the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Toward Better Conservation: A Spatial Analysis of Species Occurrence Data from the Global Biodiversity Information Facility
Abstract. The world is facing an unprecedented loss of biodiversity, with nearly one million species on the brink of extinction, and the extinction rate accelerating. Conservation efforts are often hindered by insufficient information on crucial ecosystems. To address this issue, our paper leverages advances in machine-based pattern recognition to estimate species occurrence maps using georeferenced data from the Global Biodiversity Information Facility (GBIF). Our algorithms have generated maps for more than 600,000 species, including vertebrates, arthropods, mollusks, other animals, vascular plants, fungi, and other organisms. Validation involved comparing these maps with expert maps for mammals, ants, and vascular plants. We found a close similarity in global distribution patterns, with regional differences attributed to technical variations or necessary revisions in existing expert maps based on GBIF data. As a practical application, we identified the global distributions of approximately 68,000 species with small ranges (25 km x 25 km or less) confined to a single country. Our maps reveal a skewed international distribution of these species, identifying 30 countries where 78.2 percent are concentrated. These results highlight the need to integrate the newly mapped GBIF data into global conservation planning. Our algorithms support rapid updates and the creation of new maps as GBIF occurrence reports increase. The data are available on the World Bank Development Data Hub at https://doi.org/10.57966/h21e-vq42 (Dasgupta et al. 2024).
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CC1: 'Comment on essd-2024-241', Mustafa Md. Golam, 18 Oct 2024
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This paper underscores the importance of global biodiversity data in shaping effective conservation strategies. By analyzing species occurrence maps, it reveals regional patterns that reflect ecosystem health. It highlights how species abundance helps identify conservation statuses, pinpointing critical areas and vulnerable species groups. Additionally, mapping species distribution supports the development of more precise, tailored conservation plans.
Citation: https://doi.org/10.5194/essd-2024-241-CC1 -
AC1: 'Reply on CC1', Brian Blankespoor, 23 Oct 2024
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We appreciate the insightful comment from Mr. Mustafa Md. Golam and fully agree that comprehensive, real-time, and geographically targeted data on biodiversity at risk is crucial for developing effective, evidence-based conservation strategies and for informing global biodiversity management and protection efforts. In response to this, our paper presents occurrence region maps for around 600,000 species, encompassing arthropods, mollusks, plants, fungi, and various invertebrates, alongside amphibians, birds, fish, reptiles, and mammals. This dataset represents a significant advancement in supporting conservation planning and biodiversity protection across terrestrial, freshwater, and marine environments.
Citation: https://doi.org/10.5194/essd-2024-241-AC1
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AC1: 'Reply on CC1', Brian Blankespoor, 23 Oct 2024
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CC2: 'Comment on essd-2024-241', Mainul Huq, 23 Oct 2024
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A long-awaited system such as this one would help improve our understanding of the relative importance of an area in terms of biodiversity. The area may turn out to be a rare home of a set of threatened species. Armed with such information, the policy makers would be better equipped; to undertake conservation projects especially in those areas and avoid projects, if undertaken, would adversely impact those ecologically sensitive areas. I am sure the relevant experts and policy makers would be glad to have access to such information.
Citation: https://doi.org/10.5194/essd-2024-241-CC2 -
AC2: 'Reply on CC2', Brian Blankespoor, 23 Oct 2024
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We appreciate Mr. Mainul Huq's valuable comment and fully concur with his observation. Our estimates, as presented in the paper, indicate that the traditional focus on vertebrates in conservation planning has overlooked many other critical species. The expanded coverage in our new dataset, which includes species beyond vertebrates, reveals that numerous taxa, such as arthropods, have not received sufficient attention in biodiversity conservation efforts. As a result, our expanded biodiversity database broadens the scope of conservation, identifying many more potentially threatened species globally and leading to significant revisions in "conservation hotspot" maps.
Citation: https://doi.org/10.5194/essd-2024-241-AC2
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AC2: 'Reply on CC2', Brian Blankespoor, 23 Oct 2024
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CC3: 'Comment on essd-2024-241', Mainul Huq, 23 Oct 2024
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A long-awaited system such as this one would help improve our understanding of the relative importance of an area in terms of biodiversity. The area may turn out to be a rare home of a set of threatened species. Armed with such information, the policy makers would be better equipped; to undertake conservation projects especially in those areas and avoid projects, if undertaken, would adversely impact those ecologically sensitive areas. I am sure the relevant experts and policy makers would be glad to have access to such information.
Citation: https://doi.org/10.5194/essd-2024-241-CC3 -
AC3: 'Reply on CC3', Brian Blankespoor, 23 Oct 2024
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(Please note our response to CC2 above).
