Factors and mechanisms explaining spatial heterogeneity: a review of methods for insect populations

Spatial and temporal trends of dengue infections in Curaçao: A 21-year analysis

Dengue viruses are a significant global health concern, causing millions of infections annually and putting approximately half of the world's population at risk, as reported by the World Health Organization (WHO). Understanding the spatial and temporal patterns of dengue virus spread is crucial for effective prevention of future outbreaks. By investigating these patterns, targeted dengue surveillance and control measures can be improved, aiding in the management of outbreaks in dengue-affected regions. Curaçao, where dengue is endemic, has experienced frequent outbreaks over the past 25 years. To examine the spatial and temporal trends of dengue outbreaks in Curaçao, this study employs an interdisciplinary and multi-method approach. Data on >6500 cases of dengue infections in Curaçao between the years 1995 and 2016 were used. Temporal and spatial statistics were applied. The Moran's I index identified the presence of spatial autocorrelation for incident locations, allowing us to reject the null hypothesis of spatial randomness. The majority of cases were recorded in highly populated areas and a relationship was observed between population density and dengue cases. Temporal analysis demonstrated that cases mostly occurred from October to January, during the rainy season. Lower average temperatures, higher precipitation and a lower sea surface temperature appear to be related to an increase in dengue cases. This effect has a direct link to La Niña episodes, which is the cooling phase of El Niño Southern Oscillation. The spatial and temporal analyses conducted in this study are fundamental to understanding the timing and locations of outbreaks, and ultimately improving dengue outbreak management.

The Population Dynamics and Parasitism Rates of Ceratitis capitata, Anastrepha fraterculus, and Drosophila suzukii in Non-Crop Hosts: Implications for the Management of Pest Fruit Flies

Understanding the seasonal dynamics inherent to non-crop host-fruit fly-parasitoid interactions is vitally important for implementing eco-friendly pest control strategies. This study assessed the abundance and seasonal infestation levels of three pest fly species, Ceratitis capitata (Wiedemann), Anastrepha fraterculus (Wiedemann), Drosophila suzukii (Matsumura), as well as the related saprophytic drosophilids, and their natural parasitism in a disturbed wild habitat characterized by non-crop hosts in northwestern Argentina over 40 months. Juglans australis Griseb (walnut), Citrus aurantium L. (sour orange), Eriobotrya japonica (Thunb.) Lindley (loquat), Prunus persica (L.) Batsch (peach), and Psydium guajava L. (guava) were sampled throughout their fruiting seasons. Fruits were collected from both the tree canopies and the ground. The most abundant puparia was A. fraterculus, followed by C. capitata and D. suzukii. Drosophila species from the D. melanogaster group were highly abundant only in fallen fruits. Spatiotemporal overlaps of different host fruit availability provided suitable sources for pest proliferation throughout the year. The populations of both invasive pests peaked from December to January, and were related to the highest ripe peach availability, whereas the A. fraterculus population peaked from February to April, overlapping with the guava fruiting period. The three pest fly species were parasitized mainly by three generalist resident parasitoids, which are potential biocontrol agents to use within an integrated pest management approach.

Distribution of mudsnail Bullacta caurina along smooth cordgrass Spartina alterniflora invasion stages on a coast of the Yellow Sea, China

On a Chinese coast of the Yellow Sea, a 15-year Spartina alterniflora invasion sequence was classified into five stages: no invasion, initial invasion, immature invasion, mature invasion, and senescing invasion. The effects of invasion on Bullacta caurina distribution were studied. The stem density and vegetation coverage, and sediment organic matter content increased after S. alterniflora invaded, whereas chlorophyll a concentration and porewater salinity decreased. The stem density and vegetation coverage, and porewater salinity were the dominant factors explaining habitat variations. The invasion stages, seasons and their interaction had significant effects on B. caurina density, and the density decreased after initial invasion stage of S. alterniflora. Here, a clumped spatial distribution pattern was detected on B. caurina population. Organic matter content and chlorophyll a concentration were distinguished for predicting B. caurina density. The hydrologic condition, food resources, temperature, and predation risk comprehensively affected B. caurina distribution after S. alterniflora invasion.

Spatiotemporal organization of cryptic North American Culex species along an urbanization gradient

Landscape heterogeneity creates diverse habitat and resources for mosquito vectors of disease. A consequence may be varied distribution and abundance of vector species over space and time dependent on niche requirements.We tested the hypothesis that landscape heterogeneity driven by urbanization influences the distribution and relative abundance of Culex pipiens, Cx. restuans, and Cx. quinquefasciatus, three vectors of West Nile virus (WNv) in the eastern North American landscape. We collected 9,803 cryptic Culex from urban, suburban, and rural sites in metropolitan Washington, District of Columbia, during the months of June-October, 2019-2021. In 2021, we also collected mosquitoes in April and May to measure early-season abundance and distribution. Molecular techniques were used to identify a subset of collected Culex to species (n = 2,461). Ecological correlates of the spatiotemporal distribution of these cryptic Culex were examined using constrained and unconstrained ordination.Seasonality was not associated with Culex community composition in June-October over three years but introducing April and May data revealed seasonal shifts in community composition in the final year of our study. Culex pipiens were dominant across site types, while Cx. quinquefasciatus were associated with urban environments, and Cx. restuans were associated with rural and suburban sites. All three species rarely coexisted.Our work demonstrates that human-mediated land-use changes influence the distribution and relative abundance of Culex vectors of WNv, even on fine geospatial scales. Site classification, percent impervious surface, distance to city center, and longitude predicted Culex community composition. We documented active Culex months before vector surveillance typically commences in this region, with Culex restuans being most abundant during April and May. Active suppression of Cx. restuans in April and May could reduce early enzootic transmission, delay the seasonal spread of WNv, and thereby reduce overall WNv burden. By June, the highest risk of epizootic spillover of WNv to human hosts may be in suburban areas with high human population density and mixed Culex assemblages that can transmit WNv between birds and humans. Focusing management efforts there may further reduce human disease burden.

