Geographical analysis of the Javan deer distribution in Indonesia and priorities for landscape conservation

Journal Pre-proof Geographical analysis of the Javan deer distribution in Indonesia and priorities for landscape conservation Dede Aulia Rahman, Aryo Adhi Condro, Puji Rianti, Burhanuddin ´ Masy’ud, Stephane Aulagnier, Gono Semiadi

PII:

S1617-1381(19)30329-2

DOI:

https://doi.org/10.1016/j.jnc.2020.125795

Reference:

JNC 125795

To appear in:

Journal for Nature Conservation

Received Date:

11 September 2019

Revised Date:

18 December 2019

Accepted Date:

10 January 2020

Please cite this article as: Rahman DA, Condro AA, Rianti P, Masy’ud B, Aulagnier S, Semiadi G, Geographical analysis of the Javan deer distribution in Indonesia and priorities for landscape conservation, Journal for Nature Conservation (2020), doi: https://doi.org/10.1016/j.jnc.2020.125795

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Geographical analysis of the Javan deer distribution in Indonesia and priorities for landscape conservation

Dede Aulia Rahman1,2*, Aryo Adhi Condro 2, Puji Rianti3*, Burhanuddin Masy’ud1,2, Stéphane Aulagnier4, Gono Semiadi5

Department of Forest Resources Conservation and Ecotourism, Faculty of Forestry, IPB

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University (Bogor Agricultural University), Kampus IPB Darmaga Bogor16680, Indonesia

Tropical Biodiversity Conservation Program, Department of Forest Resources Conservation and

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Ecotourism, Faculty of Forestry, IPB University (Bogor Agricultural University), Kampus

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IPBDarmaga Bogor 16680, Indonesia

Department of Biology, Faculty of Mathematics and Natural Sciences, IPB University (Bogor

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Agricultural University), Kampus IPB Darmaga Bogor 16680 Indonesia Comportement et Ecologie de la FauneSauvage, I.N.R.A.E, Université de Toulouse, CS 52627,

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31326 Castanet-Tolosan cedex, France

Research Centre for Biology, Zoology Division, The Indonesian Institute of Sciences, Cibinong

16911 Indonesia *

Corresponding author. Email: [email protected]. https://orcid.org/0000-0001-5405-

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5400 and Email: [email protected]

Abstract

Javan deer (Rusa timorensis) is a protected species in Indonesia and considered to be vulnerable under IUCN list. Nevertheless, its native geographic distribution remains unclear, and the impact

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of abiotic and biotic factors on this species are mostly unknown. We predicted the potential range of Javan deer in Java and Bali Islands using ten environmental variables, occurrence data of native (76 before 1965, and 653 after 1965) and introduced populations (559), and MaxEnt modelling. We evaluated the effects of habitat loss due to current land use, ecosystem availability, and importance of Indonesian protected areas into the models. Our predictive map significantly improved the IUCN assessment and described for the first time the spread of Javan deer out of its

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native range within Indonesia. The model of environmental suitability estimated a potential of

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3,784.43 km2 natural occurrence in Java and Bali and 36,352.61 km2 for introduced populations in protected areas of West Nusa Tenggara to Papua. The most critical environmental predictors for

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both populations are the mean annual precipitation and the conservation status of land. Then,

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45.66% of the distribution of native populations overlaps with protected areas, 18.96% with production forests, 11.07% with non-protected areas, 10.10% with limited production forests and

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4.20% with industrial oil palm plantations. Only 22.88% of the distribution of introduced populations overlaps with protected areas. Our study provides reliable information on places where

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conservation efforts must be prioritized, both inside and outside the protected area network, to safeguard one of the remaining Indonesian large deer. Keywords: Cervinae; conservation planning; distribution models; protected areas; Rusa

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timorensis; tropical deer

1. Introduction

Over the 53 species of Cervidae (Mattioli, 2011), nine have been reported from Indonesia.

One of the species, Javan deer (Rusa timorensis de Blainville, 1822), is known to be evolutionarily distinct from its closest relative sambar deer (Rusa unicolor Whitehead 1993), in Indonesia (Pitra

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et al., 2004; Gilbert et al., 2006) and possibly native only in Java and Bali (Corbet and Hill, 1992; Grubb, 2005; Hedges et al., 2015; Martins et al., 2018). The Javan deer was introduced historically in several Indonesian islands since the late Holocene (Simons and Bulbeck, 2004) and recently in New Guinea, Australia, New Zealand, New Caledonia, Mauritius, and several other areas (Mattioli, 2011). It is a highly flexible tropical grassland species, with thriving populations inhabit areas ranging from marshes at sea level to mountains up to 900 m (Whitehead, 1993; Rouys and

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Theuerkauf, 2003; Keith and Pellow, 2005). Javan deer was classified as Vulnerable in the IUCN

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Red List owing to its native wild population which are patchily distributed in a small geographical range (Hedges et al., 2015). However, the status of this species is contradictive. It is common in

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most of the countries where it was introduced, such as Mauritius (>60,000 animals) or New

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Caledonia (>100,000 animals). Conversely, native populations in Java and Bali (<10,000 animals) decreased substantially during the last few decades as the result of poaching, habitat degradation,

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and spread of invasive plant species (Hedges et al., 2015). The Indonesian law has now protected this species (Indonesian Ministry of Environment and Forestry, 2018).

