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Identifying the potential geographic distribution for Castanopsis argentea and C. tungurrut (Fagaceae) in the Sumatra Conservation Area Network, Indonesia

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Recently, Castanopsis argentea (Blume) A.DC. and Castanopsis tungurrut (Blume) A.DC. have been listed as endangered species by the International Union for the Conservation of Nature (IUCN). For conservation planning, it is important to know the full distribution of species. This study aimed to predict the potential distribution of C. argentea and C. tungurrut using MaxEnt, and understand key factors responsible for the distribution of these species. A total of 53 occurrences and six environmental variables were used to model their distribution. The AUC values of C. argentea and C. tungurrut were 0.86 and 0.91, respectively, and the models suggest the distribution of both species is mainly influenced by elevation, and temperature seasonality for C. tungurrut. The predicted distributions of the species are in the mountains of the western part of Sumatra, and their range includes 12 conservation areas that have highly suitable habitats for both species. After generating the MaxEnt prediction map, we conducted field validation to validate the model predictions. Field surveys in two predicted areas showed that the predicted distribution maps accurately estimated the distribution of C. argentea and C. tungurrut at those localities.
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B I O D I V E R S IT A S
ISSN: 1412-033X
Volume 23, Number 4, April 2022 E-ISSN: 2085-4722
Pages: 1726-1733 DOI: 10.13057/biodiv/d230402
Identifying the potential geographic distribution for Castanopsis
argentea and C. tungurrut (Fagaceae) in the Sumatra Conservation Area
Network, Indonesia
TRY SURYA HARAPAN1,2, , NURAINAS1,3, SYAMSUARDI1,3,, AHMAD TAUFIQ1,4
1Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Andalas. Jl. Universitas Andalas, Limau Manis, Padang 25163,
West Sumatra, Indonesia. Tel./fax. +62-751-71671, email: trysuryaharapan@gmail.com, email: syamsuardi@sci.unand.ac.id
2Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences & Center for Integrative Conservation, Xishuangbanna Tropical
Botanical Garden, Chinese Academy of Sciences. Mengla, Yunnan 666303, China
3Herbarium of Universitas Andalas. Jl. Universitas Andalas, Limau Manis, Padang 25163, West Sumatra, Indonesia
4Department of Biological Sciences, Graduate School of Science, Tokyo Metropolitan University. Minami-Osawa, Hachioji-shi, Tokyo 192-0397, Japan
Manuscript received: 6 January 2022. Revision accepted: 9 March 2022.
Abstract. Harapan TS, Nurainas, Syamsuardi, Taufiq A. 2022. Identifying the potential geographic distribution for Castanopsis
argentea and Castanopsis tungurrut (Family: Fagaceae) in the Sumatra Conservation Area Network, Indonesia. Biodiversitas 23: 1726-
1733. Recently, Castanopsis argentea (Blume) A.DC. and Castanopsis tungurrut (Blume) A.DC. have been listed as endangered
species by the International Union for the Conservation of Nature (IUCN). For conservation planning, it is important to know the full
distribution of species. This study aimed to predict the potential distribution of C. argentea and C. tungurrut using MaxEnt, and
understand key factors responsible for the distribution of these species. A total of 53 occurrences and six environmental variables were
used to model their distribution. The AUC values of C. argentea and C. tungurrut were 0.86 and 0.91, respectively, and the models
suggest the distribution of both species is mainly influenced by elevation, and temperature seasonality for C. tungurrut. The predicted
distributions of the species are in the mountains of the western part of Sumatra, and their range includes 12 conservation areas that have
highly suitable habitats for both species. After generating the MaxEnt prediction map, we conducted field validation to validate the
model predictions. Field surveys in two predicted areas showed that the predicted distribution maps accurately estimated the distribution
of C. argentea and C. tungurrut at those localities.
Keywords: Conservation, distribution, endangered plants, phytogeography, spatial modeling
INTRODUCTION
Indonesia is home to hundreds of threatened tree
species, including members of the family Fagaceae. The
Fagaceae is a large angiosperm family comprising eight
genera with more than 700 species, of which 112 species
have been recorded in Indonesia (Purwaningsih and
Pulosakan 2016). This paper investigates two Indonesian
species in the family which are listed as Endangered under
IUCN criteria, Castanopsis argentea (Blume) A.DC. and
C. tungurrut (Blume) A.DC. (Barstow and Kartawinata
2018a,b). According to Indonesian Forum for Threatened
Trees (FPLI), the trees are considered vulnerable to
extinction and are protected nationally by Indonesian Law
P.106/MENLHK/SETJEN/KUM.1/12/2018. Besides edible
fruits, the durable wood of many species of Castanopsis are
used for constructing houses, making wood charcoal and
their bark is used for dyeing rattan work black (Soepadmo
and van Steenis 1972). Castanopsis spp. are also
considered to be indicators of superior arable lands
(Soepadmo and van Steenis 1972). Hence these species are
of high utility, and overuse of timber from these species
will contribute to decreasing their populations and increase
the threat of extinction. In Sumatra, the two species under
study are recorded mainly from the Barisan Mountains in
the west of the island (Figure 1) (Laumonier 1997).
