Long transient response of vegetation dynamics after four millennia of anthropogenic impacts in an island ecosystem

Agents of global change commonly have a higher impact on island ecosystem dynamics. In the Mediterranean region, those dynamics have historically been influenced by anthropogenic impacts, for example, the introduction of invasive species and overharvesting of resources. Here, we analysed the spatio-temporal dynamics of vegetation in sa Dragonera island, which experienced a large environmental change ca. 4000 years ago by the arrival of humans. Anthropogenic impacts, such as herbivory by goats and over-logging, ended in the 1970s, while in 2011 the site became the largest Mediterranean island where rats were eradicated. Invasive rats and goats played the ecological role of two endemic species, the cave goat and the giant dormouse, which inhabited the island for more than 5 million years and were rapidly extinct by humans. We used Landsat imagery to explore NDVI as a proxy of vegetation productivity over the years 1984-2021, orthophotos to assess changes in land and vegetation covers and historical plant inventories to study the dynamics in plant diversity. Results showed that those indicators steadily increased both in spring and in summer, while the noise around the trends was partially explained by climate variability. The regime shifts in the temporal dynamics of vegetation productivity suggested a transient from a perturbed to a non-perturbed stable state. Trends in successional dynamics, spatial self-organization and plant diversity also showed the same type of transient dynamics. Historical perturbations related to harvesting (mainly the synergies between goat browsing, burning and forest over-logging) were more important than rat eradication or the influence of climate to explain the vegetation dynamics. Our study shows the transient nature of this small island ecosystem after 4000 years of perturbations and its current path towards vegetation dynamics more controlled by ecological interactions lacking large herbivores and omnivores, drought dynamics and the carrying capacity of the island.

Overlap between dengue, Zika and chikungunya hotspots in the city of Rio de Janeiro

Background

Arboviruses represent a threat to global public health. In the Americas, the dengue fever is endemic. This situation worsens with the introduction of emerging, Zika fever and chikungunya fever, causing epidemics in several countries within the last decade. Hotspot analysis contributes to understanding the spatial and temporal dynamics in the context of co-circulation of these three arboviral diseases, which have the same vector: Aedes aegypti.

Objective

To analyze the spatial distribution and agreement between the hotspots of the historical series of reported dengue cases from 2000 to 2014 and the Zika, chikungunya and dengue cases hotspots from 2015 to 2019 in the city of Rio de Janeiro.

Methods

To identify hotspots, Gi* statistics were calculated for the annual incidence rates of reported cases of dengue, Zika, and chikungunya by neighborhood. Kendall’s W statistic was used to analyze the agreement between diseases hotspots.

Results

There was no agreement between the hotspots of the dengue fever historical series (2000–2014) and those of the emerging Zika fever and chikungunya fever (2015–2019). However, there was agreement between hotspots of the three arboviral diseases between 2015 and 2019.

Conclusion

The results of this study show the existence of persistent hotspots that need to be prioritized in public policies for the prevention and control of these diseases. The techniques used with data from epidemiological surveillance services can help in better understanding of the dynamics of these diseases wherever they circulate in the world.

Environmental drivers of recruitment in a tropical fishery: Monsoonal effects and vulnerability to water abstraction

Fisheries and natural water resources across the world are under increasing pressure from human activity, including fishing and irrigated agriculture. There is an urgent need for information on the climatic/hydrologic drivers of fishery productivity that can be readily applied to management. We use a generalized linear mixed model framework of catch curve regression to resolve the key climatic/hydrological drivers of recruitment in Barramundi Lates calcarifer using biochronological (otolith aging) data collected from four river-estuary systems in the Northern Territory, Australia. These models were then used to generate estimates of the year class strength (YCS) outcomes of different water abstraction scenarios (ranging from 10% to 40% abstraction per season/annum) for two of the rivers in low, moderate, and high discharge years. Barramundi YCS displayed strong interannual variation and was positively correlated with regional monsoon activity in all four rivers. River-specific analyses identified strong relationships between YCS and several river-specific hydrology variables, including wet and dry season discharge and flow duration. Water abstraction scenario models based on YCS-hydrology relationships predicted reductions of >30% in YCS in several cases, suggesting that increased water resource development in the future may pose risks for Barramundi recruitment and fishery productivity. Our study demonstrates the importance of the tropical monsoon as a driver of Barramundi recruitment and the potential for detrimental impacts of increased water abstraction on fishery productivity. The biochronological and statistical approaches we used have the potential to be broadly applied to inform policy and management of water resource and fisheries.

High-Resolution Transect Sampling and Multiple Scale Diversity Analyses for Evaluating Grassland Resilience to Climatic Extremes

Diversity responses to climatic factors in plant communities are well understood from experiments, but less known in natural conditions due to the rarity of appropriate long-term observational data. In this paper, we use long-term transect data sampled annually in three natural grasslands of different species pools, soils, landscape contexts and land use histories. Analyzing these specific belt transect data of contiguous small sampling units enabled us to explore scale dependence and spatial synchrony of diversity patterns within and among sites. The 14-year study period covered several droughts, including one extreme event between 2011 and 2012. We demonstrated that all natural grasslands responded to droughts by considerable fluctuations of diversity, but, overall, they remained stable. The plant functional group of annuals showed high resilience at all sites, while perennials were resistant to droughts. Our results were robust to changing spatial scales of observations, and we also demonstrated that within-site spatial synchrony could be used as a sensitive indicator of external climatic effects. We propose the broad application of high-resolution belt transects for powerful and adaptive vegetation monitoring in the future.

