point-count-data-analysis

Papers

These papers served as the foundation for the materials presented in the workshop. To get a PDF version of these, you can either click the link, some are open access (or you might have an institutional subscription). For other PDF’s, please browse this shared Google Drive folder (organized by publication year) to find what you are looking for.

Single-visit N-mixture

Sólymos, P., Lele, S. R. and Bayne, E. 2012. Conditional likelihood approach for analyzing single visit abundance survey data in the presence of zero inflation and detection error. Environmetrics, 23: 197–205. DOI: 10.1002/env.1149

Denes, F., Sólymos, P., Lele, S. R., Silveira, L. & Beissinger, S. 2017. Biome scale signatures of land use change on raptor abundance: insights from single-visit detection-based models. Journal of Applied Ecology, 54: 1268–1278. DOI: 10.1111/1365-2664.12818

Sólymos, P., Lele, S. R. 2016. Revisiting resource selection probability functions and single-visit methods: clarification and extensions. Methods in Ecology and Evolution, 7: 196–205. DOI: 10.1111/2041-210X.12432

QPAD and SQPAD

Sólymos, P., Matsuoka, S. M., Bayne, E. M., Lele, S. R., Fontaine, P., Cumming, S. G., Stralberg, D., Schmiegelow, F. K. A. & Song, S. J., 2013. Calibrating indices of avian density from non-standardized survey data: making the most of a messy situation. Methods in Ecology and Evolution, 4: 1047–1058. DOI: 10.1111/2041-210X.12106

Lele, S. R., Sólymos, P. 2025. Single bin QPAD (SQPAD) approach for robust analysis of point count data with detection error. Ornithological Applications, in press. Preprint

Sólymos, P., Matsuoka, S. M., Cumming, S. G., Stralberg, D., Fontaine, P., Schmiegelow, F. K. A., Song, S. J., and Bayne, E. M., 2018. Evaluating time-removal models for estimating availability of boreal birds during point-count surveys: sample size requirements and model complexity. Condor, 120: 765–786. DOI: 10.1650/CONDOR-18-32.1

Edwards, B. P. M., Smith, A. C., Docherty, T. D. S., Gahbauer, M. A., Gillespie, C. R., Grinde, A. R., Harmer, T., Iles, D. T., Matsuoka, S. M., Michel, N. L., Murray, A., Niemi, G. J., Pasher, J., Pavlacky Jr, D. C., Robinson, B. G., Ryder, T. B., Sólymos, P., Stralberg, D., and Zlonis, E. J., 2023. Point count offsets for estimating population sizes of North American landbirds. Ibis, 165: 482–503. DOI: 10.1111/ibi.13169

Matsuoka, S. M., Bayne, E. M., Sólymos, P., Fontaine, P., Cumming, S. G., Schmiegelow, F. K. A., & Song, S. A., 2012. Using binomial distance-sampling models to estimate the effective detection radius of point-counts surveys across boreal Canada. Auk 129: 268–282. DOI: 10.1525/auk.2012.11190

Simulations (bSims)

Sólymos, P., 2023. Agent-based simulations improve abundance estimation. Biologia Futura, 74: 377–392. DOI: 10.1007/s42977-023-00183-2

Multi-species approaches

Sólymos, P., Matsuoka, S. M., Stralberg, D., Barker, N. K. S., and Bayne, E. M., 2018. Phylogeny and species traits predict bird detectability. Ecography, 41: 1595–1603. DOI: 10.1111/ecog.03415

Audio recordings

Yip, D. A., Knight, E. C., Haave-Audet, E., Wilson, S. J., Charchuk, C., Scott, C. D., Sólymos, P., and Bayne, E. M., 2020. Sound level measurements from audio recordings provide objective distance estimates for distance sampling wildlife populations. Remote Sensing in Ecology and Conservation, 6: 301–315. https://doi.org/10.1002/rse2.118

Van Wilgenburg, S. L., Sólymos, P., Kardynal, K. J. and Frey, M. D., 2017. Paired sampling standardizes point count data from humans and acoustic recorders. Avian Conservation and Ecology, 12(1):13. https://doi.org/10.5751/ACE-00975-120113

Yip, D. A., Leston, L., Bayne, E. M., Sólymos, P. and Grover, A., 2017. Experimentally derived detection distances from audio recordings and human observers enable integrated analysis of point count data. Avian Conservation and Ecology, 12(1):11. https://doi.org/10.5751/ACE-00997-120111

Point count methods

Bayne, E., Leston, L., Mahon, C. L., Sólymos, P., Machtans, C., Lankau, H., Ball, J., Van Wilgenburg, S., Cumming, S. G., Fontaine, T., Schmiegelow, F. K. A., and Song, S. J., 2016. Boreal bird abundance estimates within different energy sector disturbances vary with point count radius. Condor, 118:376–390. DOI: 10.1650/CONDOR-15-126.1

Barker, N. K. S., Fontaine, P. C., Cumming, S. G., Stralberg, D., Westwood, A., Bayne, E. M., Sólymos, P., Schmiegelow, F. K. A., Song, S. J., and Rugg, D. J., 2015. Ecological monitoring through harmonizing existing data: lessons from the Boreal Avian Modelling Project. Wildlife Society Bulletin, 39:480–487. DOI: 10.1002/wsb.567

Matsuoka, S. M., Mahon, C. L., Handel, C. M., Sólymos, P., Bayne, E. M., Fontaine, P. C., and Ralph, C. J., 2014. Reviving common standards in point-count surveys for broad inference across studies. Condor 116:599–608. DOI: 10.1650/CONDOR-14-108.1

Roadside effects

Yip, D. A., Bayne, E. M., Sólymos, P., Campbell, J., and Proppe, J. D., 2017. Sound attenuation in forested and roadside environments: implications for avian point count surveys. Condor, 119:73–84. DOI: 10.1650/CONDOR-16-93.1

Sólymos, P., Toms, J. D., Matsuoka, S. M., Cumming, S. G., Barker, N. K. S., Thogmartin, W. E., Stralberg, D., Crosby, A. D., Dénes, F. V., Haché, S., Mahon, C. L., Schmiegelow, F. K. A., and Bayne, E. M., 2020. Lessons learned from comparing spatially explicit models and the Partners in Flight approach to estimate population sizes of boreal birds in Alberta, Canada. Condor, 122: 1–22. DOI: 10.1093/condor/duaa007