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

Cold winters drive consistent and spatially synchronous 8-year population cycles of cabbage stem flea beetle

Population cycles have been observed in mammals as well as insects, but consistent population cycling has rarely been documented in agroecosystems and never for a beetle. We analysed the long-term population patterns of the cabbage stem flea beetle Psylliodes chrysocephala in winter oilseed rape over 50 years. Psylliodes chrysocephala larval density from 3045 winter oilseed rape fields in southern Sweden showed strong 8-year population cycles in regional mean density. Fluctuations in larval density were synchronous over time across five subregional populations. Subregional mean environmental variables explained 90.6% of the synchrony in P. chrysocephala populations at the 7-11 year time-scale. The number of days below -10°C showed strong anti-phase coherence with larval densities in the 7-11 year time-scale, such that more cold days resulted in low larval densities. High levels of the North Atlantic Oscillation weather system are coherent and anti-phase with cold weather in Scania, Sweden. At the field-scale, later crop planting date and more cold winter days were associated with decreased overwintering larval density. Warmer autumn temperatures, resulting in greater larval accumulated degree days early in the season, increased overwintering larval density. Despite variation in environmental conditions and crop management, 8-year cycles persisted for cabbage stem flea beetle throughout the 50 years of data collection. Moran effects, influenced by the North Atlantic Oscillation weather patterns, are the primary drivers of this cycle and synchronicity. Insect pest data collected in commercial agriculture fields is an abundant source of long-term data. We show that an agricultural pest can have the same periodic population cycles observed in perennial and unmanaged ecosystems. This unexpected finding has implications for sustainable pest management in agriculture and shows the value of long-term pest monitoring projects as an additional source of time-series data to untangle the drivers of population cycles.

Evaluating the Quality of Ecoinformatics Data Derived From Commercial Agriculture: A Repeatability Analysis of Pest Density Estimates

Each year, consultants and field scouts working in commercial agriculture undertake a massive, decentralized data collection effort as they monitor insect populations to make real-time pest management decisions. These data, if integrated into a database, offer rich opportunities for applying big data or ecoinformatics methods in agricultural entomology research. However, questions have been raised about whether or not the underlying quality of these data is sufficiently high to be a foundation for robust research. Here I suggest that repeatability analysis can be used to quantify the quality of data collected from commercial field scouting, without requiring any additional data gathering by researchers. In this context, repeatability quantifies the proportion of total variance across all insect density estimates that is explained by differences across populations and is thus a measure of the underlying reliability of observations. Repeatability was moderately high for cotton fields scouted commercially for total Lygus hesperus Knight densities (R = 0.631) and further improved by accounting for observer effects (R = 0.697). Repeatabilities appeared to be somewhat lower than those computed for a comparable, but much smaller, researcher-generated data set. In general, the much larger sizes of ecoinformatics data sets are likely to more than compensate for modest reductions in measurement precision. Tools for evaluating data quality are important for building confidence in the growing applications of ecoinformatics methods.

Population spatial synchrony enhanced by periodicity and low detuning with environmental forcing

Explaining why fluctuations in abundances of spatially disjunct populations often are correlated through time is a major goal of population ecologists. We address two hypotheses receiving little to no testing in wild populations: (i) that population cycling facilitates synchronization given weak coupling among populations, and (ii) that the ability of periodic external forces to synchronize oscillating populations is a function of the mismatch in timescales (detuning) between the force and the population. Here, we apply new analytical methods to field survey data on gypsy moth outbreaks. We report that at timescales associated with gypsy moth outbreaks, spatial synchrony increased with population periodicity via phase locking. The extent to which synchrony in temperature and precipitation influenced population synchrony was associated with the degree of mismatch in dominant timescales of oscillation. Our study provides new empirical methods and rare empirical evidence that population cycling and low detuning can promote population spatial synchrony.

Ecoinformatics (Big Data) for Agricultural Entomology: Pitfalls, Progress, and Promise

Ecoinformatics, as defined in this review, is the use of preexisting data sets to address questions in ecology. We provide the first review of ecoinformatics methods in agricultural entomology. Ecoinformatics methods have been used to address the full range of questions studied by agricultural entomologists, enabled by the special opportunities associated with data sets, nearly all of which have been observational, that are larger and more diverse and that embrace larger spatial and temporal scales than most experimental studies do. We argue that ecoinformatics research methods and traditional, experimental research methods have strengths and weaknesses that are largely complementary. We address the important interpretational challenges associated with observational data sets, highlight common pitfalls, and propose some best practices for researchers using these methods. Ecoinformatics methods hold great promise as a vehicle for capitalizing on the explosion of data emanating from farmers, researchers, and the public, as novel sampling and sensing techniques are developed and digital data sharing becomes more widespread.