The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach

Simple Summary

In this study, we conducted a quantitative assessment and compared the COVID-19 pandemic spread in two countries based on selected methods from the graph theory domain. The results indicate that while the applied experimental procedures are useful, we could draw limited conclusions about the dynamic nature of infection diffusion. We discussed the possible reasons for the above and used them to formulate research hypotheses that could serve the scientific community in future research efforts.

Abstract

Coronavirus disease 2019 (COVID-19) was first discovered in China; within several months, it spread worldwide and became a pandemic. Although the virus has spread throughout the globe, its effects have differed. The pandemic diffusion network dynamics (PDND) approach was proposed to better understand the spreading behavior of COVID-19 in the US and Japan. We used daily confirmed cases of COVID-19 from 5 January 2020 to 31 July 2021, for all states (prefectures) of the US and Japan. By applying the pandemic diffusion network dynamics (PDND) approach to COVID-19 time series data, we developed diffusion graphs for the US and Japan. In these graphs, nodes represent states and prefectures (regions), and edges represent connections between regions based on the synchrony of COVID-19 time series data. To compare the pandemic spreading dynamics in the US and Japan, we used graph theory metrics, which targeted the characterization of COVID-19 bedhavior that could not be explained through linear methods. These metrics included path length, global and local efficiency, clustering coefficient, assortativity, modularity, network density, and degree centrality. Application of the proposed approach resulted in the discovery of mostly minor differences between analyzed countries. In light of these findings, we focused on analyzing the reasons and defining research hypotheses that, upon addressing, could shed more light on the complex phenomena of COVID-19 virus spread and the proposed PDND methodology.

Noise-induced versus intrinsic oscillation in ecological systems

Studies of oscillatory populations have a long history in ecology. A first-principles understanding of these dynamics can provide insights into causes of population regulation and help with selecting detailed predictive models. A particularly difficult challenge is determining the relative role of deterministic versus stochastic forces in producing oscillations. We employ statistical physics concepts, including measures of spatial synchrony, that incorporate patterns at all scales and are novel to ecology, to show that spatial patterns can, under broad and well-defined circumstances, elucidate drivers of population dynamics. We find that when neighbours are coupled (e.g. by dispersal), noisy intrinsic oscillations become distinguishable from noise-induced oscillations at a transition point related to synchronisation that is distinct from the deterministic bifurcation point. We derive this transition point and show that it diverges from the deterministic bifurcation point as stochasticity increases. The concept of universality suggests that the results are robust and widely applicable.

Interspecific synchrony is related to body-length similarity in a fish community under prolonged drought conditions

Interspecific synchrony and trait-based differences between species are likely to be related to each other. Therefore, we investigated interspecific synchrony patterns in a fish community under prolonged drought conditions, using a trait-based approach. We hypothesized that trait-similarity would predict interspecific synchrony among fish populations. We also expected that a general synchronous pattern for the whole community would be high during a severe drought context, indicating low stability. The study was conducted in a semi-arid reservoir between 2010 and 2017, which encompassed a five-year period of severe drought. We considered species differences in body length, gonadosomatic index, relative condition factor, and trophic level and found that interspecific synchrony was negatively related to species differences in body length. This result can be related to species requirements in terms of habitats and food resources. We also found a significant level of community-wide synchrony, with important implications for community stability during periods of prolonged drought. In conclusion, our results indicated a strong effect of environmental filtering in fish population dynamics over time. We highlight the importance of a trait-based approach to shed light on understanding ecological processes driving population dynamics.

Mapping shifts in spatial synchrony in grassland birds to inform conservation planning

Spatial synchrony, defined as the correlated fluctuations in abundance of spatially separated populations, can be caused by regional fluctuations in natural and anthropogenic environmental population drivers. Investigations into the geography of synchrony can provide useful insight to inform conservation planning efforts by revealing regions of common population drivers and metapopulation extinction vulnerability. We examined the geography of spatial synchrony and decadal changes in these patterns for grassland birds in the United States and Canada, which are experiencing widespread and persistent population declines. We used Bayesian hierarchical models and over 50 years of abundance data from the North American Breeding Bird Survey to generate population indices within a 2° latitude by 2° longitude grid. We computed and mapped mean local spatial synchrony for each cell (mean detrended correlation of the index among neighboring cells), along with associated uncertainty, for 19 species in 2, 26-year periods, 1968-1993 and 1994-2019. Grassland birds were predicted to increase in spatial synchrony where agricultural intensification, climate change, or interactions between the 2 increased. We found no evidence of an overall increase in synchrony among grassland bird species. However, based on the geography of these changes, there was considerable spatial heterogeneity within species. Averaging across species, we identified clusters of increasing spatial synchrony in the Prairie Pothole and Shortgrass Prairie regions and a region of decreasing spatial synchrony in the eastern United States. Our approach has the potential to inform continental-scale conservation planning by adding an additional layer of relevant information to species status assessments and spatial prioritization of policy and management actions. Our work adds to a growing literature suggesting that global change may result in shifting patterns of spatial synchrony in population dynamics across taxa with broad implications for biodiversity conservation.

Identifying urban hotspots of dengue, chikungunya, and Zika transmission in Mexico to support risk stratification efforts: a spatial analysis

BACKGROUND

Effective Aedes aegypti control is limited, in part, by the difficulty in achieving sufficient intervention coverage. To maximise the effect of vector control, areas with persistently high numbers of Aedes-borne disease cases could be identified and prioritised for preventive interventions. We aimed to identify persistent Aedes-borne disease hotspots in cities across southern Mexico.

