@article{humphreys_srygley_lawton_hudson_branson_2022, title={Grasshoppers exhibit asynchrony and spatial non-stationarity in response to the El Nino/Southern and Pacific Decadal Oscillations}, volume={471}, ISSN={["1872-7026"]}, DOI={10.1016/j.ecolmodel.2022.110043}, abstractNote={Grasshoppers are preeminent herbivores and perhaps the most significant rangeland pests in the United States (US). Despite the important ecosystem functions they provide, grasshopper populations often obtain densities that cause significant economic harm to grazing operations and agricultural production. Although numerous studies conducted at the level of individual field sites have examined potential mechanisms contributing to grasshopper population “boom and bust” cycles, there has yet to be a large, regional scaled analysis that quantified grasshopper variation across the Western US as a whole. While taking steps to account for data collection biases, mediating effects, and variable confounding, we assessed the influence of Pacific Ocean sea surface temperature oscillations on a 40-year record of grasshopper density in the Western US. Central to our analysis was employing spatially varying coefficients to model time and location-specific variation in grasshopper response to climate. Our results quantitatively demonstrated interannual changes in grasshopper density to be indirectly effected by seasonal El Niño/Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) variability and to exhibit spatial asynchrony and non-stationarity such that the relative influence of climate on grasshopper density varied through time and across geographic space. Our model is the first to incorporate climate indices as spatially varying coefficients for assessment of a terrestrial species and represents a critical step towards understanding causal drivers of regional grasshopper density.}, journal={ECOLOGICAL MODELLING}, author={Humphreys, John M. and Srygley, Robert B. and Lawton, Douglas and Hudson, Amy R. and Branson, David H.}, year={2022}, month={Sep} }
 @article{lawton_huseth_kennedy_morey_hutchison_reisig_dorman_dillard_venette_groves_et al._2022, title={Pest population dynamics are related to a continental overwintering gradient}, volume={119}, ISSN={0027-8424 1091-6490}, url={http://dx.doi.org/10.1073/pnas.2203230119}, DOI={10.1073/pnas.2203230119}, abstractNote={
            Overwintering success is an important determinant of arthropod populations that must be considered as climate change continues to influence the spatiotemporal population dynamics of agricultural pests. Using a long-term monitoring database and biologically relevant overwintering zones, we modeled the annual and seasonal population dynamics of a common pest,
            Helicoverpa zea
            (Boddie), based on three overwintering suitability zones throughout North America using four decades of soil temperatures: the southern range (able to persist through winter), transitional zone (uncertain overwintering survivorship), and northern limits (unable to survive winter). Our model indicates
            H. zea
            population dynamics are hierarchically structured with continental-level effects that are partitioned into three geographic zones. Seasonal populations were initially detected in the southern range, where they experienced multiple large population peaks. All three zones experienced a final peak between late July (southern range) and mid-August to mid-September (transitional zone and northern limits). The southern range expanded by 3% since 1981 and is projected to increase by twofold by 2099 but the areas of other zones are expected to decrease in the future. These changes suggest larger populations may persist at higher latitudes in the future due to reduced low-temperature lethal events during winter. Because
            H. zea
            is a highly migratory pest, predicting when populations accumulate in one region can inform synchronous or lagged population development in other regions. We show the value of combining long-term datasets, remotely sensed data, and laboratory findings to inform forecasting of insect pests.
          }, number={37}, journal={Proceedings of the National Academy of Sciences}, publisher={Proceedings of the National Academy of Sciences}, author={Lawton, Douglas and Huseth, Anders S. and Kennedy, George G. and Morey, Amy C. and Hutchison, William D. and Reisig, Dominic D. and Dorman, Seth J. and Dillard, DeShae and Venette, Robert C. and Groves, Russell L. and et al.}, year={2022}, month={Sep} }
 @article{lawton_scarth_deveson_piou_spessa_waters_cease_2022, title={Seeing the locust in the swarm: accounting for spatiotemporal hierarchy improves ecological models of insect populations}, ISSN={["1600-0587"]}, DOI={10.1111/ecog.05763}, abstractNote={Ecological phenomena operate at different spatial scales and are not uniform across landscapes or through time. One ecological theory that attempts to account for scaling and spatiotemporal variances is hierarchical patch dynamics. It introduces a hierarchical patch network with smaller spatiotemporal scales being nested within larger scales. However, few studies have modeled its presence within animal population dynamics. Locusts are an excellent model for investigating the spatiotemporal hierarchy of animal population dynamics, due to their high migratory capacity, large geographic ranges that extend across widely differing environments, and available long‐term data on distributions. Here, we investigated the influence of preceding vegetation growth on desert locust Schistocerca gregaria and Australian plague locust Chortoicetes terminifera outbreaks on three spatial levels (species range > geographic region > land unit) and between seasons. Both species are dryland herbivores with population dynamics linked to habitat productivity pulses after rain. We used NDVI data (MODIS imagery) as a measure of vegetation growth in hierarchical generalized additive models at different scales. Locust outbreaks were either preceded by vegetation growth between 78 and 32 days (Australian plague locusts) or 32 and 20 days before (desert locust) the observation. Although prior vegetation growth characterized outbreaks of both species, the temporal pattern of NDVI differed between spatiotemporal levels. All model selection criteria selected for a similar spatial hierarchy for both species: geographic region > land unit which supports the hierarchical patch dynamics paradigm. Further, it illuminates important timing differences between geographic regions and land units for preceding vegetation growth and locust outbreaks which can help locust managers identify when and where outbreaks occur. By acknowledging the spatiotemporal patterning of locust abundance, we account for heterogeneity of population dynamics throughout species ranges. Our findings demonstrate the importance of incorporating spatiotemporal variation in population models of insects and other animals.}, journal={ECOGRAPHY}, author={Lawton, Douglas and Scarth, Peter and Deveson, Edward and Piou, Cyril and Spessa, Allan and Waters, Cathy and Cease, Arianne J.}, year={2022}, month={Jan} }