Castanopsis argentea is also found in Java, Indonesia (Mt.
Ungaran, and on Mt. Wilis at Ngebel) and C. tungurrut is
also found in the Malay Peninsula, Simalur and Banka
Island, and West Java (Soepadmo and van Steenis 1972).
Numerous factors such as agricultural clearing, forest
fires, illegal logging, illegal mining, and transport
infrastructure close to the forest are ascribed to biodiversity
loss. The Indonesian government is drafting a plan to build
a massive Trans-Sumatra Highway for connecting
Sumatra's entire island in 2024. Any infrastructure
development plan has its share of negative consequences
on its surrounding ecosystems (Sloan et al. 2019). For
conservation planning, it is important to know which
species is distributed where, so that appropriate
infrastructural development could be guided.
Understanding species distribution with a full ground
survey is costly and time-consuming. A number of
distribution modelling methods have been developed to
help predict the distribution of species, including those
employing principle of Maximum Entropy (Phillips et al.
2006). These models incorporate environmental data to
define the environmental niche of the species (McShea
2014).
HARAPAN et al. Castanopsis argentea and Castanopsis tungurrut in Sumatra, Indonesia
1727
Maximum entropy (MaxEnt) is a widely used modeling
method for predicting species distribution in poorly-
surveyed areas. The algorithm typically outperforms other
methods based on predictive accuracy (Merow et al. 2013).
Compared to other SDM tools, a maximum entropy
algorithm can develop a good model with small number of
occurrences (Harapan et al. 2020). Because of this reason,
many studies on threatened plants, which typically have
small amounts of occurrence data, use MaxEnt to model
species distributions (Adhikari et al. 2012; Yang et al.
2013; Padalia et al. 2014; Pradhan 2015; Remya et al.
2015; Yuan et al. 2015; Yi et al. 2016; Pranata et al. 2019;
Ito et al. 2020; Anand et al. 2021; Du et al. 2021; Felix et
al. 2021; Liu et al. 2021; Mahatara et al. 2021; Nguyen et
al. 2021; Purohit and Rawat 2021; Su et al. 2021; Yang et
al. 2021; Ye et al. 2021). With effective conservation
planning focused on ensuring redundancy and resiliency
for sustainable future populations (Redford et al. 2011),
SDMs are a valuable tool for the conservation community
(Mcshea 2014). This study aims to predict the potential
distribution of C. argentea and C. tungurrut in the Sumatra
Conservation Area Network, Indonesia and to understand
key factors responsible for the distribution of these species.
MATERIALS AND METHODS
Study area
Castanopsis argentea occurrences were identified based
on field surveys between December 2017 to January 2019
in West Sumatra (Nyarai and Universitas Andalas
Biological Forest), North Sumatra (Sarula) and at the
border between West Sumatra and Jambi Province (Kerinci
Seblat National Park), Indonesia. Occurrences of C.
tungurrut were derived from herbarium specimen records
and GBIF records. A total of 52 occurrences (Figure 1)
were collected from our field surveys, Herbarium of
Andalas (Voucher Code: ANDA 0001-0005, ANDA 33381
for C. argentea and ANDA 00124-00141 for C. tungurrut)
and the Global Biodiversity Information Facility (GBIF
2020a,b).
Species description
The diagnostic characteristic of Fagaceae is the cupule,
a woody bract that partially covers the fruit. The C.
argentea and C. tungurrut have similar-looking sharply
spiny cupules. The cupule of C. argentea lacks branched
spines, and there are 3 fruits in a cupule, whereas C.
tungurrut has only a single fruit per cupule, which possesses
branched slender spines. The leaves of C. argentea are
glossy above and distinctly silvery below. Castanopsis
tungurrut leaves are glossy above, widest in the middle and
slightly acute at the leaf blade base (Figure 2).
