RESUMO
BACKGROUND: Implementing REDD+ renders the development of a measurement, reporting and verification (MRV) system necessary to monitor carbon stock changes. MRV systems generally apply a combination of remote sensing techniques and in-situ field assessments. In-situ assessments can be based on 1) permanent plots, which are assessed on all successive occasions, 2) temporary plots, which are assessed only once, and 3) a combination of both. The current study focuses on in-situ assessments and addresses the effect of treatment bias, which is introduced by managing permanent sampling plots differently than the surrounding forests. Temporary plots are not subject to treatment bias, but are associated with large sampling errors and low cost-efficiency. Sampling with partial replacement (SPR) utilizes both permanent and temporary plots. RESULTS: We apply a scenario analysis with different intensities of deforestation and forest degradation to show that SPR combines cost-efficiency with the handling of treatment bias. Without treatment bias permanent plots generally provide lower sampling errors for change estimates than SPR and temporary plots, but do not provide reliable estimates, if treatment bias occurs, SPR allows for change estimates that are comparable to those provided by permanent plots, offers the flexibility to adjust sample sizes in the course of time, and allows to compare data on permanent versus temporary plots for detecting treatment bias. Equivalence of biomass or carbon stock estimates between permanent and temporary plots serves as an indication for the absence of treatment bias while differences suggest that there is evidence for treatment bias. CONCLUSIONS: SPR is a flexible tool for estimating emission factors from successive measurements. It does not entirely depend on sample plots that are installed at the first occasion but allows for the adjustment of sample sizes and placement of new plots at any occasion. This ensures that in-situ samples provide representative estimates over time. SPR offers the possibility to increase sampling intensity in areas with high degradation intensities or to establish new plots in areas where permanent plots are lost due to deforestation. SPR is also an ideal approach to mitigate concerns about treatment bias.
RESUMO
Introgression is a key process in conservation biology, genetic modification of (crop) species and in the evolutionary ecology of many species. Here we consider the case of introgression of insecticide resistance in the whitefly, Bemisia tabaci. B. tabaci is a species complex consisting of a range of biotypes, known to have a high degree of inter-biotype reproductive isolation. In areas where insecticide resistant and susceptible biotypes of B. tabaci coexist, introgression of the resistance gene will have considerable consequences for whitefly control. Using a stochastic branching process model we calculate the relative importance of life-history traits in determining the probability of introgression given that a hybridization event has occurred. We show that a fitness cost expressed through the average number of eggs laid, has the largest effect on the introgression probability as compared to fitness costs expressed through other life-history parameters. These results change when we consider a reproductive isolation mechanism, for which we show that the fitness cost expressed through the male survival and mating probability have the largest effect on the probability of introgression.
