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Effects of occupancy estimation on abundance-occupancy relationships.

ABSTRACT: Abundance-occupancy relationships predict that species that occupy more sites are also more locally abundant, where occupancy is usually estimated following the assumption that species can occupy all sampled sites. Here we use the National Ecological Observatory Network small-mammal data to assess whether this assumption affects abundance-occupancy relationships. We estimated occupancy considering all sampled sites (traditional occupancy) and only the sites found within the species geographic range (spatial occupancy) and realized environmental niche (environmental occupancy). We found that when occupancy was estimated considering only sites possible for the species to colonize (spatial and environmental occupancy) weaker abundance-occupancy relationships were observed. This shows that the assumption that the species can occupy all sampled sites directly affects the assessment of abundance-occupancy relationships. Estimating occupancy considering only sites that are possible for the species to colonize will consequently lead to a more robust assessment of abundance-occupancy relationships.

SUBMITTER: Ten Caten C

PROVIDER: S-EPMC9174727 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Effects of occupancy estimation on abundance-occupancy relationships.

Ten Caten Cleber C Holian Lauren A LA Dallas Tad T

Biology letters 20220608 6

Abundance-occupancy relationships predict that species that occupy more sites are also more locally abundant, where occupancy is usually estimated following the assumption that species can occupy all sampled sites. Here we use the National Ecological Observatory Network small-mammal data to assess whether this assumption affects abundance-occupancy relationships. We estimated occupancy considering all sampled sites (traditional occupancy) and only the sites found within the species geographic ra ...[more]

PMID: 35673875

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Project description:Abundance-occupancy (A-O) relationships are widely documented for many organismal groups and regions, and have been used to gain an understanding of regional population and community trends. Monitoring changes in abundance and occupancy over time may be what is required to document changes in conservation status and needs for some species, communities, or areas.We hypothesize that if there is a higher proportion of declining species in one group of species compared with another (e.g., migratory species vs. permanent residents), then a consequence of that difference will be vastly different abundance-occupancy relationships. If this difference persists through time, then the resulting A-O relationships between the groups will continue to diverge.For neotropical migrants, short-distance migrants, and permanent resident birds of North America, we assess the numbers of declining species over 1969-2009. We further test for differences in the A-O relationship across these three groups, and in rates of change in abundance and occupancy separately.We find significant differences in numbers of declining species across the migratory groups, a significant decline in the A-O relationship for permanent residents, a significant increase for Neotropical migrants, and a nonsignificant decline for short-distance migrants over the 40 years. Further, abundances are not changing at different rates but occupancies are consistently greater over time for neotropical migrants versus permanent residents, likely driving the changes in A-O relationships observed.In these analyses, we documented changing A-O trends for different groups of species, over a relatively long time period for ecological studies, one of only a few studies to examine A-O relationships over time. Further, we have shown that a temporally unvarying abundance-occupancy relationship is not universal, and we posit that variability in A-O relationships is due to human impacts on habitats, coupled with variation in species' abilities to respond to human impacts.

Project description:Estimating the abundance of wild carnivores is of foremost importance for conservation and management. However, given their elusive habits, direct observations of these animals are difficult to obtain, so abundance is more commonly estimated from sign surveys or radio-marked individuals. These methods can be costly and difficult, particularly in large areas with heavy forest cover. As an alternative, recent research has suggested that wolf abundance can be estimated from occupancy-abundance curves derived from "virtual" surveys of simulated wolf track networks. Although potentially more cost-effective, the utility of this approach hinges on its robustness to violations of its assumptions. We assessed the sensitivity of the occupancy-abundance approach to four assumptions: variation in wolf movement rates, changes in pack cohesion, presence of lone wolves, and size of survey units. Our simulations showed that occupancy rates and wolf pack abundances were biased high if track surveys were conducted when wolves made long compared to short movements, wolf packs were moving as multiple hunting units as opposed to a cohesive pack, and lone wolves were moving throughout the surveyed landscape. We also found that larger survey units (400 and 576 km2) were more robust to changes in these factors than smaller survey units (36 and 144 km2). However, occupancy rates derived from large survey units rapidly reached an asymptote at 100% occupancy, suggesting that these large units are inappropriate for areas with moderate to high wolf densities (>15 wolves/1,000 km2). Virtually-derived occupancy-abundance relationships can be a useful method for monitoring wolves and other elusive wildlife if applied within certain constraints, in particular biological knowledge of the surveyed species needs to be incorporated into the design of the occupancy surveys. Further, we suggest that the applicability of this method could be extended by directly incorporating some of its assumptions into the modelling framework.