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Javan deer is a crucial species for conservation purpose. Apart from its important role as economic resources in Indonesia and introduction areas (Woodford and Dunning, 1992; Le Bel et al., 1997; De Garine-Wichatitsky et al., 2004; Takandjandji et al., 2011; Santoso et al., 2012), it is also the main prey for large predators in Java and a major seed disperser (Meijaard and Groves,

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2004; Rahman et al., 2018). Despite this economic and ecological importance, the distribution of the Javan deer, either in its native range or as introduced species, remains poorly known and its potential response to environmental changes has not been evaluated in Indonesia. Such knowledge would have implications for conservation of the species at national and international levels (De Grammont and Cuarón, 2006; Mota-Vargas and Rojas-Boto, 2012). Moreover, the dramatic

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decline of natural forests in Indonesia, which started at the end of the 18thcentury and amplified since the middle of the 20th century with concessions of industrial oil palm plantations and production forests directly affected the Javan deer populations. For Indonesia, the year 1965 was a breach with an economic development strategy through the large scale development of agriculture, livestock breeding, forestry and settlement, which led to land cover changes, particularly in Java Island. Afterward, recent evolution of the species distribution can be mainly

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related to anthropogenic changes of environmental conditions.

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Classical analyses of species distribution are highly dependent on presence records, but in many cases, this information is scarce, especially when species lives in remote areas. Even when

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an adequate number of records is available, such records are potentially biased due to different

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accessibility of sites or differences in collection methodologies (Peterson et al., 1998). Mapping the occurrence of a species is complex as it involves many determinants, including both intrinsic

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(dispersal capability and adaptability to future conditions) and external (abiotic and biotic conditions) factors, which can be difficult to assess (Soberón and Peterson, 2005; Rahman et al.,

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2017). In recent years, several reliable methods have been developed to predict distribution areas by correlating presence records and environmental variables. So, more than one hundred papers are published every year (e.g. Qin et al., 2017; Rahman et al., 2017; 2018), improving our knowledge of species ranges and responses to present and future threats (e.g. Gibson et al., 2010;

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Qin et al., 2017).

Here we present an update of the Javan deer distribution in Indonesia using all available

records and ten environmental variables (abiotic, biotic and anthropogenic factors) to predict its potential past and present range over the country. We used MaxEnt to model distributions and classify the landscape suitability for the Javan deer, hypothesizing that predictors changed over

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time. We also considered the extent of protected areas and the three main managed forest type areas hypothesizing that the distribution of both native and introduced populations relies on natural forests. At last, we used the modelled distributions to support conservation issues.

2. Methods 2.1. Collection of records

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We compiled all Javan deer records in Indonesia, dating from 1894 to June 2019 from the

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following sources: 1) Global Biodiversity Information Facility database (GBIF; www.gbif.org) and Mammal Networked Information System (MaNIS, www.manisnet.org), 2) The deer Specialist

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Group (IUCN/SSC DSG-Indonesia available under request at www.iucnredlist.org/users/sign_in),

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3) fieldwork and monitoring projects report in Indonesia, 4) all scientific and reliable grey publications, and 5) specimens deposited in Museum Zoologicum Bogoriense, Research Centre

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for Biology. We used “Javan deer”, “Rusa Timor”, “Rusa timorensis” and “Cervus timorensis” as the keywords to surf online databases, such as the National Library of Indonesia, Indonesia

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Biodiversity Information (inabif.lipi.go.id), Google, Google Scholar (https://scholar.google.com/) and Biodiversity Heritage Library (http://www.biodiversitylibrary.org/). Each locality was geopositioned (latitude-longitude coordinates) in decimal degrees based on the WGS 1984 datum into Google Earth and MapLink (http://www.maplink.com/) to correct the geographic coordinates of

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imprecise recorded localities and to eliminate inconsistencies or duplicates. We applied a buffer area between points, based on the larger home range known for the species [(~5.01 km2 (4.98±0.5 km2); Spaggiari and De Garine-Wichatitsky, 2006)], to limit the spatial bias due to local high number of records. These presence data were divided into categories of native and introduced populations based on the IUCN Red List assessment (Hedges et al., 2015).

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Filters are essential for further analysis, because historical records may contain potential errors or uncertainties. Therefore, records of the species’ datasets without any additional information, including relevant or detailed description, were excluded from the analysis. In total, we used 1,364 filtered historical records (Appendix 1) and mapped the distribution of Javan deer within a 100 km2 rectangle (Appendix 2). Economic development strategy in Indonesia was carried out from 1965 through the

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development of agriculture, livestock breeding, forestry and settlement on a large scale which led

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to land cover changes, particularly in Java Island. Therefore, we divided the database in two parts: before 1965 and after 1965. The analysis of the potential distribution of the native population was

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then performed using an Ecological Niche Modelling based upon the Maximum Entropy algorithm

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(Elith et al., 2006) with only the records before 1965 (1965 model, n = 76) and with all records (All model, n = 729). We also used all occurrences of introduced Javan deer populations (n = 559)

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2.2. Environmental descriptors

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to perform a third model.

