Landscape Structure and Seasonality: Effects on Wildlife Species Richness and Occupancy in a Fragmented Dry Forest in Coastal Ecuador
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Camera Trapping
2.3. Landscape Characteristics
2.3.1. Land-Cover
2.3.2. Forest Structure and Seasonality
2.3.3. Topography
2.4. Camera Trap Data Analysis
2.4.1. Model Predictors
2.4.2. Multispecies Occupancy Modeling
2.4.3. Analysis of Species Richness
3. Results
3.1. Landscape Structure and Seasonality
3.2. Wildlife Records
3.3. Species Occupancy and Richness
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Variable | Description/Formula |
---|---|
Sentinel-2 bands | |
Blue | B2 (490 nm) |
Green | B3 (560 nm) |
Red | B4 (665 nm) |
NIR | B8 (842 nm) |
SWIR1 | B11 (1610 nm) |
SWIR2 | B12 (2190 nm) |
Simple ratios | |
NIR/Red | NIR/Red |
SWIR 1/Red | SWIR1/Red |
SWIR 1/NIR | SWIR1/NIR |
SWIR 1/SWIR 2 | SWIR1/SWIR2 |
Vegetation indices | |
NDVI | (NIR-Red)/(NIR+Red) |
SAVI a | ((NIR-Red)/(NIR+Red+L))(1+L) |
Image transformations | |
VIS123 | Blue + Green + Red |
MID57 | SWIR1 + SWIR2 |
TCT 1 b | K1 × Blue + K2 × Green + K3 × Red + K4 × NIR + K5 × SWIR1 + K6 × SWIR2 |
TCT 2 b | K7 × Blue + K8 × Green + K9 × Red + K10 × NIR + K11 × SWIR1 + K12 × SWIR2 |
TCT 3 b | K13 × Blue + K14 × Green + K15 × Red + K16 × NIR + K17 × SWIR1 + K18 × SWIR2 |
Variable | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1. Distance to roads | 1 | 0.40 | 0.44 | −0.12 | −0.28 | 0.52 | 0.33 | −0.24 | −0.35 | −0.15 | −0.30 | 0.20 | −0.19 | 0.52 | 0.15 | 0.71 | 0.75 |
2. Annual NDVI (250 m) | 0.40 | 1 | 0.51 | 0.18 | −0.03 | 0.64 | 0.02 | 0.34 | 0.36 | −0.62 | 0.05 | 0.58 | −0.65 | 0.15 | 0.64 | 0.57 | 0.45 |
3. Mean NDVI—dry (250 m) | 0.44 | 0.51 | 1 | 0.05 | −0.35 | 0.56 | 0.17 | 0.07 | 0.03 | −0.30 | −0.22 | 0.34 | −0.37 | −0.09 | 0.38 | 0.52 | 0.18 |
4. Mean NDVI—wet (250 m) | −0.12 | 0.18 | 0.05 | 1 | 0.92 | 0.31 | 0.23 | 0.50 | 0.47 | −0.53 | 0.05 | 0.51 | −0.45 | −0.26 | 0.47 | 0.13 | −0.15 |
5. Difference wet and dry NDVI (250 m) | −0.28 | −0.03 | −0.35 | 0.92 | 1 | 0.07 | 0.15 | 0.44 | 0.43 | −0.37 | 0.13 | 0.35 | −0.28 | −0.21 | 0.29 | −0.09 | −0.21 |
6. Annual NDVI (1 km) | 0.52 | 0.64 | 0.56 | 0.31 | 0.07 | 1 | 0.68 | 0.60 | 0.45 | −0.74 | −0.46 | 0.83 | −0.69 | 0.18 | 0.67 | 0.77 | 0.48 |
7. Mean NDVI—dry (1 km) | 0.33 | 0.02 | 0.17 | 0.23 | 0.15 | 0.68 | 1 | 0.37 | 0.12 | −0.34 | −0.71 | 0.51 | −0.28 | 0.21 | 0.26 | 0.60 | 0.25 |
8. Mean NDVI—wet (1 km) | −0.24 | 0.34 | 0.07 | 0.50 | 0.44 | 0.60 | 0.37 | 1 | 0.97 | −0.85 | −0.02 | 0.86 | −0.75 | −0.19 | 0.75 | 0.17 | −0.01 |
9. Difference wet and dry NDVI (1 km) | −0.35 | 0.36 | 0.03 | 0.47 | 0.43 | 0.45 | 0.12 | 0.97 | 1 | −0.82 | 0.17 | 0.78 | −0.72 | −0.26 | 0.73 | 0.02 | −0.08 |
10. Percent Agriculture (1 km) | −0.15 | −0.62 | −0.30 | −0.53 | −0.37 | −0.74 | −0.34 | −0.85 | −0.82 | 1 | −0.10 | −0.98 | 0.94 | −0.03 | −0.93 | −0.52 | −0.31 |
11. Percent Built (1 km) | −0.30 | 0.05 | −0.22 | 0.05 | 0.13 | −0.46 | −0.71 | −0.02 | 0.17 | −0.10 | 1 | −0.12 | −0.15 | −0.06 | 0.15 | −0.24 | −0.13 |