METHODS

In this spatial analysis, geocoded cases of dengue, chikungunya, and Zika from nine endemic Mexican cities were aggregated at the census-tract level. We included cities that were located in southern Mexico (the arbovirus endemic region of Mexico), with a high burden of dengue cases (ie, more than 5000 cases reported during a 10-year period), and listed as high priority for the Mexican dengue control and prevention programme. The Getis-Ord Gi*(d) statistic was applied to yearly slices of the dataset to identify spatial hotspots of each disease in each city. We used Kendall's W coefficient to quantify the agreement in the distribution of each virus.

FINDINGS

128 507 dengue, 4752 chikungunya and 25 755 Zika clinical cases were reported between Jan 1, 2008, and Dec 31, 2016. All cities showed evidence of transmission heterogeneity, with a mean of 17·6% (SD 4·7) of their total area identified as persistent disease hotspots. Hotspots accounted for 25·6% (SD 9·7; range 12·8-43·0) of the population and 32·1% (10·5; 19·6-50·5) of all Aedes-borne disease cases reported. We found an overlap between hotspots of 61·7% for dengue and Zika and 53·3% for dengue and chikungunya. Dengue hotspots in 2008-16 were significantly associated with dengue hotspots detected during 2017-20 in five of the nine cities. Heads of vector control confirmed hotspot areas as problem zones for arbovirus transmission.

INTERPRETATION

This study provides evidence of the overlap of Aedes-borne diseases within geographical hotspots and a methodological framework for the stratification of arbovirus transmission risk within urban areas, which can guide the implementation of surveillance and vector control.

FUNDING

USAID, the US Centers for Disease Control and Prevention, the Canadian Institutes of Health Research, International Development Research Centre, Fondo Mixto CONACyT (Mexico)-Gobierno del Estado de Yucatan, and the US National Institutes of Health.

TRANSLATION

For the Spanish translation of the abstract see Supplementary Materials section.

Synergistic effects of harvest and climate drive synchronous somatic growth within key New Zealand fisheries

Fisheries harvest has pervasive impacts on wild fish populations, including the truncation of size and age structures, altered population dynamics and density, and modified habitat and assemblage composition. Understanding the degree to which harvest-induced impacts increase the sensitivity of individuals, populations and ultimately species to environmental change is essential to ensuring sustainable fisheries management in a rapidly changing world. Here we generated multiple long-term (44-62 years), annually resolved, somatic growth chronologies of four commercially important fishes from New Zealand's coastal and shelf waters. We used these novel data to investigate how regional- and basin-scale environmental variability, in concert with fishing activity, affected individual somatic growth rates and the magnitude of spatial synchrony among stocks. Changes in somatic growth can affect individual fitness and a range of population and fishery metrics such as recruitment success, maturation schedules and stock biomass. Across all species, individual growth benefited from a fishing-induced release of density controls. For nearshore snapper and tarakihi, regional-scale wind and temperature also additively affected growth, indicating that future climate change-induced warming and potentially strengthened winds will initially promote the productivity of more poleward populations. Fishing increased the sensitivity of deep-water hoki and ling growth to the Interdecadal Pacific Oscillation (IPO). A forecast shift to a positive IPO phase, in concert with current harvest strategies, will likely promote individual hoki and ling growth. At the species level, historical fishing practices and IPO synergized to strengthen spatial synchrony in average growth between stocks separated by 400-600 nm of ocean. Increased spatial synchrony can, however, increase the vulnerability of stocks to deleterious stochastic events. Together, our individual- and species-level results show how fishing and environmental factors can conflate to initially promote individual growth but then possibly heighten the sensitivity of stocks to environmental change.

Variation in synchrony of production among species, sites, and intertidal zones in coastal marshes

Spatially synchronous population dynamics are important to ecosystem functioning and have several potential causes. By looking at synchrony in plant productivity over 18 yr across two elevations in three types of coastal marsh habitat dominated by different clonal plant species in Georgia, USA, we were able to explore the importance of plant species and different habitat conditions to synchrony. Synchrony was highest when comparing within a plant species and within a marsh zone, and decreased across species, with increasing distance, and with increasing elevational differences. Abiotic conditions that were measured at individual sites (water column temperature and salinity) also showed high synchrony among sites, and in one case (salinity) decreased with increasing distance among sites. The Moran effect (synchronous abiotic conditions among sites) is the most plausible explanation for our findings. Decreased synchrony between creekbank and mid-marsh zones, and among habitat types (tidal fresh, brackish, and salt marsh) was likely due in part to different exposure to abiotic conditions and in part to variation in sensitivity of dominant plant species to these abiotic conditions. We found no evidence for asynchrony among species, sites or zones, indicating that one habitat type or zone will not compensate for poor production in another during years with low productivity; however, tidal fresh, brackish. and salt marsh sites were also not highly synchronous with each other, which will moderate productivity variation among years at the landscape level due to the portfolio effect. We identified the creekbank zone as more sensitive than the mid-marsh to abiotic variation and therefore as a priority for monitoring and management.