Deep learning enables satellite-based monitoring of large populations of terrestrial mammals across heterogeneous landscape

New satellite remote sensing and machine learning techniques offer untapped possibilities to monitor global biodiversity with unprecedented speed and precision. These efficiencies promise to reveal novel ecological insights at spatial scales which are germane to the management of populations and entire ecosystems. Here, we present a robust transferable deep learning pipeline to automatically locate and count large herds of migratory ungulates (wildebeest and zebra) in the Serengeti-Mara ecosystem using fine-resolution (38-50 cm) satellite imagery. The results achieve accurate detection of nearly 500,000 individuals across thousands of square kilometers and multiple habitat types, with an overall F1-score of 84.75% (Precision: 87.85%, Recall: 81.86%). This research demonstrates the capability of satellite remote sensing and machine learning techniques to automatically and accurately count very large populations of terrestrial mammals across a highly heterogeneous landscape. We also discuss the potential for satellite-derived species detections to advance basic understanding of animal behavior and ecology.

Geostatistical Analysis of the Spatial Variation of Chrysolina aeruginosa Larvae at Different Stages in Desert Ecosystems

Chrysolina aeruginosa is a major pest of Artemisia ordosica, and knowledge of the spatial distribution pattern of its larvae in their natural habitat is crucial for the implementation of effective control measures. This study employed geostatistical methods to investigate the damage caused by larvae of different age groups and their spatial distribution pattern. The distribution of C. aeruginosa larvae, which cause damage to A. ordosica, differed significantly according to their age. Younger larvae were predominantly found in the middle and upper parts of the plant, whereas older larvae were mainly distributed in the middle and lower parts, with significant differences in distribution location. A generalized linear model analysis revealed that the height of the plant, and plant morphological characteristics such as height, crown width, and ground diameter were significantly correlated with the number of larvae present. Furthermore, the interaction of age with other variables had an impact on the number of larvae. Kriging interpolation showed that C. aeruginosa larvae were distributed in aggregated patches with strong spatial heterogeneity. The younger larvae were more abundant in the center of the sample site, while the older larvae tended to be distributed toward the edges. These findings provide valuable information for designing effective control programs.

Climate Change Influences the Population Density and Suitable Area of Hippotiscus dorsalis (Hemiptera: Pentatomidae) in China

Hippotiscus dorsalis is the main pest of Phyllostachys edulis in South China. The relationship between climate change and outbreak of H. dorsalis, and the current and future distribution of H. dorsalis are unknown. This study aimed to confirm the effect of climate on population density and the attacked bamboo rate of H. dorsalis, using field survey data from 2005 to 2013 in Huzhou, Zhejiang Province, and to reveal the potential distribution of H. dorsalis under current and future climate conditions using the MaxEnt model. The damage investigation and distribution forecast revealed the following: (1) The mean monthly temperature and maximum temperatures were main factors affecting the population density and the attacked bamboo rate in April in the Anji county of Zhejiang Province; they are all significantly and positively correlated. (2) High suitable area will significantly expand in Anhui and Jiangxi Provinces under the future climate circumstances, and the total suitable area will present a decrease because of the precipitation restriction. The significant expansion of high suitable area in the Anhui and Jiangxi Provinces under future climate circumstances means that the affected provinces will face even greater challenges. These findings provide a theoretical basis for the early forecasting and monitoring of pest outbreaks.

A theoretical modeling framework for motile and colonial harmful algae

Climate change is leading to an increase in severity, frequency, and distribution of harmful algal blooms across the globe. For many harmful algae species in eutrophic lakes, the formation of such blooms is controlled by three factors: the lake hydrodynamics, the vertical motility of the algae organisms, and the ability of the organisms to form colonies. Here, using the common cyanobacterium Microcystis aeruginosa as an example, we develop a model that accounts for both vertical transport and colony dynamics. At the core of this treatment is a model for aggregation. For this, we used Smoluchowski dynamics containing parameters related to Brownian motion, turbulent shear, differential setting, and cell‐to‐cell adhesion. To arrive at a complete description of bloom formation, we place the Smoluchowski treatment as a reaction term in a set of one‐dimensional advection‐diffusion equations, which account for the vertical motion of the algal cells through molecular and turbulent diffusion and self‐regulating buoyant motion. Results indicate that Smoluchowski aggregation qualitatively describes the colony dynamics of M. aeruginosa. Further, the model demonstrates wind‐induced mixing is the dominant aggregation process, and the rate of aggregation is inversely proportional to algal concentration. Because blooms of Microcystis typically consist of large colonies, both of these findings have direct consequences to harmful algal bloom formation. While the theoretical framework outlined in this manuscript was derived for M. aeruginosa, both motility and colony formation are common among bloom‐forming algae. As such, this coupling of vertical transport and colony dynamics is a useful step for improving forecasts of surface harmful algal blooms.

