Museum specimen data reveal emergence of a plant disease may be linked to increases in the insect vector population

Abstract

Abstract. The emergence rate of new plant diseases is increasing due to novel introductions, climate change, and changes in vector populations, posing risks to agricultural sustainability. Assessing and managing future disease risks depends on understanding the causes of contemporary and historical emergence events. Since the mid-1990s, potato growers in the western United States, Mexico, and Central America have experienced severe yield loss from Zebra Chip disease and have responded by increasing insecticide use to suppress populations of the insect vector, the potato psyllid, Bactericera cockerelli (Hemiptera: Triozidae). Despite the severe nature of Zebra Chip outbreaks, the causes of emergence remain unknown. We tested the hypotheses that (1) B. cockerelli occupancy has increased over the last century in California and (2) such increases are related to climate change, specifically warmer winters. We compiled a data set of 87,000 museum specimen occurrence records across the order Hemiptera collected between 1900 and 2014. We then analyzed changes in B. cockerelli distribution using a hierarchical occupancy model using changes in background species lists to correct for collecting effort. We found evidence that B. cockerelli occupancy has increased over the last century. However, these changes appear to be unrelated to climate changes, at least at the scale of our analysis. To the extent that species occupancy is related to abundance, our analysis provides the first quantitative support for the hypothesis that B. cockerelli population abundance has increased, but further work is needed to link B. cockerelli population dynamics to Zebra Chip epidemics. Finally, we demonstrate how this historical macro-ecological approach provides a general framework for comparative risk assessment of future pest and insect vector outbreaks.

Detecting long-term occupancy changes in Californian odonates from natural history and citizen science records

“…Historical sites were georeferenced using the standardized point-radius method in which coordinates and an uncertainty radius are assigned to text descriptions of locations (Wieczorek et al 2004). Museum specimen data exhibited a decline in records for recent decades, a pattern common to other natural history collection datasets (Tewksbury et al 2014;Zeilinger et al 2017). To augment contemporary records, we also included occurrence data from Odonata Central and CalOdes enthusiast observations, of which records have often been photovouchered and verified by odonate experts.…”

“…Contrary to natural history collection data, there has been much progress in devising approaches to account for recording biases when extracting signals of change from citizen science data . However, it remains unclear whether methods developed to estimate changes in species abundance and distribution from citizen science data can work with natural history collection data (but see Zeilinger et al 2017). This is an exciting prospect, as a successful application of these novel methods to natural history records may unlock the potential held in natural history collections for aiding conservation and management.…”

“…One way to address this is to assume that natural history records can be compiled into meaningful lists similar to citizen science lists based on the location and time in which they were collected. This assumption has previously been used to aggregate natural history records in analyses of biodiversity change over space and time (e.g., Bartomeus et al 2013;van Strien et al 2015;Zeilinger et al 2017).…”

Understanding ecological change across large spatial, temporal and taxonomic scales: integrating data and methods in light of theory

“…For instance, the application of hierarchical occupancy models to museum specimens and historical observations can vastly improve our estimates of the influence of selection on assemblages at the centennial scale (Tingley and Beissinger 2009, Tingley et al 2012, Iknayan et al 2014, Rapacciuolo et al 2017, Zeilinger et al 2017. For instance, the application of hierarchical occupancy models to museum specimens and historical observations can vastly improve our estimates of the influence of selection on assemblages at the centennial scale (Tingley and Beissinger 2009, Tingley et al 2012, Iknayan et al 2014, Rapacciuolo et al 2017, Zeilinger et al 2017.…”

“…Owing to their ability to account for different types of sampling bias, occupancy models are also becoming key to modeling longer-term data sources. For instance, the application of hierarchical occupancy models to museum specimens and historical observations can vastly improve our estimates of the influence of selection on assemblages at the centennial scale (Tingley and Beissinger 2009, Tingley et al 2012, Iknayan et al 2014, Rapacciuolo et al 2017, Zeilinger et al 2017. Although different approaches have traditionally been preferred to account for imperfect detection in paleoecological data (Alroy et al 2001, Sugita 2007a, b, Pirzamanbein et al 2014, hierarchical occupancy models are beginning to be applied to the fossil record for assemblage-level inference (Liow 2013).…”