Abstract
AbstractAccurate estimations of animal populations are necessary for management, conservation, and policy decisions. However, methods for surveying animal communities disproportionately represent specific groups or guilds. For example, transect surveys can provide robust data for large arboreal species but underestimate cryptic or small‐bodied terrestrial species, whereas camera traps have the inverse tendency. The integration of information from multiple methodologies would provide the most complete inference on population size or responses to putative covariates, yet a simple, robust framework that allows integration and comparison of multiple data sources has been lacking. We use 27,813 counts of 35 species or species groups derived from concurrent visual transects, dung transects, and camera trap surveys in tropical forests and compare them within a generalized joint attribute modeling framework (GJAM) that both compares and integrates field‐collected dung, visual, and camera trap data to quantify the species‐ and trait‐specific differences in detection for each method. The effectiveness of survey method was strongly dependent on species, as well as animal traits. These differences in effectiveness contributed to meaningful differences in the reported strength of a known important covariate for animal communities (distance to nearest village). Data fusion through GJAM allows clear and unambiguous comparisons of the counts provided from each different methodology, the incorporation of trait information, and fusion of all three data streams to generate a more complete estimate of the effects of an anthropogenic disturbance covariate. Research and conservation resources are extremely limited, which often means that field campaigns attempt to maximize the amount of information gathered especially in remote, hard‐to‐access areas. Advances in these understudied areas will be accelerated by analytical methods that can fully leverage the total body of diverse biodiversity field data, even when they are collected using different methods. We demonstrate that survey methods vary in their effectiveness for counting species based on biological traits, but more importantly that generative models like GJAM can integrate data from multiple sources in one cohesive statistical framework to make improved inference in understudied environments.
Highlights
Wildlife populations are in flux worldwide, with some species disappearing at alarming rates (Dirzo et al 2014) while others are becoming overabundant or invasive (Didham et al 2007, Doherty et al 2016)
The survey method employed strongly affected the counts obtained for many species (Fig. 2; Appendix S1: Tables S1–S3)
Camera traps positively affected the counts for nine terrestrial species (Fig. 2; Appendix S1: Table S1)
Summary
Wildlife populations are in flux worldwide, with some species disappearing at alarming rates (Dirzo et al 2014) while others are becoming overabundant or invasive (Didham et al 2007, Doherty et al 2016). Overlooking methodological differences can lead to misinterpretations of the effect of human and natural disturbances on populations and communities, leading to poor management and conservation decisions (Fragoso et al 2016). This is of particular concern in tropical forests as dense vegetation exaggerates differences in the detection ability of different methods (Espartosa et al 2011), and biodiverse communities harbor many rare and data-deficient species
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
