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Agro-ecosystem B. Contour maps of adult male codling moth distribution by means of kriging applied to cumulated pheromone trap counts in the eight intervals of 2002 ( • = trap location; other symbols as in Fig. 1). In each map, labels indicate the two dates of the weekly pheromone trap counts summed, and the number (n) of codling moths trapped.
Source publication
From 2000 to 2002, local distribution and dispersion patterns of the codling moth,Cydia pomonella (L.) (Lepidoptera: Tortricidae), captured in pheromone traps were investigated in two heterogeneous agro-ecosystems (A and
B) of the Molise region, in central Italy. The main objectives of this study were to determine the temporal and spatial variation...
Context in source publication
Context 1
... index Table 1 gives the Index of Patchiness values obtained from weekly codling moth catch data during the whole study period. In 2000, patchiness varied from 1.3 to 6.0 during flight I, and from 1.9 to 3.1 during flight II. In 2001, values varied from 1.3 to 6.7 during flight I, and from 1.1 to 4.8 during flight II. In 2002, patchiness varied from 1.5 to 5.7 during flight I, and from 1.3 to 3.3 during flight II. The dispersion of adult males among pheromone traps was clumped for all sampling dates. Geostatistical analysis Results of the covariance function analysis are reported in Figure 4 and Table 2. In all cases the exponential model provided the best mathematical fit (smallest indicative goodness of fit). The estimated range (distance between data pairs at which spatial independence is reached) varied among the data sets from 120 to 225 m, except for data referring to 21.V + 28.V.2002, which had a range of 450 m. Contour maps obtained by means of indicator kriging applied to the cumulative catches found during each flight period, in 2001 and 2002, are reported in Figure 2. These maps illustrate that the highest male population foci were confined to the apple orchards A1 and A2 and were always well separated. However, the distribution pattern observed within orchard A1 appeared to differ in both size and location of foci among sampling years and between flights within the same year. Figure 5 shows the trap captures obtained for each of the eight sampling periods during 2002. Throughout the year, even if isolines encompassed areas outside apple fields A1 and A2, individuals were only occasionally captured in traps between A1 and A2 and in or near other abandoned apple trees, pear trees, service trees, and wild service trees. For example, in the sampling period of flight II with the highest numbers of male codling moths (16.VIII + 23.VIII), it is possible to distinguish an infested zone that does not comprise the orchards and is located near a group of service trees. This sample site is about 130 m from the field A1. The trap placed between the apple field and service trees did not collect any adult male codling moths. Dispersion index The Index of Patchiness values calculated from weekly codling moth catch data during 2001 and 2002 are reported in Table 3. In 2001, patchiness varied from 1.3 to 2.9 during flight I, and from 2.4 to 5.5 during flight II. In 2002, values varied from 3.3 to 7.5 during flight I, and from 0.8 to 5.1 during flight II. The dispersion pattern of C. pomonella among traps was clumped for almost all sampling weeks. In fact, we have found only the sampling date 30.VIII.2002 had a patchiness less than 1 (0.8), indicating a random distribution. Geostatistical analyses Results of the covariance function analysis, reported in Figure 6 and Table 4, show that the exponential model provided the best mathematical fit in all cases considered. The estimated range varied among the data sets from 85 to 187 m. Figure 3 shows the contour maps obtained by geostatistical analyses carried out using indicator kriging applied to the cumulative catches of each flight period in 2002. The greatest portion of adult males captured was found to be limited to two zones: (i) orchard B1 and the next group of apple trees, and (ii) the zone in which there were scattered pear trees, service trees and walnut trees. These two main high population foci were always well separated. Comparing the observed distribution pattern in each flight period, the area encompassed by the contours appeared to increase during flight II. The contour maps drawn for the eight sampling intervals of 2002 are reported in Figure 7. The represented capture patterns confirmed that the highest abundance foci of the male population were confined to orchard B1 and the next group of apple trees and to the zone with pear trees, service trees and walnut trees. Males were rarely captured in orchard B2. During flight II, in the sampling period with highest numbers of catches (16.VIII + 23.VIII), the male codling moth population appeared to have the most extended distribution, with isolines encompassing areas outside the two most infested zones, but only occasionally were moths found in traps between ...