Figure 1. Map of Sumatra, Indonesia and the occurrence data of the targeted Castanopsis argentea and C. tungurrut
B I O D I V E R S I T A S
23 (4): 1726-1733, April 2022
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Figure 2. The dry specimen of Castanopsis argentea and C.
tungurrut
Species distribution modeling
MaxEnt ver. 3.4.1 was used to identify the potential
distribution of C. argentea and C. tungurut in Sumatra. All
coordinates from species occurrences were converted to
decimal degrees. We included the following environmental
data in the models. Altitude derived from a digital elevation
model (DEM) was obtained from Jarvis et al. (2008),
climatic variables were downloaded from WorldClim
(Hijmans 2020), and soil quality was obtained from Fischer
et al. (2008). All remote sensing raster data were resampled
to 1 km spatial resolution using the R Raster package
(Hijmans 2020). All rasters in geotiff format were
converted to ASC format. Species distribution modelling
requires variable selection to enhance the analytical power
and avoid the model overfitting (Fourcade et al. 2014; Yi et
al. 2016; Pradhan and Setyawan 2021), hence we used
PCA to inform the exclusion of highly correlated
environmental variables. If two environmental variables
were significantly correlated (R>0.8), only one was
selected as a predictor (Harapan et al. 2020). Of the
original 21 variables, six variables were chosen, including
elevation, soil quality, temperature seasonality,
precipitation of warmest quarter, temperature annual range
and precipitation of wettest quarter (Table 1). On the
MaxEnt configuration, auto functions of the predictor
variables were selected for inclusion in the model. We
followed recommended default values that were used for
the convergence threshold (10-5) and a maximum number
of 500 iterations (Harapan et al. 2020). Ten replicated
model and background samples functions were used for
determining a good species location to reflect the
environmental conditions that one is affected in contrasting
on species presences based on the spatial scale (Saupe et al.
2012; Merow et al. 2013).
Distribution value in conservation areas
Raster output from MaxEnt bearing habitat suitability
values from 0-1 for each species was loaded in R and the
values were reclassified with Raster package (Hijmans
2020) to produce a potential distribution map with ≥ 0.8
thresholds (Figure 3). We used a Sumatra conservation area
shapefile derived from http://www.globalforestwatch.org to
check the species coverage inside and outside conservation
areas according to their predicted distribution. The shapefile
was read into a spatial polygons data frame using the
readOGR function in the rgdal package (Bivand et al.
2020).
RESULTS AND DISCUSSION
Castanopsis distribution model
The predicted distributions showed the Castanopsis
species have a considerable range overlap (Figure 3). The
highest potential distribution zones in Indonesia for C.
argentea were located along with the Barisan mountain
range, with C. tungurrut having a wider potential
distribution in the north of the island in the Lake Toba
environs. These species also showed distribution zones in
the southern of the island (Bengkulu - Lampung Province).
The success of the model in predicting the distributions
for both Castanopsis species was checked using mean area
under curve (AUC); the model performances were
satisfactory based on AUC values (Table 2). Analyses of
environmental variable contributions to each of the models
are different between species. Elevation, soil quality, and
temperature seasonality were the most important variables
for C. argentea while the most important variables for C.
tungurrut were elevation, temperature seasonality, and
precipitation of warmest quarter (Table 1).
Elevation was by far the highest contributing variable
influencing the predicted distribution for both species.
Based on a habitat suitability threshold of 0.8, suitable
habitat for C. argentea was above 700 m while for C.
tungurrut it was above 1700 m altitude (Figure 4). Both
Castanopsis species occur in slight-moderate soil limitation
that restricts their land use (Class 1 soils category) and is
found in the environment with low seasonality. Suitable
habitat for C. tungurrut receives about 800-1200 mm
precipitation in warmest quarter.
Table 1. Contributing environmental variables for Castanopsis
argentea (Ca) and C. tungurrut (Ct)
Code
Variable
Contribution (%)
Ct
DEM
Elevation
28.9
S
Soil Quality
14.7
bio4
Temperature Seasonality
25.4
bio18
Precipitation of Warmest Quarter
19.8
bio7
Temperature Annual Range
6.5
bio16
Precipitation of Wettest Quarter
4.7
Table 2. Model performance and total covered area of
Castanopsis argentea and C. tungurrut
Species
Presence
record
AUC
Model
Performance
(Swets 1988)
Total suitable
area covered
(>0.8)
C. argentea
15
0.91
Excellent
33,736 km2
C. tungurrut
37
0.86
Good
54,960 km2
HARAPAN et al. Castanopsis argentea and Castanopsis tungurrut in Sumatra, Indonesia
1729
Figure 3. The predicted distribution of: A. Castanopsis argentea, B. C. tungurrut in Sumatra, Indonesia
Figure 4. Response of Castanopsis argentea and C. tungurrut to
elevation
In this study, we showed the conservation area that are
suitable for both the species. West Sumatra, North Sumatra
and Jambi conservation area networks were the most
suitable areas. The modeled distributions of both species
suggest that they are well covered by the conservation
areas of Sumatra, Indonesia (Figure 5).