Landscape Diversity and Crop Vigor Influence Biological Control of the Western Grape Leafhopper (E. elegantula Osborn) in Vineyards

This study evaluated how the proportional area of natural habitat surrounding a vineyard (i.e. landscape diversity) worked in conjunction with crop vigor, cultivar and rootstock selection to influence biological control of the western grape leafhopper (Erythroneura elegantula Osborn). The key natural enemies of E. elegantula are Anagrus erythroneurae S. Trjapitzin & Chiappini and A. daanei Triapitsyn, both of which are likely impacted by changes in landscape diversity due to their reliance on non-crop habitat to successfully overwinter. Additionally, E. elegantula is sensitive to changes in host plant quality which may influence densities on specific cultivars, rootstocks and/or vines with increased vigor. From 2010–2013, data were collected on natural enemy and leafhopper densities, pest parasitism rates and vine vigor from multiple vineyards that represented a continuum of landscape diversity. Early in the season, vineyards in more diverse landscapes had higher Anagrus spp. densities and lower E. elegantula densities, which led to increased parasitism of E. elegantula. Although late season densities of E. elegantula tended to be lower in vineyards with higher early season parasitism rates and lower total petiole nitrogen content, they were also affected by rootstock and cultivar. While diverse landscapes can support higher natural enemy populations, which can lead to increased biological control, leafhopper densities also appear to be mediated by cultivar, rootstock and vine vigor.

Diversity and abundance of leafhoppers in Canadian vineyards

Leafhoppers (Hemiptera: Cicadellidae) are pests of many temperate crops, including grapevines (Vitis species). Uncontrolled populations can induce direct and indirect damage to crops due to feeding that results in significant yield losses and increased mortality in infected vineyards due to virus, bacteria, or phytoplasmas vectored by leafhoppers. The main objective of this work was to determine the diversity of leafhoppers found in vineyards of the three main Canadian production provinces, i.e., in British Columbia, Ontario, and Quebec. Approximately 18,000 specimens were collected in 80 commercial vineyards from 2006 to 2008. We identified 54 genera and at least 110 different species associated with vineyards, among which 22 were predominant and represented more than 91% of all the leafhoppers. Species richness and diversity were estimated by both Shannon's and Pielou's indices. For each province, results indicated a temporal variation in species composition. Color photographs provide a tool to quickly identify 72 leafhoppers commonly associated with vineyards.

Ecoinformatics can reveal yield gaps associated with crop-pest interactions: a proof-of-concept

Farmers and private consultants execute a vast, decentralized data collection effort with each cropping cycle, as they gather pest density data to make real-time pest management decisions. Here we present a proof of concept for an ecoinformatics approach to pest management research, which attempts to harness these data to answer questions about pest-crop interactions. The impact of herbivory by Lygus hesperus on cotton is explored as a case study. Consultant-derived data satisfied a 'positive control' test for data quality by clearly resolving the expected negative relationship between L. hesperus density and retention of flower buds. The enhanced statistical power afforded by the large ecoinformatics dataset revealed an early-season window of crop sensitivity, during which L. hesperus densities as low as 1-2 per sample were associated with yield loss. In contrast, during the mid-season insecticide use by farmers was often unnecessary, as cotton compensated fully for moderate L. hesperus densities. Because the dataset emerged from the commercial production setting, it also revealed the limited degree to which farmers were willing to delay crop harvest to provide opportunities for compensatory fruiting. Observational approaches to pest management research have strengths and weaknesses that complement those of traditional, experimental approaches; combining these methods can contribute to enhanced agricultural productivity.

Nonlinear effect of dispersal rate on spatial synchrony of predator-prey cycles

Spatially-separated populations often exhibit positively correlated fluctuations in abundance and other population variables, a phenomenon known as spatial synchrony. Generation and maintenance of synchrony requires forces that rapidly restore synchrony in the face of desynchronizing forces such as demographic and environmental stochasticity. One such force is dispersal, which couples local populations together, thereby synchronizing them. Theory predicts that average spatial synchrony can be a nonlinear function of dispersal rate, but the form of the dispersal rate-synchrony relationship has never been quantified for any system. Theory also predicts that in the presence of demographic and environmental stochasticity, realized levels of synchrony can exhibit high variability around the average, so that ecologically-identical metapopulations might exhibit very different levels of synchrony. We quantified the dispersal rate-synchrony relationship using a model system of protist predator-prey cycles in pairs of laboratory microcosms linked by different rates of dispersal. Paired predator-prey cycles initially were anti-synchronous, and were subject to demographic stochasticity and spatially-uncorrelated temperature fluctuations, challenging the ability of dispersal to rapidly synchronize them. Mean synchrony of prey cycles was a nonlinear, saturating function of dispersal rate. Even extremely low rates of dispersal (<0.4% per prey generation) were capable of rapidly bringing initially anti-synchronous cycles into synchrony. Consistent with theory, ecologically-identical replicates exhibited very different levels of prey synchrony, especially at low to intermediate dispersal rates. Our results suggest that even the very low rates of dispersal observed in many natural systems are sufficient to generate and maintain synchrony of cyclic population dynamics, at least when environments are not too spatially heterogeneous.