Dynamical Ising model of spatially coupled ecological oscillators

Long-range synchrony from short-range interactions is a familiar pattern in biological and physical systems, many of which share a common set of 'universal' properties at the point of synchronization. Common biological systems of coupled oscillators have been shown to be members of the Ising universality class, meaning that the very simple Ising model replicates certain spatial statistics of these systems at stationarity. This observation is useful because it reveals which aspects of spatial pattern arise independently of the details governing local dynamics, resulting in both deeper understanding of and a simpler baseline model for biological synchrony. However, in many situations a system's dynamics are of greater interest than their static spatial properties. Here, we ask whether a dynamical Ising model can replicate universal and non-universal features of ecological systems, using noisy coupled metapopulation models with two-cycle dynamics as a case study. The standard Ising model makes unrealistic dynamical predictions, but the Ising model with memory corrects this by using an additional parameter to reflect the tendency for local dynamics to maintain their phase of oscillation. By fitting the two parameters of the Ising model with memory to simulated ecological dynamics, we assess the correspondence between the Ising and ecological models in several of their features (location of the critical boundary in parameter space between synchronous and asynchronous dynamics, probability of local phase changes and ability to predict future dynamics). We find that the Ising model with memory is reasonably good at representing these properties of ecological metapopulations. The correspondence between these models creates the potential for the simple and well-known Ising class of models to become a valuable tool for understanding complex biological systems.

Spatial synchrony is related to environmental change in Finnish moth communities

Spatially distinct pairs of sites may have similarly fluctuating population dynamics across large geographical distances, a phenomenon called spatial synchrony. However, species rarely exist in isolation, but rather as members of interactive communities, linked with other communities through dispersal (i.e. a metacommunity). Using data on Finnish moth communities sampled across 65 sites for 20 years, we examine the complex synchronous/anti-synchronous relationships among sites using the geography of synchrony framework. We relate site-level synchrony to mean and temporal variation in climatic data, finding that colder and drier sites-and those with the most drastic temperature increases-are important for spatial synchrony. This suggests that faster-warming sites contribute most strongly to site-level estimates of synchrony, highlighting the role of a changing climate to spatial synchrony. Considering the spatial variability in climate change rates is therefore important to understand metacommunity dynamics and identify habitats which contribute most strongly to spatial synchrony.

Spatiotemporal patterns of dengue outbreaks in Sri Lanka

Background: Dengue occurs epidemically in Sri Lanka and every year, when the monsoon season begins, health authorities warn on rising numbers of dengue cases. The popular belief is that dengue epidemics are driven by the two monsoons which feed different parts of the country over different time periods. We analysed the time series of weekly dengue cases in all districts of Sri Lanka from 2007 to 2019 to identify the spatiotemporal patterns of dengue outbreaks and to explain how they are associated with the climatic, geographic and demographic variations around the country.Methods: We used time-series plots, statistical measures such a community-wide synchrony and Kendall-W and a time-varying graph method to understand the spatiotemporal patterns and links.Results and conclusions: The southwest wet zone and surrounding areas which receive rainfall in all four seasons usually experience two epidemic waves per year. The northern and eastern coastal region in the dry zone which receives rainfall in only two seasons experiences one epidemic wave per year. The wet zone is a highly synchronised epidemic unit while the northern and eastern districts have more independent epidemic patterns. The epidemic synchrony in the wet zone may be associated with the frequent mobility of people in and out of the wet zone hot spot Colombo. The overall epidemic pattern in Sri Lanka is not a sole outcome of the two monsoons but the regional epidemic patterns are collectively shaped by monsoon an inter-monsoon rains, human mobility, geographical proximity and other climate and topographical factors.

Temporal scale of environmental correlations affects ecological synchrony

Population densities of a species measured in different locations are often correlated over time, a phenomenon referred to as synchrony. Synchrony results from dispersal of individuals among locations and spatially correlated environmental variation, among other causes. Synchrony is often measured by a correlation coefficient. However, synchrony can vary with timescale. We demonstrate theoretically and experimentally that the timescale-specificity of environmental correlation affects the overall magnitude and timescale-specificity of synchrony, and that these effects are modified by population dispersal. Our laboratory experiments linked populations of flour beetles by changes in habitat size and dispersal. Linear filter theory, applied to a metapopulation model for the experimental system, predicted the observed timescale-specific effects. The timescales at which environmental covariation occurs can affect the population dynamics of species in fragmented habitats.

Synchrony, Weather, and Cycles in Southern Pine Beetle (Coleoptera: Curculionidae)

Spatial synchrony and cycles are common features of forest insect pests, but are often studied as separate phenomenon. Using time series of timber damage caused by Dendroctonus frontalis Zimmermann (Coleoptera: Curculionidae) (southern pine beetle) in 10 states within the southern United States, this study examines synchrony in D. frontalis abundance, the synchronizing effects of temperature extremes, and the evidence for shared cycles among state populations. Cross-correlation and cluster analyses are used to quantify synchrony across a range of geographic distances and to identify groups of states with synchronous dynamics. Similar techniques are used to quantify spatial synchrony in temperature extremes and to examine their relationship to D. frontalis fluctuations. Cross-wavelet analysis is then used to examine pairs of time series for shared cycles. These analyses suggest there is substantial synchrony among states in D. frontalis fluctuations, and there are regional groups of states with similar dynamics. Synchrony in D. frontalis fluctuations also appears related to spatial synchrony in summer and winter temperature extremes. The cross-wavelet results suggest that D. frontalis dynamics may differ among regions and are not stationary. Significant oscillations were present in some states over certain time intervals, suggesting an endogenous feedback mechanism. Management of D. frontalis outbreaks could potentially benefit from a multistate regional approach because populations are synchronous on this level. Extreme summer temperatures are likely to become the most important synchronizing agent due to climate change.

