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- Knape, Jonas, et al.
(författare)
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Sensitivity of binomial N-mixture models to overdispersion: The importance of assessing model fit
- 2018
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Ingår i: Methods in Ecology and Evolution. - 2041-210X. ; 9, s. 2102-2114
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Tidskriftsartikel (refereegranskat)abstract
- 1. Binomial N-mixture models are commonly applied to analyse population survey data. By estimating detection probabilities, N-mixture models aim at extracting information about abundances in terms of absolute and not just relative numbers. This separation of detection probability and abundance relies on parametric assumptions about the distribution of individuals among sites and of detections of individuals among repeat visits to sites. Current methods for checking assumptions are limited, and their computational complexity has hindered evaluations of their performance.2. We use simulations and a case study to assess the sensitivity of binomial N-mixture models to overdispersion in abundance and in detection, develop computationally efficient graphical goodness of fit checks to detect it, and evaluate the ability of the checks to identify overdispersion.3. The simulations show that if the parametric assumptions are not exact the bias in estimated abundances can be severe: underestimation if there is overdispersion in abundance relative to the fitted model and overestimation if there is overdispersion in detection. Our goodness-of-fit checks performed well in detecting lack of fit when the abundance distribution was overdispersed, but struggled to detect lack of fit when detections were overdispersed. We show that the inability to detect lack of fit due to overdispersed detection is caused by a fundamental similarity between N-mixture models with beta-binomial detections and N-mixture models with negative binomial abundances.4. The strong biases that can occur in the binomial N-mixture model when the distribution of individuals among sites, or the detection model, is mis-specified implies that checking goodness of fit is essential for sound inference about abundance. To check the assumptions we provide computationally efficient goodness of fit checks that are available in an R-package nmixgof. However, even when a binomial N-mixture model appears to fit the data well, estimates are not robust in the presence of overdispersion. We show that problems can occur even when estimated detection probabilities are high, and that previously reported problems with negative binomial models cannot always be diagnosed by checking the sensitivity of abundance estimates to numerical cutoff values used in likelihood computations.
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| 2. |
- Ruete, Alejandro, et al.
(författare)
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Conservation benefits of international Aichi protection and restoration targets for future epiphyte metapopulations
- 2018
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Ingår i: Journal of Applied Ecology. - : Wiley. - 0021-8901 .- 1365-2664. ; 55, s. 118-128
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Tidskriftsartikel (refereegranskat)abstract
- More than half way towards the deadline for 2020 Aichi targets, a key question is whether the metapopulation dynamics of dispersal-restricted habitat specialists can be sustained under current international targets of protection and restoration.We present the first metapopulation projections under scenarios of multiple Aichi biodiversity targets of protecting high-quality habitats and restoring suboptimal quality habitats under management. We simulate 200 years of metapopulation dynamics of nine old-growth beech (Fagus sylvatica)-associated epiphytic lichens, under a range of protection and restoration scenarios in a realistic landscape realm.Protection was generally more efficient than restoration, where protection resulted in a constant increase in occupancy over time. However, projections showed that substantial increments in the number of occupied protected beech stands will most likely occur within the next 100-200 years. The time frame was dependent on species-specific dispersal restriction, occupancy levels at onset and forest-age requirements. Suboptimally restored beech stands increased lichen metapopulation sizes over a transient period and shortened the time for dispersal-restricted species to reach higher occupancy levels inside protected areas of the landscape (c. 85-125 years).Synthesis and applications. Based on projections of metapopulation dynamics of species associated with old-growth forest, we argue that a combination of protection and restoration with the shortest possible time frame for increasing occupancy is the safest strategy. This is especially important under climatic and socio-political changes that are unforeseeable over centuries. If choosing between conservation strategies, highest priority should be given to increased protection because it means larger metapopulation sizes of these species on the long term.
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