From pest data to abundance‐based risk maps combining eco‐physiological knowledge, weather, and habitat variability

Abstract

Noxious species, i.e., crop pest or invasive alien species, are major threats to both natural and managed ecosystems. Invasive pests are of special importance, and knowledge about their distribution and abundance is fundamental to minimize economic losses and prioritize management activities. Occurrence models are a common tool used to identify suitable zones and map priority areas (i.e., risk maps) for noxious species management, although they provide a simplified description of species dynamics (i.e., no indication on species density). An alternative is to use abundance models, but translating abundance data into risk maps is often challenging. Here, we describe a general framework for generating abundance-based risk maps using multi-year pest data. We used an extensive data set of 3968 records collected between 2003 and 2013 in Wisconsin during annual surveys of soybean aphid (SBA), an exotic invasive pest in this region. By using an integrative approach, we modelled SBA responses to weather, seasonal, and habitat variability using generalized additive models (GAMs). Our models showed good to excellent performance in predicting SBA occurrence and abundance (TSS = 0.70, AUC = 0.92; R = 0.63). We found that temperature, precipitation, and growing degree days were the main drivers of SBA trends. In addition, a significant positive relationship between SBA abundance and the availability of overwintering habitats was observed. Our models showed aphid populations were also sensitive to thresholds associated with high and low temperatures, likely related to physiological tolerances of the insects. Finally, the resulting aphid predictions were integrated using a spatial prioritization algorithm ("Zonation") to produce an abundance-based risk map for the state of Wisconsin that emphasized the spatiotemporal consistency and magnitude of past infestation patterns. This abundance-based risk map can provide information on potential foci of pest outbreaks where scouting efforts and prophylactic measures should be concentrated. The approach we took is general, relatively simple, and can be applied to other species, habitats and geographical areas for which species abundance data and biotic and abiotic data are available.

Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes

“…For example, similar results on the relationships between S. rubrovittatus abundance and landscape factors at similar spatial scales were reported in two independent regions, which were 300 km apart (Yasuda et al 2011;Takada et al 2012). Over large areas of hundreds of kilometers, previous studies have shown common patterns in the response of landscape factors and biological responses of arthropods (Gardiner et al 2009;Lacasella et al 2017;Zhang et al 2018), although there was no attempt to extrapolate using empirical validation like the current study. Therefore, the adjusted predictive model may be able to extrapolate even further from the area of current study if the environmental and biological context is similar.…”

“…S6), indicating regional and other related factors, which were not dealt with in this study, affecting the model tting. (Lacasella et al 2017), which is reasonable to explain the population dynamics of poikilothermic organisms. Previous studies of rice-attacking pentatomids in Japan suggested that temperature of rice heading season and grain growing season have a positive effect on the total pecky rice damage of several pentatomid species, including S. rubrovittatus in southwestern Japan (Sugiura et al 2002) and the abundance of another mirid species T. caelestialium in northern Japan (Kawasaki et al 2007).…”

Climate and land-use changes drive biodiversity turnover in arthropod assemblages over 150 years

“…Precipitation changes alter water balance, local water availability and nutrient cycling, directly affecting ecosystem productivity and food availability for primary consumers, especially in arid and semi-arid regions 52 . Precipitation changes and water stress may directly or indirectly affect eco-physiological responses of herbivores 53 and some analyses suggest that precipitation changes can have stronger effect on population dynamics 54 or species optimum elevation 55 than temperature changes alone. The effects of precipitation changes and increased drought may be even more pronounced when these changes act synergistically with temperature increases, ultimately leading to widespread tree mortality and vegetation shifts with cascading effects on animal communities and ecosystem functioning 56 .…”

Higher surfaces of a crop in the landscape increase outbreak risks the following growing season

“…The trends we identify could be used to reason the protection of the crops at the landscape level. Early warning system tools based on this approach may modulate risk estimates at the plot level and thus limit the systematic use of preventive treatments 31 . As for active landscape design, the management of host plant areas seems both the most influential and the easiest aspect to handle 32 .…”