This is an interactive open source tool for assessing how far conservation spending reduces the decline of African elephants. The tool can be used to identify where best to invest grant money and how much to invest to maximise conservation and support African elephants.
There are 3 types of analysis this tool can implement - each analysis is run in the corresponding navigation tabs above:
The outputs and estimates of elephant numbers represent the average return on investment - the ROI app does not consider the details in any conservation funding proposal. Individual actions may increase or reduce effectiveness relative to average return on investment.
This ROI app can be used to guide rather than to decide on conservation interventions.
Additional caveats and notes can be found in the documentation tab.
In the sidebar controls on each analysis tab there are blue question mark symbols (?). Clicking on these symbols will show a pop-up screen giving details of what the variable control does. Default values generally should be changed to the required amounts. Further details and guide to use the ROI app can be found in the ‘How to use this tool’ section in the Documentation tab.
These projections of elephant and population numbers are based on the data compiled during Roberto Correa’s PhD work - Full methods and background details can be found in the Documentation tab above. This tool is an output from the project ‘Identifying the Level of Funding Needed to Protect Elephant Populations Across Africa and Other Key Species’ (USFWS Grant Award F19AC00770).
University of York 2023 | contact: colin.beale@york.ac.uk
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Optimise across all sites
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Download results |
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Assess single proposal
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Download results |
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Assess set of proposals
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Download input data | Download results |
| Region | Country (ISO) | Site name |
| South | ZAF | Addo |
| East | RWA | Akagera |
| East | KEN | Amboseli |
| West | BFA | Arly |
| East | ETH | Babille |
| Central | CAF | Bamingue |
| Central | CMR | Bayang |
| Central | CMR | Boumba Bek |
| East | TZA | Burigi |
| Central | CMR | Campo Ma'an |
| East | ETH | Chebera |
| South | ZWE | Chete |
| South | ZWE | Chirisa |
| South | ZWE | Chizarira |
| South | BWA | Chobe |
| West | CIV | Comoe |
| Central | COG | Conkouati |
| Central | CMR | Dja |
| South | ZWE | Doma |
| Central | CAF | Dzanga |
| South | NAM | Etosha |
| East | ETH | Gambella |
| Central | COD | Garamba |
| South | MOZ | Gile |
| West | LBR | Gola |
| South | ZWE | Gonarezhou |
| South | MOZ | Gorongosa |
| West | MLI | Gourma |
| South | SWZ | Hlane |
| South | ZAF | Hluhluwe-iMfolozi |
| South | ZWE | Hwange |
| Central | GAB | Ivindo |
| South | ZAM | Kafue |
| South | MWI | Kasungu |
| East | TZA | Katavi |
| South | NAM | Khaudum |
| East | UGA | Kibale |
| East | UGA | Kidepo |
| South | ZAF | Kruger |
| South | MOZ | Limpopo |
| South | MWI | Liwonde |
| Central | CMR | Lobeke |
| Central | GAB | Lope |
| South | AGO | Luengue |
| East | KEN | Maasai Mara |
| South | ZAF | Madikwe |
| Central | COD | Maiko |
| South | MWI | Majete |
| South | SWZ | Malolotja |
| Central | CAF | Manovo |
| South | ZAF | Marakele |
| South | MOZ | Marromeu |
| South | ZWE | Matetsi |
| South | ZWE | Matusadona |
| East | KEN | Meru |
| East | TZA | Mikumi |
| Central | GAB | Minkebe |
| South | BWA | Moremi |
| East | TZA | Moyowosi Kigosi |
| Central | CMR | Mt Cameroon |
| East | KEN | Mt Elgon |
| East | UGA | Murchison Falls |
| Central | GAB | Mwange |
| South | MOZ | Niassa |
| East | SSD | Nimule |
| South | MWI | Nkhotakota |
| Central | CMR | Nki |
| South | ZAM | North Luangwa |
| Central | COG | Nouabale |
| South | NAM | Nyae |
| South | MWI | Nyika |
| Central | COG | Odzala |
| Central | COD | Okapi |
| East | ETH | Omo |
| West | BEN | Pendjari |
| East | UGA | Queen Elizabeth |
| South | MOZ | Quirimbas |
| East | TZA | Ruaha |
| East | TZA | Rukwa |
| East | TZA | Rungwa |
| West | LBR | Sapo |
| South | ZWE | Save |
| East | TZA | Selous |
| East | TZA | Serengeti |
| South | ZAM | Sioma |
| South | ZAM | South luangwa |
| West | CIV | Tai |
| East | TZA | Tarangire |
| South | ZAF | Tembe |
| East | KEN | Tsavo East |
| East | KEN | Tsavo West |
| East | TZA | Ugalla |
| Central | COD | Upemba |
| Central | COD | Virunga |
| South | MWI | Vwaza |
| West | BEN | W Benin |
| West | BFA | W Burkina |
| West | NER | W du Niger |
| Central | CMR | Waza |
| West | NGA | Yankari |
| Central | TCD | Zakouma |
| South | ZAM | Zambezi |
Descriptions of the data table output generated by the ROI optimization
| Column name | Description |
| Site | Site name |
| Current population | Most recent elephant population estimate |
| Projected population | Projected elephant population from the ROI optimization (median) |
| Projected pop lower CI | Lower confidence limit (uncertainty) of projected population (5%) |
| Projected pop upper CI | Upper confidence limit (uncertainty) of projected population (95%) |
| Projected population without grant | Projected elephant population if grant is not available |
| Population difference | Difference between projected elephant population with and without a grant |
| Carrying capacity | Site level elephant population carrying capacity |
| Current growth rate | Current elephant population growth rate at the site |
| Projected growth rate | Projected elephant population growth rate with a grant at the site |
| Current annual spending | Current conservation spending at the site (government and donor) |
| Optimal.annual.grant | Optimal grant identified from the ROI optimization given the input information (total annual grant budget available, number of years, conservation objective, minimum elephant population etc.) |
| $ per elephant | Annual amount of $ per single elephant - the lower the amount the better investment return |
| ROI category | This is a simple guideline traffic light system ((Very high, high, medium, low)) to categorise the return on investment (ROI):
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This list of caveats will be updated - contact rob.critchlow@york.ac.uk if you spot something new or have any queries
Problem - Increasing investment or any additional investment is not changing the number of elephants at a site (especially noticeable in assess single proposal analysis)
Reason - The maximum number of elephants will be restricted by the carrying capacity of a site, if carrying capacity (as stated in the database) has been reached, elephant numbers can’t increase. A good example of this is for Amboseli National Parkwhere the ‘official’ carrying capacity of the site is 229 but the most recent ‘official’ population estimate is 1656.
This also highlights the potential problem of how elephants are counted in areas where they migrate like Amboseli National Park. In such sites, the population estimates are likely to be for the wider ecosystem which can sustain a much larger population, whereas Amboseli National Park on its own is small
Dr. Colin Beale - Reader - colin.beale@york.ac.uk
Dr. Rob Critchlow - PDRA - rob.critchlow@york.ac.uk
Dr. Andy Plumptre - Head Key Biodiversity Areas Secretariat - aplumptre@keybiodiversityareas.org
Prof. Andrew Balmford - Professor of Conservation Science - apb12@cam.ac.uk
Roberto Correa - PhD student - rjc206@cam.ac.uk
Matt Muir - USFWS Biologist - matt_muir@fws.gov
