A study by Jhun Barit, Kwanghun Choi, and Dongwook Ko. This study discusses the threats to SMMR and how the data gathered by forest rangers can be utilized for much more effective patrolling of the area.

1. Modeling the risk of illegal forest
activity and its distribution in the
southern eastern region of the Sierra
Madre mountain range, Philippines
Jhun B. Barit1-2, Kwanghun Choi2, Dongwook W Ko2
Department of Environment and Natural Resources1
Department of Forest Environment and Systems, Kookmin University (South Korea)2
Report by: Veronica Baje
MS Biology 1, Cavite State University
Source: Daily Tribune

2. Introduction
• The forests in the Philippines are considered one of
the most significant global biodiversity hotspots and
important conservation target.
• The Philippine forest and biodiversity have been
degraded at an alarming rate.
• Biophysical phenomena is also a factor such as
typhoons, floods, and landsides.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTION IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RANGE, PHILIPPINES

3. MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES
MAJOR THREATS TO PHILIPPINE BIODIVERSITY
Illegal logging Slash-and-burn farming Mining Charcoal production
Source: ABS-CBN News Source: EcoLogic Development Fund Image by Bong Sarmiento for Mongabay Source: CIFOR

4. Policies & Programs to reduce
illegal activity in the Philippine
forests
1. Law enforcement monitoring and ground
patrolling.
2. Spatial Monitoring and Reporting Tool
(SMART)
3. SMART-Lawin Forest and Biodiversity
Protection System
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES
© Kathleen Lei Limayo
© 2023 Global Conservation

5. MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTION IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RANGE, PHILIPPINES
Source: USAID B+WISER, YouTube

6. Lawin forest and
biodiversity
protection system
Lawin uses geographic information
system (GIS) data to analyze forest cover
and biodiversity information to focus
forest protection efforts in most
vulnerable areas.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES
Source: USAID B+WISER, YouTube

7. Objectives of the study
• Develop MaxEnt models for illegal forest activity within the SMMR utilizing ranger
patrol data collected via the SMART-Lawin system to understand the spatial
patterns of this activity.
Develop
• Identify significant environmental variables that determine the
distribution of illegal forest activity.
Identify
• Assess the risk of illegal forest activity in this region and determine
the patrol coverage that is required and improve general patrol
strategy for the conservation area.
Assess
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTION IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RANGE, PHILIPPINES

8. MATERIALS AND METHODS
Source: PhilSTAR Life

9. STUDY AREA
The Baliuag Conservation Area (BCA), which is in
the southeastern region of SMMR was selected.
• Angat Watershed Forest Reserve
• Biak-na-Bato National Park
• Doña Remedios Watershed
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES
Source: Alchetron
Source: Moonlit, Blogger.com
Source: Business Mirror

10. DATA COLLECTION
• The BCA is currently managed by 23 forest rangers
registered in the SMART-Lawin system. They are
grouped into four teams wherein each team oversees
patrolling one of the four patrol sectors over an average
distance of 6km. Each team conducts three patrols a
month on average (8h per patrol).
• The data was obtained from 3445 observations of illegal
activity over the entire BCA from the SMART-Lawin
system from the period of January 2017 to December
2019.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES
Source: USAID B+WISER, YouTube

11. Environmental
predictors
Seven environmental variables at a 30 ×
30 m resolution were used as potential
predictors of illegal forest activity. All
spatial data were processed for input into
the Ecological Niche Model Evaluation.
The variance inflation factor (VIF) was
used to test the multicollinearity of the
predictors.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES

12. MODEL TUNING AND PROCESSING
& MODEL EVALUATION
Model tuning and processing – the
models were optimized using ENMeval.
Model evaluation – K-fold cross-
validation was used to evaluate the
model by partitioning the occurrence
data into training and testing sets.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES

13. SPATIAL ANALYSIS
The predictive model for the spatial
distribution was analyzed by assessing
the spatial extent of each illegal activity
by its coverage; and estimating the
overall risk of illegal activity across the
landscape.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES

14. RESULTS
Source: Fostering Education & Environment for Development, Inc.

15. ANALYSIS OF ENVIRONMENTAL
PREDICTORS
The environmental predictors differed
in their impact on each illegal forest
activity model, with land cover and
proximity to roads and rivers having
the strongest influence.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTION IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RANGE, PHILIPPINES

16. Potential distribution
of illegal forest
activity
The predicted spatial distribution
for each illegal activity category
varied across the landscape.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES

