1
|
Higino GT, Banville F, Dansereau G, Forero Muñoz NR, Windsor F, Poisot T. Mismatch between IUCN range maps and species interactions data illustrated using the Serengeti food web. PeerJ 2023; 11:e14620. [PMID: 36793892 PMCID: PMC9924135 DOI: 10.7717/peerj.14620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 12/01/2022] [Indexed: 02/12/2023] Open
Abstract
Background Range maps are a useful tool to describe the spatial distribution of species. However, they need to be used with caution, as they essentially represent a rough approximation of a species' suitable habitats. When stacked together, the resulting communities in each grid cell may not always be realistic, especially when species interactions are taken into account. Here we show the extent of the mismatch between range maps, provided by the International Union for Conservation of Nature (IUCN), and species interactions data. More precisely, we show that local networks built from those stacked range maps often yield unrealistic communities, where species of higher trophic levels are completely disconnected from primary producers. Methodology We used the well-described Serengeti food web of mammals and plants as our case study, and identify areas of data mismatch within predators' range maps by taking into account food web structure. We then used occurrence data from the Global Biodiversity Information Facility (GBIF) to investigate where data is most lacking. Results We found that most predator ranges comprised large areas without any overlapping distribution of their prey. However, many of these areas contained GBIF occurrences of the predator. Conclusions Our results suggest that the mismatch between both data sources could be due either to the lack of information about ecological interactions or the geographical occurrence of prey. We finally discuss general guidelines to help identify defective data among distributions and interactions data, and we recommend this method as a valuable way to assess whether the occurrence data that are being used, even if incomplete, are ecologically accurate.
Collapse
Affiliation(s)
- Gracielle T. Higino
- Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Francis Banville
- University of Sherbrooke, Sherbrooke, Québec, Canada,University of Montreal, Montréal, Québec, Canada,Quebec Centre for Biodiversity Science, Montréal, Québec, Canada
| | - Gabriel Dansereau
- University of Montreal, Montréal, Québec, Canada,Quebec Centre for Biodiversity Science, Montréal, Québec, Canada
| | - Norma Rocio Forero Muñoz
- University of Montreal, Montréal, Québec, Canada,Quebec Centre for Biodiversity Science, Montréal, Québec, Canada
| | - Fredric Windsor
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Timothée Poisot
- University of Montreal, Montréal, Québec, Canada,Quebec Centre for Biodiversity Science, Montréal, Québec, Canada
| |
Collapse
|
2
|
Bledsoe EK, Burant JB, Higino GT, Roche DG, Binning SA, Finlay K, Pither J, Pollock LS, Sunday JM, Srivastava DS. Data rescue: saving environmental data from extinction. Proc Biol Sci 2022; 289:20220938. [PMID: 35855607 PMCID: PMC9297007 DOI: 10.1098/rspb.2022.0938] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Historical and long-term environmental datasets are imperative to understanding how natural systems respond to our changing world. Although immensely valuable, these data are at risk of being lost unless actively curated and archived in data repositories. The practice of data rescue, which we define as identifying, preserving, and sharing valuable data and associated metadata at risk of loss, is an important means of ensuring the long-term viability and accessibility of such datasets. Improvements in policies and best practices around data management will hopefully limit future need for data rescue; these changes, however, do not apply retroactively. While rescuing data is not new, the term lacks formal definition, is often conflated with other terms (i.e. data reuse), and lacks general recommendations. Here, we outline seven key guidelines for effective rescue of historically collected and unmanaged datasets. We discuss prioritization of datasets to rescue, forming effective data rescue teams, preparing the data and associated metadata, and archiving and sharing the rescued materials. In an era of rapid environmental change, the best policy solutions will require evidence from both contemporary and historical sources. It is, therefore, imperative that we identify and preserve valuable, at-risk environmental data before they are lost to science.
Collapse
Affiliation(s)
- Ellen K. Bledsoe
- The Living Data Project, Canadian Institute of Ecology and Evolution, Vancouver, British Columbia, Canada,School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA,Department of Biology, University of Regina, Regina, Saskatchewan, Canada
| | - Joseph B. Burant
- The Living Data Project, Canadian Institute of Ecology and Evolution, Vancouver, British Columbia, Canada,Department of Biology, McGill University, Montreal, Quebec, Canada,Département de sciences biologiques, Université de Montréal, Montréal, Québec, Canada
| | - Gracielle T. Higino
- The Living Data Project, Canadian Institute of Ecology and Evolution, Vancouver, British Columbia, Canada,Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Dominique G. Roche
- The Living Data Project, Canadian Institute of Ecology and Evolution, Vancouver, British Columbia, Canada,Department of Biology and Institute for Environment & Interdisciplinary Science, Carleton University, Ottawa, Ontario, Canada
| | - Sandra A. Binning
- The Living Data Project, Canadian Institute of Ecology and Evolution, Vancouver, British Columbia, Canada,Département de sciences biologiques, Université de Montréal, Montréal, Québec, Canada
| | - Kerri Finlay
- The Living Data Project, Canadian Institute of Ecology and Evolution, Vancouver, British Columbia, Canada,Department of Biology, University of Regina, Regina, Saskatchewan, Canada
| | - Jason Pither
- The Living Data Project, Canadian Institute of Ecology and Evolution, Vancouver, British Columbia, Canada,Department of Biology and Okanagan Institute for Biodiversity, Resilience, and Ecosystem Services, University of British Columbia, Kelowna, British Columbia, Canada
| | - Laura S. Pollock
- The Living Data Project, Canadian Institute of Ecology and Evolution, Vancouver, British Columbia, Canada,Department of Biology, McGill University, Montreal, Quebec, Canada
| | - Jennifer M. Sunday
- The Living Data Project, Canadian Institute of Ecology and Evolution, Vancouver, British Columbia, Canada,Department of Biology, McGill University, Montreal, Quebec, Canada
| | - Diane S. Srivastava
- The Living Data Project, Canadian Institute of Ecology and Evolution, Vancouver, British Columbia, Canada,Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| |
Collapse
|
3
|
Higino GT, Poisot T. Beta and phylogenetic diversities tell complementary stories about ecological networks biogeography. Parasitology 2021; 148:835-842. [PMID: 33678197 PMCID: PMC11010150 DOI: 10.1017/s0031182021000391] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 02/10/2021] [Accepted: 02/24/2021] [Indexed: 11/06/2022]
Abstract
The beta-diversity of interactions between communities does not necessarily correspond to the differences related to their species composition because interactions show greater variability than species co-occurrence. Additionally, the structure of species interaction networks can itself vary over spatial gradients, thereby adding constraints on the dissimilarity of communities in space. We used published data on the parasitism interaction between fleas and small mammals in 51 regions of the Palearctic to investigate how beta-diversity of networks and phylogenetic diversity are related. The networks could be separated in groups based on the metrics that best described the differences between them, and these groups were also geographically structured. We also found that each network beta-diversity index relates in a particular way with phylogenetically community dissimilarity, reinforcing that some of these indexes have a strong phylogenetic component. Our results clarify important aspects of the biogeography of hosts and parasites communities in Eurasia, while suggesting that networks beta-diversity and phylogenetic dissimilarity interact with the environment in different ways.
Collapse
Affiliation(s)
- Gracielle T. Higino
- Universidade Federal de Goiás, Goiania, Brazil
- Québec Centre for Biodiversity Sciences, Montreal, Canada
| | - Timothée Poisot
- Québec Centre for Biodiversity Sciences, Montreal, Canada
- Université de Montréal, Montreal, Canada
| |
Collapse
|