Modeling the Influence of Abiotic and Biotic Factors on Spatial and Temporal Fluctuations of Prostephanus truncatus (Coleoptera: Bostrichidae) Populations in Mozambique

The larger grain borer, Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae), is a serious pest of stored maize in Mozambique and in other African countries. This study investigated the influence of abiotic and biotic factors on populations of P. truncatus at four sites over a two-year period (2013-2014) in Mozambique. Fourteen 250 × 250 m quadrants were selected at each site. Plant species diversity, temperature, precipitation, and relative humidity data were recorded. Pheromone-baited Uni-traps were used to monitor P. truncatus inside each quadrant. In addition, plant species were identified using visual observation and measurement of morphological features of leaves and fruits, and quantified, after which the percentage of host plant species of P. truncatus was determined out of all species in each quadrant. Multiple regression analysis and generalized linear models showed that host plant species dominance, maximum and minimum temperature, relative humidity, and rainfall influenced the variations in P. truncatus abundance. The development of these models of P. truncatus flight activity provides a baseline for further studies predicting dispersal and potential areas of invasion by this pest.

Sampling Optimization and Crop Interface Effects on Lygus lineolaris Populations in Southeastern USA Cotton

Tarnished plant bug, Lygus lineolaris (Hemiptera: Miridae), is an economically damaging pest in cotton production systems across the southern United States. We systematically scouted 120 commercial cotton fields across five southeastern states during susceptible growth stages in 2019 and 2020 to investigate sampling optimization and the effect of interface crop and landscape composition on L. lineolaris abundance. Variance component analysis determined field and within-field spatial scales, compared with agricultural district and state, accounted for more variation in L. lineolaris density using sweep net and drop cloth sampling. This result highlights the importance of field-level scouting efforts. Using within-field samples, a fixed-precision sampling plan determined 8 and 23 sampling units were needed to determine L. lineolaris population estimates with 0.25 precision for sweep net (100 sweeps per unit) and drop cloth (1.5 row-m per unit) sampling, respectively. A spatial Bayesian hierarchical model was developed to determine local landscape (<0.5 km from field edges) effects on L. lineolaris in cotton. The proportion of agricultural area and double-crop wheat and soybeans were positively associated with L. lineolaris density, and fields with more contiguous cotton areas negatively predicted L. lineolaris populations. These results will improve L. lineolaris monitoring programs and treatment management decisions in southeastern USA cotton.

Environmental spatial heterogeneity of the impacts of COVID-19 on the top-20 metropolitan cities of Asia-Pacific

This study investigated the environmental spatial heterogeneity of novel coronavirus (COVID-19) and spatial and temporal changes among the top-20 metropolitan cities of the Asia-Pacific. Remote sensing-based assessment is performed to analyze before and during the lockdown amid COVID-19 lockdown in the cities. Air pollution and mobility data of each city (Bangkok, Beijing, Busan, Dhaka, Delhi, Ho Chi Minh, Hong Kong, Karachi, Mumbai, Seoul, Shanghai, Singapore, Tokyo, Wuhan, and few others) have been collected and analyzed for 2019 and 2020. Results indicated that almost every city was impacted positively regarding environmental emissions and visible reduction were found in Aerosol Optical Depth (AOD), sulfur dioxide (SO2), carbon monoxide (CO), and nitrogen dioxide (NO2) concentrations before and during lockdown periods of 2020 as compared to those of 2019. The highest NO2 emission reduction (~ 50%) was recorded in Wuhan city during the lockdown of 2020. AOD was highest in Beijing and lowest in Colombo (< 10%). Overall, 90% movement was reduced till mid-April, 2020. A 98% reduction in mobility was recorded in Delhi, Seoul, and Wuhan. This analysis suggests that smart mobility and partial shutdown policies could be developed to reduce environmental pollutions in the region. Wuhan city is one of the benchmarks and can be replicated for the rest of the Asian cities wherever applicable.

Effects of Pure and Mixed Pine and Oak Forest Stands on Carabid Beetles

The multiple-use approach to forestry applied in Germany aims to combine timber production and habitat management by preserving specific stand structures. We selected four forest stand types comprising (i) pure oak, (ii) equal oak–pine mixtures, (iii) single tree admixtures of oak in pine forest and (iv) pure pine. We analysed the effects of stand composition parameters on species representative of the larger carabid beetles (Carabus arvensis, C. coriaceus, C. hortensis, C. violaceus, Calosoma inquisitor). The main statistical methods used were correlation analyses and generalised linear mixed models. Cal. inquisitor was observed in pure oak forests exclusively. C. coriaceus and C. hortensis were absent from pure pine stands. High activity densities of C. arvensis and C. violaceus were observed in all four forest types. When assessed at the smaller scales of species crown cover proportions and spatial tree species effect zones, C. hortensis was found to be positively related to oak trees with a regular spatial distribution, whereas C. coriaceus preferred lower and more aggregated oak tree proportions. C. violaceus showed strong sex-specific tree species affinities. Information about preferences of carabid beetles is necessary for management activities targeting the adaptation of forest structures to habitat requirements.

Dispersal in heterogeneous environments drives population dynamics and control of tsetse flies

Spatio-temporally heterogeneous environments may lead to unexpected population dynamics. Knowledge is needed on local properties favouring population resilience at large scale. For pathogen vectors, such as tsetse flies transmitting human and animal African trypanosomosis, this is crucial to target management strategies. We developed a mechanistic spatio-temporal model of the age-structured population dynamics of tsetse flies, parametrized with field and laboratory data. It accounts for density- and temperature-dependence. The studied environment is heterogeneous, fragmented and dispersal is suitability-driven. We confirmed that temperature and adult mortality have a strong impact on tsetse populations. When homogeneously increasing adult mortality, control was less effective and induced faster population recovery in the coldest and temperature-stable locations, creating refuges. To optimally select locations to control, we assessed the potential impact of treating them and their contribution to the whole population. This heterogeneous control induced a similar population decrease, with more dispersed individuals. Control efficacy was no longer related to temperature. Dispersal was responsible for refuges at the interface between controlled and uncontrolled zones, where resurgence after control was very high. The early identification of refuges, which could jeopardize control efforts, is crucial. We recommend baseline data collection to characterize the ecosystem before implementing any measures.