We used 15 environmental variables used in previous studies and identified four groups (Appendix 3). We considered elevation, slope (Carvalho et al., 2012), and distance to the nearest river (Traill and Bigalke, 2006) as physical (abiotic) variable group. Distances to the nearest forest

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edge from inside and outside (Norris et al., 2008; Ruzicka et al., 2010; García-Marmolejo et al., 2015) protected area (Kays et al., 2017) and vegetation productivity measured by NDVI (Pettorelli et al., 2006) were the resource (biotic) group. We evaluated anthropogenic disturbance group with the distance to the nearest road (Carvalho et al., 2012) and land use classification (Carvalho et al., 2012; García-Marmolejo et al., 2013; Quevedo et al., 2017). At last, the climatic variable group

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included annual mean rainfall, rainfall of the wettest month, rainfall of the driest month, annual mean temperature, maximum temperature of the warmest month, and minimum temperature of the coldest month (Hu and Jiang, 2011). Those data were obtained from different data sets: United State Geological Survey (2019) for the elevation map (30 m resolution) and the slope, Open Street Map (2019) for rivers and roads, and the Indonesian maps of land use and protected areas (Ministry of Environment and Forestry, 2011). We retrieved NDVI data from Landsat 8 imageries of 2015

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to represent the current conditions of vegetation. Cloud-masking, radio metrical corrections, and

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filter statistics (i.e. median) were performed in data pre-processing of NDVI. Google Earth Engine Platform was used for NDVI data retrieval. Generally, we used NDVI for all land cover types,

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since NDVI values has unique characteristics of each land cover classes. For the analysis, we only

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used current periods of data for NDVI and perform filter statistics using median to select pixel of the data. Climate Prediction Center (CPC) monthly global surface air temperature dataset for 1948-

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1965 and 1965-2018 periods were used to represent historical and recent data, respectively (Fan and van den Dool, 2008). We used VASClimO global gridded dataset of observed station

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precipitation for rainfall in the 1951-1965 period (Beck et al., 2005) and CHIRPS precipitation data for the recent period (Funk et al., 2014). We converted the protected area layer into a binary raster containing '0' (non-protected area) and '1' (protected area). We used 19 classes of the 2017 land use classification layer retrieved from Ministry of

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Environment and Forestry. We performed hindcast analysis using cellular automata with MOLUSCLE module in Quantum GIS 2.18 to produce the historical land cover from 1894 to 1965 (Laurence et al., 2009; Gismondi et al., 2014). The forest polygons were selected from the land use classification to generate Euclidian distances between the forest edge and the Javan deer sightings. Sightings inside the forest were assigned a value of '0' for the distance to the nearest

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edge from outside and vice versa for the distance to the nearest forest edge from inside. We also generated the distance to the nearest road and river (30 m resolution) layers using Euclidian distances. The primary analysis tool required all datasets to have exactly overlapping cells and spatial extent (Young et al., 2011). Therefore, we restricted this study to the islands of Java and Bali for native populations and other Indonesian islands for introduced populations. We delivered a raster

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mask of 0.25 km2 cell size, which covered the study areas to set a baseline environment for further

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re-sampling process of the background layers. We then re-sampled the Javan deer locations and all environmental variables with the application of a mask layer. This procedure removed any

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duplication of Javan deer locations within a cell for subsequent analysis. Due to various resolution

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of environmental variables, we re-sampled all of the data to a coarser resolution (500 m), and performed a bilinear interpolation technique to assign a new value to a cell by using a weighted

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distance average of four adjacent input cells for continuous variables. We also used nearest neighbour algorithm to resample for the categorical data (e.g. land cover). All spatial processes

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were performed using Raster Processing and Spatial Analyst tools in the ArcGIS 10.5 software (ESRI, Redlands).

2.3. Data analysis

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2.3.1. Sampling bias

The Javan deer locations were found to be biased toward the sampled areas, a situation

common to presence-only datasets (Phillips et al., 2009). We altered the mask layer into a bias grid to control the sampling bias (Elith et al., 2010; Clements et al., 2012). The bias grid is used to down-weight the importance of presence records from areas with more intense sampling. In the

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analysis, we used the value of a cell (cα) in the bias grid to assign a higher weight to Javan deer points (cβ) with fewer spatial neighbors and vice versa. The value of cα was a sum of the distances between cα and cβ as analysed using the Gaussian Kernel function, w = exp(−d2/2s2), whereas w is the weight, d is the distance (in km) between cα and cβ, and s is the standard deviation. We used 2.53 km for s because it represents the known diameter of the largest Javan deer home range size (5.01 km2) (Spaggiari and De Garine-Wichatitsky, 2006). As it shows in the Gaussian distribution

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(s) yielded points that are, for example, located 2.53 km away from a cell as having 62.8% and

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5.06 km away from a cell as having 15.4% as a strong influence, respectively. Furthermore, we used the Distance Among Points tool of the Geospatial Modelling Environment version 0.7.3.0

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(Beyer, 2012) as well as the Calculate Variable and Aggregate tools (IBM SPSS verse. 20; I BM

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Corporation, 2011) to calculate the distance between cα and cβ and the Gaussian Kernel function,

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respectively.