Citation: https://doi.org/10.5194/essd-2024-241-AC3
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AC3: 'Reply on CC3', Brian Blankespoor, 23 Oct 2024
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CC4: 'Comment on essd-2024-241', Kenneth Chomitz, 21 Nov 2024
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This paper advances the state of the art of biodiversity mapping. A long standing problem in biodiversity mapping and conservation is constructing range maps for species based on relatively small numbers of geolocated occurences. The authors use the alphahull algorithm to conservatively bound a range based on occurrence data. The paper uses it to generate global range maps for 600,000 species across a very wide range of taxa.The work is timely and important because of the urgency of biodiversity conservation, and increased demand for range maps from nascent initiatives to create biodiversity credits. At the same time, there is increased supply of occurrence data from expanded and innovative monitoring efforts. The paper illustrates how this data can be rapidly assimilated into a growing live database of biodiversity maps.Citation: https://doi.org/
10.5194/essd-2024-241-CC4 -
RC1: 'Comment on essd-2024-241', Kenneth Chomitz, 04 Jul 2025
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Dasgupta Blankespoor and Wheeler (DBW) create a fine-scale global map of the distribution of more than 600,000 species. This appears to be the most species-rich such map available. The paper states that its main contribution is ‘the expanded coverage of invertebrates’ – a key component of biodiversity that is often overshadowed by attention to charismatic mammals. From a methodological view, the paper’s main contribution is that ‘our algorithms support rapid updates and the creation of new maps as GBIF occurrence reports increase.’
Their database-cum-methodology lacks a name – let’s call it the DBW algorithm and DBW-GBIF database. It arrives at a crucial time. As the paper notes, the Global Biodiversity Framework is heightening the attention to conservation. Not noted but important is increased demand for, and supply of, mappable biodiversity data in connection with burgeoning biodiversity credit markets and corporate compliance with biodiversity reporting regimes such as the Task Force on Nature-related Disclosures. As the paper emphasizes, the volume of species occurrence data is growing very rapidly. Hence DBW’s ability to assimilate the data and update species range maps is important.
The paper would benefit from better documentation of methods and a clearer exposition of how it advances the state of the art. Main points as follows.
Algorithm and methods – Supplementary material should document methods, including datacleaning (or is this already done by GBIF?), alpha hull model parameterization, and workflow. If a main contribution of the DBW algorithm is in the ability to rapidly or continually update, it is worth discussing the ease and computational cost of doing that. It would be desirable to open-source the algorithm if possible, as that would accelerate its use and continual improvement.
Comparison with other species distribution databases. The paper could compare species coverage, spatial resolution, methodologies, and timeliness with other resources such as the Map of Life.
Alpha hull pilot example. I am not convinced that this is an essential section, since the alpha hull technique has already been demonstrated. If it is to be included, then a more compelling example would be one where convexity clearly goes wrong and the alpha hull maps a more constrained range.
Case comparisons. This section could be more clearly motivated and more thoroughly explored. I take the motivation to be showing a) that the rapid DBW algorithm produces results that are comparable to much more intensive taxonomy-specific efforts; and then b) arguing that where there are disparities, DBW may be superior. With regard to a) figures 2,3, and 4 are inadequate to make the case – it’s not possible to eyeball the differences. Instead, the paper should present and discuss a map of the differences between the GBIF and comparator rankings (and also define the rankings – percentiles? Is 10 high or low? Etc). On the comparison with Kass et al 2022, it’s worth noting that Kass don’t just use alpha hull, they also use environmental variables as a predictor, so that may explain the divergence and is worth some discussion. Also, given the interest in small-range species, Kass et al’s use of buffers around species with <3 occurrences (which can't be handled by alpha hull) seems preferable to DBW’s decision to omit them entirely. I would therefore challenge the conclusion (line 313) that ‘comparing full database results for GBIF and Kass et al. (2022) would be, in effect, comparing apples and oranges.”
Priority-setting applications. This section would benefit from comparison with prior, similar exercises such as Jenkins, Pimm and Joppa (2013) Global patterns of terrestrial vertebrate diversity. How does DBW'S wider set of taxonomies change understanding of hotspots or priorities? The tables could be better documented, it's not always immediately clear what the 'percentages' refer to (what's the denominator?) Also, the paper ends by talking about 40 countries, but the prior discussion has been of 30 countries -- that requires correction or clarification.
Citation: https://doi.org/10.5194/essd-2024-241-RC1
Data sets
Global Biodiversity Species Occurrence Endemism and Small Occurrence Data S. Dasgupta, B. Blankespoor, and D. Wheeler https://datacatalog.worldbank.org/search/dataset/0066034/global_biodiversity_data
Global Biodiversity Species Occurrence Gridded Data and Global Biodiversity Species Global Grid S. Dasgupta, B. Blankespoor, and D. Wheeler https://datacatalog.worldbank.org/search/dataset/0066034/global_biodiversity_data
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