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Cost‐effective monitoring of biological invasions under global change: a model‐based framework

Journal Article · · Journal of Applied Ecology
 [1];  [2];  [3];  [4];  [5];  [1];  [6];  [7];  [8];  [1];
  1. Centro de Investigação em Biodiversidade e Recursos Genéticos (CIBIO) Faculdade de Ciências da Universidade do Porto Campus Agrário de Vairão, 4485‐601 Vairão Portugal
  2. Centro de Investigação em Biodiversidade e Recursos Genéticos (CIBIO) Universidade de Évora 7000‐890 Évora Portugal
  3. Instituto de Ciências Agrárias e Ambientais Mediterrânicas (ICAAM) Universidade de Évora – Pólo da Mitra Apartado 94 7002‐554 Évora Portugal
  4. Instituto Politécnico de Viana do Castelo (IPVC) Praça General Barbosa 4900‐347 Viana do Castelo Portugal
  5. Institute of Integrative Biology ETH Zurich Universitätsstrasse 16 CH‐8092 Zurich Switzerland, Centre for Invasion Biology Stellenbosch University Matieland 7602 South Africa
  6. Centro de Investigação em Biodiversidade e Recursos Genéticos (CIBIO) Faculdade de Ciências da Universidade do Porto Campus Agrário de Vairão, 4485‐601 Vairão Portugal, Dépt. d'Ecologie et d'Evolution Univ. Lausanne Bâtiment Biophore CH‐1015 Lausanne Switzerland
  7. Laboratory of Applied Ecology Centre for the Research and Technology of Agro‐Environment and Biological Sciences University of Trás‐os‐Montes and Alto Douro, 5001‐801 Vila Real Portugal
  8. Centro de Investigação em Biodiversidade e Recursos Genéticos (CIBIO) Universidade de Évora 7000‐890 Évora Portugal, Department of Biodiversity and Evolutionary Biology National Museum of Natural Sciences CSIC C/José Gutiérrez Abascal 28006 Madrid Spain, Centre for Macroecology, Evolution and Climate Natural History of Denmark University of Copenhagen Universitetsparken 15 DK‐2100 Copenhagen Denmark
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Summary

Ecological monitoring programmes are designed to detect and measure changes in biodiversity and ecosystems. In the case of biological invasions, they can contribute to anticipating risks and adaptively managing invaders. However, monitoring is often expensive because large amounts of data might be needed to draw inferences. Thus, careful planning is required to ensure that monitoring goals are realistically achieved.

Species distribution models ( SDM s) can provide estimates of suitable areas to invasion. Predictions from these models can be applied as inputs in optimization strategies seeking to identify the optimal extent of the networks of areas required for monitoring risk of invasion under current and future environmental conditions. A hierarchical framework is proposed herein that combines SDM s, scenario analysis and cost analyses to improve invasion assessments at regional and local scales. We illustrate the framework with Acacia dealbata Link. (Silver‐wattle) in northern Portugal. The framework is general and applicable to any species.

We defined two types of monitoring networks focusing either on the regional‐scale management of an invasion, or management focus within and around protected areas. For each one of these two schemes, we designed a hierarchical framework of spatial prioritization using different information layers (e.g. SDM s, habitat connectivity, protected areas). We compared the performance of each monitoring scheme against 100 randomly generated models.

In our case study, we found that protected areas will be increasingly exposed to invasion by A. dealbata due to climate change. Moreover, connectivity between suitable areas for A. dealbata is predicted to increase. Monitoring networks that we identify were more effective in detecting new invasions and less costly to management than randomly generated models. The most cost‐efficient monitoring schemes require 18% less effort than the average networks across all of the 100 tested options.

Synthesis and applications . The proposed framework achieves cost‐effective monitoring networks, enabling the interactive exploration of different solutions and the combination of quantitative information on network performance with orientations that are rarely incorporated in a decision support system. The framework brings invasion monitoring closer to European legislation and management needs while ensuring adaptability under rapid climate and environmental change.

Sponsoring Organization:
USDOE
OSTI ID:
1401421
Journal Information:
Journal of Applied Ecology, Journal Name: Journal of Applied Ecology Journal Issue: 5 Vol. 53; ISSN 0021-8901
Publisher:
Wiley-BlackwellCopyright Statement
Country of Publication:
United Kingdom
Language:
English

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