2.3.2. Species distribution model and validation

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We modelled habitat suitability for Javan deer using MaxEnt version 3.4.1 (https://biodiversityinformatics.amnh.org). The program uses two data inputs: the localities (presence-only data) where the species has been recorded, and the digital layers of the environmental variables. We used a Pearson's correlation analysis with the Hmsc package (R

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Development Core Team, 2010) to define correlations among the 15 environmental variables, and removed variables when correlation was ≥ 0.70 (Rahman et al., 2017). The final set of uncorrelated environmental variables used in the subsequent analysis included elevation, distance to the nearest river, distance to the nearest forest edge from inside and from outside, protected area, NDVI,

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distance to the nearest road, land use classification, annual mean rainfall, and annual mean temperature (Appendix 4). We set protected area, NDVI, and land use classification as categorical variables. We used a Bootstrap procedure with 25% random tests, 50 replicates, and 5,000 iterations with coverage threshold 10-5 and using all other parameters in MaxEnt at default settings. We also performed Jackknife tests to assess consistency in variable importance between the training and test gains

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(Phillips, 2008). The area measured accuracy assessment for the overall model under the curve

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(AUC; the area under the ROC curve) of the receiver operating characteristic (ROC) curve (Phillips et al., 2006) with a value of 0.5 representing a random model, while values between 0.8

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and 0.9 representing models with a good fit and values over 0.9 being an excellent fit (Manel et

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al., 2001). We estimated the relative importance of each predictor to the MaxEnt model using the relative contribution and permutation importance, averaged over 50 replicates (Rahman et al.,

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the MaxEnt prediction.

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2017). We investigated the response curves to explore how the environmental predictors affected

2.3.3. Conservation and threat issues

Suitable landscapes of the Javan deer were predicted using ten-percentile training presence logistic threshold, pixels with logistic probabilities that were smaller than the threshold were

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discarded (Young et al., 2011). We converted the predicted suitable patch raster into a polygon format and defined the minimum suitable patch size for Javan deer as being large enough to contain at least five mature individuals (Santosa et al., 2008; Pairah et al., 2015); that is five times the most extensive known home range or 25.05 km2 (Spaggiari and De Garine-Wichatitsky, 2006; Pairah et al., 2015). However smaller suitable patches could be sufficient if connectivity between these

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patches is good. Therefore, we also considered suitable patches with and/or close to Javan deer localities up to 2.53km away, the diameter of the home range. We assumed that all protected areas, either national parks, nature reserves, wildlife sanctuaries, hunting parks, nature recreational parks, and pristine reserves, which at least partially overlapping with the predicted suitable patches, are necessary for Javan deer. We updated these patches with protected areas using the Update tool of the ArcGIS 10.5. This tool removed all stand-

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alone protected areas and combined them with associated suitable patches into one single polygon.

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Then, we analysed in each protected area, the identified suitable patches as an indicator of the ecological importance area to support Javan deer. Historical information of protected areas before

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1965 (Yudhistira, 2014) was used to develop a historical map of protected areas in Java and Bali.

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At last, we determined how much of the Javan deer distribution overlaps with concessions of industrial oil palm plantations and production forests and limited production forests for native

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populations after 1965’s, concessions of industrial oil palm plantations and logging concessions and timber plantation concessions for introduced populations.

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We acquired spatial vector data of industrial oil palm plantations (IOPP) from Forest Watch Indonesia, which gather the data from several sources: spatial planning agency, plantation agency, national land agency, WWF-Indonesia, SarVision Indonesia, and provincial government. Whilst spatial vector data of production forests (PF) and limited production forests (LPF)

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and logging concessions and industrial timber plantation (ITP) concessions were acquired from the Ministry of Environment and Forestry, Indonesia. Then, we performed the intersection between suitable landscapes for Javan deer with each of these plantation and/or concession areas.

3. Results

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3.1. Distribution models All model fits as measured by the mean area under the curve (AUC) of the receiver operating characteristics (ROC) were upper than 0.90, which is considered as ‘excellent’. Our result showed a well-performed species distribution model, with a mean AUC ± SE of 0.92 ± 0.02. The distribution of the native populations showed a 69.23% overlap with the IUCN range prediction and added four new areas (N° 4, 5, 6, 12; Fig. 1B), with confirmed evidence of Javan

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deer. It also revealed that native populations occur in few high fragmented areas, which are more

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isolated currently than historically (Fig. 1A). Several past locations were deserted (N° 2, 6, 7; Fig. 1A), and range contractions were obvious where forest cover changed. The modelled distribution

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covered 12.84% of Java and Bali islands (Table 1) including four main areas: a) the western and

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central region of West Java (N° 1 to 4); b) the western and central region of Central Java (N° 5, 6, 7); c) East Java (N° 8 to 13); and d) the western part of Bali (N° 14). Introduced populations were

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spread over most of the Indonesian islands, covering 11.21% of the landmass (Fig. 1C; Table 1). The three highest contributions to all models were for the variables ‘protected area’,

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followed by ‘annual mean rainfall’, and ‘distance to the nearest forest edge from outside’ (Table 2). The jackknife procedure (Fig. 2) indicated that the ‘protected area’ variable contributed more than any other variable, except for the distribution of the native Javan deer populations before 1965 where annual mean rainfall gave the biggest contribution.

