The ecological detective toolbox: using models with imperfect detection in hypothesis testing in ecology

• Grant number: 13/19250-7
• Support Opportunities: Regular Research Grants
• Start date: February 01, 2014
• End date: July 31, 2016
• Field of knowledge: Biological Sciences - Ecology - Theoretical Ecology
• Principal Investigator: Paulo Inácio de Knegt López de Prado
• Grantee: Paulo Inácio de Knegt López de Prado
• Host Institution: Instituto de Biociências (IB). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The advancement and application of ecological theory depends on unbiased and precise estimates of occurrence, size and vital rates of populations in ecological systems. There is a growing concern that such estimates are strongly affected by observation bias; the most obvious case are false absences. Thus, the assumption of perfect or constant detection of species and individuals has been strongly questioned, and hence the results derived from this assumption. Tom solve the problem there is a formalism of hierarchical statistical models, which separate two levels of variation of data: the observation layer and the layer of the biological processes. Computational applications of this formalism are already available. Colletively known as hierarchical models with imperfect detection, such statistical methods could be applied much more widely than they currently are. Nevertheless, this new approach involves complex statistical procedures and larger sampling efforts. Thus, it is necessary to evaluate the effective gains of the models with imperfect detection in different types of ecological research. The objective of this proposal is to use estimates of occurrence, abundance and vital rates of species obtained with imperfect detection models in three case studies. The cases were chosen to encompass a wide range of tests on the structure and dynamics of populations and communities in theoretical and applied aspects. Besides the importance of the theoretical and applied case studies in themselves, we aim also to evaluate the sensitivity of the results and conclusions to the use of models with imperfect detection. (AU)

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CASTILHO, LEONARDO BRAGA; PRADO, PAULO INACIO. Towards a pragmatic use of statistics in ecology. PeerJ, v. 9, SEP 1 2021. (13/19250-7)

WEDEKIN, L. L.; ENGEL, M. H.; ANDRIOLO, A.; PRADO, P. I.; ZERBINI, A. N.; MARCONDES, M. M. C.; KINAS, P. G.; SIMOES-LOPES, P. C.. Running fast in the slow lane: rapid population growth of humpback whales after exploitation. MARINE ECOLOGY-PROGRESS SERIES, v. 575, p. 195-206, JUL 20 2017. (13/19250-7)

RODRIGUES, RODOLPHO C.; PRADO, PAULO I.. Sampling methods affect observed response of bird species richness to vegetation structure in Brazilian savannas. CONDOR, v. 120, n. 2, p. 402-413, MAY 2018. (13/19250-7)

RIBEIRO, GIULIA MAGRI; PRADO, PAULO INACIO; COUTINHO, RENATO MENDES; RILLO, MARINA COSTA; PEREIRA JUNIOR, SAMUEL; PORFIRIO-SOUSA, ALFREDO L.; LAHR, DANIEL J. G.. Growth Rate Modulation Enables Coexistence in a Competitive Exclusion Scenario Between Microbial Eukaryotes. ACTA PROTOZOOLOGICA, v. 58, n. 4, p. 17-pg., 2019-01-01. (15/02689-1, 13/19250-7, 14/23497-0, 13/25729-3)