IV. Explaining and predicting the distribution of the mountain forest types
IV.3.3 Forest type prediction
The three environmental factors altitude, annual mean temperature and NDVI built the final ecological niche models for 37 samples of humid broadleaf/gallery forest, 34 samples of pine forest, 19 samples of cloud forest and 17 samples of mixed forest. Models with just one or two environmental parameters were also tested, but showed lower AUC-values and therefore are not presented. The AUC-values and ranges of the average datasets of each forest type based on the testing data are displayed in Table IV.3. AUC-values were highest for the two forest types with the highest sample sizes, humid broadleaf/gallery forest and pine forest. The best AUC-value was achieved for the pine forest prediction (0.879). The lowest AUC-value was calculated for the prediction of cloud forests (0.744).
TABLE IV.3. Mean and ranges for test AUC (averages of four replicate run types) and area pre-dicted present and absent (km2) for all forest types
Average test AUC Range test AUC Area predicted present* (km2) altitude predicted suitability decreased substantially between 600 and 1,500 m a.s.l.. Annual mean temperature and altitude contributed most to the model (Table IV.4). The geographic distribution of humid broadleaf/gallery forest is shown in Figure IV.6a. It extended over an area of 162 km2 from the lower to medium altitudes of Armando Bermúdez National Park in relatively warm areas along the river valleys at the northern border south of the villages Loma El Copey, Los Ramones, La Diferencia and Mata Grande. The average annual mean tempera-ture of 20.2˚C found for this forest type with the help of ordination of the plots is displayed as an isotherm in Figure IV.6a. The modeled average annual mean isotherm was 20.5˚C and the modeled mean elevation was 958 m a.s.l. (analysis in ArcGIS 9.3, Table IV.5). Small spots of high suitability for occurrence were modeled in the eastern part close to the border of the na-tional park near La Ciénaga and Loma de los Ríos.
For cloud forest the response to annual mean temperature consisted in a decreasing suitability with increasing temperatures (Figure IV.5b). In contrast to this increasing altitudes produced
higher predicted suitabilities for this forest type. For NDVI predictive suitability increased steadily with increasing NDVI values from zero on. The predicted geographic distribution of the cloud forest after thresholding is displayed in Figure IV.6b. Altogether 221 km2 were modeled present on mountain chains and slopes between 1,100 and 2,300 m a.s.l.. The mean annual isotherm of 16.5˚C calculated from the plots in ordination is displayed in Figure IV.6b.
The modeled distribution resulted in an average annual isotherm of 15.8˚C and a mean eleva-tion of 1,608 m a.s.l. (analysis in ArcGIS 9.3, Table IV.5).
The model for mixed forest was built on altitude and NDVI (Table IV.4). With increasing altitude predicted suitability decreased. The response to NDVI resulted in an optimum re-sponse curve. High suitabilities were predicted for low NDVI values. Towards higher NDVI values the curve falls and ends up in low suitabilities (Figure IV.5c). Higher annual mean temperatures led to an increase in predicted suitability. The predicted geographic distribution (100 km2) of the mixed forests along the northern border of the national park covered areas of low to mean elevation, largely consistent with the modeled pattern for humid broad-leaf/gallery forests (Figure IV.6c). Along the valleys of the Bao River, La Guácara River and de los Negros River the areas predicted “present” coincided with the areas predicted “present”
for pine forests.
Overall main contributor to the pine forest model was NDVI with 96.9% (Table IV.4). NDVI had also played an important role in the ordination diagram for explaining the position of the pine forest plots (Figure IV.4). The maximum response curve given as the result for pine for-est to NDVI had its peak for NDVI values around zero, decreasing then towards very low and medium NDVI values (Figure IV.5d). For high NDVI values the suitability was predicted as zero. Along the altitudinal gradient predicted suitability increased and decreased with warmer annual mean temperatures.
The annual mean isotherm of 14.5˚C of the ordinated pine plots is displayed in Figure IV.6d.
Maxent returned an average annual mean temperature of 13.9˚C and a mean elevation of 1,906 m a.s.l. (analysis in ArcGIS 9.3, Table IV.5).
TABLE IV.4. Relative contributions of the environmental variables to the Maxent model
Altitude Annual mean temperature NDVI
Humid broadleaf/Gallery forest 69.0 26.2 4.8
Cloud forest 49.4 5.5 45.0
Mixed forest 60.0 0.4 39.7
Pine forest 0.3 2.8 96.9
PS a.) Humid broadleaf/gallery forest
b.) Cloud forest
c.) Mixed forest
d.) Pine forest
Altitude Annual Mean Temperature NDVI
FIGURE IV.5. Response curves for forest types (a-d) to each single environmental variable used in the prediction
The curves reflect the dependence of the predicted suitability on the selected variable per forest type (Maxent html file). The red curve represents the mean response of the 4 replicate runs and the blue curve the mean +/- one standard deviation. The first curve in each row shows the response of the forest type to altitude, the second to annual mean temperature and the third to NDVI.
PS: Probability of Suitability of conditions (plottet on the y-axis of each diagram)
FIGURE IV.6. Modeled potential distribution of humid broadleaf/gallery, cloud, mixed and pine forests (Source: Maxent models; Annual mean temperature value as isotherms from Table IV.1; Boundaries of ABNP from Law 64-00; Villages, rivers, peaks from topographic maps 1:50,000, ICM 1983/1984 and field work)
FIGURE IV.7. Transition zone between modeled potential distribution of humid broadleaf/gallery and cloud forests (Source: Transition zone from GIS-analysis; Boundaries of ABNP from Law 64-00; Villages, roads, rivers from topographic maps 1:50,000, ICM 1983/1984 and field work)
The geographical pattern included areas in the center and southern parts of Armando Bermúdez National Park with low NDVI values between 800 and 3,087 m a.s.l.. The total predicted area for pine forest was of 133 km2. Absence was predicted for a triangle between Bao River, Loma El Tambor and Loma La Pelona (Figure IV.6d).
The transition between humid broadleaf/gallery forest and cloud forests is presented in Fig-ure IV.7. The areas of high suitability for forest types were predicted at an elevation of 1,100 and 1,200 m a.s.l.. Between cloud and pine forests no area was predicted in common.
IV.4 DISCUSSION OF RESULTS
DCA ordination techniques were used in this study to analyze vegetation samples of the mountainous forests of Armando Bermúdez National Park. The objective was to determine the natural forest types and identify the main environmental factors responsible for their spa-tial distribution. Characteristic species were extracted for each forest type. Furthermore a
pre-dictive model was developed to map the spatial distribution of the different natural mountain forest types to the entire area of the national park.
IV.4.1 Environmental gradients, mountain forest types and characteristic species