Predict Population Dynamics Research Articles

Estimating the juvenile survival rate of male Northern Fur (Сallorhinus ursinus): mathematical modelling and data analysis

For the sustainable use of the northern fur seal stocks, estimation and prediction of the number of the main age groups of males is very important. The data of direct observations make it possible to estimate only the size of the offspring (the number of pups) and the total number of bulls; and the age composition of the animals killed by the harvest is also known. It is necessary to be able to calculate the survival rates of individual age groups of fur seals to predict population dynamics using these data. This paper discusses and modernizes the previously proposed methods for estimating the survival rates of males. To narrow the calculated intervals of juvenile survival we use additional information (in particular, the estimated survival of males at subsequent stages of the life cycle), as well as adjust the evaluation procedure. Two methods for calculating the survival rates of males at different stages of the life cycle are proposed: the iteration method and the method of determining the survival limits of all age groups from the dynamic equations. Both methods are based on available observational data and features of the life cycle of the species in question, they do not require fulfillment of any assumptions about the nature of the harvest strategy. We obtain, as a result, satisfactory estimates of the coefficients characterizing the main stages of the life cycle of fur seal males. Moreover, both methods give very similar regression estimates of the average bulls’ survival: they hardly differ in size and have similar statistical characteristics. Thus, the first method gives higher juvenile survival and low survival of bachelors; and the second method, on the contrary, overestimates the survival of bachelors and underestimates the juvenile survival rate. However, as the regression analysis showed, both sets of estimates are well compatible with observational data.

Effect of thermal stress on antioxidant responses of the biocontrol agent Galerucella placida (Coleoptera: Chrysomelidae)

AbstractGalerucella placidaBaly feeds on the rice-field weedPolygonum orientaleL. (Polygonaceae) in India and Bangladesh during autumn and winter seasons. The insect is widely available during the winter season when the temperature fluctuates between 9 and 24 °C. Hence, it is of considerable interest to study how the adults cope with the stress resulting due to temperature fluctuations. Consequently, we analysed the levels of H2O2, antioxidant enzymes [catalase (CAT), superoxide dismutase (SOD), peroxidases (POD), guaiacol peroxidase (GPX), pyrogallol peroxidases (PPX), ascorbate peroxidases (APOX) and glutathione-S-transferases (GST)] and malondialdehyde (MDA) at 9, 12, 15, 18, 21 and 24 °C in adultG. placida. H2O2was highest at 24 °C followed by 9 °C and lowest at 18 and 21°C. CAT and SOD were highest at 9 °C followed by 24 °C, while POD was highest at 24 °C followed by 9 °C. CAT and POD were lowest at 18 and 21 °C, but SOD was the lowest at 21 °C. APOX were three-fold higher at 9 °C compared to 12 °C, which was the lowest at 18 and 21 °C, implying that APOX had strong detoxification function at 9 °C. GST was highest and lowest at 9 and 21 °C, respectively. MDA was highest at 9 °C and lowest at 18 and 21 °C, which did not differ significantly at 15 and 24 °C, suggesting that lower and higher temperature stress was accompanied by lipid peroxidation. This finding provides useful information for mass rearing ofG. placidafor predicting population dynamics and understanding the potential forG. placidaas biocontrol agent under varying environmental conditions.

Nonlinear averaging of thermal experience predicts population growth rates in a thermally variable environment.

As thermal regimes change worldwide, projections of future population and species persistence often require estimates of how population growth rates depend on temperature. These projections rarely account for how temporal variation in temperature can systematically modify growth rates relative to projections based on constant temperatures. Here, we tested the hypothesis that time-averaged population growth rates in fluctuating thermal environments differ from growth rates in constant conditions as a consequence of Jensen's inequality, and that the thermal performance curves (TPCs) describing population growth in fluctuating environments can be predicted quantitatively based on TPCs generated in constant laboratory conditions. With experimental populations of the green alga Tetraselmis tetrahele, we show that nonlinear averaging techniques accurately predicted increased as well as decreased population growth rates in fluctuating thermal regimes relative to constant thermal regimes. We extrapolate from these results to project critical temperatures for population growth and persistence of 89 phytoplankton species in naturally variable thermal environments. These results advance our ability to predict population dynamics in the context of global change.

