Journal of Threatened
Taxa | www.threatenedtaxa.org | 26 April 2026 | 18(4): 28615–28622
ISSN 0974-7907 (Online) | ISSN 0974-7893 (Print)
https://doi.org/10.11609/jott.9782.18.4.28615-28622
#9782 | Received 24 March 2025 | Final received 12 April 2026| Finally
accepted 16 April 2026
Importance of integrating
multiple criteria in breeding habitat management for urban frogs and toads
(Amphibia: Anura) in Jakarta City, Indonesia
Mohamad Isnin
Noer 1 , Ivan Hafidhuddin
2 , Agung Sedayu
3 , Ratna Komala 4 & Alvira Salsabila 5
1,3,4,5 Program Studi
Biologi, Faculty of Maths
and Sciences, Universitas Negeri
Jakarta, Gd. Hasjim Asjarie
lt.9. Jl, Rawamangun Muka, Jakarta 13220, Indonesia.
2 Central Proteina
Prima, Jakarta 12920, Indonesia.
1 mohamadisnin@unj.ac.id
(corresponding author), 2 hafidhuddinivan@gmail.com, 3 asedayu@unj.ac.id,
4 ratna_komala08@yahoo.co.id, 5 alvrasb@gmail.com
Editor: S.R. Ganesh, Kalinga
Foundation, Agumbe, India. Date of
publication: 26
April 2026 (online & print)
Citation: Noer, M.I., I. Hafidhuddin,
A. Sedayu, R. Komala &
A. Salsabila (2026).
Importance of integrating multiple criteria in breeding habitat management for
urban frogs and toads (Amphibia: Anura) in Jakarta
City, Indonesia. Journal of Threatened Taxa 18(4): 28615–28622. https://doi.org/10.11609/jott.9782.18.4.28615-28622
Copyright: © Noer et al. 2026. Creative Commons Attribution 4.0
International License. JoTT allows unrestricted use,
reproduction, and distribution of this article in any medium by providing
adequate credit to the author(s) and the source of publication.
Funding: This research was financially supported by a grant from the Faculty of Mathematics and Natural Sciences, Universitas Negeri Jakarta (Grant No. 38/SPK PENELITIAN/5.FMIPA/2020).
Competing interests: The authors declare no competing interests.
Author
details: Mohamad Isnin Noer is currently working in the Program Studi Biologi at Universitas Negeri Jakarta, with a research focus on urban and acoustic ecology, especially reptiles and amphibians. Ivan Hafidhuddin is a recent graduate of the BProgram Studi Biologi at Universitas Negeri Jakarta, with an interest in studying reptiles and amphibians. Agung Sedayu is currently pursuing his doctoral degree at Universitas Indonesia, with a research focus on urban plant biodiversity. Ratna Komala is a professor in the Program Studi Biologi at Universitas Negeri Jakarta, focusing on marine ecology. Alvira Salsabila is a student in the Program Studi Biologi who actively studies reptiles and amphibians.
Author contribution: MIN contributed to conceptualizing ideas and hypotheses, designing methodology, conducting investigations, analyzing data, and writing manuscripts. IH helped in providing field data (investigation), statistical analysis, and data visualization. AS contributed to detailing the research ideas and methods, validating results, and refining the discussion. RK added insight into the manuscript, refining the methodology, and validating the results.
Acknowledgements: We would like to express our sincere gratitude to the faculty of Mathematics and Natural
Sciences at Universitas Negeri Jakarta for generously providing the funding that made this research possible. Our heartfelt thanks also go to the Dinas Pertamanan dan Hutan Kota DKI Jakarta for granting us the necessary permissions to conduct research across various urban parks and forested areas within the city. We are especially grateful to Yudi Saputra and Dhany Ardiansyah for their invaluable assistance in the field, whose dedication and hard work significantly contributed to the success of this study. Their efforts in navigating challenging conditions and collecting data were instrumental in shaping the outcomes of this research.