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The response curves indicated that Javan deer was more likely to occur in protected areas

and landscapes with lower annual mean rainfall (Appendix 5). Land use in protected areas was highly dominated by secondary forests, shrubs and primary forests are additional (Appendix 6.A).

3.2. Suitable landscape, protected areas and concessions

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With the analysis of a ten-percentile threshold, only model pixels with a logistic probability of minimum 0.45 were classified as being suitable for Javan deer. The area of suitable landscape was 16,972.89 km2 including 3,784.43 km2 (13.32%) in protected areas for native populations, and 139,654.22 km2 including 41,521.19 km2 (15.09%) in protected areas for introduced populations. More than half of the native (76.84%) and introduced (59.25%) Javan deer records occurred inside the protected area network, with evidence of deer in all the 21 protected areas (nine national parks,

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eight nature reserves, three wildlife sanctuaries, and one grand forest park) in Java and Bali.

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Introduced populations were recorded in 87 protected areas [(10 national parks, 24 nature reserves, 12 wildlife sanctuaries, 29 nature recreation parks, 3 grand forest parks, 5 hunting parks, 4 Nature

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Reserve Area (KSA)/Nature Conservation Areas (KPAs)] from West Nusa Tenggara to Papua

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(Appendix 6.B).

Apart from protected areas the native Javan deer distribution overlapped with PF

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concessions (18.96%), LPF concessions: (10.10%) and IOPP concessions (4.20%). The distribution of introduced populations overlapped with ITP concessions (19.74%), followed by

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IOPP concessions: (10.05%) and logging concessions (3.94%) (Table 1, Fig. 3).

4. Discussion

Our dataset, based on 729 occurrence records for native populations, updates the Javan

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deer distribution in Indonesia and improves the IUCN assessment (Hedges et al., 2015). However, this study has some limitations as our dataset was simply a presence-only dataset, and records were obtained from multiple sources which surveys might not standardized yet. MaxEnt analyses require unbiased samples independent of the distribution of the target species (Phillips, 2008). The high AUC value recorded in our results could be an artefact as it can be higher for species with

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small home range sizes relative to the study area (Phillips, 2008). Nevertheless, this potential sampling bias might have been overcome in our study by using a relatively large dataset from all habitat types across Java and Bali for native populations, and the rest of Indonesia for introduced populations.

4.1. Drivers of Javan deer distribution

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Our results gave the first spatial-explicit model for the native populations of Javan deer.

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The most important predictor variable for both present native and introduced populations was the protected status of land. Although this species proved to be highly flexible in several regions where

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it was introduced, native populations have decreased substantially over the last few decades as the

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result of poaching, habitat degradation (Hedges et al., 2015), and the decrease of food quality in grasslands under the pressures of alien plant species and overgrazing by livestock (Djufri, 2009).

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Therefore, together with Long (2003) and Hedges et al. (2015), we assume that human interference shapes the distribution of Javan deer. Furthermore, in our models the variable ‘protected area’ was

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overweighed by the ‘distance from forest edges to the exterior’ suggesting an increasing role of deforestation for timber production and plantations. Most deforestation and land function changing occurred over the Indonesian colonialism era, when the Dutch opened a large rubber and teak plantation across Indonesia’s natural forest. Only after the new order era arose (after the year 1965;

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20 years after Indonesian’s independent declaration), the new government established many protected forest statuses to the remaining natural habitat. The economic development strategy in Indonesia were carried out from 1965 through the development of agriculture, livestock breeding, forestry and settlement on a large scale which led to land cover changes, particularly in Java Island. However, the government's commitment to and public awareness of the importance of wildlife

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conservation have currently increased starting with the Suharto's New Order Government (19671998) adopting a science-based protected area policy made by the Dutch colonial government and expanding the designated area to nearly 10% of land areas in the form of nature reserves, wildlife reserves, and national parks (Jepson and Whittaker, 2002; Jepson et al., 2002). The distribution of native Javan deer is narrower than reported before 1965 but with larger suitable areas for Javan deer. We presume this discrepancy, both for native Javan deer population after 1965 and

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introduced populations, is related to the history of the establishment of protected areas in

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Indonesia. The first national parks (Gunung Leuser, Ujung Kulon, Gunung Gede Pangrango, Baluran, and Komodo), were established as late as 1980, followed by the declaration of Bogani

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Nani Wartabone and Manusela as National Park. Such protected areas are less prone to changes

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than other lands (e.g. logging concessions) and thus may provide more stable long-term habitat for Javan deer.

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In this study, we found that most of the recent Javan deer records were located within large forest protected areas which serve as refuges. We identified eight national parks in Java and Bali,

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which habitats could sustain native populations, i.e. Ujung Kulon (1,121.75 km2), Merbabu (59.24 km2), Merapi (67.28 km2), Alas Purwo (450.04 km2), Baluran (301.83 km2), Bromo Tengger Semeru (502.43 km2), Meru Betiri (537.58 km2), and Bali Barat (151.06 km2). Introduced population were distributed in more different types of protected areas, i.e. national parks, nature

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reserves, wildlife reserves, nature recreation parks, hunting parks, and grand forest parks. This network contributed 24% of the total suitable areas in West Nusa Tenggara to Papua. MaxEnt models also showed high contributions of mean annual rainfall to the presence of

Javan deer; a variable, which is even the most important for the before-1965 model. For native Javan deer populations, landscapes appeared more suitable in eastern Java than in western Java.

