large number of primary human macrophages over long time periods of several days in a biomimetic 3D microenvironment. The new technology provides a highly affordable platform for long-term studies of single cell behavior in 3D settings with minimal cell manipulation and can be implemented for various studies regarding cell-matrix interactions, cell-cell interactions as well as drug screening platform for primary and heterogeneous cell populations.

Population Dynamics of Early Visual Cortex during Working Memory.

Although the content of working memory (WM) can be decoded from the spatial patterns of brain activity in early visual cortex, how populations encode WM representations remains unclear. Here, we address this limitation by using a model-based approach that reconstructs the feature encoded by population activity measured with fMRI. Using this approach, we could successfully reconstruct the locations of memory-guided saccade goals based on the pattern of activity in visual cortex during a memory delay. We could reconstruct the saccade goal even when we dissociated the visual stimulus from the saccade goal using a memory-guided antisaccade procedure. By comparing the spatiotemporal population dynamics, we find that the representations in visual cortex are stable but can also evolve from a representation of a remembered visual stimulus to a prospective goal. Moreover, because the representation of the antisaccade goal cannot be the result of bottom-up visual stimulation, it must be evoked by top-down signals presumably originating from frontal and/or parietal cortex. Indeed, we find that trial-by-trial fluctuations in delay period activity in frontal and parietal cortex correlate with the precision with which our model reconstructed the maintained saccade goal based on the pattern of activity in visual cortex. Therefore, the population dynamics in visual cortex encode WM representations, and these representations can be sculpted by top-down signals from frontal and parietal cortex.

Phase and antigenic variation govern competition dynamics through positioning in bacterial colonies

Cellular positioning towards the surface of bacterial colonies and biofilms can enhance dispersal, provide a selective advantage due to increased nutrient and space availability, or shield interior cells from external stresses. Little is known about the molecular mechanisms that govern bacterial positioning. Using the type IV pilus (T4P) of Neisseria gonorrhoeae, we tested the hypothesis that the processes of phase and antigenic variation govern positioning and thus enhance bacterial fitness in expanding gonococcal colonies. By independently tuning growth rate and T4P-mediated interaction forces, we show that the loss of T4P and the subsequent segregation to the front confers a strong selective advantage. Sequencing of the major pilin gene of the spatially segregated sub-populations and an investigation of the spatio-temporal population dynamics was carried out. Our findings indicate that pilin phase and antigenic variation generate a standing variation of pilin sequences within the inoculation zone, while variants associated with a non-piliated phenotype segregate to the front of the growing colony. We conclude that tuning of attractive forces by phase and antigenic variation is a powerful mechanism for governing the dynamics of bacterial colonies.

Year-to-year variation in the density of Ixodes ricinus ticks and the prevalence of the rodent-associated human pathogens Borrelia afzelii and B. miyamotoi in different forest types

The human pathogens Borrelia afzelii, which causes Lyme borreliosis and B. miyamotoi, which causes relapsing fever, both circulate between Ixodes ricinus ticks and rodents. The spatiotemporal dynamics in the prevalence of these pathogens have not yet been fully elucidated, but probably depend on the spatiotemporal population dynamics of small rodents. We aimed to evaluate the effect of different forest types on the density of infected nymphs in different years and to obtain more knowledge about the spatial and temporal patterns of ticks and tick-borne pathogens. We analysed unfed nymphal ticks from 22 stands of four different forest types in Belgium in 2009, 2010, 2013 and 2014 and found that the density of nymphs in general and the density of nymphs infected with B. afzelii and B. miyamotoi varied yearly, but without temporal variation in the infection prevalence. The yearly variation in density of infected nymphs in our study thus seems to be caused most by the variation in the density of nymphs, which makes it a good predictor of disease risk. The risk for rodent-associated tick-borne diseases also varied between forest types. We stress the need to elucidate the contribution of the host community composition to tick-borne disease risk.

Nkx2.5 marks angioblasts that contribute to hemogenic endothelium of the endocardium and dorsal aorta.