Spatial distribution and sample size to estimate Lycosa erythrognatha (Araneae: Lycosidae) population density overwintering

Lycosa erythrognatha Lucas, 1833 (Araneae: Lycosidae) is a predatory arthropod with potential for conservation biological control. In addition to being considered a bioindicator of environmental quality, this arthropod provides an important service for agriculture by reducing insect-pest populations. In this work we seek to understand how the plants Andropogon bicornis L., Saccharum angustifolium Nees and Eustachys retusa Lag (Poales: Poaceae) and their different clump sizes affect the population density, spatial distribution and determination of the minimum number of samples to estimate its population density during the winter. Among the evaluated host plants, S. angustifolium and A. bicornis presented higher population density than E. retusa, but we observed that the clump diameter significantly influences the population density and the minimum number of samples. We observed a gregarious behavior in plants of A. bicornis and E. retusa. For S. angustifolium, a uniform distribution was observed.

How geographic productivity patterns affect food-web evolution

It is well recognized that spatial heterogeneity and overall productivity have important consequences for the diversity and community structure of food webs. Yet, few, if any, studies have considered the effects of heterogeneous spatial distributions of primary production. Here, we theoretically investigate how the variance and autocorrelation length of primary production affect properties of evolved food webs consisting of one autotroph and several heterotrophs. We report the following findings. (1) Diversity increases with landscape variance and is unimodal in autocorrelation length. (2) Trophic level increases with landscape variance and is unimodal in autocorrelation length. (3) The extent to which the spatial distribution of heterotrophs differ from that of the autotroph increases with landscape variance and decreases with autocorrelation length. (4) Components of initial disruptive selection experienced by the ancestral heterotroph predict properties of the final evolved communities. Prior to our study reported here, several authors had hypothesized that diversity increases with the landscape variance of productivity. Our results support their hypothesis and contribute new facets by providing quantitative predictions that also account for autocorrelation length and additional properties of the evolved communities.

Spatially Explicit Changes in Potato Psyllid (Hemiptera: Triozidae) Populations in Three South Texas Potato Fields

Insect abundance is commonly recorded in the form of discrete counts taken from plants. Analyses of these counts provide information about spatial distributions and population structure. A study was conducted in the Lower Rio Grande Valley of Texas during April and May 2014 to determine how populations of potato psyllids [Bactericera cockerelli (Šulc)] within three potato fields change over time. It was found that potato psyllid populations in these potato fields frequently changed both spatially and temporally. Chi-square goodness of fit tests and Akaike's Information Criterion indicated that the frequency distributions of potato psyllid counts conformed to a negative binomial distribution, implying an aggregated spatial pattern. Variance-mean ratios were always much larger than one, also implying spatially clumped populations. However, with a few exceptions, a Spatial Analysis by Distance IndicEs analysis showed that potato psyllid counts were mostly random in space, the clumping generally occurring on individual potato plants and rarely involving groups of potato plants in close proximity. Trends in proportions of plants infested by at least one potato psyllid and the clumping parameter k were similar for all three potato fields. Potato psyllid spatial population structure is a dynamic process that involves continuous adult movements leading to substantial redistribution of potato psyllids over limited time spans of 2 to 3 d. By capturing elements of their spatial and temporal patterns of redistribution, the study reported here is a step towards a better understanding of the population dynamics and movement of potato psyllids.

Predicting impact of a biocontrol agent: integrating distribution modeling with climate-dependent vital rates

Species distribution models can predict the suitable climatic range of a potential biological control agent (BCA), but they provide little information on the BCA's potential impact. To predict high population buildup, a prerequisite of biocontrol impact, studies are needed that assess the effect of environmental factors on vital rates of a BCA across the environmental gradient of the BCA's suitable habitats, especially for the region where the BCA is considered for field release. We extended a published species distribution model with climate-dependent vital rates of Ophraella communa, a recently and accidentally introduced potential BCA of common ragweed, Ambrosia artemisiifolia in Europe. In field and laboratory experiments, we collected data on climate-dependent parameters assumed to be the most relevant for the population buildup of O. communa, i.e., temperature driving the number of generations per year and relative humidity (RH) determining egg hatching success. We found that O. communa concluded one generation in 334 cumulative degree days, and that egg hatching success strongly decreased from > 80% to < 20% when RH drops from 55% to 45% during the day. We used these values to spatially explicitly project population densities across the European range suitable for both A. artemisiifolia and the beetle and found that the present distribution of the beetle in Europe is within the range with the highest projected population growth. The highest population density of O. communa was predicted for northern Italy and parts of western Russia and western Georgia. Field observations of high impact on A. artemisiifolia with records of 80% aerial pollen reduction in the Milano area since the establishment of O. communa are in line with these predictions. The relative importance of temperature and RH on the population density of O. communa varies considerably across its suitable range in Europe. We propose that the combined statistical and mechanistic approach outlined in this paper helps to more accurately predict the potential impact of a weed BCA than a species distribution model alone. Identifying the factors limiting the population buildup of a BCA across the suitable range allows implementation of more targeted release and management strategies to optimize biocontrol efficacy.