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Likewise, for the introduced Javan deer populations, drier regions such as West and East Nusa Tenggara were more likely suitable than in other parts of eastern Indonesia. Eastern Java, as well as West and East Nusa Tenggara, which were suitable for introduced populations, are characterized by a strongly seasonal, drier, colder climate (climate-data.org), and higher grassland productivity for deer diet (Mishra et al., 2010). Higher rainfall of western Java could influence Javan deer distribution through several indirect processes including leaching of soils, which could lead to less

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productive forests (Wich et al., 2011), and cloud cover that reduces solar radiation and primary

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productivity (Boisvenue and Running, 2006). Two long-term studies in western and eastern Java, showed different patterns of climate change. In western Java, when compared with previous years,

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the number of days with rainfall exceeding 50 and 100mm has shown a statistically significant

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increase over the 1961-2010 period (Siswanto et al., 2015). On the contrary, in eastern Java, there was a decrease of monthly and annual rainfall in the period of 1955-2005 (Aldrian and Djamil,

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2008). This pattern suggests that the distribution of Javan deer remained relatively unchanged

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before and after 1965, although it decreased in both eastern and western parts of Java Island.

4.2. Contribution of different land-use types to Javan deer conservation Understanding the most relevant landscape characteristics is vital for maintaining or increasing population size of large deer, which are threatened by extinction (Wäber et al., 2013;

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Hodder et al., 2014; Pan et al., 2014). Identifying suitable landscapes next to protected areas needs to be complemented by the involvement of key stakeholders advised by conservation managers. There has been no study comparing survival of Javan deer populations in protected areas and other land-use types, yet some general patterns can be inferred. This study confirmed the resilience of Javan deer outside primary forests with nearly half of the introduced Javan deer locations were

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reported outside both protected areas and unmanaged forests. Such ability of deer to spread in human-modified habitats (De Garine-Wichatitsky et al., 2004; Ministry of Environment and Forestry, 2017), was reported from New Caledonia (Chardonnet, 1988), and Australia (Cripps et al., 2019). Even for native populations, our study showed that 11.07% of the suitable landscape was mapped in production forests and secondary forests. Moreover, with less than 16% of primary forest occurring out of protected areas, the production and secondary forests should, therefore,

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play an essential role in providing refuges for the remaining Javan deer populations.

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Both native and introduced Indonesian populations of Javan deer were recorded in forest concessions, either IOPP, PF, LPF, logging, or ITP concessions. There were already some

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evidence indicating that forests concessions can play an essential role in the conservation of wild

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populations in tropical areas (Fimbel et al., 2001; Mayor et al., 2015). Forest concessions are effective for reducing disturbances and smallholder encroachments (Gaveau et al., 2013). They

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can also serve as corridors for facilitating dispersal between viable and otherwise non-viable deer populations. Then, some conservation managers now understand that forest concessions are an

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essential component for maintaining forest habitats while promoting economic development (Gaveau et al., 2013). However, concessions should engage proper management for Javan deer conservation. In addition, compared to protected areas, forest concessions are more vulnerable to

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changes in land-use including deforestation.

4.3. Threats and impacts 4.3.1. Native population We identified that 26% of the protected area network in Java and Bali provided suitable habitat for Javan deer. However, protected areas contributed nearly 46% of the suitable landscapes.

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Moreover, although protected areas suffered lower forest degradation and fewer incidences of poaching than outside, these areas have been and continue to be affected by illegal logging, encroachments and wildfires. So native deer populations are thought to have decreased in the recent years except in relatively well managed protected areas such as Ujung Kulon and Meru Betiri National Parks in Java (G. Semiadi pers.). Furthermore, it is difficult to assess the minimum viable population as no Population and Habitat Viability Assessment (PHVA) has been conducted

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so far. The successful reintroduction of Javan deer (3 males and 13 females in 1978-1982) on

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Panaitan Island of ca. 175 km2 (Ujung Kulon National Park) provides data of space requirements (Pairah et al., 2015). Thus, five suitable landscape patches (Leuwang Sancang, Nusa Kambangan

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Island, Karimunjawa Island, Kawah Ijen, and Saobi Island) are considered too small to support a

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viable population. Even in a metapopulation consisting of large high-density populations interconnected by considerable dispersal rates, genetic diversity can decrease and directly affect

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the fitness of individuals and increase the risk of extinction through demographic and genetic stochasticity (Vandewoestijne et al., 2008; Lino et al., 2018). Then, we guess that some populations

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living in small and isolated suitable habitats will not survive. On the other hand, some introduced Javan deer populations showed a higher genetic diversity (G. Semiadi pers. comm. 2014) and could be used as genetic sources to enrich native populations in the future.