Abstract: This study assessed the local and
landscape factors that support breeding habitats for native frog species in Jakarta,
the capital city of Indonesia. We surveyed 25 wetlands categorized into two
management states and varying local and landscape features. Our results
revealed that frog species exhibit diverse habitat preferences for breeding;
some species prefer constructed or managed environments, some depend on more
natural or minimally managed habitats, and one species was highly linked with
vegetation cover and light intensity. These findings emphasize the need to
incorporate multiple criteria when designing strategies to support breeding
habitats for all native frog species in Jakarta. We also explored specific
factors influencing breeding site selection, providing insights into the
drivers of breeding habitat preferences in urban environments.
Keywords: Anthropogenic, conservation,
green infrastructure, landscape ecology, native, urban wetland.
INTRODUCTION
Urban
environments are experiencing a high degree of land-use changes to support
ever-increasing human populations and economies. As a result, natural habitats
that support native wildlife species are unsustainably degraded in terms of
both quality and quantity (Wang & Kintrea 2021;
Pereira et al. 2022). Only a few native species can tolerate these dramatic
changes and would likely persist in the remaining remnant patches of habitats
(Callaghan et al. 2021; Hahs et al. 2023). Frogs are
considered key-stone species living in urban environments (Hutto Jr &
Barrett 2021). The ongoing degradation of natural habitats has driven even the
most resilient of frogs to cope with degraded habitats left over by humans,
known as constructed habitats (Scheffers & Paszkowski 2013). Although utilizing degraded and
constructed habitats poses greater risks to the survival of the frogs, finding
an isolated or inaccessible natural habitat is more costly
considering the risks of bypassing unsuitable urban matrixes (Klop-Toker et al. 2016; Watchorn et al. 2023).
The
utilization of urban habitats by frogs is not only to find prey and seek
shelter, but they also utilize these areas as breeding habitats to find mates
and reproduce (Watchorn et al. 2023). Breeding habitats for frogs are usually
unique with certain characteristics that probably might not always be obtained
in their foraging habitats (Băncilă et al. 2017;
Nakanishi et al. 2020). Male frogs find a mate by vocalizing sporadically to
get attention from the females that could be at some distance (Wells 1977). Thus,
a greater chance of getting a mate is influenced by the greater efficacy of
acoustic signals (Gridi-Papp et al. 2006; Simmons et
al. 2013). The trade-off of choosing high-quality habitats persisting in
isolation can be compensated for by selecting medium or low-quality habitats
but gaining better access for movements and dispersal. The quality of the
aquatic habitat used by frogs to deposit eggs is also pivotal to ensure the
development and survival of their offspring. However, the presence of ubiquitous
disturbances and fragmentation in urban environments is highly reducing the
access of urban frog populations to find suitable habitats for breeding. Thus,
frogs need to compensate for the risks of finding a suitable breeding habitat
by choosing a novel habitat in an urban environment. Instead of considering
multiple factors in their breeding decision, they are constrained to settle
down for few fundamental criteria in selecting a breeding habitat in the urban
environment (McCaffery et al. 2014; Băncilă et al.
2017).
Previous
studies have reported that frogs could utilize constructed or managed habitats
(Simon et al. 2009; Holzer 2014; Hutto Jr & Barrett 2021) either foraging
or breeding even though the preferences are highly associated with the level of
synurbism. Synurbic species are usually well adapted
to substantial changes made by humans, thus the
potential risks are negligible (Feoktistova et al.
2020). However, some urban areas have retained many nature-dependent or seminatural species that require habitats with low
disturbances and changes (Scheffers & Paszkowski 2013). In general, there are so many factors
considered by frogs to choose their breeding habitat in urban environments,
which generally can be classified into two categories based on their role,
specifically local and landscape factors. Local factors are strongly linked to
the quality of breeding habitats, encompassing the key parameters that frogs
require to ensure breeding success and support the growth and survival of their
offspring. Landscape factors relate to the extent of human interference at
breeding sites, which influence the environmental conditions preferred by
certain frog species. In urban environments, frogs are likely face trade-offs
when selecting breeding habitats, as areas that offer both suitable local and
landscape conditions are scarce (Pope et al. 2000). As a result, we expect that
frogs will select breeding habitats based on the most influential conditions
available in urban environments, in an effort to minimize the cost of finding
ideal habitats. The selection may likely vary in all species found in the city
since each species of frog has a different fundamental niche and sensitivity
level.