Identifying multispecies synchrony in response to environmental covariates

The importance of multispecies models for understanding complex ecological processes and interactions is beginning to be realized. Recent developments, such as those by Lahoz-Monfort et al. (2011), have enabled synchrony in demographic parameters across multiple species to be explored. Species in a similar environment would be expected to be subject to similar exogenous factors, although their response to each of these factors may be quite different. The ability to group species together according to how they respond to a particular measured covariate may be of particular interest to ecologists. We fit a multispecies model to two sets of similar species of garden bird monitored under the British Trust for Ornithology's Garden Bird Feeding Survey. Posterior model probabilities were estimated using the reversible jump algorithm to compare posterior support for competing models with different species sharing different subsets of regression coefficients. There was frequently good agreement between species with small asynchronous random-effect components and those with posterior support for models with shared regression coefficients; however, this was not always the case. When groups of species were less correlated, greater uncertainty was found in whether regression coefficients should be shared or not. The methods outlined in this study can test additional hypotheses about the similarities or synchrony across multiple species that share the same environment. Through the use of posterior model probabilities, estimated using the reversible jump algorithm, we can detect multispecies responses in relation to measured covariates across any combination of species and covariates under consideration. The method can account for synchrony across species in relation to measured covariates, as well as unexplained variation accounted for using random effects. For more flexible, multiparameter distributions, the support for species-specific parameters can also be measured.

Three Centuries of Synchronous Forest Defoliator Outbreaks in Western North America

Insect outbreaks often occur synchronously across large spatial scales, but the long-term temporal stability of the phenomenon and the mechanisms behind it are not well understood. In this study, I use a widespread lepidopteran defoliator native to western North America—the western spruce budworm—as a case study to explore patterns of and potential causes for synchronous population fluctuations. Analyses of synchrony are typically severely limited by the short historical records available for many species. To overcome this limitation, I compiled multi-century dendrochronological reconstructions of western spruce budworm outbreaks from across much of the species’ range. This allowed me to analyze synchrony at a sub-continental spatial scale over the last three centuries. I found statistically significant synchrony among regional outbreak records up to 2,000 km apart and identified numerous outbreak periods that occurred synchronously across much of the species’ range. I quantified spatial and temporal associations between climate and synchronous outbreak periods using paleoclimate reconstructions. The spatial patterns of outbreak histories and climate records were remarkably similar, with higher similarity in outbreak histories apparent between regions with more similar climate conditions. Synchronous outbreaks typically occurred during periods of average or above average moisture availability preceded by periods of low moisture availability. My results suggest that climatic variability has played a key role in synchronizing western spruce budworm population fluctuations in disjunct forests across western North America for at least the last three centuries. Widespread synchrony appears to be a natural part of this species’ population dynamics, though synchronous outbreaks have occurred more frequently during the 20^th century than during prior centuries. This study uses a novel combination of statistical methods and dendrochronological data to provide analyses of this species’ population dynamics with an unprecedented combination of spatial extent and temporal depth.

Using multivariate cross correlations, Granger causality and graphical models to quantify spatiotemporal synchronization and causality between pest populations

Background

This work combines multivariate time series analysis and graph theory to detect synchronization and causality among certain ecological variables and to represent significant correlations via network projections. Four different statistical tools (cross-correlations, partial cross-correlations, Granger causality and partial Granger causality) utilized to quantify correlation strength and causality among biological entities. These indices correspond to different ways to estimate the relationships between different variables and to construct ecological networks using the variables as nodes and the indices as edges. Specifically, correlations and Granger causality indices introduce rules that define the associations (links) between the ecological variables (nodes). This approach is used for the first time to analyze time series of moth populations as well as temperature and relative humidity in order to detect spatiotemporal synchronization over an agricultural study area and to illustrate significant correlations and causality interactions via graphical models.

Results

The networks resulting from the different approaches are trimmed and show how the network configurations are affected by each construction technique. The Granger statistical rules provide a simple test to determine whether one series (population) is caused by another series (i.e. environmental variable or other population) even when they are not correlated. In most cases, the statistical analysis and the related graphical models, revealed intra-specific links, a fact that may be linked to similarities in pest population life cycles and synchronizations. Graph theoretic landscape projections reveal that significant associations in the populations are not subject to landscape characteristics. Populations may be linked over great distances through physical features such as rivers and not only at adjacent locations in which significant interactions are more likely to appear. In some cases, incidental connections, with no ecological explanation, were also observed; however, this was expected because some of the statistical methods used to define non trivial associations show connections that cannot be interpreted phenomenologically.

Conclusions

Incorporating multivariate causal interactions in a probabilistic sense comes closer to reality than doing per se binary theoretic constructs because the former conceptually incorporate the dynamics of all kinds of ecological variables within the network. The advantage of Granger rules over correlations is that Granger rules have dynamic features and provide an easy way to examine the dynamic causal relations of multiple time-series variables. The constructed networks may provide an intuitive, advantageous representation of multiple populations’ associations that can be realized within an agro-ecosystem. These relationships may be due to life cycle synchronizations, exposure to a shared climate or even more complicated ecological interactions such as moving behavior, dispersal patterns and host allocation. Moreover, they are useful for drawing inferences regarding pest population dynamics and their spatial management. Extending these models by including more variables should allow the exploration of intra and interspecies relationships in larger ecological systems, and the identification of specific population traits that might constrain their structures in larger areas.

