ABSTRACT
Tourism is one of the most important issues facing marine protected areas (MPAs) and small islands worldwide. Tourism development is considered a contribution to pollution levels in the environment. This paper aims to evaluate the hypothetical effects of tourism development on water quality spatially and temporally using the coastal water quality index (CWQI) and Geographic Information System (GIS) in search of improved management for marine conservation areas. This study showed significant tourism influences on the CWQI in the Marine Tourism Park of the Gili Matra Islands, Lombok, Indonesia. Water quality variability indicates a significant spatiotemporal difference (p < 0.05) in the two tourism seasons. During the peak season of tourism, the CWQI decreased to poor conditions, i.e., ranging from 9.95 to 21.49 for marine biota and from 7.98 to 30.42 for marine tourism activities in 2013, and ranging from 39.52 to 44.42 for marine biota and from 44.13 to 47.28 for marine tourism activities, which were below the standard for both marine biota and marine tourism activities. On the contrary, it showed a better level (from poor to moderate) during the low season of tourism (ranging from 41.92 to 61.84 for marine biota and from 48.06 to 65.27 for marine tourism activities in 2014), providing a more acceptable condition for both aspects. The study proved that massive tourism development in the MPA and small islands could reduce water quality and increase vulnerability. Accordingly, integrated tourism management and the environment, waters, and land will be needed to develop sustainable tourism. The CWQI and GIS were applicable to assess water quality, both spatially and temporally, and become a quick reference in monitoring and initial evaluation of impact management.
ABSTRACT
Land-use change and habitat fragmentation are well-known to affect host-parasitoid interactions. However, the study of the effects of landscape composition, as a result of habitat fragmentation, on host-parasitoid food webs is still limited especially in a tropical agricultural landscape. This research was aimed to study the effect of agricultural landscape composition on the structure of host-parasitoid food webs. Field research was conducted in sixteen long-bean fields located in Bogor Regency, West Java, Indonesia. In each long-bean field, sampling of insect pests and their parasitoids was carried out using direct observation within a plot size of 25 m × 50 m. The collected insects were brought to the laboratory for rearing and observed for emerging parasitoids. Landscape composition of each long-bean field was measured by digitizing the whole patch within a radius of 500 m from the long-bean field as a center of landscape, and landscape parameters were then quantified by focusing on number of patches and class area of both semi-natural habitats and crop fields. In total, we found 51 morphospecies of insect pests and 110 morphospecies of associated parasitoids from all research locations. Lepidopteran pests are the most abundant and species-rich with 35 morphospecies and with 76 morphospecies of parasitoids. Based on the generalized linear models, landscape composition especially class area of natural habitat and crop field showed a positive relationship with host-parasitoid food-web structure especially on connectance and compartment diversity. In conclusion, landscape composition contributes to shaping the host-parasitoid food-webs in a tropical agricultural landscape.
ABSTRACT
Indonesia has a large number of primate diversity where a majority of the species are threatened. In addition, climate change is conservation issues that biodiversity may likely face in the future, particularly among primates. Thus, species-distribution modeling was useful for conservation planning. Herein, we present protected areas (PA) recommendations with high nature-conservation importance based on species-richness changes. We performed maximum entropy (Maxent) to retrieve species distribution of 51 primate species across Indonesia. We calculated species-richness change and range shifts to determine the priority of PA for primates under mitigation and worst-case scenarios by 2050. The results suggest that the models have an excellent performance based on seven different metrics. Current primate distributions occupied 65% of terrestrial landscape. However, our results indicate that 30 species of primates in Indonesia are likely to be extinct by 2050. Future primate species richness would be also expected to decline with the alpha diversity ranging from one to four species per 1 km2. Based on our results, we recommend 54 and 27 PA in Indonesia to be considered as the habitat-restoration priority and refugia, respectively. We conclude that species-distribution modeling approach along with the categorical species richness is effectively applicable for assessing primate biodiversity patterns.
