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OVERVIEW: The BCN Census is a breeding season monitoring program that was implemented in the Chicago Wilderness region by the Bird Conservation Network. The Chicago Wilderness region, which incorporates about a dozen counties centered around the the City of Chicago, is very unique and notably set apart from other adjacent counties and regions. Much of the land in the Chicago Wilderness region is either preserved land or land that is already heavily developed. Urban development radiates out a great distance in all directions from Lake Michigan and downtown Chicago. Farmland only dominates in the far fringe counties that comprise the Chicago Wilderness region. To the north where the terrain is more varied, some unfarmed (but unprotected) land also still remains. Because a large portion of the region is already developed, results from the BCN Census are not particularly useful for examining how urban expansion is affecting bird populations in the area. The results presented here are most useful for examining how birds are fairing in protected areas in and around the Chicago area. When viewing the results presented here, also keep in mind that many of the preserved lands in the Chicago Wilderness region are also being actively managed and restored by local forest preserve districts, state and national government agencies, and most notably by hundreds of volunteers working through programs like the Volunteer Stewardship Network. Restoration practices that effect our local breeding birds include (but are not limited to) buckthorn and honeysuckle removal, garlic mustard removal, removal of hedgerows in grasslands, seed planting, controlled burning, and deer management. Many of the current initiatives are highlighted on the Habitat Project website run by Audubon - Chicago Region through cooperation with Chicago Wilderness. SURVEY METHODS: The BCN Census has three protocols that are recommended for use by our monitors. Point Counts are recommended during the breeding season. Recommendations ask that monitors conduct a minimum of two visits during June, but they are also encouraged to conduct additional counts in late April and early May, when resident breeders have begun nesting, and in early July, when many young are being fed. Monitors are asked to start as close as possible to sunrise (between 5:15 a.m. to 5:20 a.m.), and complete counts by no later than about 9:00 a.m. Point counts are usually set up at points located at about 150-meter intervals. Point counts are five minutes in length and all birds detected within a 75 meter radius of the point are counted. Birds detected outside the radius are noted in a separate area. It is also requested that monitors start at different points on different days in order to maximize the number of birds detected during the hours when birds are most active. Points are usually placed at intervals designed to get the best views or coverage of the habitat being surveyed (not randomly placed). Points are almost exclusively placed in preserved areas that are usually owned by one of the county forest preserve districts, the state, or other local municipalities. The DuPage County Forest Preserve District point count data is also included in BCN eBird and this analysis. Their data uses similar, but still slightly different protocols. After monitoring has been completed, data is entered on the BCN eBird website. For more details regarding our survey methods, please visit the BCN Census protocol page. DATA PREPARATION: Data collected from the BCN eBird website is imported into MS Access where records are filtered, trimmed, and converted into a usable format for analysis in statistics software (TRIM). MS Access was also used to substantially decrease manual labor / work time and automate many tasks including the export of records (for each species) for later import into TRIM, creation of a TRIM "command file" to fully automate the analyses performed in the TRIM software, converting TRIM results into MS Excel format (where improved graphs were created), and to automate the creation of web pages for each species (including automatically inserted titles, names, data, linked images, and linked graphs). DATA ANALYSIS: The total numbers of birds of each species detected at each point was calculated for each year. Because point counts are visited multiple times during the breeding season, the model uses the maximum total recorded during a single visit for each point-species-year combination. Data is limited to observations between June 1st and June 30th as a simple means of attempting to filter out some of the records pertaining to late migrants (common through end of May), post-breeding dispersal (July-Aug.), and other factors. We have noted where records of migrants still affect the results of these trends, especially for species that are known to migrate through the Chicagoland area well into early June. Records of adults and juveniles are not separated out by the BCN Census. Species not recorded on a point count during a visit are assigned a count value of zero in order to distinguish between species absences during survey years and missing data during non-survey years. Annual population indices for each species are calculated using a program called TRIM (Trends & Indices for Monitoring Data), developed by Statistics Netherlands. This program uses a log-linear regression model with Poisson error terms for the analysis of time series of counts that contain missing observations (a linear trend approach was used in these analyses). "If observations are missing, the TRIM estimates the missing values on the basis of changes observed on plots that were monitored. This means that when a new year is added the index figures on previous years may change." (Statistics Netherlands 2005) Because the actual numbers of populations are often unknown, time series are converted to index numbers with the base year set as the year the census began, or in this case the first year that the census had an adequate amount of data for analysis. The base year is set at 1. "A time-point index is a total for a time-point divided by the total for the first time-point. Indices are thus the increase (decrease) factors with respect to the first time-point." (Pannekoek & van Strien 1996) The resulting index values on the graph show how percentages have changed with respect to the base year and allow for better comparison of changes for various species. The TRIM program also attempts to take into account the effects of over-sampling and serial correlation. "The model used in TRIM requires at least two points in the time series to estimate parameters and hence, [points] counted in only one year are excluded. Moreover, if the data are too sparse, i.e. contain too many missing values, the model parameters cannot be estimated." (British Trust for Ornithology 2004) Although various models were tested, the Linear Trend model was used in TRIM to analyze each species trend because trends across the entire monitoring period were desired and data was usually too sparse to run the Time Effects model. The effects of overdispersion and serial correlation were both taken into account in these analyses, resulting in higher levels of standard error. Categorical covariates were not used in this analysis. The use of covariates allows one to more accurately compare trends within various habitat types by weighting habitat types based on how heavily they are surveyed. BCN Census point counts and transects focus almost exclusively on preserved areas. General observations (included in the All Data types analyses) are more likely to incorporate urban environments, but are still heavily centered on preserved areas. Although only limited data is available regarding the percent coverage of each habitat type, grasslands are likely monitored the most, followed by woodlands and shrublands, then distantly followed by wetlands and urban / unpreserved areas. Changes in the proportion of each habitat type monitored may also change from year to year, further affecting the results. These biases need to be carefully considered when viewing many of the species trends. Although a species like Grasshopper Sparrow may be shown as increasing overall, the species may be increasing in preserved grasslands yet decreasing in unprotected areas that are being developed. As additional resources, funds, and data become available, we hope to incorporate these variables in a future analysis. Two indices are calculated in the program and displayed on the graphs: Imputed and Model-based. IMPUTED indices: "Summation of real counts plus - for missing counts - model predictions.a Closer to real counts (more realistic course in time)."
MODEL-based indices: "Summation of model predictions of all sites. Often more stable; standard errors available in TRIM."
Confidence intervals (see "Avg. Yearly Rate of Change" under "Technical Notes") are calculated at plus or minus two times the multiplicative slope (approx. 95% CI). Three tests are performed to determine the Goodness of Fit of each model. The Pearson’s chi-squared statistic ("Chi-square") and the likelihood ratio statistic ("Likelihood Ratio") tests pass (good fit) if the p-value is greater than 0.05 and the associated values are low. The tests fail (poor fit) if the p-value is less than 0.05 and the associated values are high. The Akaike’s Information Criterion (AIC) is somewhat different. "According to this approach, models with smaller values of AIC, or equivalently LR-2df, provide better fits than models with larger values." (see Pannekoek & van Strien 1996, Sec. 2.5 for further details) For additional information, see Interpreting the Data. If you have any questions or would like to obtain additional data or information, please Contact Us. |
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