Field validation
After identifying areas with the highest probability of
occurrence for both species in Sumatra, Indonesia, we
chose Marapi Mountain, West Sumatra and Mount Tujuh,
Jambi to do field surveys for both species. A total of 5
individuals of C. argentea and 11 individuals of C.
tungurrut were recorded across the sites (Figure 6).
Figure 5. The distribution probability value (%) in Conservation Areas for Castanopsis argentea and C. tungurrut. Red circles are C.
argentea; green circles are C. tungurrut. *Field validation site
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23 (4): 1726-1733, April 2022
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Figure 6. Map of ground validation for Castanopsis argentea and C. tungurrut in Marapi Mountain and Mount Tujuh, Indonesia
In addition, we also recorded C. argentea occurrences
in Baruah Gunuang, West Sumatra, Indonesia (0.02329,
100.40715) and along the Padang - Solok road, West
Sumatra (-1.03290, 100.68198). These areas were also
predicted as highly suitable habitats outside protected
areas. Voucher specimens were deposited in Herbarium
ANDA (ANDA38871- ANDA38879).
Discussion
Prior to this study, little was known about the potential
distribution of the endangered tree species C. argentea and
C. tungurrut in Sumatra, Indonesia, and how much of this
was represented in the protected area network. Using a
modelling approach, we used herbarium and field records
to predict the distribution of both species and overlaid this
with a map of protected areas. We also gained insight into
the environmental variables which are most important in
determining the distribution of the species. This approach
allowed us to understand better future threats to the species
from land use change.
Our model suggested C. argentea and C. tungurrut are
strongly influenced by elevation (Table 1). Previous studies
(Pielou 1979; Adhikari et al. 2012; Chunco et al. 2013; Yi
et al. 2016; Kamyo and Asanok 2020) have reported a
significant relationship between elevation and plant
distribution. Environmental characteristics are very
important for determining potential species distributions,
and analyzing the various environmental factors related to a
habitat. It is also essential to discover the potential presence
of a species in their habitat and to recognize basic
ecological knowledge of the species (Koo et al. 2019). The
limitation of this study is MaxEnt model only predicts
species distribution by analyzing the relationship between
species and selected environmental variables using
presence data. The model suggests the presence of species
in areas with suitable environmental conditions (Li et al.
2020). Besides the environmental variables, the
distributions of the species are also affected by biotic
factors, speciation mechanisms, and dispersal ability (Kaky
et al. 2020). However, despite model limitations, MaxEnt
can determine habitat use and species distribution across
many different taxa and localities generated from
incomplete data.
Our field surveys revealed C. argentea and C. tungurrut
are closely distributed with C. rhamnifolia (Figure 6).
Based on recorded occurrences, C. argentea population is
relatively small in size compared to C. tungurrut.
Whitmore (1972) and Laumonier (1997) reported these
taxa as important components from lowland to high
montane forest. Our model confirmed that the altitudinal
characteristics of the plant is consistent with Fujii et al.
(2006) who conducted topographic census of Fagaceae in
West Sumatra. The study reported distribution of C.
argentea at altitudinal range of 1200-1800 m and C.
tungurrut at 1400-1800 m but also in the lowlands at about
400 m (Fujii et al. 2006). Our field surveys in two areas
with a high probability of occurrence indicated that both of
these species could be available in 2000 m asl at Gunung
Tujuh, Indonesia (Kerinci Seblat National Park). Similar to
HARAPAN et al. Castanopsis argentea and Castanopsis tungurrut in Sumatra, Indonesia
1731
the predictions of the model, Laumonier (1997) recorded C.
argentea in upper montane forest about 2300 m in West
Sumatra, Indonesia. It is indicated these endangered
species occur at high altitudes in montane forest, however,
according to IUCN (Barstow and Kartawinata 2018a,b), C.
tungurrut has distributional range up to 1920 m and 150-
1400 m for C. argentea, while those reports also suggest
that both species are almost extinct in lowland areas due to
conversion of their native habitat to palm oil plantation.
Although in this study we could still find these species in
montane area.