Electronic supplementary material

The online version of this article (doi:10.1186/s12898-016-0087-7) contains supplementary material, which is available to authorized users.

Climate change-related regime shifts have altered spatial synchrony of plankton dynamics in the North Sea

During the 1980s, the North Sea plankton community underwent a well-documented ecosystem regime shift, including both spatial changes (northward species range shifts) and temporal changes (increases in the total abundances of warmer water species). This regime shift has been attributed to climate change. Plankton provide a link between climate and higher trophic-level organisms, which can forage on large spatial and temporal scales. It is therefore important to understand not only whether climate change affects purely spatial or temporal aspects of plankton dynamics, but also whether it affects spatiotemporal aspects such as metapopulation synchrony. If plankton synchrony is altered, higher trophic-level feeding patterns may be modified. A second motivation for investigating changes in synchrony is that the possibility of such alterations has been examined for few organisms, in spite of the fact that synchrony is ubiquitous and of major importance in ecology. This study uses correlation coefficients and spectral analysis to investigate whether synchrony changed between the periods 1959-1980 and 1989-2010. Twenty-three plankton taxa, sea surface temperature (SST), and wind speed were examined. Results revealed that synchrony in SST and plankton was altered. Changes were idiosyncratic, and were not explained by changes in abundance. Changes in the synchrony of Calanus helgolandicus and Para-pseudocalanus spp appeared to be driven by changes in SST synchrony. This study is one of few to document alterations of synchrony and climate-change impacts on synchrony. We discuss why climate-change impacts on synchrony may well be more common and consequential than previously recognized.

Assessing spatial covariance among time series of abundance

For species of conservation concern, an essential part of the recovery planning process is identifying discrete population units and their location with respect to one another. A common feature among geographically proximate populations is that the number of organisms tends to covary through time as a consequence of similar responses to exogenous influences. In turn, high covariation among populations can threaten the persistence of the larger metapopulation. Historically, explorations of the covariance in population size of species with many (>10) time series have been computationally difficult. Here, we illustrate how dynamic factor analysis (DFA) can be used to characterize diversity among time series of population abundances and the degree to which all populations can be represented by a few common signals. Our application focuses on anadromous Chinook salmon (Oncorhynchus tshawytscha), a species listed under the US Endangered Species Act, that is impacted by a variety of natural and anthropogenic factors. Specifically, we fit DFA models to 24 time series of population abundance and used model selection to identify the minimum number of latent variables that explained the most temporal variation after accounting for the effects of environmental covariates. We found support for grouping the time series according to 5 common latent variables. The top model included two covariates: the Pacific Decadal Oscillation in spring and summer. The assignment of populations to the latent variables matched the currently established population structure at a broad spatial scale. At a finer scale, there was more population grouping complexity. Some relatively distant populations were grouped together, and some relatively close populations – considered to be more aligned with each other – were more associated with populations further away. These coarse‐ and fine‐grained examinations of spatial structure are important because they reveal different structural patterns not evident in other analyses.

Evolutionary drivers of mast-seeding in a long-lived desert shrub

PREMISE OF THE STUDY

The evolutionary drivers and proximal regulators of mast-seeding are well understood for species of mesic environments, but how these regulators interact with high spatial and interannual variability in growing-season precipitation for a masting species in a desert environment has never been examined.

METHOD

We followed flowering and seed production in 16 populations of the North American desert shrub blackbrush (Coleogyne ramosissima) from contrasting environments across its range over an 11-year period to determine patterns of interannual reproductive output variation.

KEY RESULT

Patterns of reproductive output in blackbrush did not track current growing season precipitation, but instead were regulated by prior-year weather cues. The strength of the response to the masting cue depended on habitat quality, with higher mean reproductive output, shorter intervals between years of high seed production, and lower CVp at more favorable sites. Wind pollination efficiency was demonstrated to be an important evolutionary driver of masting in blackbrush, and satiation of heteromyid seed predator-dispersers was supported as an evolutionary driver based on earlier studies.

CONCLUSIONS

Both the evolutionary drivers and proximal regulators of masting in blackbrush are similar to those demonstrated for masting species of mesic environments. Relatively low synchrony across populations in response to regional masting cues occurs at least partly because prior-year environmental cues can trigger masting efforts in years with resource limitation due to suboptimal precipitation, especially in more xeric low-elevation habitats.

Variation in Population Synchrony in a Multi-Species Seabird Community: Response to Changes in Predator Abundance

Ecologically similar sympatric species, subject to typical environmental conditions, may be expected to exhibit synchronous temporal fluctuations in demographic parameters, while populations of dissimilar species might be expected to show less synchrony. Previous studies have tested for synchrony in different populations of single species, and those including data from more than one species have compared fluctuations in only one demographic parameter. We tested for synchrony in inter-annual changes in breeding population abundance and productivity among four tern species on Coquet Island, northeast England. We also examined how manipulation of one independent environmental variable (predator abundance) influenced temporal changes in ecologically similar and dissimilar tern species. Changes in breeding abundance and productivity of ecologically similar species (Arctic Sterna paradisaea, Common S. hirundo and Roseate Terns S. dougallii) were synchronous with one another over time, but not with a species with different foraging and breeding behaviour (Sandwich Terns Thalasseus sandvicensis). With respect to changes in predator abundance, there was no clear pattern. Roseate Tern abundance was negatively correlated with that of large gulls breeding on the island from 1975 to 2013, while Common Tern abundance was positively correlated with number of large gulls, and no significant correlations were found between large gull and Arctic and Sandwich Tern populations. Large gull abundance was negatively correlated with productivity of Arctic and Common Terns two years later, possibly due to predation risk after fledging, while no correlation with Roseate Tern productivity was found. The varying effect of predator abundance is most likely due to specific differences in the behaviour and ecology of even these closely-related species. Examining synchrony in multi-species assemblages improves our understanding of how whole communities react to long-term changes in the environment and suggests that changes in predator abundance may differentially affect populations of sympatric seabird species.