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The codling moth Cydia pomonella (L.) (Lepidoptera Tortricidae) is one of the key pests in apple and pear trees and its high harmfulness on the fruits requires a strongly effective pest management. Among the pest control strategies adopted in the years, nowadays integrated pest management (IPM) represents one of the most diffused methods and it req...
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Citations
... 29 Studies on this moth's distribution and dispersal across various landscapes suggest that local populations are influenced by surrounding landscape features. [30][31][32][33] However, for codling moth, which is a multivoltine species that has several generations during the growing season, its responses to landscape features across the whole growing season have rarely been studied. In China, codling moth is an important quarantine pest that was first reported in Xinjiang in the 1960s, where it soon posed a great threat to apple production. ...
... Some studies have reported landscape composition effects on codling moth abundance at distances below 0.5 km. 30,32 Ricci et al. found that the major effects of landscape variables on the number of codling moths were observed for distances less than 150 m from the focus orchards, likely because of the limited dispersal ability of codling moths. 31 In this study, the impacts of landscape variables on codling moth populations showed a spatial scale effect. ...
BACKGROUND
Agricultural land‐use change is an important driver of pest population dynamics, and can alter source–sink dynamics and the concentration‐dilution effects of the landscape. Understanding the effects of land use on pests at both landscape and regional levels is essential for the development of sustainable pest management strategies given the large changes occurring in cropping systems in China. At the landscape level, we investigated the impacts of landscape composition and edge density on pheromone trap catch of codling moth (Cydia pomonella) in apple orchards, in Aksu, Xinjiang, China. At the regional scale, we conducted a meta‐analysis using data from studies performed across the Aksu area in recent decades, to assess the relationship between trends in codling moth abundance and the area of apple cultivation.
RESULTS
Both extensive planting of apple and large areas of annual crops in the landscape increased the abundance of codling moth, whereas the presence of secondary host plants (peach, pear, walnut, plum, and apricot) had a negative effect. Seminatural habitats and landscape edge density did not significantly affect codling moth abundance. The responses of different generations of codling moth to landscape factors were varied. At the regional level, codling moth occurrence was positively correlated with the expansion of apple production areas.
CONCLUSION
Expansion of apple cultivation increases the abundance of codling moth in agricultural landscapes. We recommend decreasing the area devoted to monocultures of apple when designing agricultural landscapes and increasing plantings of secondary host crops to dilute and reduce the abundance of codling moth. © 2024 Society of Chemical Industry.
... Sexual competition between male codling moths can be described as a form of scramble competition [24,25]. However, the underlying codling moth populations are aggregated across different spatial and temporal scales [26,27], and the locations of these aggregations may be unknown to pest managers, making the goal of outnumbering the wild pest more challenging. As such, the OKSIR program has employed a strategy of uniformly distributing sterile insects within a given orchard [28] with varying release rates used between orchards according to their underlying wild populations [29]. ...
The codling moth is a serious pest of apples in most regions of the world where this fruit is produced. The sterile insect technique is one strategy used to control this pest and is employed as part of an area-wide integrated pest management program for the codling moth in British Columbia, Canada. Modified fixed wing aircraft are the most common method for the release of sterile insects in large area-wide pest management programs. However, aerial release with a full-size aircraft can be prohibitively expensive. We evaluated the use of small, uncrewed aircraft systems (UASs) for the release of sterile codling moths. Sterile codling moths released from greater altitudes were more broadly distributed and drifted more in strong winds, compared to those released from lower altitudes. Most of the released insects were recaptured in a 50 m wide swath under the release route. Recapture rates for aerially released insects were 40–70% higher compared to those released from the ground. UASs provide a promising alternative to ground release and conventional aircraft for the release of sterile codling moths.
... H. S., unpublished data). However, these conditions do not match those that codling moths would be likely to encounter in the field [19,45]. This background knowledge set the stage for interpreting experimental results trapping codling moths in the field under a comparable spatial setup to that of Figure 2A. ...
... We postulated that males would exhibit a mean c.s.d. falling between 30 • and 50 • , because such an intermediate value would perform reasonably well for either a dense or sparse female population, both of which can be encountered by natural codling moth populations across generations [45]. ...