Novel regenerative therapies may stem from deeper understanding of the mechanisms governing cardiovascular lineage diversification. Using enhancer mapping and live imaging in avian embryos, and genetic lineage tracing in mice, we investigated the spatio-temporal dynamics of cardiovascular progenitor populations. We show that expression of the cardiac transcription factor Nkx2.5 marks a mesodermal population outside of the cardiac crescent in the extraembryonic and lateral plate mesoderm, with characteristics of hemogenic angioblasts. Extra-cardiac Nkx2.5 lineage progenitors migrate into the embryo and contribute to clusters of CD41+/CD45+ and RUNX1+ cells in the endocardium, the aorta-gonad-mesonephros region of the dorsal aorta and liver. We also demonstrated that ectopic expression of Nkx2.5 in chick embryos activates the hemoangiogenic gene expression program. Taken together, we identified a hemogenic angioblast cell lineage characterized by transient Nkx2.5 expression that contributes to hemogenic endothelium and endocardium, suggesting a novel role for Nkx2.5 in hemoangiogenic lineage specification and diversification.

Nonlinear amplitude dynamics in flagellar beating.

The physical basis of flagellar and ciliary beating is a major problem in biology which is still far from completely understood. The fundamental cytoskeleton structure of cilia and flagella is the axoneme, a cylindrical array of microtubule doublets connected by passive cross-linkers and dynein motor proteins. The complex interplay of these elements leads to the generation of self-organized bending waves. Although many mathematical models have been proposed to understand this process, few attempts have been made to assess the role of dyneins on the nonlinear nature of the axoneme. Here, we investigate the nonlinear dynamics of flagella by considering an axonemal sliding control mechanism for dynein activity. This approach unveils the nonlinear selection of the oscillation amplitudes, which are typically either missed or prescribed in mathematical models. The explicit set of nonlinear equations are derived and solved numerically. Our analysis reveals the spatio-temporal dynamics of dynein populations and flagellum shape for different regimes of motor activity, medium viscosity and flagellum elasticity. Unstable modes saturate via the coupling of dynein kinetics and flagellum shape without the need of invoking a nonlinear axonemal response. Hence, our work reveals a novel mechanism for the saturation of unstable modes in axonemal beating.

Influence of sampling frequency on detectability of fish community and fish species in a fishery-independent survey

Understanding the dynamics and regulation of a particular ecological process requires monitoring of the process at appropriate spatial and temporal scales. Information collected at an inappropriate spatio-temporal scale may be insufficient for capturing spatio-temporal dynamics of fish populations and community. In this study, a Monte Carlo method was developed to evaluate the detectability performances of different sampling frequencies, sampling timings and sampling intensities on fish community indices and fish species. Species richness indices tended to decrease with an increased sampling frequency, while species diversity indices had small changes in response to changes in sampling frequency. The diversity index was more likely to be influenced by the choice of sampling timing compared to the richness index. The total number of species, especially seasonal and rare species present in the simulated sampling, increased with sampling frequency. Although sampling frequency is more important than sampling intensity, sampling intensity is also important for the detectability of fish species. This study showed that sampling frequency and intensity could greatly influence the estimation of fish community. Choices of sampling timing, sampling frequency and intensity may result in different estimates of fish species compositions and community structure. It is very necessary to consider the importance of sufficient sampling frequency and intensity in a survey program.

Spatio-temporal dynamics of a fish predator: Density-dependent and hydrographic effects on Baltic Sea cod population.

Understanding the mechanisms of spatial population dynamics is crucial for the successful management of exploited species and ecosystems. However, the underlying mechanisms of spatial distribution are generally complex due to the concurrent forcing of both density-dependent species interactions and density-independent environmental factors. Despite the high economic value and central ecological importance of cod in the Baltic Sea, the drivers of its spatio-temporal population dynamics have not been analytically investigated so far. In this paper, we used an extensive trawl survey dataset in combination with environmental data to investigate the spatial dynamics of the distribution of the Eastern Baltic cod during the past three decades using Generalized Additive Models. The results showed that adult cod distribution was mainly affected by cod population size, and to a minor degree by small-scale hydrological factors and the extent of suitable reproductive areas. As population size decreases, the cod population concentrates to the southern part of the Baltic Sea, where the preferred more marine environment conditions are encountered. Using the fitted models, we predicted the Baltic cod distribution back to the 1970s and a temporal index of cod spatial occupation was developed. Our study will contribute to the management and conservation of this important resource and of the ecosystem where it occurs, by showing the forces shaping its spatial distribution and therefore the potential response of the population to future exploitation and environmental changes.