Multigenerational Effects and Demographic Responses of Zebrafish ( Danio rerio) Exposed to Organo-Bromine Compounds.

Long-term exposure to toxic chemicals often has deleterious effects on aquatic organisms. In order to support appropriate environmental management of chemicals, a mathematical model was developed to characterize the effects of chemicals on multigenerational population dynamics in aquatic animals. To parametrize the model, we conducted a multigenerational laboratory toxicity test in zebrafish ( Danio rerio) exposed to 2-bromo-4,6-dinitroaniline (BDNA). Long-term exposure to BDNA considerably reduced the fecundity of adult zebrafish (F0 and F1) and caused deformities in the offspring (F2). Life history data, including changes in fecundity and population growth, were then integrated into the model to predict population dynamics of zebrafish exposed to two novel brominated flame retardants, bis(2-ethylhexyl)-2,3,4,5-tetrabromophthalate (TBPH) and 2-ethylhexyl-2,3,4,5-tetrabromobenzoate (TBB). The model predicted that the fecundity of adult zebrafish would be significantly impaired after exposure to 90.36 μM TBPH and 99.16 μM TBB. Thus, prolonged exposure to such levels over multiple generations could result in population extinction within 20 years. Our results provide an intensive temporal perspective to investigate a keystone that connects with individual response to chemicals, population dynamics, and ultimately ecosystem influences.

Clipperton Atoll as a model to study small marine populations: Endemism and the genomic consequences of small population size.

Estimating population sizes and genetic diversity are key factors to understand and predict population dynamics. Marine species have been a difficult challenge in that respect, due to the difficulty in assessing population sizes and the open nature of such populations. Small, isolated islands with endemic species offer an opportunity to groundtruth population size estimates with empirical data and investigate the genetic consequences of such small populations. Here we focus on two endemic species of reef fish, the Clipperton damselfish, Stegastes baldwini, and the Clipperton angelfish, Holacanthus limbaughi, on Clipperton Atoll, tropical eastern Pacific. Visual surveys, performed over almost two decades and four expeditions, and genetic surveys based on genomic RAD sequences, allowed us to estimate kinship and genetic diversity, as well as to compare population size estimates based on visual surveys with effective population sizes based on genetics. We found that genetic and visual estimates of population numbers were remarkably similar. S. baldwini and H. limbaughi had population sizes of approximately 800,000 and 60,000, respectively. Relatively small population sizes resulted in low genetic diversity and the presence of apparent kinship. This study emphasizes the importance of small isolated islands as models to study population dynamics of marine organisms.

Trophic overlap between expanding and contracting fish predators in a range margin undergoing change

Climate change is predicted to cause a freshening of the Baltic Sea, facilitating range expansions of freshwater species and contractions of marine. Resident marine flounders (Platichthys flesus) and expansive freshwater roach (Rutilus rutilus) are dominant consumers in the Baltic Sea sublittoral where they occur in partial sympatry. By comparing patterns of resource use by flounders and roach along a declining resource gradient of blue mussels (Mytilus trossulus) our aim was to explore predator functional responses and the degree of trophic overlap. Understanding the nature of density-dependent prey acquisition has important implications for predicting population dynamics of both predators and their shared prey. Results showed a highly specialized diet for both species, high reliance on blue mussels throughout the range, similar prey size preference and high trophic overlap. Highest overlap occurred where blue mussels were abundant but overlap was also high where they were scarce. Our results highlight the importance of a single food item - the blue mussel - for both species, likely promoting high population size and range expansion of roach. Findings also suggest that range expansion of roach may have a top-down structuring force on mussels that differ in severity and location from that originating from resident flounders.