The highest deforestation activity occurred in lowland
area. For example, Riau contributed 46% of total Sumatran
forest degradation between 1990 to 2010, and remaining
primary forest is located in upland mostly in Aceh (40%)
followed by West Sumatra (15%) and Bengkulu (12%)
(Margono et al. 2012). A study by Dwiyahreni et al. (2021)
showed in 2012 and 2017 Tesso Nilo National Park lost
47% of total forest cover while Kerinci Seblat National
Park only lost 1.96%. However, the upland in Sumatra is
not completely safe from forest cover loss. The road
constructions also play important role in driving
deforestation. The Trans-Sumatra road development would
pass several important ecosystems like northern boundary
of Kerinci Seblat National Park and northeast flank of
Gunung Leuser National Park. These protected areas are
expected to be negatively impacted by road development
(Sloan et al. 2019).
The first step for the conservation is to understand the
relationship between the geographical distribution of taxa
and the environmental conditions. Then, we need to assess
the predicted distribution areas for collecting the current
population data (Mir et al. 2020; Kaky et al. 2020). The
predicted areas from MaxEnt can be applied easily to help
identify important suitability areas specifically in Sumatra
where conservation efforts need to be executed at broad
scale. Our field survey into two predicted areas
successfully confirmed the model is fairly accurate. The
promising areas with a presence probability greater than
80% would be a base for a quantifiable assessment (Figure
4). This assessment can help the protection and restoration
efforts for the endangered plants to be more scientific and
cost-effective (Gillenwater et al. 2006). The spatial
distribution model has directed us to understand better the
potential habitat of both the Castanopsis species studied.
The suitable area must be protected for reforestation and a
future reintroduction to reserve the associated habitat. The
predicted geographical map can analyze tree distribution
data, potential habitat, and disturbance risks (Kamyo and
Asanok 2020).
We propose combining the ex-situ conservation with
reintroduction to multiply the individuals before their
release to the natural habitat. The botanical garden would
be a proper place for ex-situ conservation (Widyatmoko
2019). North Sumatra and West Sumatra have the highest
value for suitable habitat for establishing an ex-situ
conservation strategy. There are four botanical gardens in
Sumatra, Solok Botanical Garden, Samosir Botanical
Garden, Sriwijaya Botanical Garden and Bukit Sari
Botanical Garden. Solok Botanical Garden was found to be
located in suitable areas for these endangered plants, giving
us the benefit of focusing on the growing population in the
natural region. The botanical garden with suitable
environmental conditions can use its financial resources
and limited land more efficiently (Volis 2017). Solok
botanical garden can focus on conservation of living
collection Castanopsis. Eco-regional climatic conditions
are important for living collection of plant species.
However, it’s ineffective in creating a living collection if
these conditions are expected to become unsuitable. After
identifying current suitable habitat, future work can be
conducted with MaxEnt to identify the areas where the
habitat remains suitable over time, e.g., year 2080 (Volis
2017). Therefore, all stakeholder groups need to develop
protocols to equally and fairly share species and habitat
management costs. Practically, the majority of actions will
be governed by national policies. Hence, all management
actions should be developed and implemented in
association with appropriate monitoring programs where
possible, which may be strategically the best way to
increase their number of occurrences and reverse trend of
their declining populations.
ACKNOWLEDGEMENTS
This work was partly supported by Institute for
Research and Community Service (LPPM), Universitas
Andalas. We thank IdeaWild grant id (HARAINDO0320)
for computer support in this study. We thank reviewers for
their efforts towards improving our manuscript. We are
grateful to Erizal Mukhtar, Wilson Novarino, Tesri
Maideliza, Heru Handika, Kyle W Tomlinson and Mark
Hughes for valuable comments on the manuscript draft. We
thank Kuswata Kartawinata for the detail of IUCN data
support of these endangered plant species. We also thank
Rezi Rahmi Amolia and Ardea Musfar for helping with
plant specimens and occurrences collection.
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... According to Harapan et al. (2022), for endangered taxa, field surveys in areas with a probability ≥80% have a high potential for locating the targeted taxa. This suggests that areas with high probability predictions in the model are indeed likely to be suitable habitats for the species in question. ...
... The MaxEnt model demonstrates good performance in predicting the potential distribution of C. sumatrana. An AUC value between 0.90 and 0.95 indicates a good model, while values between 0.95 and 1.00 suggest excellence, reflecting a close approximation to real-world conditions (Harapan et al. 2022). The IUCN assessment indicates that C. sumatrana is facing habitat decline due to human activities and is likely to be classified as endangered in the future (Nurainas and Ardiyani 2019). ...
