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Dryad

Grasshopper species’ seasonal timing underlies shifts in community phenological overlap in response to climate gradients, variability, and change

Cite this dataset

Nufio, César; Graham, Stuart; Buckley, Lauren (2021). Grasshopper species’ seasonal timing underlies shifts in community phenological overlap in response to climate gradients, variability, and change [Dataset]. Dryad. https://doi.org/10.5061/dryad.9ghx3ffgb

Abstract

1. Species with different life histories and communities that vary in their seasonal constraints tend to shift their phenology (seasonal timing) differentially in response to climate warming.

2. We investigate how these variable phenological shifts aggregate to influence phenological overlap within communities. Phenological advancements of later-season species and extended durations of early-season species may increase phenological overlap, with implications for species’ interactions such as resource competition.

3. We leverage extensive historic (1958-1960) and recent (2006-2015) weekly survey data for communities of grasshoppers along a montane elevation gradient to assess the impact of climate on shifts in the phenology and abundance distributions of species. We then examine how these responses are influenced by the seasonal timing of species and elevation, and how in aggregate they influence degrees of phenological overlap within communities.

4. In warmer years, abundance distributions shift earlier in the season and become broader. Total abundance responds variably among species and we do not detect a significant response across species. Shifts in abundance distributions are not strongly shaped by species’ seasonal timing or sites of variable elevations. The area of phenological overlap increases in warmer years due to shifts in the relative seasonal timing of compared species. Species that overwinter as nymphs increasingly overlap with later season species that advance their phenology. The days of phenological overlap also increase in warm years but the response varies across sites of variable elevation. Our phenological overlap metric based on comparing single events- the dates of peak abundance- does not shift significantly with warming.

5. Phenological shifts are more complex than shifts in single dates such as first occurrence. As abundance distributions shift earlier and become broader in warm years, phenological overlap increases. Our analysis suggests that overall grasshopper abundance is relatively robust to climate and associated phenological shifts but we find that increased overlap can decrease abundance, potentially by strengthening species interactions such as resource competition.

Methods

Expanded dataset will be maintained in the Niwot Ridge LTER Data Catalog via the Environmental Data Initiative (https://nwt.lternet.edu/data-catalog).  The subset of the data here, corresponding to that used in the paper, is for residents (common species in both surveys) during 1959-1960 and 2006-2015.

Methods

Study sites

During 2006-2015,  we resurveyed the grasshopper (family: Acrididae) communities at four sites in the Front Range of northern Colorado that were originally sampled 60 years prior during the field seasons of 1958 to 1960 (Alexander and Hilliard 1969, Nufio et al. 2009, 2010). These surveyed sites found along an elevational gradient within Boulder County, Colorado, USA, were sampled during both the historic and contemporary surveys on a weekly basis from spring (May-June, depending on elevation) to early fall (August-October).  The sites are referred to as Chautauqua Mesa (1752 m; 39.999° N, -105.285° W), A1 (2200 m; 40.015° N, -105.375° W), 3.9 km west of B1 (hereafter referred to as B1; 2577 m; 40.019° N -105.454° W), and C1 (3048 m; 40.030° N, -105.540° W). The habitats at these sites are south east facing grassy clearings associated with prairie, lower montane, upper montane, and subalpine forests, respectively.

Survey methods

Each weekly survey consisted of systematic 1.0-person-hours of sweep-netting (divided among 1 to 3 surveyors) and 0.5 person-hours of time spent searching for adults that may have been missed by sweep netting.  Weekly survey data consists of species counts by developmental stage (instar numbers and adults). At these suites, grasshoppers have five developmental stages before reaching adulthood (stage 6). A subset of common adult grasshoppers, and those that required ID confirmations or that represented unusual sightings were often brought to the University of Colorado Museum of Natural History. Voucher specimens associated with these surveys have been deposited at the CU Museum of Natural History’s Entomology Collection.    

Analysis

For the current study (Buckley et al. 2021), at each site, we compared changes in the phenology, abundance and levels of overlap for a subset of species that were with associated with yearly warming patterns. The subset of species reflected species that were present and commonly collected during the historic and contemporary surveys. 

Weather data

Three of the four Alexander and Hilliard survey sites were associated with long-term weather stations referred to as A1, B1 and C1. These weather stations were established in 1952 and designed to collect daily temperature data, which they continue to do. These weather stations are currently serviced by the Niwot Ridge Long-Term Ecological Research (LTER) Project and the University of Colorado Mountain Research Station. See the Niwot Ridget LTER site for access to available data, and their correction and infilling protocols, as they may vary from our own.

