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Global opportunities and challenges for transboundary conservation


Rapid biodiversity loss has prompted global action to prevent further declines, yet coordinated conservation action among nations remains elusive. As a result, species with ranges that span international borders—which include 53.8% of terrestrial birds, mammals and amphibians—are in increasing peril through uncoordinated management and artificial barriers to human movement, such as border fences. Transboundary conservation initiatives represent a unique opportunity to better protect species through coordinated management across national borders. Using metrics of governance, collaboration and human pressure, we provide an index of transboundary conservation feasibility to assess global opportunities and challenges for different nations. While the transboundary conservation potential of securing multinational threatened species varied substantially, there are distinct opportunities in South-East Asia, Northern Europe, North America and South America. But to successfully avert the loss of transboundary species, the global community must be prepared to invest in some regions facing greater implementation challenges, including the nations of Central Africa, where efforts may necessitate establishing rapid conservation interventions postconflict that align with local socio-cultural opportunities and constraints. Sanctioned and coordinated approaches towards managing transboundary species are now essential to prevent further declines of many endangered species, and global policy efforts must do more to produce and enact legitimate mechanisms for collaborative action in conservation.

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Fig. 1: Framework for determining the global potential for transboundary conservation.
Fig. 2: Proportions of terrestrial species with transboundary ranges.
Fig. 3: Distribution of threatened species richness and feasibility scores.
Fig. 4: Global opportunities for transboundary conservation.

Data availability

The datasets analysed in this paper are available via the UQ eSpace digital repository at (ref. 68).

Code availability

Transboundary species richness and feasibility were calculated using a combination of Python v.2.7 (ref. 62) and ESRI ArcMap v.10 (ref. 63). The Python code is available from the corresponding author upon reasonable request.


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This research was supported by Australian Research Council Discovery Project grant no. DP160101397. The work was also funded by the NASA Biodiversity and Ecological Forecasting Program under the 2016 ECO4CAST solicitation through grant no. NNX17AG51G.

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Authors and Affiliations



R.K.R., J.E.M.W. and O.V. conceived the study. N.M. conducted the analyses with assistance from M.W. and R.K.R. All authors contributed to the interpretation of the results. N.M. led the writing of the manuscript with input from all authors.

Corresponding author

Correspondence to Natalie Mason.

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The authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Number of transboundary species with ranges that span national borders.

Number of transboundary species with ranges that span national borders. Figure includes species of any threat status, including least concern.

Extended Data Fig. 2 Raw values used in the feasibility index.

Raw values used in the feasibility index. Shows (a) collaboration (Goldstein) Score calculated for each country pair over the time period 1995-2017, and (b) mean governance score for each country pair over the time period 1996-2016 calculated using the Worldwide Governance Indicators.

Extended Data Fig. 3 Human pressure score sensitivity to changes in human pressure by altering buffer width.

Sensitivity to changes in human pressure by altering buffer width. This shows the mean human footprint and standard deviation calculated using line buffer widths of (a, b) 10km, (c, d) 50km and, (e, f) 100km over the human footprint dataset 2013.

Extended Data Fig. 4 Changes in global feasibility scores under different temporal and spatial analysis.

Changes in global feasibility scores under different temporal and spatial analysis. This shows how global feasibility scores shift when restricting the length of timescale for governance and collaboration data from (a) the 20-year timescale, (b) past 10 years, (c) a 5-year period (2011-2015) around the 2013 human footprint dataset, (d) a 5-year period (1998-2002) around the 2000 human footprint dataset. We showed how feasibility scores shift when using a 100km buffer (e) with the original 20-year timescale. Grey lines indicate borders where there was no calculable feasibility score.

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Mason, N., Ward, M., Watson, J.E.M. et al. Global opportunities and challenges for transboundary conservation. Nat Ecol Evol 4, 694–701 (2020).

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