Centre for Environmental Research and Impact Studies @ University of Bucharest
CCMESI
CCMESI
Centre for Environmental Research and Impact Studies @ University of Bucharest

WildPop

Link to app web pageProject title: Interactive tool for estimating abundance of wildlife populations (WildPop)

Project number: PN-III-P2-2.1-PED-2021-1965; Proiect experimental demonstrativ (PED)

Contract no.: PED699/2022

Funding body: Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI)

Budget: 598 669 RON

Period: 2022-2024

Research team:

For Romanian version of this project presentation page click here!

Project summary:

Estimating species abundance is one of the most challenging and important question in wildlife management. To obtain data on wildlife populations, two field methods are widely used worldwide: traditional mark-recapture techniques, where every detected individual can be uniquely identified, and occupancy-type modeling, where individuals cannot be uniquely identified. Data for occupancy-type analyses can be obtained by sign surveys and camera traps. Sign and camera traps are easy to deploy, however, they require rigorous sampling protocols and advanced statistical analyses, e.g. via R software platform, package „unmarked”. R platform is widely used for ecological modeling, however, complex methods such as those included in the „unmarked” package can be explored only by modelers with very good programming skills and a throughout understanding of hierarchical analysis of population data.

The aim of the WildPop proposal is to improve wildlife estimation in Romania by developing, testing, and deploying a user-friendly interactive tool for population assessment based on data collected by scientists and citizens and state-of-the-art hierarchical models. Apart from other projects, ones that have as an objective the monitoring of wildlife, our work aims to evaluate the outcomes of wildlife estimation projects, evaluate the weaknesses and strengths of using occupancy-type modeling in Romania, and construct a streamlined workflow for estimating wildlife abundance and occupancy using remote cameras and transects. Wildlife practitioners will have a reliable framework for planning and deploying robust animal monitoring programs and produce practical conservation measures with minimal associated costs.

Objectives:

  • O1: To review the use and outcomes of wildlife estimation initiatives in Romania, with a focus on species of E.U. conservation concern – brown bears, wolves, lynx;
  • O2: To co-create with stakeholders a guideline for developing cost-effective and robust local wildlife monitoring protocols for unmarked individuals;
  • O3: To develop a tailored web-based application for single-season occupancy and single-season wildlife abundance using R Shiny framework;
  • O4: To unlock the development of statistically robust wildlife monitoring services by training interested parties such as public authorities, wildlife managers, and consultants.

Expected results:

  • Documenting best practices in creating Shiny apps for population ecology;
  • Roadmap for WILDPOP app development;
  • Wildlife monitoring guidelines (including stand-alone R code);
  • Interactive Shiny app for estimation of single-season occupancy and abundance (including user manual);
  • Testing Interactive R Shiny app during two workshops with potential users;
  • Dissemination of results by participating in scientific conferences and scientific articles (participation at 5 conferences and submission of a minimum of 2 scientific articles).

Reports:

2022 Report (Romanian version)

2023 Report (Romanian version)

2024 Final Report (Romanian version)

Products:

Bancila, R.I., Popescu, V.D., Miu, I.V., Manolache, S., Mirea, M.D., Nita, A. & Rozylowicz, L. (2024) Ghid pentru estimarea abundenței și ocupanței animalelor sălbatice. OSF Preprints. https://doi.org/10.31219/osf.io/4xvrs [In Romanian]

Use R manual for beginners (RO version)

WildPop Shiny interactive app (cloud version)

WildPop Shiny interactive app (desktop version)

WildPop User manual

Conferences:

Rozylowicz L., Popescu V., Bancila R., Nita A., Manolache S., Gradinaru S., Mirea M. (2022) Interactive tool for estimating abundance of wildlife populations. Geographical perspectives on global changes (18-19 November 2022, Bucharest).

Mirea M. (2022) Modeling the distribution of saproxylic insects in Romania under different climate change scenarios. Geographical perspectives on global changes (18-19 November 2022, Bucharest).

Rozylowicz L., Bancila R.I., PopescuV.D., Nita A., Mirea M.D., Manolache S. Hierarchical methods for alien species data collection. In Trichkova T., Kalcheva H., Tomov R., Vladimirov V., Tyufekchieva V. (Eds.) 2023. Book of Abstracts. Joint ESENIAS and DIAS Scientific Conference 2023 and 12th ESENIAS Workshop ‘Globalisation and invasive alien species in the Black Sea and Mediterranean regions – management challenges and regional cooperation’, 11–14 October 2023, Varna, Bulgaria, IBER-BAS, ESENIAS, DIAS, 152 pp.

Mirea M. Rozylowicz L. (2023) Modeling the Distribution of Saproxylic Insects in Europe Under Different Climate Change Scenarios. International Association of Climatology Conference Climate, water and society: changes and challenges (3 – 7 July 2023 Bucharest)

Rozylowicz L. (2023) WildPop: modelling abundance and occupancy for non-coders. Environment at Crossroads: SMART approaches for sustainable future (17-18 November 2023, Bucharest).

Rozylowicz L., Bancila R.I., Popescu V.D., Nita A., Mirea M.D., Manolache S. (2024) Interactive tool for estimating abundance of wildlife populations (WildPop) International Conference Present Environment and Sustainable Development 19th edition, 7-8 June 2024 Iasi.

Articles:

Rozylowicz, L., Popescu, V. D., Manolache, S., Nita, A., Gradinaru, S. R., Mirea, M. D., Bancila, R. I. (2024). Occupancy and N-mixture modeling applications in ecology: a bibliometric analysis. Global Ecology and Conservation 50. e02838

Rozylowicz L., Popescu V.D., Mirea M.D., Manolache S., Miu I.V., Nita A., Pindaru L.C., Bancila R.I. (2024) WildPop: an interactive tool for estimating occupancy and abundance of wildlife populations. Carpathian Journal of Earth and Environmental Sciences 19(2) 321-328

Project achievements:

Estimating species abundance is one of the most challenging and important question in wildlife management. To obtain data on wildlife populations, two field methods are widely used worldwide: traditional mark-recapture techniques, where every detected individual can be uniquely identified, and occupancy-type modeling, where individuals cannot be uniquely identified. Data for occupancy-type analyses can be obtained by sign surveys and camera traps. Sign and camera traps are easy to deploy, however, they require rigorous sampling protocols and advanced statistical analyses, e.g. via R software platform, package „unmarked”. R platform is widely used for ecological modeling, however, complex methods such as those included in the „unmarked” package can be explored only by modelers with very good programming skills and a throughout understanding of hierarchical analysis of population data.

To facilitate implementing more hierarchical analyses in Romania, we developed a Shiny app able to run models implemented in unmarked without codding, i.e., WildPop app. The app is available for download and run from computer (standalone app available at https://github.com/rlaurentiu/wildpopapp) or in cloud (https://wildpop.ccmesi.ro/). WildPop is able to run hierarchical models with simulated and real-life data, hence, practitioners such as wildlife and protected areas managers can now make use their data and implement statistically robust wildlife monitoring programmes. WildPop is available with open-source MIT license.

WildPop is povided via an informative webpage (https://wildpop.ccmesi.ro), and a guide for estimating wildlife occupancy and abundance (https://doi.org/10.31219/osf.io/4xvrs).

WildPop Shiny app – logical scheme.

Example of data for occupancy and wildlife, obtained via wildlife camera. In the image is a wolf pack from Vrancea county. Data can be introduced in app as 1 (woves detected) for occupancy studies or 9 (nine wolves counted) for N-mixture studies.

WildPop Shiny app in cloud (occupancy modeling with user provided data).