Contrasting spatial, temporal and environmental patterns in observation and specimen based species occurrence data

Biodiversity dataset and atlas of the special area of conservation Montesinho/Nogueira, Portugal

Background

The special area of conservation Montesinho/Nogueira (SAC-MN) is a key area for biodiversity conservation in the Iberian Peninsula. Covering an area of approximately 1081 km² in the northeast of Portugal mainland, the SAC-MN is home to a wide range of species, including several endemic and endangered species and priority habitats. Despite its ecological significance and importance for conservation, there is a lack of publicly available biodiversity data, which urges the need to create a comprehensive and up-to-date biodiversity dataset for the SAC-MN.

New information

To bridge the knowledge gap on biodiversity in SAC-MN, we undertook a thorough data collection process, including species occurrence records and conservation status information at regional (Portugal) and European levels, from multiple sources. We collected and compiled this information for five major taxonomic groups (amphibians, birds, flora - vascular plants, mammals and reptiles) in SAC-MN, resulting in a total of 31,871 records with 1,312 documented species. In addition, we developed an easy-to-navigate web-based geographic information system (Web GIS). In this article, we present an in-depth report on the process of compiling and preparing data, as well as the development and design of our Web GIS to increase awareness and enhance understanding of the importance of preserving biodiversity in SAC-MN.

Exploring the impact of data curation criteria on the observed geographical distribution of mosses

Biodiversity data records contain inaccuracies and biases. To overcome this limitation and establish robust geographic patterns, ecologists often curate records keeping those that are most suitable for their analyses. Yet, this choice is not straightforward and the outcome of the analysis may vary due to a trade-off between data quality and volume. This problem is particularly recurrent for less-studied groups with patchy sampling effort. The latitudinal pattern of mosses richness remains inconsistent across studies and these may emerge purely from sampling artefacts. Our main objective here is to assess the effect of different curation criteria on this spatial pattern in the Temperate Northern Hemisphere (above 20° latitude). We contrasted the geographical distribution of moss species records and the latitude-species richness relation obtained under different data curation scenarios. These scenarios comprehend five sources of taxonomical standardisations and eight data cleaning filters. The analyses are based on the selection of well-surveyed cells at 100 km cell resolution. The application of some 'data curation scenarios' severely affects the number of records selected for analysis and substantially changes the proportion of richness per cell. The sensitivity to data curation becomes detectable at regional and at the cell scales showing a large shift in the latitudinal richness peak in Europe, from 60° N to 45° N latitude, when only preserved specimens are selected and duplicates based on date of collection and coordinates are excluded. Our results stress the importance of justifying the criteria used for filtering biodiversity data retrieved from biodiversity databases to avoid detecting misleading patterns. Curating records under particular criteria compromises the information in some areas displaying different spatial information of mosses. This problem can be ameliorated if data filtering is combined with identifying well-surveyed cells, render relatively constant results under different combinations of filtering even for less well-known groups such as mosses.

Not all who wander are lost: Trail bias in community science

The exponential growth and interest in community science programs is producing staggering amounts of biodiversity data across broad temporal and spatial scales. Large community science datasets such as iNaturalist and eBird are allowing ecologists and conservation biologists to answer novel questions that were not possible before. However, the opportunistic nature of many of these enormous datasets leads to biases. Spatial bias is a common problem, where observations are biased towards points of access like roads and trails. iNaturalist-a popular biodiversity community science platform-exhibits strong spatial biases, but it is unclear how these biases affect the quality of biodiversity data collected. Thus, we tested whether fine-scale spatial bias due to sampling from trails affects taxonomic richness estimates. We compared timed transects with experienced iNaturalist observers on and off trails in British Columbia, Canada. Using generalized linear mixed models, we found higher overall taxonomic richness on trails than off trails. In addition, we found more exotic as well as native taxa on trails than off trails. There was no difference between on and off trail observations for species that are rarely observed. Thus, fine-scale spatial bias from trails does not reduce the quality of biodiversity measurements, a promising result for those interested in using iNaturalist data for research and conservation management.

