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This file contains detailed descriptions of the methods used to create the resistance surface, identify source and sink locations, and run the GFLOW simulation software to create the circuit theoretic accessibility metric. It also contains Figures S1-S6 and Table S1.

Rainforests on Borneo support exceptional concentrations of endemic insect biodiversity, but many of these forest-dependent species are threatened by land-use change. Totally protected areas (TPAs) of forest are key for conserving biodiversity, and we examined the effectiveness of the current TPA network for conserving range-restricted butterflies in Sabah (Malaysian Borneo). We found that mean diurnal temperature range and precipitation of the wettest quarter of the year were the most important predictors of butterfly distributions (N = 77 range-restricted species), and that species richness increased with elevation and aboveground forest carbon. On average across all species, TPAs were effective at conserving ~43% of species’ ranges, but encompassed only ~40% of areas with high species richness (i.e. containing at least 50% of our study species). The TPA network also included only 33-40% of areas identified as high priority for conserving range-restricted species, as determined by a systematic conservation prioritization analysis. Hence, the current TPA network is reasonably effective at conserving range-restricted butterflies, although considerable areas of high species richness (6565 km2) and high conservation priority (11,152-12,531 km2) are not currently protected. Sabah’s remaining forests, and the range-restricted species they support, are under continued threat from agricultural expansion and urban development, and our study highlights important areas of rainforest that require enhanced protection.

Wild meat (or ‘bushmeat’) hunting is nearly ubiquitous across the tropics and is very often unsustainable—driving declines and extirpation of numerous mammal populations. Loss of these animals can alter the transport of nutrients within and between ecosystems. But whether the physical removal of vertebrate carcasses and the nutrients that they store can reduce overall nutrient availability in ecosystems has been little explored. At 32 sites on three continents, we show that annual phosphorus (P) loss via mammal exploitation was low relative to the rate of atmospheric P deposition. But at four sites in Africa and Southeast Asia, removal of P in the skeletons of hunted mammals exceeded the atmospheric input of this nutrient by 10-fold or more. Because P is the growth-limiting nutrient for many tropical terrestrial ecosystems and certain large mammals, the imbalance created by the removal of mammal biomass under very high hunting scenarios could reduce ecosystem carrying capacity if no compensatory P additions occur in the system. This biogeochemical perspective on bushmeat exploitation raises further concerns about harvest sustainability and human food security in areas where hunting rates are high and ecosystem P inputs low.

S1. Supplementary Tables; S2. Trait information; S3. Supplementary Methods and Results; S4. Supplementary Figures

Additional information on study sites, species detections, and temperature predictions

The masked palm civet Paguma larvata is a small carnivore within the civet family Viverridae, currently listed as Least Concern on The IUCN Red List of Threatened Species. Across its global range the masked palm civet uses a range of habitats in tropical and subtropical regions, from lowlands to highlands, but its exact ecological requirements and the use of modified habitat remains unclear. We analysed 49 (Balanced Model) and 72 (Spatial Filtering Model) location records of the masked palm civet from Borneo to predict habitat suitability. The resulting model predicted the interior and high elevation areas of Borneo to be suitable habitat, while the coastal and other low-lying areas, such as the extensive peat swamp forests in Central Kalimantan, were predicted to be unsuitable. Greater survey effort in South, Central and West Kalimantan and in Brunei is necessary to obtain more records to improve current models and understanding. The species is probably widespread in Borneo and its likely stronghold is in the higher-elevation forests which are currently less threatened and for a large part protected. Thus, speciesspecific conservation efforts are not considered warranted at this time.

The Sunda clouded leopard Neofelis diardi is a medium sized (15–25 kg) cat, found only on the Sundaic islands of Borneo and Sumatra. In recent years intensive camera-trapping surveys in Borneo have begun to shed light on the habitat associations and basic ecology of this elusive wild cat, but its distribution on an island-wide scale remains very poorly known. Such information is an essential element in the assessment of the Sunda clouded leopard’s conservation status and in the development of conservation action. In this paper we use MaxEnt niche distribution modelling to make predictions regarding the current distribution of this cat on Borneo. We collected a total of 259 occurrence records for the Sunda clouded leopard, stemming from all Bornean regions apart from Brunei and South Kalimantan, of which 48 (Balanced Model) or 94 (Spatial Filtering Model) were used in our modelling. Our habitat suitability model suggests that this species has a widespread distribution over a large contiguous portion of Borneo. The only exception is South Kalimantan, which is predicted largely to comprise unsuitable habitat. The predicted distribution closely follows the current distribution of little-encroached forest on Borneo (including selectively logged and unlogged areas). The species is notably predicted to be absent from the extensive areas of oil palm plantation, particularly in much of the low-lying coastal land. The predicted range encompasses a large proportion of the existing and proposed protected area network on Borneo. We highlight the priority areas for the conservation of the Sunda clouded leopard in Borneo based on our predicted distribution.

Background: Plasmodium knowlesi is a zoonotic pathogen, transmitted among macaques and to humans by anopheline mosquitoes. Information on P. knowlesi malaria is lacking in most regions so the first step to understand the geographical distribution of disease risk is to define the distributions of the reservoir and vector species. Methods: We used macaque and mosquito species presence data, background data that captured sampling bias in the presence data, a boosted regression tree model and environmental datasets, including annual data for land classes, to predict the distributions of each vector and host species. We then compared the predicted distribution of each species with cover of each land class. Results: Fine-scale distribution maps were generated for three macaque host species (Macaca fascicularis, M. nemestrina and M. leonina) and two mosquito vector complexes (the Dirus Complex and the Leucosphyrus Complex). The Leucosphyrus Complex was predicted to occur in areas with disturbed, but not intact, forest cover (> 60 % tree cover) whereas the Dirus Complex was predicted to occur in areas with 10–100 % tree cover as well as vegetation mosaics and cropland. Of the macaque species, M. nemestrina was mainly predicted to occur in forested areas whereas M. fascicularis was predicted to occur in vegetation mosaics, cropland, wetland and urban areas in addition to forested areas. Conclusions: The predicted M. fascicularis distribution encompassed a wide range of habitats where humans are found. This is of most significance in the northern part of its range where members of the Dirus Complex are the main P. knowlesi vectors because these mosquitoes were also predicted to occur in a wider range of habitats. Our results support the hypothesis that conversion of intact forest into disturbed forest (for example plantations or timber concessions), or the creation of vegetation mosaics, will increase the probability that members of the Leucosphyrus Complex occur at these locations, as well as bringing humans into these areas. An explicit analysis of disease risk itself using infection data is required to explore this further. The species distributions generated here can now be included in future analyses of P. knowlesi infection risk.