- D.J. Brus (1)
- Marieke E. Timmerman (1)
- Timothy G. O'Brien (1)
- I.R. Geijzendorffer (1)
- R.H.G. Jongman (1)
- Manuel K. Schneider (1)
- M. Knotters (1)
- Edoardo Saccenti (1)
- I.G. Staritsky (1)
- Stefano Targetti (1)
- Jeroen Vos (1)
Payment for ecosystem services in Lima’s watersheds: power and imaginaries in an urban-rural hydrosocial territory
Bleeker, Sonja ; Vos, Jeroen - \ 2019
Water International 44 (2019)2. - ISSN 0250-8060 - p. 224 - 242.
hydrosocial territories - Lima - Payment for ecosystem services - power analysis - rural-urban relations
In Peru, payment for ecosystem services is an increasingly popular mechanism to secure the transfer of water from rural to urban areas. This article analyzes the process of setting up such a scheme in the watersheds of Lima. The concept of hydrosocial territories and a power analysis are used to scrutinize how urban-based imaginaries and top-down approaches result in a disregard of local knowledge, rationalities, history of urban–rural relations and land ownership structures in the highlands. This could result in unintended outcomes of the scheme and in subordinating upstream communities to the city’s needs.
Detecting tropical wildlife declines through camera-trap monitoring : An evaluation of the Tropical Ecology Assessment and Monitoring protocol
Beaudrot, Lydia ; Ahumada, Jorge ; O'Brien, Timothy G. ; Jansen, Patrick A. - \ 2019
Oryx 53 (2019)1. - ISSN 0030-6053 - p. 126 - 129.
Camera trap - conservation - monitoring - power analysis - sampling design - Tropical Ecology Assessment and Monitoring - wildlife management
Identifying optimal sampling designs for detecting population-level declines is critical for optimizing expenditures by research and monitoring programmes. The Tropical Ecology Assessment and Monitoring (TEAM) network is the most extensive tropical camera-trap monitoring programme, but the effectiveness of its sampling protocol has not been rigorously assessed. Here, we assess the power and sensitivity of the programme's camera-trap monitoring protocol for detecting occupancy changes in unmarked populations using the freely available application PowerSensor!. We found that the protocol is well suited to detect moderate (≥ 5%) population changes within 3-4 years for relatively common species that have medium to high detection probabilities (i.e. p > 0.2). The TEAM protocol cannot, however, detect typical changes in rare and evasive species, a category into which many tropical species and many species of conservation concern fall. Additional research is needed to build occupancy models for detecting change in rare and elusive species when individuals are unmarked.
Approaches to sample size determination for multivariate data : Applications to PCA and PLS-DA of omics data
Saccenti, Edoardo ; Timmerman, Marieke E. - \ 2016
Journal of Proteome Research 15 (2016)8. - ISSN 1535-3893 - p. 2379 - 2393.
covariance estimation - dimensionality - eigenvalue distribution - hypothesis testing - loading estimation - multivariate analysis - power analysis - random matrix theory
Sample size determination is a fundamental step in the design of experiments. Methods for sample size determination are abundant for univariate analysis methods, but scarce in the multivariate case. Omics data are multivariate in nature and are commonly investigated using multivariate statistical methods, such as principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). No simple approaches to sample size determination exist for PCA and PLS-DA. In this paper we will introduce important concepts and offer strategies for (minimally) required sample size estimation when planning experiments to be analyzed using PCA and/or PLS-DA.
Data from: How much would it cost to monitor farmland biodiversity in Europe?
Geijzendorffer, I.R. ; Targetti, Stefano ; Schneider, Manuel K. ; Brus, D.J. ; Jongman, R.H.G. ; Knotters, M. ; Bogers, M.M.B. ; Staritsky, I.G. - \ 2015
species richness - farmland biodiversity - habitat - plants - spiders - bees - earth worms - agriculture - agri-environment schemes - biodiversity indicator - common agricultural policy - empirical data - farming system - sampling design - species trend - power analysis
To evaluate progress on political biodiversity objectives, biodiversity monitoring provides information on whether intended results are being achieved. Despite scientific proof that monitoring and evaluation increase the (cost) efficiency of policy measures, cost estimates for monitoring schemes are seldom available, hampering their inclusion in policy programme budgets. Empirical data collected from 12 case studies across Europe were used in a power analysis to estimate the number of farms that would need to be sampled per major farm type to detect changes in species richness over time for four taxa (vascular plants, earthworms, spiders and bees). A sampling design was developed to allocate spatially, across Europe, the farms that should be sampled. Cost estimates are provided for nine monitoring scenarios with differing robustness for detecting temporal changes in species numbers. These cost estimates are compared with the Common Agricultural Policy (CAP) budget (2014–2020) to determine the budget allocation required for the proposed farmland biodiversity monitoring. Results show that the bee indicator requires the highest number of farms to be sampled and the vascular plant indicator the lowest. The costs for the nine farmland biodiversity monitoring scenarios corresponded to 0·01%–0·74% of the total CAP budget and to 0·04%–2·48% of the CAP budget specifically allocated to environmental targets. Synthesis and applications. The results of the cost scenarios demonstrate that, based on the taxa and methods used in this study, a Europe-wide farmland biodiversity monitoring scheme would require a modest share of the Common Agricultural Policy budget. The monitoring scenarios are flexible and can be adapted or complemented with alternate data collection options (e.g. at national scale or voluntary efforts), data mobilization, data integration or modelling efforts.