Spatial Patterns and Sequential Sampling Plans for Estimating Densities of Stink Bugs (Hemiptera: Pentatomidae) in Soybean in the North Central Region of the United States

Stink bugs are an emerging threat to soybean (Fabales: Fabaceae) in the North Central Region of the United States. Consequently, region-specific scouting recommendations for stink bugs are needed. The aim of this study was to characterize the spatial pattern and to develop sampling plans to estimate stink bug population density in soybean fields. In 2016 and 2017, 125 fields distributed across nine states were sampled using sweep nets. Regression analyses were used to determine the effects of stink bug species [Chinavia hilaris (Say) (Hemiptera: Pentatomidae) and Euschistus spp. (Hemiptera: Pentatomidae)], life stages (nymphs and adults), and field locations (edge and interior) on spatial pattern as represented by variance-mean relationships. Results showed that stink bugs were aggregated. Sequential sampling plans were developed for each combination of species, life stage, and location and for all the data combined. Results for required sample size showed that an average of 40-42 sample units (sets of 25 sweeps) would be necessary to achieve a precision of 0.25 for stink bug densities commonly encountered across the region. However, based on the observed geographic gradient of stink bug densities, more practical sample sizes (5-10 sample units) may be sufficient in states in the southeastern part of the region, whereas impractical sample sizes (>100 sample units) may be required in the northwestern part of the region. Our findings provide research-based sampling recommendations for estimating densities of these emerging pests in soybean.

SPATIAL ASPECT OF HUNTING COOPERATION IN PREDATORS WITH HOLLING TYPE II FUNCTIONAL RESPONSE

In this paper, we have investigated a spatial predator–prey model with hunting cooperation in predators. Using linear stability analysis, we obtain the condition for diffusive instability and identify the corresponding domain in the space of controlling parameters. Using extensive numerical simulations, we obtain complex patterns, namely, spotted pattern, stripe pattern and mixed pattern in the Turing domain, by varying the hunting cooperation parameter in predators and carrying capacity of preys. The results focus on the effect of hunting cooperation in pattern dynamics of a diffusive predator–prey model and help us in better understanding of the dynamics of the predator–prey interaction in real environments.

Developing a Sampling Plan for Brown Stink Bug (Hemiptera: Pentatomidae) in Field Corn

Brown stink bug, Euschistus servus (Say), is a damaging pest of corn, Zea mays (L.), in the southeastern United States. Developing a reliable and practical sampling plan for population monitoring of this pest is essential for implementing integrated pest management measures. E. servus was sampled from commercial corn fields (n = 14) in North Carolina in 2016 and 2017. Both the adults and nymphs had a predominantly aggregated spatial distribution, estimated using the variance to mean ratio and Taylor's power law constant (b). Using the Taylor's power law constants, the optimum sample size required to estimate population density with a given level of reliability was calculated. For early vegetative stage corn (V4-V6), using whole plant visual sampling and an economic threshold density of 2 adult stink bugs per 20 plants, 27 sample units were required to estimate population density within 30% of the mean. At the same growth stage, using partial plant sampling and an economic threshold density of 1.73 adult stink bugs per 20 plants, 28 sample units were required to estimate population density with the same level of reliability. Reproductive stage corn (R1-R4) required eight sample units for whole plant sampling and nine sample units for partial plant sampling (Dx = 0.3). For E. servus adults, the partial plant sampling method was equally or more cost-reliable than the whole-plant sampling method for pest management in all corn growth stages tested.

Effects of habitat heterogeneity on epiedaphic Collembola (Arthropoda: Hexapoda) in a semiarid ecosystem in Northeast Brazil

The spatial distribution of abiotic resources and environmental conditions can vary at small scales within terrestrial ecosystems, influencing the composition of soil fauna. Epiedaphic springtails (Collembola) of a semiarid Caatinga ecosystem were studied to determine if factors related to vegetation structure, such as species richness, aerial biomass, litterfall, and soil characteristics (pH, granulometry and soil organic matter), influence species richness and abundance of this group. A total of 5,513 individuals were collected of 15 species distributed in 13 genera and 9 families. The most abundant species wereTemeritassp., with 2,086 (38% of the total abundance) individuals, andNeotropiellameridionalis(Arlé, 1939), with 1,911 (35% of the total abundance) individuals. None of the variables in the regression model were significantly related to Collembola species richness, but abundance was significantly related to plant species richness, aerial biomass and soil pH. Thus, even at a small spatial scale, habitat heterogeneity influences the epiedaphic Collembola in the Caatinga ecosystem, especially their abundance.

Herbivore-induced plant volatiles and tritrophic interactions across spatial scales

Herbivore-induced plant volatiles (HIPVs) are an important cue used in herbivore location by carnivorous arthropods such as parasitoids. The effects of plant volatiles on parasitoids have been well characterised at small spatial scales, but little research has been done on their effects at larger spatial scales. The spatial matrix of volatiles ('volatile mosaic') within which parasitoids locate their hosts is dynamic and heterogeneous. It is shaped by the spatial pattern of HIPV-emitting plants, the concentration, chemical composition and breakdown of the emitted HIPV blends, and by environmental factors such as wind, turbulence and vegetation that affect transport and mixing of odour plumes. The volatile mosaic may be exploited differentially by different parasitoid species, in relation to species traits such as sensory ability to perceive volatiles and the physical ability to move towards the source. Understanding how HIPVs influence parasitoids at larger spatial scales is crucial for our understanding of tritrophic interactions and sustainable pest management in agriculture. However, there is a large gap in our knowledge on how volatiles influence the process of host location by parasitoids at the landscape scale. Future studies should bridge the gap between the chemical and behavioural ecology of tritrophic interactions and landscape ecology.