Identifying the time scale of synchronous movement: a study on tropical snakes

BACKGROUND

Individual movement is critical to organismal fitness and also influences broader population processes such as demographic stochasticity and gene flow. Climatic change and habitat fragmentation render the drivers of individual movement especially critical to understand. Rates of movement of free-ranging animals through the landscape are influenced both by intrinsic attributes of an organism (e.g., size, body condition, age), and by external forces (e.g., weather, predation risk). Statistical modelling can clarify the relative importance of those processes, because externally-imposed pressures should generate synchronous displacements among individuals within a population, whereas intrinsic factors should generate consistency through time within each individual. External and intrinsic factors may vary in importance at different time scales.

RESULTS

In this study we focused on daily displacement of an ambush-foraging snake from tropical Australia (the Northern Death Adder Acanthophis praelongus), based on a radiotelemetric study. We used a mixture of spectral representation and Bayesian inference to study synchrony in snake displacement by phase shift analysis. We further studied autocorrelation in fluctuations of displacement distances as "one over f noise". Displacement distances were positively autocorrelated with all considered noise colour parameters estimated as >0. We show how the methodology can reveal time scales of particular interest for synchrony and found that for the analysed data, synchrony was only present at time scales above approximately three weeks.

CONCLUSION

We conclude that the spectral representation combined with Bayesian inference is a promising approach for analysis of movement data. Applying the framework to telemetry data of A. praelongus, we were able to identify a cut-off time scale above which we found support for synchrony, thus revealing a time scale where global external drivers have a larger impact on the movement behaviour. Our results suggest that for the considered study period, movement at shorter time scales was primarily driven by factors at the individual level; daily fluctuations in weather conditions had little effect on snake movement.

Accounting for sampling error when inferring population synchrony from time-series data: a Bayesian state-space modelling approach with applications

Background

Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation.

Methodology/Principal findings

The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength.

Conclusion/Significance

The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates.

Taï chimpanzees use botanical skills to discover fruit: what we can learn from their mistakes

Fruit foragers are known to use spatial memory to relocate fruit, yet it is unclear how they manage to find fruit in the first place. In this study, we investigated whether chimpanzees (Pan troglodytes verus) in the Taï National Park make use of fruiting synchrony, the simultaneous emergence of fruit in trees of the same species, which can be used together with sensory cues, such as sight and smell, to discover fruit. We conducted observations of inspections, the visual checking of fruit availability in trees, and focused our analyses on inspections of empty trees, so to say "mistakes". Learning from their "mistakes", we found that chimpanzees had expectations of finding fruit days before feeding on it and significantly increased inspection activity after tasting the first fruit. Neither the duration of feeding nor density of fruit-bearing trees in the territory could account for the variation in inspection activity, which suggests chimpanzees did not simply develop a taste for specific fruit on which they had fed frequently. Instead, inspection activity was predicted by a botanical feature-the level of synchrony in fruit production of encountered trees. We conclude that chimpanzees make use of the synchronous emergence of rainforest fruits during daily foraging and base their expectations of finding fruit on a combination of botanical knowledge founded on the success rates of fruit discovery, and a categorization of fruit species. Our results provide new insights into the variety of food-finding strategies employed by primates and the adaptive value of categorization capacities.

Synchrony in dynamics of giant kelp forests is driven by both local recruitment and regional environmental controls

Populations of many species display spatially synchronous fluctuations in abundance. Synchrony is most commonly attributed to three processes: factors that influence recruitment (e.g., dispersal, early survival), large-scale environmental variability, and spatially autocorrelated trophic interactions. However it is often difficult to link population synchrony to a specific dominant process, particularly when multiple synchronizing forces are operating. We utilized a new satellite-based data set of giant kelp (Macrocystis pyrifera) canopy biomass to examine population synchrony in southern California kelp forests on spatial scales ranging from 50 m to 300 km and temporal scales ranging from 1 to 11 years. We examined the relationship between synchrony and distance for adult kelp populations, kelp recruits, sea urchin abundance (a major grazer of kelp), and environmental variables known to influence kelp population dynamics. Population synchrony in giant kelp decreased with distance between populations: an initial rapid exponential decrease between 50 m and 1.3 km was followed by a second, large-scale decrease between distances of 1.3 km and 172 km. The 50-m to 1.3-km spatial scale corresponded to the scales of synchrony in the abundance of sea urchins and young kelp recruits, suggesting that local drivers of predation and recruitment influence small-scale synchrony in kelp populations. The spatial correlation patterns of environmental variables, particularly wave height, were similar to the synchrony-distance relationship of kelp populations from 1.3 km to 172 km, suggesting that regional environmental variability, i.e., the Moran effect, was the dominant process affecting synchrony at larger spatial scales. This two-step pattern in the relationship between kelp biomass synchrony and distance was apparent in each of the 11 years of our study. Our results highlight the potential for synthesizing approaches from both landscape and population ecology in order to identify the multiple processes that generate synchrony in population dynamics.