Mass production of unvouchered records fails to represent global biodiversity patterns

The ever-increasing human footprint even in very remote places on Earth has inspired efforts to document biodiversity vigorously in case organisms go extinct. However, the data commonly gathered come from either primary voucher specimens in a natural history collection or from direct field observations that are not traceable to tangible material in a museum or herbarium. Although both datasets are crucial for assessing how anthropogenic drivers affect biodiversity, they have widespread coverage gaps and biases that may render them inefficient in representing patterns of biodiversity. Using a large global dataset of around 1.9 billion occurrence records of terrestrial plants, butterflies, amphibians, birds, reptiles and mammals, we quantify coverage and biases of expected biodiversity patterns by voucher and observation records. We show that the mass production of observation records does not lead to higher coverage of expected biodiversity patterns but is disproportionately biased toward certain regions, clades, functional traits and time periods. Such coverage patterns are driven by the ease of accessibility to air and ground transportation, level of security and extent of human modification at each sampling site. Conversely, voucher records are vastly infrequent in occurrence data but in the few places where they are sampled, showed relative congruence with expected biodiversity patterns for all dimensions. The differences in coverage and bias by voucher and observation records have important implications on the utility of these records for research in ecology, evolution and conservation research.

A regionally coherent ecological fingerprint of climate change, evidenced from natural history collections

Climate change has dramatic impacts on ecological systems, affecting a range of ecological factors including phenology, species abundance, diversity, and distribution. The breadth of climate change impacts on ecological systems leads to the occurrence of fingerprints of climate change. However, climate fingerprints are usually identified across broad geographical scales and are potentially influenced by publication biases. In this study, we used natural history collections spanning over 250 years, to quantify a range of ecological responses to climate change, including phenology, abundance, diversity, and distributions, across a range of taxa, including vertebrates, invertebrates, plants, and fungi, within a single region, Central Norway. We tested the hypotheses that ecological responses to climate change are apparent and coherent at a regional scale, that longer time series show stronger trends over time and in relation to temperature, and that ecological responses change in trajectory at the same time as shifts in temperature. We identified a clear regional coherence in climate signal, with decreasing abundances of limnic zooplankton (on average by 7691 individuals m-3 °C-1) and boreal forest breeding birds (on average by 1.94 territories km-2 °C-1), and earlier plant flowering phenology (on average 2 days °C-1) for every degree of temperature increase. In contrast, regional-scale species distributions and species diversity were largely stable. Surprisingly, the effect size of ecological response did not increase with study duration, and shifts in responses did not occur at the same time as shifts in temperature. This may be as the long-term studies include both periods of warming and temperature stability, and that ecological responses lag behind warming. Our findings demonstrate a regional climate fingerprint across a long timescale. We contend that natural history collections provide a unique window on a broad spectrum of ecological responses at timescales beyond most ecological monitoring programs. Natural history collections are thus an essential source for long-term ecological research.

Urbanisation and land-cover change affect functional, but not compositional turnover of bird communities

Land-use and land-cover change strongly affect biodiversity patterns and are assumed to be growing threats in the future. Particularly increasing urbanisation may affect species turnover and functional composition of biological communities. This study aimed to assess the characteristics of land-cover change in a medium-sized urban municipality from 2011 to 2018, and the effects of urbanisation on avian species- and functional diversity. The study was performed in Trondheim (Norway), using local land-cover maps and GBIF bird species occurrence records. GLMMs were used to model species turnover as a function of urbanisation, and the probability of species appearance and disappearance based on urbanisation and species traits. The extent of bird species turnover within a municipality-wide 500 × 500m2 grid was not predicted by a changes in developed area, but the probability of disappearance and appearance of bird species varied with urbanisation and bird functional traits. Species associated with urban- or open areas showed a decreasing probability of disappearing and an increasing probability of appearing with increasing amount of developed area within grid cells. Similarly, granivorous species showed a decreasing probability of disappearing. Species feeding above ground-level showed positive responses to changes in land-cover. The probability of both appearance and disappearance, thus species turnover, increased with increasing longevity. Most functional groups respond negatively to increasing urbanisation, indicating a potential impoverishment of local avifauna with future land-cover modifications. Considering planned future land-cover changes within the municipality, the local avian communities are in danger of homogenisation. The recommendations for local management are to minimise conversion of vulnerable habitats, such as wetlands and woodlands, in particular if these are converted to developed area.

