How to identify future sampling areas when information is biased and scarce: An example using predictive models for species richness of Iberian water beetles

Completeness of Digital Accessible Knowledge (DAK) about terrestrial mammals in the Iberian Peninsula

The advent of online data aggregator infrastructures has facilitated the accumulation of Digital Accessible Knowledge (DAK) about biodiversity. Despite the vast amount of freely available data records, their usefulness for research depends on completeness of each body of data regarding their spatial, temporal and taxonomic coverage. In this paper, we assess the completeness of DAK about terrestrial mammals distributed across the Iberian Peninsula. We compiled a dataset with all records about mammals occurring in the Iberian Peninsula available in the Global Biodiversity Information Facility and in the national atlases from Portugal and Spain. After cleaning the dataset of errors as well as records lacking collection dates or not determined to species level, we assigned all occurrences to a 10-km grid. We assessed inventory completeness by calculating the ratio between observed and expected richness (based on the Chao2 richness index) in each grid cell and classified cells as well-sampled or under-sampled. We evaluated survey coverage of well-sampled cells along four environmental gradients and temporal coverage. Out of 796,283 retrieved records, quality issues led us to remove 616,141 records unfit for this use. The main reason for discarding records was missing collection dates. Only 25.95% cells contained enough records to robustly estimate completeness. The DAK about terrestrial mammals from the Iberian Peninsula was low, and spatially and temporally biased. Out of 5,874 cells holding data, only 620 (9.95%) were classified as well-sampled. Moreover, well-sampled cells were geographically aggregated and reached inventory completeness over the same temporal range. Despite the increasing availability of DAK, its usefulness is still compromised by quality issues and gaps in data. Future work should therefore focus on increasing data quality, in addition to mobilizing unpublished data.

Water Beetles as Models in Ecology and Evolution

Beetles have colonized water many times during their history, with some of these events involving extensive evolutionary radiations and multiple transitions between land and water. With over 13,000 described species, they are one of the most diverse macroinvertebrate groups in most nonmarine aquatic habitats and occur on all continents except Antarctica. A combination of wide geographical and ecological range and relatively accessible taxonomy makes these insects an excellent model system for addressing a variety of questions in ecology and evolution. Work on water beetles has recently made important contributions to fields as diverse as DNA taxonomy, macroecology, historical biogeography, sexual selection, and conservation biology, as well as predicting organismal responses to global change. Aquatic beetles have some of the best resolved phylogenies of any comparably diverse insect group, and this, coupled with recent advances in taxonomic and ecological knowledge, is likely to drive an expansion of studies in the future.

Biodiversity data obsolescence and land uses changes

Background

Primary biodiversity records (PBR) are essential in many areas of scientific research as they document the biodiversity through time and space. However, concerns about PBR quality and fitness-for-use have grown, especially as derived from taxonomical, geographical and sampling effort biases. Nonetheless, the temporal bias stemming from data ageing has received less attention. We examine the effect of changes in land use in the information currentness, and therefore data obsolescence, in biodiversity databases.

Methods

We created maps of land use changes for three periods (1956–1985, 1985–2000 and 2000–2012) at 5-kilometres resolution. For each cell we calculated the percentage of land use change within each period. We then overlaid distribution data about small mammals, and classified each data as ‘non-obsolete or ‘obsolete,’ depending on both the amount of land use changes in the cell, and whether changes occurred at or after the data sampling’s date.

Results

A total of 14,528 records out of the initial 59,677 turned out to be non-obsolete after taking into account the changes in the land uses in Navarra. These obsolete data existed in 115 of the 156 cells analysed. Furthermore, more than one half of the remaining cells holding non-obsolete records had not been visited at least for the last fifteen years.

Conclusion

Land use changes challenge the actual information obtainable from biodiversity datasets and therefore its potential uses. With the passage of time, one can expect a steady increase in the availability and use of biological records—but not without them becoming older and likely to be obsolete by land uses changes. Therefore, it becomes necessary to assess records’ obsolescence, as it may jeopardize the knowledge and perception of biodiversity patterns.

How to describe species richness patterns for bryophyte conservation?

A large amount of data for inconspicuous taxa is stored in natural history collections; however, this information is often neglected for biodiversity patterns studies. Here, we evaluate the performance of direct interpolation of museum collections data, equivalent to the traditional approach used in bryophyte conservation planning, and stacked species distribution models (S‐SDMs) to produce reliable reconstructions of species richness patterns, given that differences between these methods have been insufficiently evaluated for inconspicuous taxa. Our objective was to contrast if species distribution models produce better inferences of diversity richness than simply selecting areas with the higher species numbers. As model species, we selected Iberian species of the genus Grimmia (Bryophyta), and we used four well‐collected areas to compare and validate the following models: 1) four Maxent richness models, each generated without the data from one of the four areas, and a reference model created using all of the data and 2) four richness models obtained through direct spatial interpolation, each generated without the data from one area, and a reference model created with all of the data. The correlations between the partial and reference Maxent models were higher in all cases (0.45 to 0.99), whereas the correlations between the spatial interpolation models were negative and weak (−0.3 to −0.06). Our results demonstrate for the first time that S‐SDMs offer a useful tool for identifying detailed richness patterns for inconspicuous taxa such as bryophytes and improving incomplete distributions by assessing the potential richness of under‐surveyed areas, filling major gaps in the available data. In addition, the proposed strategy would enhance the value of the vast number of specimens housed in biological collections.

[Sampling effort and floristic atlases: survey completeness of localities and description of knowledge gaps]

Floristic atlases have an important input to flora conservation planning even though their data quality varied greatly across countries. This study aimed to assess survey completeness of cells of floristic atlases. Then, a surveying guide is designed to overcome as efficiently as possible sampling biases. A review and analyses on a wide dataset were carried out to select an estimator of the true species richness of surveyed cells. The Jackknife 1, a non-parametric estimator, appeared as the best compromise for regional floristic atlases. The number of records in each cell was used as an estimator of sampling effort. The ratio between the observed species richness and the estimated species richness measures the completeness of inventories in each surveyed cell. Eighteen variables were selected to describe current inventories and design new surveys. These variables highlight locations, periods and species to be given priority in future studies.