Jakarta is
one of Indonesia’s major urban centres that supports
a vast and densely packed human population spread across various districts. The
urban landscape exhibits marked disparities in the distribution of green
spaces. Central regions, typically characterized by extensive urbanization,
contain minimal natural areas. In contrast, peripheral zones often feature
substantial green spaces, with some areas maintaining access to semi-natural
habitats (Ardiansyah et al. 2018; Hwang et al. 2020).
A tiny body of research studying frog diversity exists in some parts of the
city, reporting a quite diverse frog composition in such suboptimal habitat
patches. Approximately, nine species of frogs have been documented in this
city, displaying different habitat preferences (Rushayati
et al. 2023). Till date, no study has exclusively focused on the breeding
activities of Jakarta frogs. Thus, this study attempted to examine the breeding
site selection of frogs within these urban environments, focusing on some
remaining patches of green areas in Jakarta City.
MATERIALS AND METHODS
Sampling
Sites
A total of
25 wetlands were surveyed sporadically in 2022 and 2023 encompassing a diverse
urban landscape in Jakarta, Indonesia. The study areas covered private areas,
parks, fishing sites, and vacant lots. We conducted frog surveys at the
beginning of the rainy season when many frogs started breeding activities.
These areas were categorized into two distinct groups based on their levels of
management intensity, allowing for a comparative analysis of how human
intervention influences habitat suitability. In addition, we assessed the
factors that contribute to the attractiveness of these habitats for breeding,
shedding light on how urban green spaces, despite varying degrees of
modification, continue to play a crucial role in supporting wildlife,
particularly frogs.
Breeding survey
Breeding
activities and frog abundance were determined using an acoustic approach from
1900–2100 h WIB. Most urban frogs in the city of Jakarta are selective breeders
that vocalize exclusively in their breeding sites or period, they would not
produce calls outside those constraints. Thus, the acoustic survey is reliable
for assessing the breeding habitat of frogs in Jakarta. Some areas, such as
private lands, were also difficult to access and explore at night for
conducting visual search, utilizing an acoustic survey was best for these
circumstances. If available, we also incorporated mating calls for some species
of frogs to ascertain that the sites surveyed were utilized by frogs for
breeding activities. Frogs were identified acoustically using a database
provided by Xeno-Canto (Xeno-canto
Foundation, 2026), frog voices of Borneo (Inger et al. 2017), and other
information sources from previous studies, such as (Márquez & Eekhout 2006; Kurniati et al.
2010). The number of individual frogs in each site was estimated using the
method outlined by Scheffers & Paszkowski (2013). We used an 1800-point count
for 10 minutes to detect the vocalization and count the number of males calling
within 50 m. Based on our preliminary surveys, 10 minutes of observation is
adequate to detect nearly all species in the city of Jakarta. We used 20
minutes pre-observation to ensure there were no undetected or cryptic species
that did not emit calls during observation.