Measures of path meander are highly relevant to studies of optimal foraging by animals. However, directly recording paths of small animals such as insects can be difficult because of small size or crepuscular activity. Computer simulations of correlated random walkers demonstrated that the rates of decay in captures across a rectangular grid of traps when movers were released at its corner can be used to produce calibration curves for quantifying path meander indirectly. Simulations using spatial parameters matching those previously documented for male codling moths (Cydia pomonella (L.)) foraging for female pheromone plumes in the field predicted that meander, as measured in circular standard deviation (c.s.d.) of turn angles between track segments, should be ca. 50° and 30° when the target population density is high vs. low, respectively. Thus, if optimized, the mean value measured for C. pomonella populations encountering an unknown target density should fall between these limits. We recorded decay in C. pomonella catch across a 5 × 5 grid of pheromone-baited traps each separated by 15 m on 39 occasions where batches of ca. 800 males were released 10 m outside the corner of trapping grids arranged in five large Michigan apple orchards. This decay constant was translated into mean c.s.d value for path meander using the standard curve generated by the computer simulations. The measured decay constant for C. pomonella males was negative 0.99 ± 0.02 (S.E.M.), which translates to a path meander of 37 ± 2° c.s.d. Thus, the measured path meander of 37° fell between the 50° and 30° values optimal for dense and sparse populations, respectively. In addition to providing a rare documented example of optimal foraging for odor plumes, this research offers proof-of-concept for a novel approach to quantifying path meander of movers that could prove useful across diverse taxa.
... Unmanaged orchards and backyard host trees are now known to have an impact upon an area-wide integrated pest management or AW-IPM codling moth program, with immigration occurring into orchards already under active suppression or eradication [14,15]. Spatial analyses of pheromone trap catches of codling moth in heterogeneous agro-ecosystems in Italy have also shown that trap capture foci were clumped in productive orchards and in zones containing host trees [16]. However, it is possible to eradicate codling moth. ...
Codling moth, Cydia pomonella (Lepidoptera: Tortricidae), is a phytosanitary pest of New Zealand's export apples. The sterile insect technique supplements other controls in an eradication attempt at an isolated group of orchards in Hawke's Bay, New Zealand. There has been no attempt in New Zealand to characterize potential sources of uncontrolled peri-urban populations, which we predicted to be larger than in managed orchards. We installed 200 pheromone traps across Hastings city, which averaged 0.32 moths/trap/week. We also mapped host trees around the pilot eradication orchards and installed 28 traps in rural Ongaonga, which averaged 0.59 moths/trap/week. In Hastings, traps in host trees caught significantly more males than traps in non-host trees, and spatial interpolation showed evidence of spatial clustering. Traps in orchards operating the most stringent codling moth management averaged half the catch rate of Hastings peri-urban traps. Orchards with less rigorous moth control had a 5-fold higher trap catch rate. We conclude that peri-urban populations are significant and ubiquitous, and that special measures to reduce pest prevalence are needed to achieve area-wide suppression and reduce the risk of immigration into export orchards. Because the location of all host trees in Hastings is not known, it could be more cost-effectively assumed that hosts are ubiquitous across the city and the area treated accordingly.
... 8 m away) and showed the mean dispersal distance between two oviposition sites was 30 m and the median 10 m. Geostatistical tools have been used to estimate the influence of landscape attributes on trap catch (Trematerra et al. 2004;Basoalto et al. 2010;Comas et al. 2012). A field technique which involves marking adults with low cost crude food proteins (milk, egg, wheat or soybean) and then releasing and re-capturing has been developed to study dispersal (Jones et al. 2006a,b;Basoalto et al. 2010). ...
... Dispersal from unmanaged surroundings into managed orchards is also of great relevance for insecticide resistance evolution (Fuentes-Contreras et al. 2007. Dispersal of adult CM among orchards and unmanaged hosts is affected by area and connectivity between habitat patches (Trematerra et al. 2004;Garcia-Salazar et al. 2007;Tyson et al. 2007;Ricci et al. 2009Ricci et al. , 2011, but other factors such as patch resource quality and population density may also be relevant. For example, unmanaged host plants frequently show alternate fruit bearing, and therefore likely strongly influence seasonal dispersal patterns between habitat patches (Gu et al. 2006). ...
