Use of classical bird census transects as spatial replicates for hierarchical modeling of an avian community

Abstract

New monitoring programs are often designed with some form of temporal replication to deal with imperfect detection by means of occupancy models. However, classical bird census data from earlier times often lack temporal replication, precluding detection-corrected inferences about occupancy. Historical data have a key role in many ecological studies intended to document range shifts, and so need to be made comparable with present-day data by accounting for detection probability. We analyze a classical bird census conducted in the region of Murcia (SE Spain) in 1991 and 1992 and propose a solution to estimating detection probability for such historical data when used in a community occupancy model: the spatial replication of subplots nested within larger plots allows estimation of detection probability. In our study, the basic sample units were 1-km transects, which were considered spatial replicates in two aggregation schemes. We fit two Bayesian multispecies occupancy models, one for each aggregation scheme, and evaluated the linear and quadratic effect of forest cover and temperature, and a linear effect of precipitation on species occupancy probabilities. Using spatial rather than temporal replicates allowed us to obtain individual species occupancy probabilities and species richness accounting for imperfect detection. Species-specific occupancy and community size decreased with increasing annual mean temperature. Both aggregation schemes yielded estimates of occupancy and detectability that were highly correlated for each species, so in the design of future surveys ecological reasons and cost-effective sampling designs should be considered to select the most suitable aggregation scheme. In conclusion, the use of spatial replication may often allow historical survey data to be applied formally hierarchical occupancy models and be compared with modern-day data of the species community to analyze global change process.

Keywords: Bayesian multispecies occupancy models; cell size; community models; community size; detectability; environmental covariates; forest birds; historical data.

Figure 1

Nine representative bird species of the study area. From left to right, and top to bottom: Carduelis carduelis, Sylvia undata, Parus major, Turdus viscivorus, Sylvia melanocephala, Emberiza cia, Lophophanes cristatus, Aegithalos caudatus, and Loxia curvirostra. Photograph credit: Carlos González Revelles

Figure 2

Distribution of 1‐km bird transects conducted in Mediterranean forest areas in the study area (region of Murcia, SE Spain), considering two different grid sizes: (a) aggregation scheme AS2x2 (60‐s latitude/longitude) and (b) aggregation scheme AS3x3 (90‐s latitude/longitude). Cross symbols represent the mean positions for the 377 transects, which were grouped as spatial replicates considering two different aggregation schemes for sites: (c) 246 sites for AS2x2; (d) 185 sites for AS3x3

Figure 3

Mean of estimates of (a) occupancy probability Psi and (b) detection probability p for bird species under the two aggregation schemes AS2x2 and AS3x3 (x and y axes, respectively)

Figure 4

Community response of bird species occupancy probability to forest cover, temperature and precipitation for the aggregation schemes AS2x2 (a–c) and AS3x3 (d–f). Gray lines show 95% CI of the community mean

Figure 5

Relationships between the number of bird species (community size, Nsite) and the covariates of each sampled site: (a) forest cover, (b) temperature, and (c) precipitation. Each point represents the richness of each cell site surveyed (n = 246 and n = 185 for the aggregation schemes AS2x2 and AS3x3, respectively). Lines represent splines smooth. Comparison of aggregation schemes shown in different colors: AS2x2 (black) and AS3x3 (green, yellow, and blue for the percentage of forest cover, annual mean temperature, and annual precipitation, respectively). Note slight offset of color points in the x direction for the aggregation scheme AS3x3