Project description:Myriapods, including the diverse and familiar centipedes and millipedes, are one of the dominant terrestrial arthropod groups. Although molecular evidence has shown that Myriapoda is monophyletic, its internal phylogeny remains contentious and understudied, especially when compared to those of Chelicerata and Hexapoda. Until now, efforts have focused on taxon sampling (e.g., by including a handful of genes from many species) or on maximizing matrix size (e.g., by including hundreds or thousands of genes in just a few species), but a phylogeny maximizing sampling at both levels remains elusive. In this study, we analyzed 40 Illumina transcriptomes representing 3 of the 4 myriapod classes (Diplopoda, Chilopoda, and Symphyla); 25 transcriptomes were newly sequenced to maximize representation at the ordinal level in Diplopoda and at the family level in Chilopoda. Ten supermatrices were constructed to explore the effect of several potential phylogenetic biases (e.g., rate of evolution, heterotachy) at 3 levels of gene occupancy per taxon (50%, 75%, and 90%). Analyses based on maximum likelihood and Bayesian mixture models retrieved monophyly of each myriapod class, and resulted in 2 alternative phylogenetic positions for Symphyla, as sister group to Diplopoda + Chilopoda, or closer to Diplopoda, the latter hypothesis having been traditionally supported by morphology. Within centipedes, all orders were well supported, but 2 deep nodes remained in conflict in the different analyses despite dense taxon sampling at the family level. Relationships among centipede orders in all analyses conducted with the most complete matrix (90% occupancy) are at odds not only with the sparser but more gene-rich supermatrices (75% and 50% supermatrices) and with the matrices optimizing phylogenetic informativeness or most conserved genes, but also with previous hypotheses based on morphology, development, or other molecular data sets. Our results indicate that a high percentage of ribosomal proteins in the most complete matrices, in conjunction with distance from the root, can act in concert to compromise the estimated relationships within the ingroup. We discuss the implications of these findings in the context of the ever more prevalent quest for completeness in phylogenomic studies.

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Project description:Multispecies occupancy models can estimate species richness from spatially replicated multispecies detection/non-detection survey data, while accounting for imperfect detection. A model extension using data augmentation allows inferring the total number of species in the community, including those completely missed by sampling (i.e., not detected in any survey, at any site). Here we investigate the robustness of these estimates. We review key model assumptions and test performance via simulations, under a range of scenarios of species characteristics and sampling regimes, exploring sensitivity to the Bayesian priors used for model fitting. We run tests when assumptions are perfectly met and when violated. We apply the model to a real dataset and contrast estimates obtained with and without predictors, and for different subsets of data. We find that, even with model assumptions perfectly met, estimation of the total number of species can be poor in scenarios where many species are missed (>15%-20%) and that commonly used priors can accentuate overestimation. Our tests show that estimation can often be robust to violations of assumptions about the statistical distributions describing variation of occupancy and detectability among species, but lower-tail deviations can result in large biases. We obtain substantially different estimates from alternative analyses of our real dataset, with results suggesting that missing relevant predictors in the model can result in richness underestimation. In summary, estimates of total richness are sensitive to model structure and often uncertain. Appropriate selection of priors, testing of assumptions, and model refinement are all important to enhance estimator performance. Yet, these do not guarantee accurate estimation, particularly when many species remain undetected. While statistical models can provide useful insights, expectations about accuracy in this challenging prediction task should be realistic. Where knowledge about species numbers is considered truly critical for management or policy, survey effort should ideally be such that the chances of missing species altogether are low.

Dataset Information

Effects of occupancy estimation on abundance-occupancy relationships.

Publications

Effects of occupancy estimation on abundance-occupancy relationships.

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