... Our model shows that soil and precipitation significantly limits the distribution of C. sumatrana. Soil properties, in particular, have been shown to influence the habitat suitability of endangered species (Harapan et al. 2022). Previous studies on various taxa have indicated that precipitation is a more crucial factor for plant distribution than temperature (Song et al. 2016;Chen et al. 2017;He et al. 2021;Harapan et al. 2022;Mkala et al. 2023;Shi et al. 2024;Solfiyeni et al. 2024;Song et al. 2024;. ...
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Syafira F, Nurainas, Syamsuardi. 2024. New record and potential spatial distribution of Curcuma sumatrana (Zingiberaceae): An endemic wild turmeric in Sumatra, Indonesia. Biodiversitas 25: 4127-4138. Curcuma sumatrana Miq. is a Sumatran turmeric species with medicinal potential. However, it remains underutilized and is classified as vulnerable by the IUCN. Its vulnerability is aggravated by limited knowledge of its distribution, a need for more data on habitat preferences, and habitat degradation. Field observations revealed significant morphological variations among populations, likely influenced by environmental factors. This study assessed the morphology, microhabitat preferences, and spatial distribution of C. sumatrana in West Sumatra, Indonesia. Surveys and laboratory observations highlighted morphological traits, such as leaf and ligule length and width, significantly contribute to these observed variations. Notably, the leaf shape differed between open and shaded areas, being narrowly elliptic in open areas and broadly elliptic in shaded areas. Populations in Koto Malintang and Lubuk Minturun showed distinct differences, separated by six morphological traits. The C. sumatrana prefers habitats with fertile soils, moderate plant diversity, and open land cover, often coexisting with species like Dendrocnide stimulans (L.fil.) Chew, Macaranga tanarius (L.) Müll.Arg., and Diplazium sp. Maximum Entropy modeling (AUC 0.944) predicted a highly suitable habitat of 918 hectares in the western Bukit Barisan range. The model suggests distribution is influenced by soil type and precipitation patterns during the seasonal, warmest, and coldest quarters, as well as land cover. New records from West Sumatra extend the species' known range, reaffirming its vulnerable status with a potential risk of becoming endangered.
... This can help gain insights into broader ecological processes, potentially improving conservation efforts for C. tungurrut and other related plant species in the park. Harapan et al. (2022) claimed that the most important variables for predicting the distribution of C. tungurrut are elevation, temperature seasonality, and precipitation in the warmest quarter. This species' distribution has been limited to an altitudinal range of 1400-1800 m asl in Sumatera and 1000-1800 m asl in Java, and it is mostly absent at lower elevations due to human activities, including agriculture and settlement (Simbolon, 2001;Harapan et al., 2022). ...
... Harapan et al. (2022) claimed that the most important variables for predicting the distribution of C. tungurrut are elevation, temperature seasonality, and precipitation in the warmest quarter. This species' distribution has been limited to an altitudinal range of 1400-1800 m asl in Sumatera and 1000-1800 m asl in Java, and it is mostly absent at lower elevations due to human activities, including agriculture and settlement (Simbolon, 2001;Harapan et al., 2022). ...
... According to Körner et al. (2016), plants have well-defined threshold responses to temperature, which reveal unique abnormalities in cell function within a constrained temperature range, affecting the plant's survival, growth, and ability to regenerate. The result that temperature is the dominant climatic driver of C. tungurrut distribution conforms to the findings of previous studies by Harapan et al. (2022), Fathia et al. (2019), Kusmana and Suwandhi (2019), Santhyami et al. (2021), and Wibowo (2006). They revealed that temperature and altitude were the dominant factors influencing the distribution of C. tungurrut in Sumatera, while in West Java, including Mount Galunggung, Pakenjeng Garut and Mount Gede Pangrango, the altitude in the submontane zone (1000-1400 m asl) and slopes > 40% were observed to be the limiting environmental factors for the distribution of C. tungurrut. ...