Spatially explicit approach to estimation of total population abundance in field surveys

Population abundance is fundamental in ecology and conservation biology, and provides essential information for predicting population dynamics and implementing conservation actions. While a range of approaches have been proposed to estimate population abundance based on existing data, data deficiency is ubiquitous. When information is deficient, a population estimation will rely on labor intensive field surveys. Typically, time is one of the critical constraints in conservation, and management decisions must often be made quickly under a data deficient situation. Hence, it is important to acquire a theoretical justification for survey methods to meet a required estimation precision. There is no such theory available in a spatially explicit context, while spatial considerations are critical to any field survey. Here, we develop a spatially explicit theory for population estimation that allows us to examine the estimation precision under different survey designs and individual distribution patterns (e.g. random/clustered sampling and individual distribution). We demonstrate that clustered sampling decreases the estimation precision when individuals form clusters, while sampling designs do not affect the estimation accuracy when individuals are distributed randomly. Regardless of individual distribution, the estimation precision becomes higher with increasing total population abundance and the sampled fraction. These insights provide theoretical bases for efficient field survey designs in information deficiency situations.

Predicting landscape‐level distribution and abundance: Integrating demography, fire, elevation and landscape habitat configuration

Abstract Demography varies in response to multiple interactive drivers at varying scales. However, these relationships are often assessed piecemeal, particularly without consideration of drivers at the landscape level. We developed a model to predict population dynamics of an endangered, perennial herb Hypericum cumulicola across a range of landscape drivers. We estimated vital rates using 22 years of annual census data from 15 populations (10,910 and 38,313 unique observations) and additional seeding experiments, considering four landscape drivers (time‐since‐fire, patch area, patch aggregation and patch elevation). We combined these models into integral projection models to assess population parameters. Predictions of occupancy and density were compared with an independent dataset of 33 habitat patches. We also evaluated the effect of fire‐return interval on population persistence. The landscape drivers had interactive effects on vital rates and demography. Occupancy was predicted for most patches, including many that were unoccupied. Abundances were poorly predicted, primarily because projections were unreliable for patches having intermediate areas and aggregation. When these patches were removed, the model explained 42% of the variance in abundance. Projected population growth was greater and extinction risk lower under more frequent fire‐return intervals, at higher elevations, and in larger and more aggregated patches. Our modelling suggests that fire can be prescribed less often in larger than smaller patches to support a viable metapopulation of H. cumulicola. Synthesis. The integration of landscape‐level drivers and detailed demographic data is a valuable tool for understanding species abundances, distributions and dynamics at large scales. We evaluated the effect of interactions among fire, patch elevation, area and aggregation on the demography of a rare and endangered plant. Our findings reinforce the importance of regional dynamics. These drivers and their interactions suggest locations that can support higher vital rates, occupancy and abundance, and what fire‐return intervals are optimal depending on landscape characteristics. This approach demonstrates a link between plant demography and landscape variables, although further work is needed to improve ecological predictions.

How ecology shapes exploitation: a framework to predict the behavioural response of human and animal foragers along exploration-exploitation trade-offs.

Understanding how humans and other animals behave in response to changes in their environments is vital for predicting population dynamics and the trajectory of coupled social-ecological systems. Here, we present a novel framework for identifying emergent social behaviours in foragers (including humans engaged in fishing or hunting) in predator-prey contexts based on the exploration difficulty and exploitation potential of a renewable natural resource. A qualitative framework is introduced that predicts when foragers should behave territorially, search collectively, act independently or switch among these states. To validate it, we derived quantitative predictions from two models of different structure: a generic mathematical model, and a lattice-based evolutionary model emphasising exploitation and exclusion costs. These models independently identified that the exploration difficulty and exploitation potential of the natural resource controls the social behaviour of resource exploiters. Our theoretical predictions were finally compared to a diverse set of empirical cases focusing on fisheries and aquatic organisms across a range of taxa, substantiating the framework's predictions. Understanding social behaviour for given social-ecological characteristics has important implications, particularly for the design of governance structures and regulations to move exploited systems, such as fisheries, towards sustainability. Our framework provides concrete steps in this direction.