12. Percent Forest (1 km) | 0.20 | 0.58 | 0.34 | 0.51 | 0.35 | 0.83 | 0.51 | 0.86 | 0.78 | −0.98 | −0.12 | 1 | −0.90 | 0.04 | 0.89 | 0.57 | 0.33 |
13. Percent Agriculture (250 m) | −0.19 | −0.65 | −0.37 | −0.45 | −0.28 | −0.69 | −0.28 | −0.75 | −0.72 | 0.94 | −0.15 | −0.90 | 1 | 0.09 | −1.00 | −0.59 | −0.38 |
14. Percent Built (250 m) | 0.52 | 0.15 | −0.09 | −0.26 | −0.21 | 0.18 | 0.21 | −0.19 | −0.26 | −0.03 | −0.06 | 0.04 | 0.09 | 1 | −0.15 | 0.40 | 0.46 |
15. Percent Forest (250 m) | 0.15 | 0.64 | 0.38 | 0.47 | 0.29 | 0.67 | 0.26 | 0.75 | 0.73 | −0.93 | 0.15 | 0.89 | −1.00 | −0.15 | 1 | 0.56 | 0.35 |
16. Mean Slope (1 km) | 0.71 | 0.57 | 0.52 | 0.13 | −0.09 | 0.77 | 0.60 | 0.17 | 0.02 | −0.52 | −0.24 | 0.57 | −0.59 | 0.40 | 0.56 | 1 | 0.66 |
17. Mean Slope (250 m) | 0.75 | 0.45 | 0.18 | −0.15 | −0.21 | 0.48 | 0.25 | −0.01 | −0.08 | −0.31 | −0.13 | 0.33 | −0.38 | 0.46 | 0.35 | 0.66 | 1 |
Reference Data | ||||||
---|---|---|---|---|---|---|
Agriculture | Built | Forest | M. Wetland | TOTAL | User. Acc. | |
Agriculture | 44 | 2 | 11 | 0 | 57 | 77.19 |
Built | 3 | 23 | 0 | 0 | 26 | 88.46 |
Forest | 8 | 2 | 51 | 0 | 61 | 83.61 |
M. Wetland | 1 | 1 | 1 | 20 | 23 | 86.96 |
TOTAL | 56 | 28 | 63 | 20 | 167 | |
Prod. Acc. | 78.57 | 82.14 | 80.95 | 100.00 | ||
Overall Accuracy: 0.826 | ||||||
Kappa: 0.753 |
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Name | Description | BV | SF | DF |
---|---|---|---|---|
Covariates for occupancy (ψ) | ||||
Percent forest cover (250 m) | Percent of pixels classfied as forest in 250 m buffers around each sampling site. This variable indicates habitat extent for mammal species and is inversly proporcional to percent agrigulture. | 40 ± 20 | 98 ± 2 | 88 ± 10 |
Built area percentage (250 m) | Percent of pixels classfied as built in 250 m buffers around each sampling site. This variable indicates direct human activity. | 0 | 0 | 1.3 ± 2.4 |
Annual NDVI (250 m) | Average Normalized Difference Vegetation Index (NDVI) in 250 m buffers around each sampling site. This variable indicates overall vegetation greenness is taken to be a good estimator of forest quality in the study landscape. | 0.29 ± 0.01 | 0.39 ± 0.05 | 0.37 ± 0.02 |
Mean NDVI—wet season (250 m) | Average Normalized Difference Vegetation Index (NDVI) from the wet season in 250 m buffers around each sampling site. This variable indicates vegetation greenness during the wet season is taken to be a good indicator of forest type and habitat quality. | 0.27 ± 0.02 | 0.37 ± 0.1 | 0.33 ± 0.05 |
Mean NDVI—dry season (1 km) | Average Normalized Difference Vegetation Index (NDVI) from the dry season in 1 km buffers around each sampling site. This variable indicates vegetation greenness during the dry season is taken to be a good indicator of forest type and habitat quality. | 0.24 ± 0.01 | 0.26 ± 0.02 | 0.26 ± 0.02 |
Difference wet and dry NDVI (1 km) | Average Normalized Difference Vegetation Index (NDVI) from the wet season minus average NDVI from the dry season in 1 km buffers around each sampling site. Indicator of forest and vegetation seasonality. High values of this variable indicate high seasonality and vice versa. | 0.02 ± 0.0 | 0.09 ± 0.04 | 0.2 ± 0.03 |