Constant Flux of Spatial Niche Partitioning through High-Resolution Sampling of Magnetotactic Bacteria

Magnetotactic bacteria (MTB) swim along magnetic field lines in water. They are found in aquatic habitats throughout the world, yet knowledge of their spatial and temporal distribution remains limited. To help remedy this, we took MTB-bearing sediment from a natural pond, mixed the thoroughly homogenized sediment into two replicate aquaria, and then counted three dominant MTB morphotypes (coccus, spirillum, and rod-shaped MTB cells) at a high spatiotemporal sampling resolution: 36 discrete points in replicate aquaria were sampled every ∼30 days over 198 days. Population centers of the MTB coccus and MTB spirillum morphotypes moved in continual flux, yet they consistently inhabited separate locations, displaying significant anticorrelation. Rod-shaped MTB were initially concentrated toward the northern end of the aquaria, but at the end of the experiment, they were most densely populated toward the south. The finding that the total number of MTB cells increased over time during the experiment argues that population reorganization arose from relative changes in cell division and death and not from migration. The maximum net growth rates were 10, 3, and 1 doublings day-1 and average net growth rates were 0.24, 0.11, and 0.02 doublings day-1 for MTB cocci, MTB spirilla, and rod-shaped MTB, respectively; minimum growth rates for all three morphotypes were -0.03 doublings day-1 Our results suggest that MTB cocci and MTB spirilla occupy distinctly different niches: their horizontal positioning in sediment is anticorrelated and under constant flux.IMPORTANCE Little is known about the horizontal distribution of magnetotactic bacteria in sediment or how the distribution changes over time. We therefore measured three dominant magnetotactic bacterium morphotypes at 36 places in two replicate aquaria each month for 7 months. We found that the spatial positioning of population centers changed over time and that the two most abundant morphotypes (MTB cocci and MTB spirilla) occupied distinctly different niches in the aquaria. Maximum and average growth and death rates were quantified for each of the three morphotypes based on 72 sites that were measured six times. The findings provided novel insight into the differential behavior of noncultured magnetotactic bacteria.

Impact of environmental variables on Dubas bug infestation rate: A case study from the Sultanate of Oman

Date palm cultivation is economically important in the Sultanate of Oman, with significant financial investment coming from both the government and from private individuals. However, a global infestation of Dubas bug (Ommatissus lybicus Bergevin) has impacted the Middle East region, and infestations of date palms have been widespread. In this study, spatial analysis and geostatistical techniques were used to model the spatial distribution of Dubas bug infestations to (a) identify correlations between Dubas bug densities and different environmental variables, and (b) predict the locations of future Dubas bug infestations in Oman. Firstly, we considered individual environmental variables and their correlations with infestation locations. Then, we applied more complex predictive models and regression analysis techniques to investigate the combinations of environmental factors most conducive to the survival and spread of the Dubas bug. Environmental variables including elevation, geology, and distance to drainage pathways were found to significantly affect Dubas bug infestations. In contrast, aspect and hillshade did not significantly impact on Dubas bug infestations. Understanding their distribution and therefore applying targeted controls on their spread is important for effective mapping, control and management (e.g., resource allocation) of Dubas bug infestations.

Spatiotemporal dynamics of the Southern California Asian citrus psyllid (Diaphorina citri) invasion

Biological invasions are governed by spatial processes that tend to be distributed in non-random ways across landscapes. Characterizing the spatial and temporal heterogeneities of the introduction, establishment, and spread of non-native insect species is a key aspect of effectively managing their geographic expansion. The Asian citrus psyllid (Diaphorina citri), a vector of the bacterium associated with huanglongbing (HLB), poses a serious threat to commercial and residential citrus trees. In 2008, D. citri first began expanding northward from Mexico into parts of Southern California. Using georeferenced D. citri occurrence data from 2008-2014, we sought to better understand the extent of the geographic expansion of this invasive vector species. Our objectives were to: 1) describe the spatial and temporal distribution of D. citri in Southern California, 2) identify the locations of statistically significant D. citri hotspots, and 3) quantify the dynamics of anisotropic spread. We found clear evidence that the spatial and temporal distribution of D. citri in Southern California is non-random. Further, we identified the existence of statistically significant hotspots of D. citri occurrence and described the anisotropic dispersion across the Southern California landscape. For example, the dominant hotspot surrounding Los Angeles showed rapid and strongly asymmetric spread to the south and east. Our study demonstrates the feasibility of quantitative invasive insect risk assessment with the application of a spatial epidemiology framework.

Environmental Heterogeneity in Parasitoid-Host Interaction for Mutillidae (Hymenoptera: Apocrita)

Environmental heterogeneity is a major factor influencing the spatial distribution of organisms. Due to intimate relationships with their hosts, parasitic insects are inclined to be even more sensitive to variations. This study aimed to verify the relationship between spatial distribution of Mutillidae, potential hosts, and the effect of heterogeneity in the distribution of both, testing the hypotheses: i) the spatial distribution of mutillids depends on the distribution of hosts and ii) variation in environmental heterogeneity affects the distribution of both. Sampling was conducted in four fragments of the Cerrado. We collected Hymenopteran specimens from 25 plots of one hectare using 18 Malaise traps throughout one year, totalizing 32,400 trap-hours. Female Mutillidae were hand collected at all sampling points, for a total of 450 man-hours. At each hectare plot, we obtained the environmental variables from nine plots of 25 m² A total of 1,089 individuals were collected (Apidae: 311; Crabronidae: 165; Shpecidae: 84; Vespidae: 229) belonging to 127 species of potential hosts (bees and wasps) and 300 individuals (42 species) of Mutillidae. Leaf-litter depths showed significant relation in host-parasitoid distribution. The spatiotemporal distribution followed the predator-prey model for Mutillidae, and environmental heterogeneity was a factor that determined the structure of the host-parasitoid community. The results suggest an intense relationship between the Mutillidae and Crabronidae, as well as Sphecidae and two Apidae subfamilies (Halictinae and Colletinae). These families and subfamilies present behavior in which they build nests in aggregations even each female being solitary. Crabronidae is considered the best potential host for Mutillidae.