Local and landscape variables
We measured
six local and five landscape variables for all surveyed sites. We recorded all
local variables directly in the field at the time when frogs were sampled to
ensure that all variables represent the exact condition of their breeding
habitat. Six local variables comprised of one management state and five water
chemistry parameters. Management state was classified into managed and
unmanaged sites following the description proposed by Garcia-Gonzalez &
Garcia-Vazquez (2011). We defined ‘unmanaged sites’ as areas that were not
subject to any form of management or control. In contrast, ‘managed sites’ were
those where vegetation, particularly surface vegetation, is frequently mowed,
and leaf litter is regularly cleared. To accurately classify all sites into
proper categories, we carried out day surveys (immediately after night surveys)
to quantify management state as well as water chemistry parameters. Water
chemistry parameters measured in this study were turbidity, temperature,
salinity, pH, and total nitrogen using LAQUA NO3 2000-S ION
NITRATE/PH/ORP/TEMP. METER. All five water chemistry parameters were measured
randomly at three distinct locations within a single site. Five landscape
variables recorded were normalized difference vegetation index (NDVI), normalized
difference water index (NDWI), normalized difference building index (NDBI),
land surface temperature (LST), and light intensity. Landscape variables were
mapped within 1 km of the surrounding site by creating a buffer and the data
were extracted using zonal statistic plugin. NDVI, NDWI, and NDBI were
extracted from Landsat 8 L2SP taken at or near the time when the survey was
conducted. LST and light intensity respectively were extracted from Terra/MODIS
provided by NASA at 0,1 degrees of resolution and VIIRS night-time lights
provided by Earth Observation Group (EOG). All landscape variable analyses were
performed using QGIS 3.38.
Data analysis
The number
of calling individuals per site was used to characterize male abundance and
were organized into two distinct categories of site management (managed and
unmanaged). In order to determine which local and landscape variables are the
best predictors for breeding occurrence in 25 surveyed wetlands, we used a
generalized linear regression model (GLM) with a binomially distributed error
term and a logit link function in R 4.4.1 using lme4 package. We tested five
local and four landscape models consisting of nine multivariate models. Models
were evaluated using Akaike’s information criterion adjusted for small samples
(AICc) to determine the best variables that predict
the occurrence of breeding activities. The smallest value of ΔAICc was chosen as the top model, while the value of ΔAICc <2 was considered as the best predictive model.
Since some species of frog were very rare such that their sightings sample size
does not entertain running statistical analyses, we ran this model evaluation
only on three common frogs with adequate sighting frequencies obtained in our
study.
RESULTS
This study
recorded six species of frogs that utilize the remnant green areas of Jakarta
as their breeding habitat. The most common or generalist species that occupied
urban wetlands for breeding were Duttaphrynus
melanostictus, Hylarana
nicobariensis, and Polypedates
leucomystax. In contrast, others were found in a
deficient number of detections (Table 1). Duttaphrynus
melanostictus was considered more generalist in
terms of their utilization of breeding sites, it was found breeding in
unmanaged and managed sites. Most other frog species were also found using
these two habitats but were more likely to breed in unmanaged habitats (Figure
1). Only one species, Fejervarya limnocharis, was found utilizing unmanaged habitat
exclusively for breeding.
The
occupancy of H. nicobariensis was best predicted
by NDVI (Normalized Difference Vegetation Index) and light, which were
consistently identified as the most influential landscape predictors. These two
factors appeared in three out of the four top models evaluated, highlighting
their significance in determining habitat preference. On a more localized
scale, pH levels and total nitrogen were identified as the most important
predictors influencing H. nicobariensis
occupancy, as detailed in Table 2. This suggests that while local variables
play a role, the species tends to prioritize landscape-level features when
selecting breeding sites, as evidenced by models with ΔAICc
values of less than two, indicating strong model performance. The interplay
between landscape and local variables underscores the complexity of habitat
selection for this species, with landscape factors exerting a stronger
influence.
For D. melanostictus, local variables played a more
significant role in predicting their occupancies compared to landscape
variables, as shown in Table 3. Among these local variables, pH and total
nitrogen were identified as the strongest predictors, explaining the selection
of breeding sites with a ΔAICc of less than two,
indicating robust model performance. Interestingly, NDVI (Normalized difference
vegetation index), while not the best predictor, also appeared as a
landscape-level predictor for D. melanostictus,
similar to its role in the occupancy models for H. nicobariensis.
Despite its presence, NDVI was not considered a top predictor for D. melanostictus, emphasizing the species’ stronger
reliance on local environmental factors over broader landscape features when
choosing breeding habitats. This distinction highlights the varying degrees of
influence between local and landscape variables on different species’ habitat
preferences.