Distance to roads | Distance (in m) to paved or unpaved roads. This variable indicates direct and indirect human activity. | 237 ± 140 | 1114 ± 330 | 263 ± 264 |
Covariates for detection (p) | ||||
Number of days | Number of days each camera was active. | 1420 ± 32 | 1603 ± 74 | 2444 ± 45 |
Dogs presence | Number of dog photographs per day in each camera. Indicator of human activity. | 8 ± 2.5 | 5 ± 1.2 | 42 ± 3.7 |
Cattle | Number of photographs detecting cattle per day in each camera. Indicator of human activity. | 7 ± 2.3 | 0 | 0 |
Slope (250 m) | The mean slope in 250 m buffers around each sampling site. Indicator of topography. | 10.1 ± 0.3 | 8.9 ± 0.5 | 8.9 ± 0.5 |
Scientific Name | English Name | IUCN Status | National Status * 1 | Altitudinal Range | Independent Records (1-day) | ||
---|---|---|---|---|---|---|---|
DF | SF | BV | |||||
Canidae | |||||||
Lycalopex sechurae | Sechuran fox | NT | NT | 0–2000 | 11 | 0 | 32 |
Cervidae | |||||||
Odocoileus virginianus ssp. peruvianus | Peruvian White-tailed deer | -- | EN | 0–5000 | 121 | 35 | 32 |
Dasypodidae | |||||||
Dasypus novemcinctus | Nine-banded armadillo | LC | LC | 0–2000 | 6 | 20 | 0 |
Didelphidae | |||||||
Didelphis marsupialis | Lowland opossum | LC | LC | 0–2000 | 6 | 0 | 5 |
Felidae | |||||||
Leopardus pardalis | Ocelot | LC | NT | 0–3000 | 59 | 55 | 11 |
Leopardus wiedii | Margay | NT | VU | 0–3000 | 75 | 49 | 5 |
Herpailurus yagouaroundi | Jaguarundi | LC | NT | 0–3200 | 12 | 15 | 8 |
Mustelidae | |||||||
Eira barbara | Tayra | LC | LC | 0–2400 | 25 | 13 | 4 |
Galictis vittata | Greater Grison | LC | DD | 0–1200 | 4 | 1 | 0 |
Myrmecophagidae | |||||||
Tamandua mexicana | Northern tamandua | LC | VU | 0–2000 | 47 | 11 | 6 |
Procyonidae | |||||||
Nasua nasua | South American coati | LC | LC | 0–2500 | 61 | 100 | 33 |
Sciuridae | |||||||
Simosciurus stramineus | Guayaquil squirrel | -- | LC | 4 | 0 | 5 | |
Tayassuidae | |||||||
Pecari tajacu | Collared peccary | LC | NT | 0–3000 | 2 | 26 | 0 |
Leporidae | |||||||
Sylvilagus daulensis | Daule tapeti | -- | NE * 2 | 0–3400 | 16 | 7 | 0 |
Cebidae | |||||||
Cebus aequatorialis | Ecuadorian white-fronted capuchin | CR | CR | 0–2000 | 8 | 0 | 0 |
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Haro-Carrión, X.; Johnston, J.; Bedoya-Durán, M.J. Landscape Structure and Seasonality: Effects on Wildlife Species Richness and Occupancy in a Fragmented Dry Forest in Coastal Ecuador. Remote Sens. 2021, 13, 3762. https://doi.org/10.3390/rs13183762
Haro-Carrión X, Johnston J, Bedoya-Durán MJ. Landscape Structure and Seasonality: Effects on Wildlife Species Richness and Occupancy in a Fragmented Dry Forest in Coastal Ecuador. Remote Sensing. 2021; 13(18):3762. https://doi.org/10.3390/rs13183762
Chicago/Turabian StyleHaro-Carrión, Xavier, Jon Johnston, and María Juliana Bedoya-Durán. 2021. "Landscape Structure and Seasonality: Effects on Wildlife Species Richness and Occupancy in a Fragmented Dry Forest in Coastal Ecuador" Remote Sensing 13, no. 18: 3762. https://doi.org/10.3390/rs13183762