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

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

Understanding long-term fruit fly (Diptera: Tephritidae) population dynamics: implications for areawide management

Fruit flies (Diptera: Tephritidae) are devastating agricultural pests worldwide but studies on their long-term population dynamics are sparse. Our aim was to determine the mechanisms driving long-term population dynamics as a prerequisite for ecologically based areawide pest management. The population density of three pestiferous Anastrepha species [Anastrepha ludens (Loew), Anastrepha obliqua (Macquart), and Anastrepha serpentina (Wiedemann)] was determined in grapefruit (Citrus x paradisi Macfad.), mango (Mangifera indica L.), and sapodilla [Manilkara zapota (L.) P. Royen] orchards in central Veracruz, México, on a weekly basis over an 11-yr period. Fly populations exhibited relatively stable dynamics over time. Population dynamics were mainly driven by a direct density-dependent effect and a seasonal feedback process. We discovered direct and delayed influences that were correlated with both local (rainfall and air temperature) and global climatic variation (El Niño Southern Oscillation [ENSO] and North Atlantic Oscillation [NAO]), and detected differences among species and location of orchards with respect to the magnitude and nature (linear or nonlinear) of the observed effects, suggesting that highly mobile pest outbreaks become uncertain in response to significant climatic events at both global and local levels. That both NAO and ENSO affected Anastrepha population dynamics, coupled with the high mobility of Anastrepha adults and the discovery that when measured as rate of population change, local population fluctuations exhibited stable dynamics over time, suggests potential management scenarios for the species studied lie beyond the local scale and should be approached from an areawide perspective. Localized efforts, from individual growers will probably prove ineffective, and nonsustainable.

Challenges to assessing connectivity between massive populations of the Australian plague locust

Linking demographic and genetic dispersal measures is of fundamental importance for movement ecology and evolution. However, such integration can be difficult, particularly for highly fecund species that are often the target of management decisions guided by an understanding of population movement. Here, we present an example of how the influence of large population sizes can preclude genetic approaches from assessing demographic population structuring, even at a continental scale. The Australian plague locust, Chortoicetes terminifera, is a significant pest, with populations on the eastern and western sides of Australia having been monitored and managed independently to date. We used microsatellites to assess genetic variation in 12 C. terminifera population samples separated by up to 3000 km. Traditional summary statistics indicated high levels of genetic diversity and a surprising lack of population structure across the entire range. An approximate Bayesian computation treatment indicated that levels of genetic diversity in C. terminifera corresponded to effective population sizes conservatively composed of tens of thousands to several million individuals. We used these estimates and computer simulations to estimate the minimum rate of dispersal, m, that could account for the observed range-wide genetic homogeneity. The rate of dispersal between both sides of the Australian continent could be several orders of magnitude lower than that typically considered as required for the demographic connectivity of populations.

Ecoinformatics for integrated pest management: expanding the applied insect ecologist's tool-kit

Experimentation has been the cornerstone of much of integrated pest management (IPM) research. Here, we aim to open a discussion on the possible merits of expanding the use of observational studies, and in particular the use of data from farmers or private pest management consultants in "ecoinformatics" studies, as tools that might complement traditional, experimental research. The manifold advantages of experimentation are widely appreciated: experiments provide definitive inferences regarding causal relationships between key variables, can produce uniform and high-quality data sets, and are highly flexible in the treatments that can be evaluated. Perhaps less widely considered, however, are the possible disadvantages of experimental research. Using the yield-impact study to focus the discussion, we address some reasons why observational or ecoinformatics approaches might be attractive as complements to experimentation. A survey of the literature suggests that many contemporary yield-impact studies lack sufficient statistical power to resolve the small, but economically important, effects on crop yield that shape pest management decision-making by farmers. Ecoinformatics-based data sets can be substantially larger than experimental data sets and therefore hold out the promise of enhanced power. Ecoinformatics approaches also address problems at the spatial and temporal scales at which farming is conducted, can achieve higher levels of "external validity," and can allow researchers to efficiently screen many variables during the initial, exploratory phases of research projects. Experimental, observational, and ecoinformatics-based approaches may, if used together, provide more efficient solutions to problems in pest management than can any single approach, used in isolation.