As expected
for P. leucomystax, pH and total nitrogen were
the best predictor variables explaining this species’ occupancy. However, our
models demonstrated that landscape variables were also important variables to
consider. Four of five models revealed the inclusion of NDVI, LST, and light as
the best-explained predictors for breeding site selection by P. leucomystax (Table 3).
DISCUSSION
Frog
surveys in the city of Jakarta have not been conducted intensively, making
scientific data on frogs in this city scarce. This study provides important
information to fill the gap in the species that inhabit Jakarta’s urban
ecosystem and breeding site selection, which can be used as baseline
information to enhance urban biodiversity in Jakarta. By selecting 25 sites of
breeding sites across urban landscapes, we found six species of frogs residing
in Jakarta. Most of the frogs are generalist and synurbic species that are
capable of utilizing urban habitats and matrices (Iskandar 1998), only one
species (H. erythrea) which is considered
exceptional since this frog is usually found in rural areas.
Our
findings demonstrated that most species were capable of using both managed and
unmanaged sites for breeding, as only F. limnocharis
was obtained exclusively in unmanaged sites. However, species that utilized
both types of sites showed different occupancies on those sites. Duttaphrynus melanostictus
is found more often in managed sites, whereas H. nicobariensis
is found in unmanaged sites. Duttaphrynus melanosticus is a synurbic toad that favours a human-modified environment. This species is
capable of using man-made structures for foraging and breeding. In the context
of breeding habitat, D. melanostictus can
utilize areas that contain many human populations and less vegetated areas or
natural habitats (Bickford et al. 2010), including stormwater
ponds, in the middle of the city. Seemingly, this toad’s tadpole fundamentally
has developed adaptive features to cope with urban disturbances such as shortening
the larval periods (Mahapatra & Mahapatra 2015; Mogali
2017; Saidapur 2025). In line with our findings which
found undemanding features of the habitat chosen by D. melanostictus
to breed. This frog only considers pH and total nitrogen as a fundamental
requirement for breeding. Duttaphrynus melanostictus would thrive in water bodies with a
neutral to slightly alkaline due to the essential pH for optimal egg
development and larval survival (Rout et al. 2019). Total nitrogen is another
critical factor, as it affects the nutrient availability in breeding sites.
Higher nitrogen levels can enhance algal growth, thus providing adequate food
for tadpoles to grow more quickly in the changing environment of urban city (Edirisinghe & Amarasinghe
2011).
Hylarana nicobariensis is
commonly found in disturbed areas (Inger & Stuebing
1997), favouring swampy areas in urban environments (Kurniati & Hamidy 2017). This
frog is typically abundant in the city’s fringe, but some manage to survive
around the city centre. The breeding habitat used by
this frog in urban is a bit more complex than D. melanostictus
or even somewhat in contrast, even though they can occupy the same habitat on
some occasions. The dependency of this frog on swampy areas characterized by
the lower rate of human frequentation is the reason why this frog has a greater
connection with NDVI and other landscape parameters associated with the lower
level of human frequentation. The quality of landscape features is probably
linked with other landscape-derived features, such as moisture. Previous study
highlighted the importance of moist environments for the breeding and survival
of H. nicobariensis, indicating that
inhabiting swampy areas with higher NDVI is beneficial to maintaining
acceptable moisture (Basukriadi et al. 2021; Laurence
et al. 2023).
Polypedates leucomystax probably
is a fussy breeder in the urban city of Jakarta. Previous studies have
documented the capability of this frog to utilize urban structures (Kuraishi et al. 2013; Shahrudin
2016). However, the quality of the man-made structures utilized by this frog is
significantly different from D. melanostictus.
Polypedates leucomystax
favours aged or senescent stagnant water with a low
level of disturbances or modification to breed. Aged ponds often have stable
water conditions, which are conducive to the growth of algae and microorganisms
that serve as food sources for P. leucomystax
larvae (Sandifer et al. 1993). In addition, our findings also highlighted the
importance of landscape factors in defining the breeding selection of this
frog. Polypedates leucomystax
is a tree frog, though this frog can adapt to man-made structures for laying
eggs, P. leucomystax needs green areas to
facilitate movement and other activities, especially for finding mates since
this frog is solitary (Shahrudin 2016; Simon et al.