Demography of Rusty Grain Beetle in Stored Bulk Wheat: Part II. Mathematical Modeling to Characterize and Predict Population Dynamics.

Data collected in Part I of this study were further analyzed by using mathematical modeling methods. Out of the nine unstructured population models tested, no model could fit the insect numbers under all of the tested conditions. This analysis showed that Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae) inside small patches (50 ml volume) had different characterization of population dynamics from that inside large patches (18 liter volume) and had different population demography when the insect number at the previous time was different. The key factor analysis showed that the first two main factors influencing the population dynamics were the temperature and the previous insect numbers. The total numbers of insects increased with the increase of sum of degree days. However, the degree day model developed based on the constant temperatures could not predict insect numbers under fluctuating temperatures. A newly developed model, which used the result of the unstructured population models, key factor analysis, and the degree day model, could explain about 66% of the insect numbers under fluctuating temperature conditions.

Strong evidence for changing fish reproductive phenology under climate warming on the Tibetan Plateau.

Phenological responses to climate change have been widely observed and have profound and lasting effects on ecosystems and biodiversity. However, compared to terrestrial ecosystems, the long-term effects of climate change on species' phenology are poorly understood in aquatic ecosystems. Understanding the long-term changes in fish reproductive phenology is essential for predicting population dynamics and for informing management strategies, but is currently hampered by the requirement for intensive field observations and larval identification. In this study, a very low-frequency sampling of juveniles and adults combined with otolith measurements (long axis length of the first annulus; LAFA) of an endemic Tibetan Plateau fish (Gymnocypris selincuoensis) was used to examine changes in reproductive phenology associated with climate changes from the 1970s to 2000s. Assigning individual fish to their appropriate calendar year class was assisted by dendrochronological methods (crossdating). The results demonstrated that LAFA was significantly and positively associated with temperature and growing season length. To separate the effects of temperature and the growing season length on LAFA growth, measurements of larval otoliths from different sites were conducted and revealed that daily increment additions were the main contributor (46.3%), while temperature contributed less (12.0%). Using constructed water-air temperature relationships and historical air temperature records, we found that the reproductive phenology of G.selincuoensis was strongly advanced in the spring during the 1970s and 1990s, while the increased growing season length in the 2000s was mainly due to a delayed onset of winter. The reproductive phenology of G.selincuoensis advanced 2.9days per decade on average from the 1970s to 2000s, and may have effects on recruitment success and population dynamics of this species and other biota in the ecosystem via the food web. The methods used in this study are applicable for studying reproductive phenological changes across a wide range of species and ecosystems.

Predicting Heliothis (Helicoverpa armigera) pest population dynamics with an age-structured insect population model driven by satellite data

The cotton bollworm (Helicoverpa armigera) is among the most damaging agricultural insect pests in the world. The life cycle of H. armigera is temperature dependent and as such modeling its population dynamics for integrated pest management (IPM) purposes requires accurate temperature information throughout the area of interest, which is not always available. We present, for the first time, a continuous age-structured insect population model driven by satellite-derived land surface temperature (LST) to derive population dynamics of H. armigera. We use LST data from the Moderate resolution imaging spectroradiometer (MODIS) conducting model simulations and validating the model with H. armigera larvae counts from in-field scout reports in nine sweet corn (Zea mays convar) and four tomato (Solanum lycopersicum) crop fields in Northern Israel. We compared our results with a similar model that uses air temperature derived from the nearest weather station as an input. To accurately predict population dynamics, we used different model initiation scenarios considering pesticide application and migration patterns between neighboring corn and tomato fields, which were identified as sink and source of the adult population. Results show that our LST-driven model outperformed the model driven by ambient air temperature. Model simulations generally followed the larval population development observed in the field when the model was initiated the day before the first larvae were detected, providing realistic population dynamics. Simulations with different adult population migration rates showed the importance of including between-field migration in the LST-driven model. In conclusion, this study provides a basis for future development of real-time IPM support systems, particularly when combining a temperature-driven age-structured insect population model with real-time satellite-derived information.