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Castanopsis tungurrut (Blume) A. DC. (Fagaceae) is an Indonesian native plant species with limited spatial distribution; it is found only in Java, Kalimantan, and Sumatera in lower montane to submontane forests. This species has been classified as endangered by the IUCN, necessitating collection of more information on its habitat and environmental preferences before embarking on conservation planning. Studies on the species' natural habitat are scarce. This study aims to identify the environmental factors (edaphic + climatic factors) influencing the distribution of C. tungurrut along an altitudinal gradient in the Cibodas Biosphere Reserve. The nested plot method was applied to assess the forest vegetation at an altitudinal range of ca. 750-1800 m asl. Environmental factors were measured using portable equipment and through laboratory analysis. Ordination technique using canonical correspondence analysis (CCA) was utilised to pinpoint the environmental factors influencing the species' distribution based on basal area. CCA showed temperature to be the most limiting factor affecting the distribution. Edaphic factors-cation exchange capacity, content of carbon, nitrogen, phosphorus, and potassium, and soil pH-had less influence. Thus, it can be inferred that dependence of C. tungurrut on temperature determines its distribution pattern in its natural habitat, like Ostodes paniculata and Sloanea sigun. In contrast, the distribution of Castanopsis javanica, Castanopsis argentea, Schima wallichii, Altingia excelsa, Dacrycarpus imbricatus, Cestrum aurantiacum, and Castanopsis acuminatissima was found to be more influenced by edaphic factors than by climatic factors.
... The first step in conservation is to understand the relationship between the geographic distribution of taxa and environmental conditions. And this assessment can help conserve and restore endangered plants more scientifically and cost-effectively (Harapan et al., 2022). In this study, the contribution of environmental variables to the geographic distribution was determined by percent contribution and permutation importance. ...
... Bio01 value in SSP126 and SSP585 and box plots of bio01 change within CPD. The first step in conservation is to understand the relationship between the geographical distribution of taxa and environmental conditions (Harapan et al., 2022). The results show that precipitation (bio15) and temperature (bio01 and bio03) are the main factors limiting the distribution of G. manshurica. ...
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... A comprehensive understanding of the species, along with further surveys and spatial distribution analysis, is crucial for protecting against potential extinction. Future strategies must focus on the long-term survival of the species through ex situ conservation in suitable habitats combined with in situ conservation efforts (Volis and Blecher 2010;Harapan et al. 2022). ...
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A new species of stone oak, Lithocarpus tapanuliensis Harapan, W.H.Tan, Nurainas & Strijk from South Tapanuli, North Sumatra, Indonesia is described. We provide colour photographs, a distribution map and a new IUCN conservation status assessment for inclusion on the global Red List. The unique cupule morphology, particularly the shape, placement and distinctness of the cupule protuberances, are distinctive from other Lithocarpus species in the region. Ecological interactions (e.g. consumption and nesting) with Tapanuli orangutans were recorded in the field.
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Cunninghamia konishii Hayata is a rare and endangered plant species that plays a relevant role in ecological and commercial systems of natural forests in Vietnam. In this research, we evaluated the potential geographic distribution of C. konishii under current and future climatic conditions in Northern Vietnam using the ecological niche modelling approach based on the largest available database of occurrence records for this species. C. konishii is mainly distributed in the northern part of Vietnam at altitudes above 1000 m where the slopes range between 12 and 25 degrees, particularly in special-use and protected forest. The optimal distribution area of C. konishii requires specific climatic conditions: an annual precipitation around 1200 mm, precipitation of the warmest quarter ranging from 600 to 800 mm, a precipitation seasonality of 90 to100 mm, an annual mean temperature ranging from 12°C to 19°C, and a temperature seasonality ranging from 300 to 350. Additionally, the species requires specific soil groups: humic acrisols, ferralic acrisols, and yellow-red humic soils. Considering these requirements, the results of our research show that the suitable regions for the growth of C. konishii are found in the provinces of Ha Giang, Son La, Thanh Hoa and Nghe An, covering a total area of 1509.56 km2. However, analyzing the results under the Community Climate System Model version 4 (CCSM4) model, it is possible to observe that the area will decline to 504.39 km2 by 2090 according to RCP 2.6 scenario, to 406.25 km2 in the RCP 4.5 scenario, and to 47.62 km2 in the RCP 8.5 scenario. The findings of this present research may be applied to several additional studies such as identifying current and future locations to establish conservation areas for C. konishii.