Open Data Practices among Users of Primary Biodiversity Data

Presence-only biodiversity data are increasingly relied on in biodiversity, ecology, and conservation research, driven by growing digital infrastructures that support open data sharing and reuse. Recent reviews of open biodiversity data have clearly documented the value of data sharing, but the extent to which the biodiversity research community has adopted open data practices remains unclear. We address this question by reviewing applications of presence-only primary biodiversity data, drawn from a variety of sources beyond open databases, in the indexed literature. We characterize how frequently researchers access open data relative to data from other sources, how often they share newly generated or collated data, and trends in metadata documentation and data citation. Our results indicate that biodiversity research commonly relies on presence-only data that are not openly available and neglects to make such data available. Improved data sharing and documentation will increase the value, reusability, and reproducibility of biodiversity research.

occAssess: An R package for assessing potential biases in species occurrence data

Species occurrence records from a variety of sources are increasingly aggregated into heterogeneous databases and made available to ecologists for immediate analytical use. However, these data are typically biased, i.e. they are not a probability sample of the target population of interest, meaning that the information they provide may not be an accurate reflection of reality. It is therefore crucial that species occurrence data are properly scrutinised before they are used for research. In this article, we introduce occAssess, an R package that enables straightforward screening of species occurrence data for potential biases. The package contains a number of discrete functions, each of which returns a measure of the potential for bias in one or more of the taxonomic, temporal, spatial, and environmental dimensions. Users can opt to provide a set of time periods into which the data will be split; in this case separate outputs will be provided for each period, making the package particularly useful for assessing the suitability of a dataset for estimating temporal trends in species' distributions. The outputs are provided visually (as ggplot2 objects) and do not include a formal recommendation as to whether data are of sufficient quality for any given inferential use. Instead, they should be used as ancillary information and viewed in the context of the question that is being asked, and the methods that are being used to answer it. We demonstrate the utility of occAssess by applying it to data on two key pollinator taxa in South America: leaf-nosed bats (Phyllostomidae) and hoverflies (Syrphidae). In this worked example, we briefly assess the degree to which various aspects of data coverage appear to have changed over time. We then discuss additional applications of the package, highlight its limitations, and point to future development opportunities.

Suitability of open digital species records for assessing biodiversity patterns in cities: a case study using avian records

Openly available species observation records on various online platforms achieve good coverage in urban areas. Thus, such digital data could provide a basis for biodiversity assessments in cities. Here, we investigated suitability of open digital species occurrence data, compared with systematically field surveyed data, in Freiburg, Germany (a Western city) and Dhaka, Bangladesh (a global-South city). We focused on resident bird species richness as an indicator of local biodiversity. We collected avian records for urban areas from ‘ornitho.de’ in Freiburg and ‘gbif.org’ in Dhaka. Additionally, we conducted point count surveys at several urban locations in both cities. Using these records, we prepared three grid (cell size 250 m × 250 m) based datasets—open digital dataset (i.e. records compiled from well-surveyed grid cells), field surveyed dataset (i.e. records of systematic bird surveys) and combined dataset (i.e. digital data and field data combined). We compared the relationship of resident bird richness with different habitat factors by applying linear regression models, separately using each of the three datasets. We assessed suitability of data from online platforms by comparing the variables retained after model selection based on digital data versus field surveyed data. We found that field surveyed data and combined data did not alter general understanding of the key driving factors of bird richness patterns we obtained from open digital data. This held for both case examples, Freiburg vs. Dhaka, respectively. This suggests that open digital data from well-surveyed urban locations can provide a suitable basis to assess drivers of biodiversity patterns within cities.