17. RESULTS
The threshold values for the presence and absence of
agricultural expansion, infrastructure expansion, and forest
product extraction were 0.083, 0.191, and 0.214, respectively.
Forest product extraction was the most common illegal activity
across the landscape (66%), followed by infrastructure
expansion (44%) and agricultural expansion (30%).
The overall risk assessment, which represents the total
frequency of all illegal activity occurrences, revealed that 25%
of the conservation area was at high risk, 20% at moderate
risk, 25% at low risk, and 30% at no risk.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTION IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RANGE, PHILIPPINES

18. DISCUSSION
Source: Municipality of Montalban, InformationHub

19. DISCUSSION
• Illegal activity were classified into three categories: agricultural expansion, infrastructure expansion, and forest
product extraction.
• Each illegal activity was affected by different environmental variables. Agricultural and infrastructure expansion
demonstrated similar patterns in terms of the main environmental variables affecting the models. They were
evenly affected by land cover and roads and slightly affected by the proximity of settlement areas, indicating
the gradual expansion of both types of illegal activity. On the other hand, forest product extraction was mainly
affected by land cover and the proximity of roads and rivers, which can be used to transport forest products.
• Illegal activity tends to occur at locations where it is difficult to detect but where it is easy to transport the
products quickly.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTION IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RANGE, PHILIPPINES

20. Optimal strategy for
mitigating illegal activity
The results of this study can be used to deploy patrol
teams that prioritize high-risk areas. Managers can either
target the deterrence of a specific illegal activity or a
combination of multiple illegal activities. However, the
results are limited by the range of variables used in
developing the model. The focus was limited to seven
important variables that are likely to affect the occurrence
of illegal activity.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES
© Jack Board

21. Improving the patrol strategy
The study area in the BCA is 90,448 ha in
size, which is covered by four patrol teams.
This means that each team is responsible for
patrolling over 20,000 ha. Given the limited
human and logistic resources, it is almost
impossible to cover the entire area in a
systematic manner. Unfortunately, this lack of
conservation resources is not uncommon for
most protected areas in the tropics. The large
patrol coverage area and the limited budget
and human resources, hinder the effective
implementation of law enforcement
strategies.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTION IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RANGE, PHILIPPINES
© WWF Philippines

22. The results can be used to improve patrolling by shifting
focus to three specific goals:
1. Focus efforts on a specific illegal forest activity. In this case, the
output map for the extent of the illegal activity can be used to
identify the target areas for a particular illegal activity.
2. Detecting as many types of illegal activity as possible at once. The
map can provide the best information.
3. Focus on conserving such as protected areas and vulnerable areas
covered with intact forest (closed/open forest). In this case,
overlaying the risk map for each illegal activity with landcover or
forest maps will be useful.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES
Source: Philippine Star

23. CONCLUSION
© J Kahlil Panopio/Haribon Foundation

24. CONCLUSION
• It is important for conservation area managers
to identify the drivers determining the
occurrence of illegal activity and the locations
where it is most likely to occur within their
areas of jurisdiction in order to effectively
implement forest protection and law
enforcement.
• The study has also made it possible to predict
locations with a high potential for illegal activity,
which is helpful for improving the patrol
strategy within protected areas.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTIO N IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES
© Cornell University © Philippine Daily Inquirer

25. CONCLUSION
• Future research should include significant
environmental predictors that were not used in
this study but that are likely to affect the
occurrence of illegal activity.
• An improved version of the approach showcased in
this study could be implemented in other priority
conservation areas with wider coverage using a
large sample size of illegal forest activity generated
over a longer time period, allowing for more
effective patrol strategies.
• It is important to note that the behavior of
poachers or violators is likely to change in
response to changes in patrol strategies.
MODELING THE RISK OF ILLEGAL FOREST ACTIVITY AND ITS DISTRIBUTION IN THE SOUTHERN EASTERN REGION OF THE SIERRA MADRE MOUNTAIN RA NGE, PHILIPPINES
Source: Sunstar
Source: Philin|Con

26. REFERENCES:
• Barit JB, Choi K, Ko DW (2022). Modeling the risk of illegal forest
activity and its distribution in the southeastern region of the Sierra
Madre Mountain Range, Philippines. iForest 15: 63-70. - doi:
10.3832/ifor3937-014
• Philippines becomes the global leader in using SMART conservation
software for forest protection (2017). Biodiversity and Watersheds
Improved for Stronger Economy and Ecosystem Resilience (B+WISER)
Program. Retrieved May 14, 2023, from
https://forestry.denr.gov.ph/b+wiser/index.php/bulletin/50-
2017/april-2017/141-philippines-becomes-the-global-leader-in-
using-smart-conservation-software-for-forest-protection
• [USAID B+WISER]. (2017, April 19). Philippines: A Global Leader of
SMART Technology [Video]. Youtube.
https://www.youtube.com/watch?v=JdPHX8yQ2Cs