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Data Analysis & Interpretation
Data analysis and interpretation are part of the evaluation aspect of adaptive management, the process for conserving, protecting, and, where appropriate, restoring lands, waters and other resources in a protected area. Adaptive management is often defined as a system of management practices based upon clearly identified outcomes, where monitoring evaluates whether management actions are achieving desired results (objectives). Adaptive management is a decision process that promotes flexible decision making that can be adjusted in the face of uncertainties as outcomes from management actions and other events become better understood through data analysis and interpretation.
Adaptive management accounts for the fact that complete knowledge about fish, wildlife, plants, habitats, and the ecological processes supporting them may be lacking. The role of natural variability contributing to ecological resilience also is recognized as an important principle of adaptive management. It is not a “trial and error” process, but rather emphasizes learning while doing based upon available scientific information and best professional judgment considering site-specific biotic and abiotic factors in protected areas. Adaptive management results in effective monitoring and evaluation of a protected area management plan.
For many protected area practitioners, data analysis and interpretation can be a daunting task. Often, resources and training are provided on the practical aspects of monitoring without much guidance on how to analyse and interpret the data for adaptive management. However, there is little point in collecting data unless you have plans to use that data for communication and/or adaptive management purposes and it is therefore very important to acquire some skills in this area.
Below are some key resources that can be used by practitioners prior to designing monitoring programs right through to the process of adaptive management. For those who have time and are truly invested in understanding data analysis, Houk’s (2010) guidebook is highly recommended. Beneath the data analysis guidebooks are a short list of references for statistical analysis.
U.S. Department of the Interior. 2009. Adaptive Management: The U.S. Department of the Interior Technical Guide.
The purpose of this technical guide is to present an operational definition of adaptive management, identify the conditions in which adaptive management should be considered, and describe the process of using adaptive management for managing natural resources. The guide is not an exhaustive discussion of adaptive management, nor does it include detailed specifications for individual projects. However, it should aid protected area managers in determining when and how to apply adaptive management.
Quod, JP., Salvat, B.; Bissery, C., Terrasson, S., Caugant, G., Lacouture, P., Raude, M. 2010. CoReMo Coral Reef Monitoring Data Entry System 2 v3.6.1. ARVAM Oceanology
CoReMo software was developed by ARVAM with support from the French Overseas Ministry, Réunion Regional Council and the EU, and in close collaboration with the WorldFish Center, Penang, Malaysia. The software is fully interoperable with ReefBase and FishBase.
CoReMo 3 is designed to help users enter and analyse data collected using the methods and protocols outlined in Methods for Ecological Monitoring of Coral Reefs.
Feinsinger, P. 2001. Designing Field Studies for Biodiversity Conservation. Island Press.
This book explains how to undertake field studies to guide conservation work and is for anyone working in conservation regardless of their professional or scientific background. The methods and procedures of scientific inquiry are explained in a step-by-step manner. The author wants to make the process of doing science accessible and effective. The purpose of this book is not only to offer information, but primarily to catalyze the process of good thinking, so that readers can learn how to think and understand the importance of broad inquiry, no matter what the conservation project.
Pomeroy, R.S., Parks, J.E., Watson, L. M. 2004. How is your MPA Doing? A Guidebook of Natural and Social Indicators for Evaluating Marine Protected Area Management Effectiveness. IUCN Gland, Switzerland and Cambridge, UK.
Chapter 3 (pages 30 – 35) of this handbook contains a description of managing MPA data once it has been collected. It discusses the various steps of data coding, storage, entry and runs through the various types of exploratory statistics that are possible. There are brief descriptions of further analysis options. The chapter concludes with a discussion of the importance of ascertaining internal and external evaluation of results.
Impact of anthropogenic disturbances on a diverse riverine fish assemblage in Fiji predicted by functional traits
Anthropogenic disturbances particularly affect biodiversity in sensitive freshwater ecosystems by causing species loss. Thus, measuring the response of species to multiple disturbances is a key issue for conservation and environmental management. 2. As it is not practical to assess the response of every species in a community, we compared the performance of trait and taxonomic-based groupings of species for their abilities to predict species loss in a threatened freshwater fish assemblage. Specifically, we examined responses of a Fijian freshwater fish assemblage to deforestation, placement of anthropogenic barriers (overhanging culverts) and the presence of introduced cichlids. 3. Species grouped by traits showed more consistent responses to disturbances than taxonomic groups.