2022). Therefore, green connectivity is an important factor in supporting the
breeding activities of P. leucomystax in urban
environments.
Even though
three common frog species documented in this study exhibit variation in
preference for managed and unmanaged habitats, management criteria are not the
best predictor explaining the habitat selection for breeding. Management state
is probably not strongly associated with the local and landscape parameters
required by frogs. Some managed habitats are capable of providing the resources
and environmental conditions required by frogs to carry out breeding activities
and safe habitats for the tadpoles. In contrast, unmanaged habitats in urban
areas are probably not always safe for sensitive species to breed. Some of them
are subjected to high exposure to water pollution such as heavy metals, or have
potential risks of predators, especially fish. Most of the unmanaged habitats
are linked strongly to wilderness habitats that are suitable for some other
cryptic frogs that rely on low levels of ecological reset and enrichment.
Other frogs
that are found in lower detection probably have similar basic requirements to
other common frogs. Some of them (F. cancrivora
and F. limnocharis) showed strong dependencies
on paddy fields or related areas that were seemingly limited only to the urban
periphery (Iskandar 1998; Kurniati 2006; Kurniati et al. 2010). In order to manage these species to
persist in Jakarta, building paddy fields or related habitats scattered in the
city of Jakarta is encouraged as well as providing connectivity among these
areas. For H. erythrea, we recognized the
challenging issue for urban planners and designers to maintain this frog. This
frog is very sensitive to human disturbances and extreme temperatures, making
this frog usually found in natural or rural areas located especially at medium
levels of elevation. Temperature is likely the important factor that explains
the presence of this species in Jakarta (Widyasamratri
et al. 2019; Siswanto et al. 2023) since human
disturbances are ubiquitous in Jakarta and the city’s geographic location is at
a low elevation. Therefore, urban planners and designers need to deal with
urban heat islands as a general effort to maintain many areas in the city of
Jakarta that are suitable for frog breeding and foraging activities.
Our
findings indicate that all common frog species residing in the urban landscape
of Jakarta share different fundamental needs for their breeding habitats.
Therefore, urban planning must take into account
multiple criteria to ensure these habitats are preserved or created. Addressing
these ecological requirements is essential not only for the survival of
amphibian populations but also for achieving broader sustainable urban
development goals, where biodiversity and natural habitats are integrated into
the city’s growth plans (Sedayu et al. 2024).
Table 1. Occupancy
and abundance of six anurans
organized based on site management types.
|
Species |
Type |
N |
Occa |
% Occb |
Abundancec |
|
D. melanostictus |
Unmanaged |
28 |
3 |
14.28 |
3.11 |
|
Managed |
26 |
6 |
28.57 |
2.16 |
|
|
F. cancrivora |
Managed |
1 |
1 |
4.76 |
0.08 |
|
Unmanaged |
1 |
1 |
4.76 |
0.11 |
|
|
F. limnocharis |
Unmanaged |
3 |
1 |
4.76 |
0.33 |
|
Managed |
0 |
0 |
0 |
0 |
|
|
H. erythrea |
Managed |
6 |
2 |
9.52 |
0.5 |
|
Unmanaged |
0 |
0 |
0 |
0 |
|
|
H. nicobariensis |
Unmanaged |
63 |
6 |
28.57 |
7 |
|
Managed |
18 |
2 |
9.52 |
1.5 |
|
|
P. leucomystax |
Unmanaged |
18 |
3 |
14.28 |
2 |
|
Managed |
11 |
4 |
19.04 |
0.91 |
a—Occurrences of anuran species | b—Percent
occurrences between two management types | c—Mean abundance based on
two management types.