... Landscape features could also be key to IPM programmes if they can affect a pest's dispersal behaviour. Any management decisions made therefore need to incorporate these features into developing a suitable monitoring strategy for pest populations as well as aiding the most effective precise targeted interventions (Trematerra et al., 2004). ...
Dessert apple orchards in the UK have successfully intensified their growing systems to enable a higher yield output per unit area. This agricultural intensification has allowed for more efficient crop management. However, this intensification has come at the detriment to space for non-crop vegetation in the orchards, attributed to sustaining invertebrate populations of pollinators and natural pest enemies with alternative resources and refuge. Therefore, the remaining populations of beneficial invertebrates in these systems might not be able to deliver sufficient or stable regulating ecosystem services such as pollination and pest control to the crop system.
To address this concern, I firstly carried out a survey with a select group of top-fruit growers in my study region to understand the practices and perceptions surrounding existing non-crop vegetation in orchards. Non-crop trees were already in place on farms as hedgerow or windbreak structures; however, these had rarely been designed to support beneficial invertebrates. Furthermore, various blockers for annual wildflower adoption were identified. Therefore, this knowledge contributed to the design of a novel ecological experiment to enhance apple orchard edges with perennial lavender and thyme plants. The aim was for these plants to provide successional floral resources in close vicinity to the crops to sustain pollinator populations after the mass apple bloom, whilst not deterring natural enemy populations to thrive on-site during the apple-growing season.
Orchard edges with either a mixed lavender and thyme treatment, or a lavender treatment, successfully sustained wild pollinators, such as bumblebees, in the orchards over the late summer months. The wild bee visitation rate to apple flowers in the spring also increased in orchards with a mixed orchard edge treatment. Although no repellent effects of lavender and thymes on natural enemies were found; the effects on ground or tree dwelling natural enemy populations remain uncertain due to sampling methods and agrochemical use. Aerial hoverfly abundances were higher in the orchards with a mixed lavender and thyme edge however, it would need to be confirmed that these were aphidophagous species before concluding that natural enemies with an aerial life stage, which relies on floral nectar or pollen provision, could benefit from this orchard edge enhancement. Apple yield and quality were both unaffected by orchard edge treatments in the first two years after establishment. However, pollinator exclusion experiments confirmed the necessity of pollinators to the apples to achieve good yields and quality. Therefore, any increase to wild bee abundances from the orchard edge treatments could potentially contribute stability to the pollination service delivery by buffering the natural fluctuations in pollinator populations and the potentially inconsistent pollination services from managed honeybees.
This research shows how collaborating with the select group of growers that are responsible for non-crop habitat provision and management on farms in the study region can enable the development of novel alternatives to ensure that floral resource provision is available on-site for beneficial invertebrate populations.
... Geostatistics quantifies and models spatial and temporal correlations and enable the analysis of large data series in a very short time and thus carry out large-scale studies. This technique was first developed in the field of geology and has since been applied to agriculture (Emmen, 2004), and in a number of cases it has been employed to study the spatial distribution of insects (Midgarden, Youngman & Fleischer, 1993;Ribes-Dasi, Avilla & Bascuñana, 1998;Farias et al., 2004;Boiteau, 2005;Ramirez-Davila et al., 2005;Castillo et al., 2006;Moral García et al., 2004;Trematerra, Gentile & Sciarretta., 2004;Sciarretta & Trematerra, 2006, 2014Basoalto et al., 2010;Calvo et al., 2011;Comas et al., 2012;Duarte, 2012;Duarte et al., 2015aDuarte et al., , 2015b. Spatial analysis is based on the theory of regionalized variables put forward by Matheron (1970), whereby the value of a variable at a given point is related to the value of that variable at another point nearby (Rossi et al., 1992). ...
... All factors mentioned above influence the creation of foci that could act as a source of insects or work as corridors to disperse them to other areas (Trematerra, Gentile & Sciarretta, 2004;Basoalto et al., 2010). These authors found that C. pomonella distribution appears to be structured as metapopulations in heterogeneous agro-ecosystems. ...