Spatio-Temporal Distribution of Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) and Pectinophora gossypiella (Saunders) (Lepidoptera: Gelechiidae) in a Cotton Production Area

Helicoverpa armigera (Hübner) and Pectinophora gossypiella (Saunders) are major pests of cotton in Greece and elsewhere. Analysing male captures in pheromone traps over two seasons, in two cotton producing sites in central Greece, the spatial and temporal variation in population dynamics were examined. In 2007, captures of male H. armigera increased in late July and maintained at high levels for 1 month and declined at the end of August. For P. gossypiella, male captures remained at low levels during summer, increased late in August, peaked at mid of September and declined toward the end of the season. In 2008, trap captures of both species increased sharply by the end of June and remained at relatively high levels until August and September for P. gossypiella and H. armigera, respectively. Spatial analysis produced a spatial trend map over space, a temporal stability map over time and a spatial and temporal trend map for both species, which could lead in separating the field into management zones, and direct control to areas that exhibit high densities of the pest population and are stable over time.

A Generic Individual-Based Spatially Explicit Model as a Novel Tool for Investigating Insect-Plant Interactions: A Case Study of the Behavioural Ecology of Frugivorous Tephritidae

Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.

Dispersal variability and associated population-level consequences in tree-killing bark beetles

BACKGROUND

Dispersal is a key process in the response of insect populations to rapidly changing environmental conditions. Variability among individuals, regarding the timing of dispersal initiation and travelled distance from source, is assumed to contribute to increased population success through risk spreading. However, experiments are often limited in studying complex dispersal interactions over space and time. By applying a local-scaled individual-based simulation model we studied dispersal and emerging infestation patterns in a host - bark beetle system (Picea abies - Ips typgraphus). More specifically, we (i) investigated the effect of individual variability in beetle physiology (flight capacity) and environmental heterogeneity (host susceptibility level) on population-level dispersal success, and (ii) elucidated patterns of spatial and/or temporal variability in individual dispersal success, host selectivity, and the resulting beetle density within colonized hosts in differently susceptible environments.

RESULTS

Individual variability in flight capacity of bark beetles causes predominantly positive effects on population-level dispersal success, yet these effects are strongly environment-dependent: Variability is most beneficial in purely resistant habitats, while positive effects are less pronounced in purely susceptible habitats, and largely absent in habitats where host susceptibility is spatially scattered. Despite success rates being highest in purely susceptible habitats, scattered host susceptibility appeared most suitable for dispersing bark beetle populations as it ensures population spread without drastically reducing success rates. At the individual level, dispersal success generally decreases with distance to source and is lowest in early flight cohorts, while host selectivity increased and colonization density decreased with increasing distance across all environments.

CONCLUSIONS

Our modelling approach is demonstrated to be a powerful tool for studying movement ecology in bark beetles. Dispersal variability largely contributes to risk spreading among individuals, and facilitates the response of populations to changing environmental conditions. Higher mortality risk suffered by a small part of the dispersing population (long-distance dispersers, pioneers) is likely paid off by reduced deferred costs resulting in fitness benefits for subsequent generations. Both, dispersal variability in space and time, and environmental heterogeneity are characterized as key features which require particular emphasis when investigating dispersal and infestation patterns in tree-killing bark beetles.

Spatial Distribution and Minimum Sample Size for Overwintering Larvae of the Rice Stem Borer Chilo suppressalis (Walker) in Paddy Fields

The rice stem borer, Chilo suppressalis (Walker), feeds almost exclusively in paddy fields in most regions of the world. The study of its spatial distribution is fundamental for designing correct control strategies, improving sampling procedures, and adopting precise agricultural techniques. Field experiments were conducted during 2011 and 2012 to estimate the spatial distribution pattern of the overwintering larvae. Data were analyzed using five distribution indices and two regression models (Taylor and Iwao). All of the indices and Taylor's model indicated random spatial distribution pattern of the rice stem borer overwintering larvae. Iwao's patchiness regression was inappropriate for our data as shown by the non-homogeneity of variance, whereas Taylor's power law fitted the data well. The coefficients of Taylor's power law for a combined 2 years of data were a = -0.1118, b = 0.9202 ± 0.02, and r (2) = 96.81. Taylor's power law parameters were used to compute minimum sample size needed to estimate populations at three fixed precision levels, 5, 10, and 25% at 0.05 probabilities. Results based on this equation parameters suggesting that minimum sample sizes needed for a precision level of 0.25 were 74 and 20 rice stubble for rice stem borer larvae when the average larvae is near 0.10 and 0.20 larvae per rice stubble, respectively.

Effect of site level environmental variables, spatial autocorrelation and sampling intensity on arthropod communities in an ancient temperate lowland woodland area

The interaction of arthropods with the environment and the management of their populations is a focus of the ecological agenda. Spatial autocorrelation and under-sampling may generate bias and, when they are ignored, it is hard to determine if results can in any way be trusted. Arthropod communities were studied during two seasons and using two methods: window and panel traps, in an area of ancient temperate lowland woodland of Zebracka (Czech Republic). The composition of arthropod communities was studied focusing on four site level variables (canopy openness, diameter in the breast height and height of tree, and water distance) and finally analysed using two approaches: with and without effects of spatial autocorrelation. I found that the proportion of variance explained by space cannot be ignored (≈20% in both years). Potential bias in analyses of the response of arthropods to site level variables without including spatial co-variables is well illustrated by redundancy analyses. Inclusion of space led to more accurate results, as water distance and tree diameter were significant, showing approximately the same ratio of explained variance and direction in both seasons. Results without spatial co-variables were much more disordered and were difficult to explain. This study showed that neglecting the effects of spatial autocorrelation could lead to wrong conclusions in site level studies and, furthermore, that inclusion of space may lead to more accurate and unambiguous outcomes. Rarefactions showed that lower sampling intensity, when appropriately designed, can produce sufficient results without exploitation of the environment.