Table 2. Occupancy models for nine predictor variables observed for Hylarana nicobariensis.
|
Variable categories |
Predictors |
K |
AICc |
Delta_AICc |
AICcWt |
Cum.Wt |
LL |
|
Landscape |
NDVI+Light |
3 |
27.91 |
0 |
0.53 |
0.53 |
-10.25 |
|
|
NDVI+LST+Light |
4 |
30.12 |
2.2 |
0.17 |
0.7 |
-9.81 |
|
|
LST+Light |
3 |
30.91 |
3 |
0.12 |
0.82 |
-11.75 |
|
|
NDVI+NDWI+NDBI+LST |
5 |
32.93 |
5.01 |
0.04 |
0.96 |
-9.46 |
|
Local |
pH+TN |
3 |
31.3 |
3.39 |
0.1 |
0.92 |
-11.95 |
|
|
Sal+pH+TN |
4 |
34.39 |
6.48 |
0.02 |
0.98 |
-11.95 |
|
|
Type+Sal+pH+TN |
5 |
34.86 |
6.95 |
0.02 |
1 |
-10.43 |
|
|
Type+Turbid+Sal+pH+TN |
6 |
38.82 |
10.91 |
0 |
1 |
-10.41 |
|
|
Type+Turbid+Temp+Sal+pH+TN |
7 |
38.86 |
10.95 |
0 |
1 |
-8.12 |
Table 3. Occupancy models for nine predictor variables observed for Duttaphrynus
melanostictus.
|
Variable categories |
Predictors |
K |
AICc |
Delta_AICc |
AICcWt |
Cum.Wt |
LL |
|
Local |
pH+TN |
3 |
30.75 |
0 |
0.58 |
0.58 |
-11.67 |
|
|
Sal+pH+TN |
4 |
33.04 |
2.29 |
0.18 |
0.76 |
-11.27 |
|
|
LST+Light |
3 |
35.03 |
4.28 |
0.07 |
0.91 |
-13.81 |
|
|
Type+Sal+pH+TN |
5 |
36.49 |
5.74 |
0.03 |
0.95 |
-11.25 |
|
|
Type+Turbid+Temp+Sal+pH+TN |
7 |
41.39 |
10.64 |
0 |
1 |
-9.39 |
|
Landscape |
NDVI+Light |
3 |
34.63 |
3.88 |
0.08 |
0.85 |
-13.61 |
|
|
NDVI+LST+Light |
4 |
36.82 |
6.07 |
0.03 |
0.97 |
-13.16 |
|
|
Type+Turbid+Sal+pH+TN |
6 |
37.68 |
6.93 |
0.02 |
0.99 |
-9.84 |
|
|
NDVI+NDWI+NDBI+LST |
5 |
40.25 |
9.5 |
0.01 |
1 |
-13.13 |
Table 4. Occupancy models for nine predictor variables observed for Polypedates
leucomystax.
|
Variable categories |
Predictors |
K |
AICc |
Delta_AICc |
AICcWt |
Cum.Wt |
LL |
|
Local |
pH+TN |
3 |
33.2 |
0 |
0.35 |
0.35 |
-12.89 |
|
|
Sal+pH+TN |
4 |
36.28 |
3.09 |
0.08 |
0.91 |
-12.89 |
|
Landscape |
LST+Light |
3 |
33.85 |
0.65 |
0.26 |
0.61 |
-13.22 |
|
|
NDVI+Light |
3 |
34.1 |
0.9 |
0.23 |
0.83 |
-13.34 |
|
|
NDVI+LST+Light |
4 |
36.86 |
3.66 |
0.06 |
0.97 |
-13.18 |
|
|
NDVI+NDWI+NDBI+LST |
5 |
39.15 |
5.95 |
0.02 |
0.98 |
-12.58 |
|
|
Type+Sal+pH+TN |
5 |
39.75 |
6.56 |
0.01 |
1 |
-12.88 |
|
|
Type+Turbid+Sal+pH+TN |
6 |
43.7 |
10.51 |
0 |
1 |
-12.85 |
|
|
Type+Turbid+Temp+Sal+pH+TN |
7 |
47.9 |
14.7 |
0 |
1 |
-12.64 |
FOR
FIGURE - - CLICK HERE FOR FULL PDF
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