Режимы динамики лимитированной структурированной популяции при избирательном промысле

The paper investigates influence of age specific harvest on the dynamics of populations with density dependent regulation of birth rate. We consider the population which by the end of each reproduction season, consists of two age groups: juveniles (immature individuals) and adults (participants of the reproduction process). A harvest rate growth of any age class is shown to give, as a rule, the dynamics stabilization. However, the system with harvesting demonstrates multimodality phenomenon as well as the population model without exploitation. The phenomenon means different dynamic modes are observed with the same values of the population parameters. As a result, some difficulties occur in predicting population dynamics, because harvest can lead to significant changes of population size due to shifting current population size from one attraction basin to another. To neutralize the oscillations emerged is necessary to change the current population size so that it falls into the attraction basin of the fixed point. The stability loss way of model with juvenile harvesting does not depend on the harvest rate value and is completely determined by the intensity of competitive relationships between the age classes. In the case of adult exploitation, a higher harvest rate can result in growing stationary population size. The changing the time of adult harvesting can lead to both the dynamics population stabilization and the occurrence of fluctuations. Exploitation before the reproduction season allows to have more yield than after reproduction season because mature age group size is higher. Conditions when the age specific harvest gives the maximum sustainable yield are considered.

The power of hybrid modelling: An example from aquatic ecosystems

Planktonic communities in ponds and lakes show a high annual dynamic controlled by biotic interactions, nutrients and weather. In recent years, there has been an increase in demand for realistic and accurate lake models to improve ecological management of water bodies and to answer ecotoxicological questions in aquatic risk assessment. Most existing aquatic models are either ecosystem models aimed at describing the overall ecosystem dynamics, but which are incapable of including individual life-cycles and plasticity, or very detailed and realistic individual-based models lacking an appropriate level of environmental complexity. To reconcile these concepts, we present here a modelling approach using an individual-based population model (IBM), integrated within an ecosystem lake model, to link responses at the individual and population levels. We combine an IBM for Daphnia magna (IDamP) and a complex biogeochemical lake model (StoLaM), to create the DaLaM (Daphnia Lake Model). We use DaLaM to predict population dynamics of D. magna and phytoplankton within a simplified, daphnid-dominated food web under field conditions. In DaLaM, relevant variable environmental conditions such as underwater light climate, water temperature, turbulence, and nutrient availability are realistically simulated forced by weather conditions. For model testing we used data from aquatic mesocosm field studies exhibiting variable nutrient and weather conditions and lasting from several months to 2 years. DaLaM gave improved predictions of the overall population patterns of daphnids and phytoplankton in the mesocosms in contrast to its separate submodels. This study is an example of successfully merging individual-based population models with dynamic ecosystem models utilising the accuracy of the former and the dynamic environment of the latter to simulate more realistic field populations.

Linking environmental factors, life history and population density in the endangered freshwater snail Margarya melanioides (Viviparidae) in Lake Dianchi, China

Understanding how environmental changes affect life-history traits is important for predicting population dynamics of a species. As one of the most pervasive forms of environmental changes in freshwater systems, eutrophication can change life-history traits of freshwater animals through density-dependent/independent processes. However, empirical evidence remains scarce regarding the mechanisms by which eutrophication influences life-history traits. We conducted a field study linking eutrophication, life-history traits and population density in a population of Margarya melanioides in Lake Dianchi, the largest lake of the Yun-Gui plateau in China and the most eutrophicated by humans, over 14 months in 2009-2010. We estimated key life-history traits (growth and reproduction) of M. melanioides in 2009-2010. Then, by comparing some life-history traits with those recorded in 1931-1933 (when the extent of eutrophication was comparatively low), we found that this snail had increased its fecundity (from 1.07 to 4.24 offspring/brood-bearing female) and the proportion of females with broods (23.6 to 77.4%), decreased its body size (54.2 to 47.6 mm) and the threshold size for reproduction (46 to 35 mm), and distorted its female/male sex ratio (1.6:1 to 0.97:1). These findings suggest that M. melanioides has adapted some life-history traits in response to intensified eutrophication. A structural equation model indicated that eutrophication influenced the reproduction of this snail through two related but opposing pathways: primarily by decreasing its population size to reduce its reproduction and secondarily by directly promoting its reproduction. Our results not only support the significance of eutrophication in determination of life-history traits of freshwater animals, but also suggest that density-dependent effects on reproduction may be stronger than direct environmental influences when population size is small.