An agent-based simulation of extirpation of Ceratitis capitata applied to invasions in California

We present an agent-based simulation (ABS) of Ceratitis capitata ("Medfly") developed for estimating the time to extirpation of this pest in areas where quarantines and eradication treatments were immediately imposed. We use the ABS, implemented in the program MED-FOES, to study seven different outbreaks that occurred in Southern California from 2008 to 2010. Results are compared with the length of intervention and quarantine imposed by the State, based on a linear developmental model (thermal unit accumulation, or "degree-day"). MED-FOES is a useful tool for invasive species managers as it incorporates more information from the known biology of the Medfly, and includes the important feature of being demographically explicit, providing significant improvements over simple degree-day calculations. While there was general agreement between the length of quarantine by degree-day and the time to extirpation indicated by MED-FOES, the ABS suggests that the margin of safety varies among cases and that in two cases the quarantine may have been excessively long. We also examined changes in the number of individuals over time in MED-FOES and conducted a sensitivity analysis for one of the outbreaks to explore the role of various input parameters on simulation outcomes. While our implementation of the ABS in this work is motivated by C. capitata and takes extirpation as a postulate, the simulation is very flexible and can be used to study a variety of questions on the invasion biology of pest insects and methods proposed to manage or eradicate such species.

Identifying environmental drivers of insect phenology across space and time: Culicoides in Scotland as a case study

Interpreting spatial patterns in the abundance of species over time is a fundamental cornerstone of ecological research. For many species, this type of analysis is hampered by datasets that contain a large proportion of zeros, and data that are overdispersed and spatially autocorrelated. This is particularly true for insects, for which abundance data can fluctuate from zero to many thousands in the space of weeks. Increasingly, an understanding of the ways in which environmental variation drives spatial and temporal patterns in the distribution, abundance and phenology of insects is required for management of pests and vector-borne diseases. In this study, we combine the use of smoothing techniques and generalised linear mixed models to relate environmental drivers to key phenological patterns of two species of biting midges, Culicoides pulicaris and C. impunctatus, of which C. pulicaris has been implicated in transmission of bluetongue in Europe. In so doing, we demonstrate analytical tools for linking the phenology of species with key environmental drivers, despite using a relatively small dataset containing overdispersed and zero-inflated data. We demonstrate the importance of landcover and climatic variables in determining the seasonal abundance of these two vector species, and highlight the need for more empirical data on the effects of temperature and precipitation on the life history traits of palearctic Culicoides spp. in Europe.

Mathematical modelling of mosquito dispersal in a heterogeneous environment

Mosquito dispersal is a key behavioural factor that affects the persistence and resurgence of several vector-borne diseases. Spatial heterogeneity of mosquito resources, such as hosts and breeding sites, affects mosquito dispersal behaviour and consequently affects mosquito population structures, human exposure to vectors, and the ability to control disease transmission. In this paper, we develop and simulate a discrete-space continuous-time mathematical model to investigate the impact of dispersal and heterogeneous distribution of resources on the distribution and dynamics of mosquito populations. We build an ordinary differential equation model of the mosquito life cycle and replicate it across a hexagonal grid (multi-patch system) that represents two-dimensional space. We use the model to estimate mosquito dispersal distances and to evaluate the effect of spatial repellents as a vector control strategy. We find evidence of association between heterogeneity, dispersal, spatial distribution of resources, and mosquito population dynamics. Random distribution of repellents reduces the distance moved by mosquitoes, offering a promising strategy for disease control.

Modelling the spread of Wolbachia in spatially heterogeneous environments

The endosymbiont Wolbachia infects a large number of insect species and is capable of rapid spread when introduced into a novel host population. The bacteria spread by manipulating their hosts' reproduction, and their dynamics are influenced by the demographic structure of the host population and patterns of contact between individuals. Reaction-diffusion models of the spatial spread of Wolbachia provide a simple analytical description of their spatial dynamics but do not account for significant details of host population dynamics. We develop a metapopulation model describing the spatial dynamics of Wolbachia in an age-structured host insect population regulated by juvenile density-dependent competition. The model produces similar dynamics to the reaction-diffusion model in the limiting case where the host's habitat quality is spatially homogeneous and Wolbachia has a small effect on host fitness. When habitat quality varies spatially, Wolbachia spread is usually much slower, and the conditions necessary for local invasion are strongly affected by immigration of insects from surrounding regions. Spread is most difficult when variation in habitat quality is spatially correlated. The results show that spatial variation in the density-dependent competition experienced by juvenile host insects can strongly affect the spread of Wolbachia infections, which is important to the use of Wolbachia to control insect vectors of human disease and other pests.

Should I stay or should I go? A habitat-dependent dispersal kernel improves prediction of movement

The analysis of animal movement within different landscapes may increase our understanding of how landscape features affect the perceptual range of animals. Perceptual range is linked to movement probability of an animal via a dispersal kernel, the latter being generally considered as spatially invariant but could be spatially affected. We hypothesize that spatial plasticity of an animal's dispersal kernel could greatly modify its distribution in time and space. After radio tracking the movements of walking insects (Cosmopolites sordidus) in banana plantations, we considered the movements of individuals as states of a Markov chain whose transition probabilities depended on the habitat characteristics of current and target locations. Combining a likelihood procedure and pattern-oriented modelling, we tested the hypothesis that dispersal kernel depended on habitat features. Our results were consistent with the concept that animal dispersal kernel depends on habitat features. Recognizing the plasticity of animal movement probabilities will provide insight into landscape-level ecological processes.