Field-scale roles of density, temperature, nitrogen, and predation on aphid population dynamics

Leveraging satellite observations to reveal ecological drivers of pest densities across landscapes

Landscape ecologists have long suggested that pest abundances increase in simplified, monoculture landscapes. However, tests of this theory often fail to predict pest population sizes in real-world agricultural fields. These failures may arise not only from variation in pest ecology, but also from the widespread use of categorical land-use maps that do not adequately characterize habitat-availability for pests. We used 1163 field-year observations of Lygus hesperus (Western Tarnished Plant Bug) densities in California cotton fields to determine whether integrating remotely-sensed metrics of vegetation productivity and phenology into pest models could improve pest abundance analysis and prediction. Because L. hesperus often overwinters in non-crop vegetation, we predicted that pest abundances would peak on farms surrounded by more non-crop vegetation, especially when the non-crop vegetation is initially productive but then dries down early in the year, causing the pest to disperse into cotton fields. We found that the effect of non-crop habitat on pest densities varied across latitudes, with a positive relationship in the north and a negative one in the south. Aligning with our hypotheses, models predicted that L. hesperus densities were 35 times higher on farms surrounded by high versus low productivity non-crop vegetation (EVI area 350 vs. 50) and 2.8 times higher when dormancy occurred earlier versus later in the year (May 15 vs. June 30). Despite these strong and significant effects, we found that integrating these remote-sensing variables into land-use models only marginally improved pest density predictions in cotton compared to models with categorical land cover metrics alone. Together, our work suggests that the remote sensing variables analyzed here can advance our understanding of pest ecology, but not yet substantively increase the accuracy of pest abundance predictions.

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.

Improving inference for nonlinear state-space models of animal population dynamics given biased sequential life stage data

State‐space models (SSMs) are a popular tool for modeling animal abundances. Inference difficulties for simple linear SSMs are well known, particularly in relation to simultaneous estimation of process and observation variances. Several remedies to overcome estimation problems have been studied for relatively simple SSMs, but whether these challenges and proposed remedies apply for nonlinear stage‐structured SSMs, an important class of ecological models, is less well understood. Here we identify improvements for inference about nonlinear stage‐structured SSMs fit with biased sequential life stage data. Theoretical analyses indicate parameter identifiability requires covariates in the state processes. Simulation studies show that plugging in externally estimated observation variances, as opposed to jointly estimating them with other parameters, reduces bias and standard error of estimates. In contrast to previous results for simple linear SSMs, strong confounding between jointly estimated process and observation variance parameters was not found in the models explored here. However, when observation variance was also estimated in the motivating case study, the resulting process variance estimates were implausibly low (near‐zero). As SSMs are used in increasingly complex ways, understanding when inference can be expected to be successful, and what aids it, becomes more important. Our study illustrates (a) the need for relevant process covariates and (b) the benefits of using externally estimated observation variances for inference about nonlinear stage‐structured SSMs.

Disease, contagious cannibalism, and associated population crash in an omnivorous bug, Geocoris pallens

Disease and cannibalism are two strongly density-dependent processes that can suppress predator populations. Here we show that California populations of the omnivorous predatory bug Geocoris pallens are subject to infection by a pathogen, as yet unidentified, that elicits elevated expression of cannibalism. Laboratory experiments showed that the pathogen is moderately virulent, causing flattened abdomens, elevated nymphal mortality, delayed development, and reduced body size of adult females. Infection furthermore increases the expression of cannibalism. Field populations of Geocoris spp. declined strongly in association with sharp increases in the expression of egg cannibalism by adult G. pallens. Increased cannibalism was accompanied by a strongly bimodal distribution of cannibalism expression, with some females (putatively uninfected) expressing little cannibalism and others (putatively infected) consuming most or all of the eggs present. Highly cannibalistic females did not increase their consumption of Ephestia cautella moth eggs, suggesting that the high cannibalism phenotype reflected a specific loss of restraint against eating conspecifics. Highly cannibalistic females also often exhibited reduced egg laying, consistent with a virulent pathogen; less frequently, more cannibalistic females exhibited elevated egg laying, suggesting that cannibalism might also facilitate recycling of nutrients in eggs. Elevated cannibalism was not correlated with reduced prey availability or elevated field densities of G. pallens. Geocoris pallens population crashes appear to reflect the combined consequences of direct virulence-adverse pathogen effects on the infected host's physiology-and indirect virulence-mortality of both infected and uninfected individuals due to elevated cannibalism expression by infected individuals.