Geostatistics can support pest management by analyzing the spatial distribution of a pest at a local or regional level. Therefore, specific site pest control can be performed based on accurate spatio-temporal information. Cydia pomonella (L.) (Lepidoptera: Tortricidae), the most serious apple and pear pest, requires several insecticide applications to reduce injury to acceptable levels. The aim of this research was to study the temporal and spatial variation in distribution and abundance of C. pomonella in the main fruit-growing area of Uruguay. From 2007 to 2009, approximately 120 pheromone traps per year were installed in apple and pear orchards distributed over 50,000 ha, and georeferenced. Male adult captures were registered weekly from October to March. Spatial analysis of the captures was done, obtaining semivariograms for the accumulated captures analyzed by generation and by growing season. Maps were constructed based on significant models obtained, where the population level of the pest was estimated using ordinary kriging. The correlation range estimated was from 1720 to 2690 m. Hot spots of high population level and some areas with comparatively low populations were constant over the 2-year period.
... Geostatistics quantifies and models spatial and temporal correlations and enable the analysis of large data series in a very short time and thus carry out large-scale studies. This technique was first developed in the field of geology and has since been applied to agriculture (Emmen, 2004), and in a number of cases it has been employed to study the spatial distribution of insects (Midgarden, Youngman & Fleischer, 1993;Ribes-Dasi, Avilla & Bascuñana, 1998;Farias et al., 2004;Boiteau, 2005;Ramirez-Davila et al., 2005;Castillo et al., 2006;Moral García et al., 2004;Trematerra, Gentile & Sciarretta., 2004;Sciarretta & Trematerra, 2006, 2014Basoalto et al., 2010;Calvo et al., 2011;Comas et al., 2012;Duarte, 2012;Duarte et al., 2015aDuarte et al., , 2015b. Spatial analysis is based on the theory of regionalized variables put forward by Matheron (1970), whereby the value of a variable at a given point is related to the value of that variable at another point nearby (Rossi et al., 1992). ...
... All factors mentioned above influence the creation of foci that could act as a source of insects or work as corridors to disperse them to other areas (Trematerra, Gentile & Sciarretta, 2004;Basoalto et al., 2010). These authors found that C. pomonella distribution appears to be structured as metapopulations in heterogeneous agro-ecosystems. ...
In a test of fecal apparent digestibility (FAD) and protein metabolism in rearing pigs six isoproteic and isocaloric diets with different components were studied: T1 (control): corn and soybean meal (SM); T2: corn + 11 % of SM + 23 % peas (P) + 12,5 % canola expeller (C); T3: corn + 5 % of SM + 30 % P + 16.3 % C; T4: low tannin (LT) sorghum + SM; T5: LT sorghum + 13 % of SM + 13,5 % P + 15 % C; T6: LT sorghum + 5 % of SM + 35 % P + 15,3 % C. Four pigs per treatment, with an average weight of 43.43 kg, housed in individual digestibility cages were used. The experimental period comprised seven days of habituation and five days of collection. The consumption level was established to make a contribution of 2.4 times the energy requirement for maintenance. Total collection of feces and urine was performed. We determined the FAD of dry matter (DM), organic matter (OM), crude protein (CP) and gross energy (GE) as well as the apparent biological value of the protein (VB), and the apparent net protein value (NPV) of diets. LT sorghum diets were higher in FAD of the MS and EB. There were no differences in protein value between diets. We concluded that it is possible to totally replace the corn by LT sorghum in diets for growing pigs, and that the combination of peas and canola expeller can replace up to 83 % of the soybean meal maintaining the levels of lysine and sulfur amino acids, without affecting its nutritional contribution.
... There are no similar studies that would allow a direct comparison, but for poikilothermic organisms and insects in particular, moderate temperatures and rich humidity favor reproduction and development [15]. In closely related species such as the codling moth Cydia pomonella, geostatistical spatial analysis revealed that high populations are captured at sites most suitable for the pest and the host [60]. Moreover, similar spatial analysis performed in South Italy for A. lineatella and G. molesta showed that the main 'hot spot' for both lepidopterous pests was in a stone fruit orchard in the northern zone of the study area; other infested areas were in peach orchards and, in the case of A. lineatella, also in plum orchards. ...