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Pradhan P, Setyawan AD. 2021. Filtering multi-collinear predictor variables from multi-resolution rasters of WorldClim 2.1 for Ecological Niche Modeling in Indonesian context. Asian J For 5: 111-122. WorldClim is one of the popular environmental datasets which hosts multi-resolution interpolated gridded climate raster surfaces and derived bioclimatic variables for both the immediate past, present and future scenarios. Bioclimatic variables along with other environmental factors like solar radiation, wind speed, water vapour pressure etc. have been used as primary set of explanatory variables for mapping and spatial modeling of many biological processes, including defining environmental niche of a species and identifying potential areas for its distribution through machine learning methods like Ecological Niche Modeling or Species Distribution Modeling or Habitat Suitability Modeling. However, the interpolated explanatory datasets are known to cause over-fitting of the models mainly due to multi-collinearity or redundancy within the variables. In the present study, 58 bioclimatic and environmental variables of Indonesian extent extracted from WorldClim 2.1 are screened to investigate the presence of multi-collinearity or redundancy. From the total 3364 variable pairs per raster resolution, 174 variable pairs were known to be affected by multicollinearity, from which temperature related bioclimatic variables, water vapour pressure and elevation associated variables were highly notable. For all the raster resolutions, bioclimatic variable 2, 3, 4, 15, 18 and 19, as well as slope, aspect, solar radiation be non-collinear for 30s, 2.5m and 5m raster resolutions; Wind speed of July was non-collinear for 30s and 2.5m; Solar radiation for February and June were non-collinear for 10m; water vapour pressure for August for 2.5m and wind speed for January was non-collinear for 30s raster resolutions. The results of this study might serve as a convenient reference for investigators of the region for selection of bioclimatic and other environmental variables for conducting ecological niche modeling studies.
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Houttuynia cordata Thunb is an important medicinal and edible plant widely distributed in East Asia. To understand the potential distribution characteristics of H. cordata and its response to future climatic change, the Maxent model is used to simulate potential distribution under current climatic condition, and predict changes in its distribution under three different future climate scenarios, and analyze the dominant factors affecting its distribution. The results showed that the suitable habitat area of H. cordata at present is 177.45 × 10⁴ km², among which the high suitable area is 26.66 × 10⁴ km², mainly distributed in Guizhou, eastern Sichuan, northwest Guangxi and Chongqing, west Hunan and southeast Hubei. The current distribution of H. cordata is mainly affected by the annual precipitation (bio12, 57.4% contribution rate), min. Temperature of coldest month (bio6, 26% contribution rate) and standard deviation of temperature seasonality (bio4, 6.1% contribution rate), and its total contribution rate is 89.5%. The suitable regional area of H. cordata showed an increasing trend under three climate change scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) in both the 2050s and 2070s, and its suitable distribution area extended to the north as a whole. The simulation results are helpful to understand the geoecological characteristics of H. cordata, and provide a basis for the regional prediction of this species under current and future climate change scenarios in China.
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Rare and endangered plants (REPs) act as key indicators for species habitat priorities, and can thus be critical in global biodiversity protection work. Human activities and climate change pose great threats to REPs, so protection should be a top priority. In this study, we used the maximum entropy model (Maxent) to identify current and future (2050) potential habitats of REPs in the Xishuangbanna tropical area of China. We compared potential habitats with existing protected areas (PAs) in gap analysis, and used a transfer matrix to quantify changes in potential habitats. By comparing the potential distribution obtained with existing land use and land cover, we analyzed the impact of human-dominated land use changes on potential habitats of REPs and identified the main habitat patch types of REPs. The results showed that the current potential habitat area of hotspots is 2989.85 km², which will be reduced to 247.93 km² by 2050, accounting for 15.60% and 1.29% of the total research area, respectively. Analysis of land use and land cover showed that rubber plantation was the human-dominated land use posing the greatest threat to potential habitats of REPs, occupying 23.40% and 21.62% of current and future potential habitats, respectively. Monsoon evergreen broad-leaved forest was identified as the main habitat patch type for REPs in Xishuangbanna and occupied the highest proportion of potential habitat area. Gap analysis showed that only 35.85% of habitat hotspots are currently included in existing PAs and that this will decrease to 32.26% by 2050. This emphasizes the importance of protecting current and future potential habitats of REPs in a dynamic conservation approach that can adapt to changes in future climate and human activities.
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Climate change has emerged as the main threat to global biodiversity and even the protected areas (PAs) are not immune to this problem. Here, we have focused on PAs with the aim of assessing the impacts of climate change on their habitat suitability and their effectiveness to protect threatened species, in this case three endemic Spanish plants: Isatis platyloba, Rhaponticum exaltatum and Succisella microcephala. We used the machine-learning technique called Maxent that is able to protect the potential species distribution under four future climate scenarios. Our results show a strong reduction of the potential areas with high suitability for Isatis platyloba. By contrast, for Rhaponticum exaltatum and Succisella microcephala our results suggested an increase of potential habitats. Regarding to the PAs specially designed to protect some important populations of these species, most of them would be located in areas with high suitability for all species in the future. Our study supports the necessity of the proposed Plant Micro-reserves to guarantee the preservation of these three species and, most importantly, can serve as a model to evaluate the efficiency of a given PA in protecting any species taking into account the climate change scenario. Supplemental data for this article is available online at https://doi.org/10.1080/11263504.2021.1918777.