Spatial climate patterns explain negligible variation in strength of compensatory density feedbacks in birds and mammals

The use of long-term population data to separate the demographic role of climate from density-modified demographic processes has become a major topic of ecological investigation over the last two decades. Although the ecological and evolutionary mechanisms that determine the strength of density feedbacks are now well understood, the degree to which climate gradients shape those processes across taxa and broad spatial scales remains unclear. Intuitively, harsh or highly variable environmental conditions should weaken compensatory density feedbacks because populations are hypothetically unable to achieve or maintain densities at which social and trophic interactions (e.g., competition, parasitism, predation, disease) might systematically reduce population growth. Here we investigate variation in the strength of compensatory density feedback, from long-term time series of abundance over 146 species of birds and mammals, in response to spatial gradients of broad-scale temperature precipitation variables covering 97 localities in 28 countries. We use information-theoretic metrics to rank phylogenetic generalized least-squares regression models that control for sample size (time-series length) and phylogenetic non-independence. Climatic factors explained < 1% of the remaining variation in density-feedback strength across species, with the highest non-control, model-averaged effect sizes related to extreme precipitation variables. We could not link our results directly to other published studies, because ecologists use contrasting responses, predictors and statistical approaches to correlate density feedback and climate--at the expense of comparability in a macroecological context. Censuses of multiple populations within a given species, and a priori knowledge of the spatial scales at which density feedbacks interact with climate, seem to be necessary to determine cross-taxa variation in this phenomenon. Despite the availability of robust modelling tools, the appropriate data have not yet been gathered for most species, meaning that we cannot yet make any robust generalisations about how demographic feedbacks interact with climate.

Differential population responses of native and alien rodents to an invasive predator, habitat alteration and plant masting

Invasive species and anthropogenic habitat alteration are major drivers of biodiversity loss. When multiple invasive species occupy different trophic levels, removing an invasive predator might cause unexpected outcomes owing to complex interactions among native and non-native prey. Moreover, external factors such as habitat alteration and resource availability can affect such dynamics. We hypothesized that native and non-native prey respond differently to an invasive predator, habitat alteration and bottom-up effects. To test the hypothesis, we used Bayesian state-space modelling to analyse 8-year data on the spatio-temporal patterns of two endemic rat species and the non-native black rat in response to the continual removal of the invasive small Indian mongoose on Amami Island, Japan. Despite low reproductive potentials, the endemic rats recovered better after mongoose removal than did the black rat. The endemic species appeared to be vulnerable to predation by mongooses, whose eradication increased the abundances of the endemic rats, but not of the black rat. Habitat alteration increased the black rat's carrying capacity, but decreased those of the endemic species. We propose that spatio-temporal monitoring data from eradication programmes will clarify the underlying ecological impacts of land-use change and invasive species, and will be useful for future habitat management.

Effects of combining an intraguild predator with a cannibalistic intermediate predator on a species-level trophic cascade

A greater diversity of natural enemies can in some cases disrupt prey suppression, particularly when natural enemies engage in intraguild predation, where natural enemies compete with and prey upon each other. However, empirical studies have often demonstrated enhanced prey suppression despite intraguild predation. A recent theoretical study proposed the hypothesis that, when the intermediate predator is cannibalistic, intraguild predation can reduce cannibalism within the intermediate predator population, leading to little change in intermediate predator mortality and thus enhanced prey suppression. The goal of this study was to examine this hypothesis empirically. Two summer-long field enclosure experiments were conducted in cotton fields. We investigated the effects of adding an intraguild predator, Zelus renardii, on (1) the abundance of a cannibalistic intermediate predator, Geocoris pallens, (2) the abundance of a herbivore, Lygus hesperus, and (3) cotton plant performance. G. pallens adult abundance did not increase, even when food availability was high and natural enemies were absent, suggesting that density-dependent cannibalism imposes an upper limit on its densities. Furthermore, although Z. renardii is an intraguild predator of G. pallens, G. pallens long-term densities were unaffected by Z. renardii. In the presence of the intermediate predator, the addition of the intraguild predator Z. renardii enhanced suppression of L. hesperus, and there were suggestions that Z. renardii and G. pallens partitioned the L. hesperus population. Effects of herbivore suppression cascaded to the plant level, improving plant performance. In conclusion, we provide empirical support for the hypothesis that the addition of an intraguild predator may enhance prey suppression if the intermediate predator expresses density-dependent cannibalism. Intraguild predation and cannibalism co-occur in many communities; thus their joint effects may be broadly important in shaping predator effects on herbivores and plant performance.

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

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