Maximum entropy model trained to estimate probability to host trees taller then 70 m based on environmental factors
Creators
- Gorgens, Eric Bastos1
- Nunes, Matheus Henrique2
- Jackson, Tobias3
- Coomes, David3
- Keller, Michael4
- Reis, Cristiano Rodrigues5
- Valbuena, Rubén6
- Rosette, Jacqueline7
- Almeida, Danilo Roberti Alves5
- Gimenez, Bruno8
- Cantinho, Roberta9
- Motta, Alline Zagnolli1
- Assis, Mauro10
- Pereira, Francisca Rocha de Souza10
- Spanner, Gustavo8
- Higuchi, Niro8
- Ometto, Jean Pierre10
- 1. Universidade Federal dos Vales do Jequitinhonha e Mucuri
- 2. University of Helsinki
- 3. University of Cambridge
- 4. United States Forest Service
- 5. Universidade de São Paulo
- 6. Bangor University
- 7. Swansea University
- 8. Instituto Nacional de Pesquisas da Amazônia
- 9. Universidade de Brasília
- 10. Instituto Nacional de Pesquisas Espaciais
Description
Focusing only on the tallest trees - those over 70 m in height – we built an environmental envelope model to assess the conditions which allow them to occur. We employed the maximum entropy approach (MaxEnt) commonly applied to modelling species geographic distributions with presence-only data to discriminate suitable versus unsuitable areas for the species. We initially considered a total of 18 environmental variables: (1) fraction of absorbed photosynthetically active radiation (FAPAR; in %); (2) elevation above sea level (Elevation; in m); (3) the component of the horizontal wind towards east, i.e. zonal velocity (u-speed ; in m s-1); (4) the component of the horizontal wind towards north, i.e. meridional velocity (v-speed ; in m s-1); (5) the number of days not affected by cloud cover (clear days; in days yr-1); (6) the number of days with precipitation above 20 mm (days > 20mm; in days yr-1 ); (7) lightning frequency (flashes rate); (8) annual precipitation (in mm); (9) potential evapotranspiration (in mm); (10) coefficient of variation of precipitation (precipitation seasonality; in %); (11) amount of precipitation on the wettest month (precip. wettest; in mm); (12) mean annual temperature (in °C); (13) standard deviation of temperature (temp. seasonality; in °C); (14) annual maximum temperature (in °C); (15) soil clay content (in %); and (16) soil water content (in %).
Notes
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Additional details
Related works
- Is referenced by
- Journal article: 10.1111/gcb.15423 (DOI)
Funding
- Understanding mechanisms of habitat change in fragmented tropical forests for improving conservation 319905
- Academy of Finland
- A 3D perspective on the effects of topography and wind on forest height and dynamics NE/S010750/1
- UK Research and Innovation