Reproductive performance of resident and migrant males, females and pairs in a partially migratory bird.

Quantifying among‐individual variation in life‐history strategies, and associated variation in reproductive performance and resulting demographic structure, is key to understanding and predicting population dynamics and life‐history evolution. Partial migration, where populations comprise a mixture of resident and seasonally migrant individuals, constitutes a dimension of life‐history variation that could be associated with substantial variation in reproductive performance. However, such variation has rarely been quantified due to the challenge of measuring reproduction and migration across a sufficient number of seasonally mobile males and females.We used intensive winter (non‐breeding season) resightings of colour‐ringed adult European shags (Phalacrocorax aristotelis) from a known breeding colony to identify resident and migrant individuals. We tested whether two aspects of annual reproductive performance, brood hatch date and breeding success, differed between resident and migrant males, females and breeding pairs observed across three consecutive winters and breeding seasons.The sex ratios of observed resident and migrant shags did not significantly differ from each other or from 1:1, suggesting that both sexes are partially migratory and that migration was not sex‐biased across surveyed areas.Individual resident males and females hatched their broods 6 days earlier and fledged 0.2 more chicks per year than migrant males and females on average. Resident individuals of both sexes therefore had higher breeding success than migrants.Hatch date and breeding success also varied with a pair's joint migratory strategy such that resident–resident pairs hatched their broods 12 days earlier than migrant–migrant pairs, and fledged 0.7 more chicks per year on average. However, there was no evidence of assortative pairing with respect to migratory strategy: observed frequencies of migrant–migrant and resident–resident pairs did not differ from those expected given random pairing.These data demonstrate substantial variation in two key aspects of reproductive performance associated with the migratory strategies of males, females and breeding pairs within a partially migratory population. These patterns could reflect direct and/or indirect mechanisms, but imply that individual variation in migratory strategy and variation in pairing among residents and migrants could influence selection on migration and drive complex population and evolutionary dynamics.

Age-stage two-sex life table analysis of Sesamia nonagrioides (Lep.: Noctuidae) reared on different host plants

The effects of maize and sugarcane were studied on the demographic parameters of Sesamia nonagrioides under controlled environmental conditions. Life table parameters were estimated using age-stage two-sex life table method. Total developmental times of immature stages were 53.51 ± 0.42 and 39.58 ± 0.14 days on maize and sugarcane, respectively. The fecundity values were found to be 93.07 ± 2.94 and 122.95 ± 6.72 eggs/female on maize and sugarcane, respectively. Based on the analysis, the intrinsic rates of increase (r) and the mean generation time (T) of S. nonagrioides were determined as 0.0909 ± 0.0027 and 0.0579 ± 0.0021 day−1; 42.09 ± 0.21 and 56.83 ± 0.63 days on sugarcane and maize, respectively. Consequently, the sugarcane was a better host for development and population increase of S. nonagrioides than maize. These results can be used to predict population dynamics of the pest on the natural hosts and to improve mass rearing technique on natural diets in insectariums.