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4.3.2. Introduced population

Introductions of non-native Javan deer population can be valuable but are also potentially

harmful for its biodiversity (Spaggiari and De Garine-Wichatitsky, 2006). In Indonesia deer species are suspected to cause disturbances, especially for endemic species such as anoa (Bubalus spp.), babiroussa (Babyrousa spp.), Sumba horse (Equus caballus), Macassar ebony (Diospyros

18

celebica), Begonia (Begonia aptera), etc. Moreover, Javan deer could be a reservoir for Trypanosoma evansi introduced in Papua New Guinea by transmigrants and livestock. Aside from threatening some species, Javan deer population may also potentially cause changes in plant communities (Moriarty, 2004; Keith and Pellow, 2005), interspecific competition with native fauna (e.g. Davis et al. 2008; Forsyth and Davis 2011), livestock (Dryden 2009), and hybridization with sambar deer (Rusa unicolor) (Martins et al., 2018). On the other hand, Javan deer plays an

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indirect role in preserving the local species when concentrating hunting instead of indigenous

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species (Pangau-Adam et al., 2012).

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5. Conclusions

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Javan deer’s remaining native populations are living in small and fragmented areas within a few national parks and inaccessible areas. The critical points are to reinforce the network of

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protected areas and to maintain habitat connectivity among populations and/or translocate individuals into small isolated populations to minimize the risks of inbreeding and loss of genetic

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diversity. A successful strategy for conserving wide-ranging large ungulates will be to rely on the protection of population source and providing dispersal opportunities with sink populations through connected habitat (Pan et al., 2014). This strategy should be conducted with a reduction in deer offtake from hunting, retaliatory killing and problem animal removal (Wang et al., 2006;

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Davis et al., 2016). Introduced populations, which have a relatively broad distribution, in almost all regions of Indonesia except Sumatra and Kalimantan, are least concerned. The high economic value of deer livestock for people in West Nusa Tenggara and East Nusa Tenggara or the traditional hunting activities for Papua peoples could support the spread of this species. Although Javan deer is considered a pest species in areas where it has been recently introduced (e.g., New Caledonia –

19

Soubeyran 2008; Australia - Keith and Pellow, 2005), no such evidence has been reported from Indonesia so far. However, potential impacts on natural ecosystems of some islands should be investigated.

Conflicts of interest The authors declare that there are no conflicts of interest. The manuscript described is originally carried out

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by the authors. All authors acknowledge their participation in conducting the research leading to the

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manuscript with the agreement to its submission to be considered fornication by the Journal for Nature Conservation, and that all have agreed on the final version. The manuscript is approved tacitly or explicitly

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by the responsible where the work was carried out. Any research in the manuscript not carried out by the authors is fully acknowledged in the manuscript. No part of the research has been published in any form

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elsewhere unless it is fully acknowledged in the manuscript. There are no sources of funding needs to acknowledge in the manuscript, except for the support of data which is authorized under a research

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agreement Number PKS.3/KSDAE/PIKA/KSA.0/1/2018 between Natural Resources Conservation Center, Ministry of Environment and Forestry, Republic of Indonesia and Faculty of Forestry, IPB University, the

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document act as ethical research clearance of the study

Acknowledgements

We wish to thank the Indonesian Ministry of Environment and Forestry, civil society partners, and

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individual contributors, as listed in the Appendix 1, for supporting the project.

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Whitehead, K.G., 1993. The Whitehead encyclopedia of deer. Voyageur Press, Inc, Stillwater,

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Wich, S.A, Vogel, E.R., Larsen, M.D., Fredriksson, G., Leighton, M., Yeager, C.P., Brearley, F.Q.,

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van Schaik, C.P., Marshall, A.J., 2011. Forest fruit production is higher on Sumatra than on Borneo. PLoS ONE, 6: e21278. https://doi.org/10.1371/journal.pone.0021278.

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Woodford, K.B., Dunning, A., 1992. Production cycles and characteristics of rusa deer in Queensland, Australia. In: Brown R.D. (eds) The biology of deer, pp.197-202. Springer, New York, NY. http://doi.org/10.1007/978-1-4612-2782-3_47. Young, N., Carter, L., Evangelista, P.A., 2011. Maxent model v3.3.3e Tutorial (ArcGIS v7).

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Colorado State University.

Yudhistira, P., 2014. Sang Pelopor Peranan Dr. SH. Koorders dalam Sejarah Perlindungan Alam di Indonesia. Direktorat Kawasan Konservasi dan Bina Hutan Lindung Ditjen Perlindungan Hutan dan Konservasi Alam Kementerian Kehutanan. http://ksdae.menlhk.go.id/sejarahksdae.html.

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Fig. 1. Predictive maps of areas suitable for native populations of Javan deer in Indonesia before 1965 (A), after 1965 (B), and for introduced populations (C). The MaxEnt model outputs were defined to be suitable for Javan deer if they had a logistic probability of 0.45 or higher. Numbers

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identify the main areas of the Javan deer distribution.

Fig. 2. Jackknife tests of AUC values of the MaxEnt models applied to the native populations of Javan deer in Indonesia before 1965 (A), after 1965 (B), and to the introduced populations (C).