Improving Local Capacity for Coral Reef Monitoring Data Interpretation. A Guidebook with Step-by-Step Exercises Using Regional Datasets to Improve Local Capacity for Data Interpretation.
Houk, P. 2010. Improving Local Capacity for Coral Reef Monitoring Data Interpretation. A Guidebook with Step-by-Step Exercises Using Regional Datasets to Improve Local Capacity for Data Interpretation. Pacific Marine Resources Institute, Saipan, FSM. 151pp.
This comprehensive guidebook uses Microsoft Excel, Access, PRIMER-E, and Sigma Plot software programmes and runs through step-by-step examples with sample data sets provided. The guidebook has accompanying data sets and can be used for practise and training on data analysis and interpretation.
Hodgson, G., Hill, J., Kiene, W., Maun, L., Mihaly, J., Liebeler, J., Shuman, C. and Torres, R. 2006. Instruction Manual. A Guide to Reef Check Monitoring . Reef Check Foundation, Pacific Palisades, California, USA
Reef Check provides excel spread sheets with built in macros for carrying out preliminary data analysis. Pages 31-36 of their manual have illustrated instructions for how to correctly complete the spreadsheets with explanations of the output data.
There is also a chapter discussing data analysis that explains how to interpret the results including the meanings of the standard error and the standard deviation.
Harvesting, consumption and trade of forest meat are key causes of biodiversity loss. Successful mitigation programs are proving difcult to design, in part because anthropogenic pressures are treated as internationally uniform. Despite illegal hunting being a key conservation issue in the Pacifc Islands, there is a paucity of research. Here, we examine the dynamics of hunting of birds and determine how these contribute to biodiversity loss on the islands of Samoa. We focus on the interactive efects of hunting on two key seed dispersing bird species: the Pacifc pigeon (Ducula pacifca) and the critically endangered Manumea or tooth-billed pigeon (Didunculus strigiristris). We interviewed hunters, vendors and consumers and analyzed household consumption.
The province of Lau, located in Fiji’s Eastern Division,comprises 60 islands and islets collectively known asthe Lau Group. The Lau Group has been identified as anarea of national significance and high priority for marineprotection. On 20 February 2016, Fiji was hit by Category 5 Tropical Cyclone Winston that caused widespread damage across the country. Cyclone Winston made first landfall through the Eastern Division, severely damagingthe islands and diverse ecosystems of Northern Lau. An 8 day marine biological baseline survey was conducted by Vatuvara Foundation and the Wildlife Conservation Society (WCS) from 8−16 May, 2017.
Wilkinson, C., Hill, J. 2004. Methods for Ecological Monitoring of Coral Reefs. A Resource for Managers. Australian Institute of Marine Science, Townsville, Australia and Reef Check, Los Angeles, USA. 117pp.
There is a section on data handling and storage of results on page 14 of this resource. It covers data storage, analysis and reporting. There is also a discussion of the importance in involving the public in the dissemination of the results which can be a key factor in determining the success of protected areas.
Monitoring Coral Reef Marine Protected Areas: Version 1. A Practical Guide on how Monitoring can Support Effective Management of MPAs
Wilkinson,C., Green, A., Almany, J., Dionne, S. 2003. Monitoring Coral Reef Marine Protected Areas: Version 1. A Practical Guide on how Monitoring can Support Effective Management of MPAs . Australian Institute of Marine Science, Townsville, Australia and the IUCN Marine Program, Gland, Switzerland.
Chapter 8 (Page 49) of this guide on how to carry out effective monitoring of MPAs considers data storage, analysis, accessibility and reporting. There is a description of the 8 critical steps for data management which contain some useful advice for practitioners to consider prior to carrying out data collection.
This is the first of a new series of dialogues from Equilibrium Research, in light of current opportunities and pressures on protected areas, building up to the revision of the Convention on Biological Diversity’s biodiversity targets in 2020, the implementation of the Sustainable Development Goals and wider patterns of economic and social development. The views are those of the authors and represent no other organisation or institution.
Dialogues are not referenced for reasons of space; key sources are available on request. The ideas outlined here build on our research since our founding in 1991, and in conversations and interaction with people throughout the world.