The fourth site, Chautauqua Mesa, was established as a protected area in 1898 and is currently managed by Boulder City Open Space. For long-term climate data associated with Chautauqua Mesa we used the United States Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) weather station (Cooperative ID 050848) currently in Boulder, Colorado (1672 m; 39.99° N, 105.27°W). This weather station is located 1.3 km away from Chautauqua Mesa and at a similar elevation (Chautauqua Mesa, 1752 m). We used an additional COOP weather station at Gross Reservoir to fill in some missing data from 2008-2015 (COOP ID 52629, 2423 m, 39.94° N, 105.35° W).

We archive daily maximum and minimum temperature data spanning the grasshopper surveys. Most data are a compilation from 1953 to 2008 (McGuire et al. 2012). Some missing data were interpolated using data from other stations as detailed in the publication. When necessary, these data were normalized and adjusted for instrument change (Pepin 2000). In addition, the replacement of the hygrothermographs by electronic datapods at A1 and B1 in 1987 resulted in a need to set the lower temperature limits of the total max and min records (1953–2008) for these two sites at −17.8°C because the datapods could not record temperatures below this threshold. Daily minimum and maximum temperatures for Boulder, Colorado, have been continuously recorded since 1897, excepting a period from 1989 to 1990. From 1947 to 1989 temperature data were recorded by the Boulder Fire Department from instrumentation located on the fire station grounds. From 1990 onwards, weather observations from Boulder were collected from the NIST building and administered by NOAA. Temperature data for Boulder for the period 1952–1989 were adjusted to reflect a stable location at NIST across the data record (McGuire et al. 2012).

Regression techniques were used to infill data as described in McGuire et al. (2012). We extended the temperature record from 2008 to 2015 using the same weather stations and infilling approach (Nufio and Buckley 2019). The technique from McGuire et al. (2012) allowed infilling data gaps of more than a month to reconstruct temperature data missing due to instrument failures: site B1 in 2009 and site A1 in 2009 and 2010. We used data from the NOAA and C1 weather stations to predict temperatures at A1 and data from the NOAA, Gross Reservoir, and C1 weather stations to predict temperatures at B1. We established linear regression relationships between the station missing data and the other stations for daily temperatures using data for 2005–2008. Regressions were constructed separately for minimum and maximum temperatures. We filled each missing data point using the weighted average of the two or three predicted values. The weight was determined by the r2 values of the regressions for each of the two sites. All r2 values were >0.8. We additionally used the R function na.approx in the zoo package to linearly interpolate additional missing data, for a maximum of 5 d, for B1 in 2012, C1 in 2013 and 2015, and A1 in 2010.

References

Alexander, G. 1964. Occurence of grasshoppers as accidentals in the Rocky Mountains of northern Colorado. Ecology 45:77–86.

Alexander, G., and J. R. Hilliard. 1969. Altitudinal and seasonal distribution of Orthoptera in the Rocky Mountains of northern Colorado. Ecological Monographs 39:385–431.

McGuire, C. R., C. R. Nufio, M. D. Bowers, and R. P. Guralnick. 2012. Elevation-Dependent Temperature Trends in the Rocky Mountain Front Range: Changes over a 56-and 20-Year Record. PLoS ONE 7:e44370.

Nufio, C. R., and L. B. Buckley. 2019. Grasshopper phenological responses to climate gradients, variability, and change. Ecosphere 10:e02866.

Nufio, C. R., K. J. Lloyd, M. D. Bowers, and R. P. Guralnick. 2009. Gordon Alexander, grasshoppers, and climate change. American Entomologist 55:10–13.

Nufio, C. R., C. R. McGuire, M. D. Bowers, and R. P. Guralnick. 2010. Grasshopper community response to climatic change: variation along an elevational gradient. PLoS ONE 5:e12977.

Pepin, N. 2000. Twentieth-century change in the climate record for the Front Range, Colorado, USA. Arctic, Antarctic, and Alpine Research 32:135–146.

 

 

Usage notes

Please see the README file for dataset details.

Files:

FocalGrasshoppers_Nufio.csv: Weekly grasshopper survey data

Temperature_Nufio.csv: Daily maximum and minimum temperature data

Expanded dataset will be maintained in the Niwot Ridge LTER Data Catalog via the Environmental Data Initiative (https://nwt.lternet.edu/data-catalog)

Funding

National Science Foundation, Award: DBI-0447315, DEB-0718112, DBI-1349865

National Science Foundation, Award: DBI-0447315, DEB-0718112, DBI-1349865