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.

An integrative approach to discern the seed dispersal role of frugivorous guilds in a Mediterranean semiarid priority habitat

“…Moreover, the barcoding technique used in this study was fundamental to detect the key role in seed dispersal of this species, which was not registered by bird surveys in the study area (F. Robledano & J.F. Calvo, 2016, personal communication) due to the imperfect detection of this avian species (Jiménez-Franco et al, 2019).…”

Evaluating temporal turnover in avian species richness in a Mediterranean semiarid region: Different responses to elevation and forest cover

“…We F I G U R E 1 (a) Location of the study area (Region of Murcia, SE Spain), the distribution of 1-Km spatial transects for the bird surveys in the historical (1990,1991) and modern period (2012,2017), as well as the environmental covariates: (b) elevation, (c, d) percentage of forest cover for the two time periods. defined sites as cells in a grid that covers our study area (Jiménez-Franco et al, 2019). We selected cell size to be 2 × 2 km, based on the species in our bird community (most of them passerines with small home ranges; Jiménez-Franco et al, 2019;Rechetelo et al, 2016), which may be suitable for evaluating the effects of environmental covariates on bird species occupancy at a regional scale (Kéry et al, 2013;Lipsey et al, 2017).…”

“…Specifically, our aims are: (1) to analyse the relationships between changes in the bird species richness and key environmental variables (elevation and forest cover) along a comparison time span of 21–25 years; and (2) to evaluate the temporal turnover in the avian species richness by mapping species richness for each period, as well as the species turnover rate between the two periods. We used bird community survey data from the historical period considering multiple 1‐km transect bird surveys as spatial replicates for larger cells interpreted as ‘sites’ (Jiménez‐Franco et al., 2019), and resurveying them in modern time using the same protocol. This data set allows us to fit two hierarchical multispecies occupancy models for each period, obtaining species‐specific estimates of occupancy probability in relation to environmental covariates that are interpreted as surrogates for global change effects (Clement et al., 2016), as well as estimates of average occupancy probability of the entire bird community (Zipkin et al., 2009).…”

Advances in modelling demographic processes: The Euring 2017 Analytical Meeting

“…Jiménez‐Franco et al. () describe how to estimate detection probability from historical data records thus providing a means for comparison with modern‐day surveys. These papers highlight the issues of detection in estimating species distributions and also demonstrate the growing interest in integration of data from different sources, times, spatial units, etc.…”