Projecting population growth as a dynamic measure of regional urban warming

Urban development is characterized by drastic land use and land cover changes, rooted in urban population growth, with concomitant anthropogenic stressors contributing to global climate changes. While there is extensive literature on predicting future urban climate using biogeophysical models, the direct link between emergent meteorological patterns and the population dynamics remains obscure. In this study, we propose an operative model for predicting regional urban warming using a population growth model based on different scaling laws. We choose the annual average air temperature as the climatic indicator and relate the historical temperature data to demographic data for 10 megapolitan areas in the United States. Linear regression analysis shows that the coefficients of determination range from 0.164 to 0.563 for the study areas, indicating a significant correlation between urban population and climate dynamics. Specifically, the Phoenix Metropolitan Area is selected as a testbed where the regression is applied for correlating the population growth and trend of urban warming. Based on the predicted population dynamics, the annual average temperature in Phoenix is projected to increase by 0.65–3.40°C in the next 35 years.

Mechanistic model for predicting the seasonal abundance of Culicoides biting midges and the impacts of insecticide control

BackgroundUnderstanding seasonal patterns of abundance of insect vectors is important for optimisation of control strategies of vector-borne diseases. Environmental drivers such as temperature, humidity and photoperiod influence vector abundance, but it is not generally known how these drivers combine to affect seasonal population dynamics.MethodsIn this paper, we derive and analyse a novel mechanistic stage-structured simulation model for Culicoides biting midges-the principle vectors of bluetongue and Schmallenberg viruses which cause mortality and morbidity in livestock and impact trade. We model variable life-history traits as functional forms that are dependent on environmental drivers, including air temperature, soil temperature and photoperiod. The model is fitted to Obsoletus group adult suction-trap data sampled daily at five locations throughout the UK for 2008.ResultsThe model predicts population dynamics that closely resemble UK field observations, including the characteristic biannual peaks of adult abundance. Using the model, we then investigate the effects of insecticide control, showing that control strategies focussing on the autumn peak of adult midge abundance have the highest impact in terms of population reduction in the autumn and averaged over the year. Conversely, control during the spring peak of adult abundance leads to adverse increases in adult abundance in the autumn peak.ConclusionsThe mechanisms of the biannual peaks of adult abundance, which are important features of midge seasonality in northern Europe and are key determinants of the risk of establishment and spread of midge-borne diseases, have been hypothesised over for many years. Our model suggests that the peaks correspond to two generations per year (bivoltine) are largely determined by pre-adult development. Furthermore, control strategies should focus on reducing the autumn peak since the immature stages are released from density-dependence regulation. We conclude that more extensive modelling of Culicoides biting midge populations in different geographical contexts will help to optimise control strategies and predictions of disease outbreaks.

Low migratory connectivity is common in long-distance migrant birds.

Estimating how much long-distance migrant populations spread out and mix during the non-breeding season (migratory connectivity) is essential for understanding and predicting population dynamics in the face of global change. We quantify variation in population spread and inter-population mixing in long-distance, terrestrial migrant land-bird populations (712 individuals from 98 populations of 45 species, from tagging studies in the Neotropic and Afro-Palearctic flyways). We evaluate the Mantel test as a metric of migratory connectivity, and explore the extent to which variance in population spread can be explained simply by geography. The mean distance between two individuals from the same population during the non-breeding season was 743km, covering 10-20% of the maximum width of Africa/South America. Individuals from different breeding populations tended to mix during the non-breeding season, although spatial segregation was maintained in species with relatively large non-breeding ranges (and, to a lesser extent, those with low population-level spread). A substantial amount of between-population variation in population spread was predicted simply by geography, with populations using non-breeding zones with limited land availability (e.g. Central America compared to South America) showing lower population spread. The high levels of population spread suggest that deterministic migration tactics are not generally adaptive; this makes sense in the context of the recent evolution of the systems, and the spatial and temporal unpredictability of non-breeding habitat. The conservation implications of generally low connectivity are that the loss (or protection) of any non-breeding site will have a diffuse but widespread effect on many breeding populations. Although low connectivity should engender population resilience to shifts in habitat (e.g. due to climate change), we suggest it may increase susceptibility to habitat loss. We hypothesize that, because a migrant species cannot adapt to both simultaneously, migrants generally may be more susceptible to population declines in the face of concurrent anthropogenic habitat and climate change.