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Black bars represent models generated with the variable alone. Light grey bars represent the model generated without this variable. Dark grey bars represent the model generated with all variables.

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Fig. 3. Maps of land use by the main concessions in the range of native (A) and introduced (B) populations of Javan deer in Indonesia. Maps showing the overlap of these concessions with Javan

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deer distribution for native (C) and introduced populations (D).

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Table 1. Suitable areas for native and introduced populations of Javan deer within Indonesian regions calculated by MaxEnt modelling including predicted range in protected areas (PA), nonprotected areas (non-PA), Industrial oil palm plantation (IOPP), Production forest (PF), Limited production forest (LPF), Logging concessions (LC) and Industrial timber plantation (ITP) (areas in km2)

32,847 47,800

Bali

5,780

Total

132,129.5

Introduced populations Province Total area State West Nusa Tenggara East Nusa Tenggara West Sulawesi South Sulawesi Gorontalo

19,709

North Sulawesi Central Sulawesi Southeast Sulawesi Maluku

13,852

47,246 16,787

1,650.73 (1,819.90) 2,262.90 (5,257.11) 327.22 (1,901.44) 1,503.65 (8,111.92) 3,130.04 (3,754.41) 296.26 (1,646.31) 4,247.78 (9,892.95) 2,608.14 (17,232.63) 2,538.41 (4,347.93) 1,721.64 (2,203.20) 6,063.88 (32,529.77) 10,001.96 (70,165.90)

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46,717

PA (Total PA)

64.79

61,841

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174,600

46,914

North Maluku West Papua

31,982

420,540

Papua

319,036

1.81 (579.14) 406.41 (2,159.30) 113.82 (3,730.27) 2,240.98 (8,103.76)

9.81 (404.51) 314.37 (1,784.64) 84.01 (1,846.50)

0.18 (6,18)

0 2,763.02 (14,572.47)

0 408.37 (4,041.83)

LC (Total LC)

ITP (Total ITP)

6.64 (7.64)

267.35 (279.02)

0

0

0 194.12 (229.86) 161.06 (537.06) 9.81 (67.40) 488.08 (1,615.09) 93.68 (198.24) 21.58 (119.46) 68.46 (487.15) 39.55 (4,446.88) 2,431.62 (27,251.11)

0 (315.61)

673.82 (843.99) 527.09 (545.46) 43.96 (635.74) 109.28 (441.21) 561.73 (635.17) 31.59 (97.71) 322.99 (1,911.04) 525.21 (1,262.65) 70.14 (928.24) 74.30 (707.59) 0 (2,531.92) 1,003.97 (9,440.53)

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LPF (Total LPF)

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West Java & Jakarta Central Java & DIY East Java

412.48 (1,198.34) 771.91 (3,091,32) 116.76 (1,407.05) 2,311.23 (2,364,64) 172.05 (227.02) 3,784.43 (8,288,36)

PF (Total PF)

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9,663

non-PA IOPP (Total non(Total PA) IOPP) 36.55 0.04 (4,581.66) (106.07) 3,348.83 9.34 (32,286.68) (117.40) 1329.98 (31,393.95) 0 7,007.59 (45,435.36) 0 1,464.51 (5,405.98) 0 13,187.46 9.38 (119,103.64) (223.47) non-PA (Total nonPA) 13,952.53 (17,889.10) 35,520.79 (41,988.89) 1,288.41 (145,405.56) 8,184.90 (38,605.08) 3,821.81 (8,680.59) 3,431.26 (12,205.69) 10,398.32 (51,948.05) 9,622.15 (20,907.37) 2,141.18 (42,566.07) 2,512.64 (29,778.80) 501.74 (107,846.23) 6,732.59 (248,870.10)

IOPP (Total IOPP)

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PA (Total PA)

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Native populations Province Total area State

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0 0 2.97 (263.94) 875.31 (4,774.89) 0 577.35 (9,037.49) 556.45 (6,573.97) 66.77 (32,926.85) 970.39 (29,989.28)

Total

1,199,289.79

36,352.61 (158,863.49)

98,108.32 (766,691.51)

3,514.60 (34,959.90)

3,316.59 3,944.08 (84,161.04) (19,981.24)

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Table 2. Relative contribution (RC) and permutation importance (PI) of each variable calculated by Maxent modelling. Values are averaged over the 50 replicates and normalized to give percentages. Permutation importance was used to assess variable importance. Variable Historical Native Introduced RC PI RC PI RC PI Elevation 4.5 5.6 2.1 8.8 3.7 2.0 Distance to the nearest river 5.5 6.6 0.8 1.8 0.9 2.3 Distance to the nearest forest 20.0 17.1 11.1 14.2 25.0 13.2 edge from inside Distance to the nearest forest 6.1 15.0 8.6 7.0 4.3 1.0 edge from outside Protected area 25.2 12.9 30.6 36.6 37.3 23.6 NDVI 0.5 0.9 0.4 0.8 Distance to the nearest road 3.5 1.2 0.2 7.2 Land use classification 10.2 9.3 10.7 8.6 9.4 15.4 Annual mean rainfall 24.5 27.5 24.4 18.1 16.3 26.2 Annual mean temperature 4.0 6.0 7.7 2.8 2.5 8.3

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