Reproductive success of individuals with different fruit production patterns. What does it mean for the predator satiation hypothesis?

The predator satiation hypothesis states that synchronous periodic production of seeds is an adaptive strategy evolved to reduce the pressure of seed predators. The seed production pattern is crucial to the predator satiation hypothesis, but there are few studies documenting the success of individuals that are in synchrony and out of synchrony with the whole population. This study is based on long-term data on seed production of Sorbus aucuparia and specialised pre-dispersal seed predation by Argyresthia conjugella, in a subalpine spruce forest in the Western Carpathians (Poland). At the population level, we tested whether functional and numerical responses of predators to the variation of fruit production operate. At the individual level, we tested whether individuals with higher interannual variability in their own seed crops and higher synchrony with the population have higher percentages of uninfested fruits. The intensity of pre-dispersal seed predation was high (average 70 %; range 19–100 %). There were both functional and numerical responses of predators to the variation of fruit production at the population level. We found that individuals that were expected to be preferred under seed predator pressure had higher reproductive success. With increasing synchrony of fruit production between individual trees and the population, the percentage of infested fruits decreased. There was also a negative relationship between the interannual variation in individual fruit production and the percentage of infested fruits. These results confirm selection for individuals with a masting strategy. However, the population does not seem well adapted to strong seed predation pressure and we suggest that this may be a result of prolonged diapause of A. conjugella.

Synchrony of population dynamics of two vineyard arthropods occurs at multiple spatial and temporal scales

When populations are synchronized, they rise and fall together. Analysis of population synchrony and its relationship to distance has played a major role in population ecology but has been absent from most studies of managed populations, such as agricultural arthropods. The extent to which populations at different locations are synchronized reflects the relative roles of shared environmental impacts, such as weather, and localizing processes, such as dispersal. The strength and pattern of synchrony, and the processes generating synchrony, have direct management implications. For the first time, we bring together two major paths of population-ecology research: spatial synchrony of population dynamics, which has been studied across birds, mammals, and insects, and spatial ecology of agricultural arthropod populations. We compare and contrast synchrony of two arthropod species, a spider mite and a leafhopper, across a vineyard region spanning 30-km distances, at within-year (weekly) and between-year time scales. Despite the enormous scope of agriculture, such long-term, large-scale data sets suitable for investigating local and regional dynamics are rare. For both species, synchrony is more strongly localized for annual peak abundance across 11 years than it typically is for weekly dynamics within each year's growing season. This suggests that between-year processes such as overwintering merit greater investigation. Within each year, both localized and region-wide synchrony was found for both species, but leafhoppers showed stronger localization than spider mites, corresponding to their longer generation time and stronger dispersal ability. This demonstrates that the overall herbivore dynamics of the system occur at multiple spatial scales and that the importance of different processes generating synchrony varies by species. The analysis includes new spatiotemporal randomization and bootstrap tests that can be applied to many systems. Our results highlight the value of large-scale, long-term monitoring programs for many kinds of managed populations. They also point toward the potential to test synchrony mechanisms more directly and to synthesize synchrony and landscape analyses.

Synchrony and stability of food webs in metacommunities

Synchrony has fundamental but conflicting implications for the persistence and stability of food webs at local and regional scales. In a constant environment, compensatory dynamics between species can maintain food web stability, but factors that synchronize population fluctuations within and between communities are expected to be destabilizing. We studied the dynamics of a food web in a metacommunity to determine how environmental variability and dispersal affect stability by altering compensatory dynamics and average species abundance. When dispersal rate is high, weak correlated environmental fluctuations promote food web stability by reducing the amplitude of compensatory dynamics. However, when dispersal rate is low, weak environmental fluctuations reduce food web stability by inducing intraspecific synchrony across communities. Irrespective of dispersal rate, strong environmental fluctuations disrupt compensatory dynamics and decrease stability by inducing intermittent correlated fluctuations between consumers in local food webs, which reduce both total consumer abundance and predator abundance. Strong correlated environmental fluctuations lead to (i) spatially asynchronous and highly correlated local consumer dynamics when dispersal is low and (ii) spatially synchronous but intermediate local consumer correlation when dispersal is high. By controlling intraspecific synchrony, dispersal mediates the capacity of strong environmental fluctuations to disrupt compensatory dynamics at both local and metacommunity scales.

Using mechanistic models to understand synchrony in forest insect populations: the North American gypsy moth as a case study

In many forest insects, subpopulations fluctuate concurrently across large geographical areas, a phenomenon known as population synchrony. Because of the large spatial scales involved, empirical tests to identify the causes of synchrony are often impractical. Simple models are, therefore, a useful aid to understanding, but data often seem to contradict model predictions. For instance, chaotic population dynamics and limited dispersal are not uncommon among synchronous forest defoliators, yet both make it difficult to achieve synchrony in simple models. To test whether this discrepancy can be explained by more realistic models, we introduced dispersal and spatially correlated stochasticity into a mechanistic population model for the North American gypsy moth Lymantria dispar. The resulting model shows both chaotic dynamics and spatial synchrony, suggesting that chaos and synchrony can be reconciled by the incorporation of realistic dynamics and spatial structure. By relating alterations in model structure to changes in synchrony levels, we show that the synchrony is due to a combination of spatial covariance in environmental stochasticity and the origins of chaos in our multispecies model.