Background
This work combines multivariate time series analysis and graph theory to detect synchronization and causality among certain ecological variables and to represent significant correlations via network projections. Four different statistical tools (cross-correlations, partial cross-correlations, Granger causality and partial Granger causality) utilized to quantify correlation strength and causality among biological entities. These indices correspond to different ways to estimate the relationships between different variables and to construct ecological networks using the variables as nodes and the indices as edges. Specifically, correlations and Granger causality indices introduce rules that define the associations (links) between the ecological variables (nodes). This approach is used for the first time to analyze time series of moth populations as well as temperature and relative humidity in order to detect spatiotemporal synchronization over an agricultural study area and to illustrate significant correlations and causality interactions via graphical models. ResultsThe networks resulting from the different approaches are trimmed and show how the network configurations are affected by each construction technique. The Granger statistical rules provide a simple test to determine whether one series (population) is caused by another series (i.e. environmental variable or other population) even when they are not correlated. In most cases, the statistical analysis and the related graphical models, revealed intra-specific links, a fact that may be linked to similarities in pest population life cycles and synchronizations. Graph theoretic landscape projections reveal that significant associations in the populations are not subject to landscape characteristics. Populations may be linked over great distances through physical features such as rivers and not only at adjacent locations in which significant interactions are more likely to appear. In some cases, incidental connections, with no ecological explanation, were also observed; however, this was expected because some of the statistical methods used to define non trivial associations show connections that cannot be interpreted phenomenologically. Conclusions
Incorporating multivariate causal interactions in a probabilistic sense comes closer to reality than doing per se binary theoretic constructs because the former conceptually incorporate the dynamics of all kinds of ecological variables within the network. The advantage of Granger rules over correlations is that Granger rules have dynamic features and provide an easy way to examine the dynamic causal relations of multiple time-series variables. The constructed networks may provide an intuitive, advantageous representation of multiple populations’ associations that can be realized within an agro-ecosystem. These relationships may be due to life cycle synchronizations, exposure to a shared climate or even more complicated ecological interactions such as moving behavior, dispersal patterns and host allocation. Moreover, they are useful for drawing inferences regarding pest population dynamics and their spatial management. Extending these models by including more variables should allow the exploration of intra and interspecies relationships in larger ecological systems, and the identification of specific population traits that might constrain their structures in larger areas.
... Indeed, animals like beetles are often caught in traps thereby disguising the beetles' spatial position at a given moment in time (Stoyan & Kuschka 2001). In such situations, the data are collected on a latticesampling basis, where the coordinates of each cell are known and the observed phenomenon is characterized by numbers of animals or area covered by plants per cell (Müller-Dombois & Ellenberg 1974, Trematerra et al. 2004. For statistical analysis it can be useful to convert the random field data to point pattern data, as described in Illian et al. (2008). ...
... In such case, it is appropriate to replace random-field patterns by point patterns. We applied a snapshot-technique here, which may be refined by spatial interpolation (e.g., kriging - Trematerra et al. 2004). However, the chosen size of the cells in our investigation (15 × 15 m) seems to be small enough to appropriately sample spatial gradients of beetles activity and density. ...
The understanding of habitat demands of single species needs an explicit habitat element approach which includes both the effect of intensity of the habitat element on the species population and the spatial effect of that habitat element in a given matrix (e.g., forest or water). An established tool in ecological research for this purpose is the point pattern analysis, which yields information on relationships between organisms and habitat elements, as well as on interactions among individuals. However, the application of this tool seems to be restricted so far to locally fixed species and habitat elements. As our model system consists of carabid beetles and single old oak trees in a Scots pine forest, we needed to address the issue of fauna mobility in point pattern analysis. We adopted a random field approach to transform the lattice beetle traps data to point data. For the resulting bivariate point pattern we applied the toroidal shift test to verify the independence of tree and beetle distribution. To overcome the problem of irregular window shape, we reconstructed the oak data to obtain a point pattern in a larger rectangular window to make toroidal shifts possible. We could justify a positive spatial association between oak tree and carabid beetle distributions. By our results, specific spatial fields of oak influence on the beetle species can be derived which may allow for beetles supporting management measures like an increase of oak tree proportion and a more regular spatial distribution of single admixed oak trees. Those measures may increase the ecological effect of C. coriaceus as an antagonist for pest insects in mono-cultured Scots pine forests.
