presence of whale sharks based on oceanographic variations in Cenderawasih Bay National Park, Papua, Indonesia

Manuhutu JF, Wiadnya DGR, Sambah AB, Herawati EY. 2021. The presence of whale sharks based on oceanographic variations in Cenderawasih Bay National Park, Papua, Indonesia. Biodiversitas 22: 4948-4955. Oceanographic factors have an important role in the study of estimating the distribution of fish resource habitats. Sea Surface Temperature (SST), Sea Surface Chlorophyll (SSC), Current Speed, Sea Surface Height (SSH), and bathymetry are important parameters that have been used in estimating the habitat of certain species. Through analyzing these environmental factors, research on the appearance and distribution of whale shark habitats in the Cenderawasih Bay National Park in Papua, Indonesia, utilized field observation data and satellite imagery. This study applied data on the presence of whale sharks and oceanographic parameter data from satellite recordings during 2019 – 2020. Analysis of the relationship and habitat modeling between the monthly presence of whale sharks and environmental parameters was carried out through the Generalized Additive Model (GAM) statistical approach and spatial analysis through the Geographic Information System approach. In the GAM analysis, data on the presence of whale sharks was used as a response variable. In contrast, the predictor variables consisted of SST, SSC, current speed, SSH, and bathymetric data. The results showed that the highest frequency of whale shark presence occurred in the transitional monsoon, with an average presence of 31.77 ± 4.00 %. The study also showed that all predictors showed a highly significant relationship (P < 0.001) to the number of whale sharks present. SST values range from 30.3 – 31.3 °C, SSC of 0.39 – 0.86 mg/L, the current speed of 0.46 – 0.65 m/s, SSH showed 0.63 to 1.00 cm, and bathymetry between 40 – 50 m . In the GAM model, the SST and SSC parameters were the two most important parameters that affect the presence of whale sharks, followed by SSHD, depth (bathymetry), and current parameters.

Marbled Murrelets prefer stratified waters close to freshwater inputs in Haida Gwaii, British Columbia, Canada

The Marbled Murrelet (Brachyramphus marmoratus) is a small seabird that is currently listed as threatened in Canada. Understanding this species’ marine habitat preferences plays a vital role in our ability to focus conservation planning. We used the longest-running at-sea survey dataset available in British Columbia to examine hotspot persistence and habitat use at Laskeek Bay, Haida Gwaii, BC. The Laskeek Bay Conservation Society has been conducting spring and summer surveys along fixed transect routes in open and shoreline waters from 1997 to 2018. Along with analyzing this long-term dataset, we conducted surveys to measure oceanographic variables (2018–2019) and tested whether Marbled Murrelets in the same area used prey and oceanographic information to select marine habitat in conjunction with physical habitat features. Our hotspot persistence map, defined as areas that repeatedly had counts above a 75% threshold relative to other areas during a given survey, showed that murrelets consistently preferred shoreline transects. Murrelets also preferred shallow marine areas closer to streams, above higher proportions of sandy substrate and closer proximity to abundant nesting habitat. Modeling weather and time variables contributed little additional predictive power. Nonetheless, models that included physical environmental, oceanographic, and prey variables outperformed those with only physical environmental variables. Stratified water was the oceanographic variable most strongly related to higher counts. Our study suggests that stratified waters could work with stream systems to create productive zones for foraging murrelets, and highlights the importance of murrelets having access to marine areas with the preferred physical features.

GIS Mapping and Distribution of Indian Peafowl (Pavo cristatus) in India by Using Citizen Science Data

The Indian peacock or Blue peafowl (Pavo cristatus.), the largest of the pheasants commonly called Mor or Mayur, is a bird species recognized for its beauty. Pavo cristatus (Indian peafowl) has been justifiably declared as the National Bird of India in 1963. In India, it is given the ultimate protection by its inclusion in the Schedule I of Wildlife (Protection) Act, 1972. The main objective is to encourage citizen participation in generating baseline information using sight records and enable long-term monitoring of Indian peafowl in India. The present study deals with the status and distribution of Indian peafowl in India and the data used is taken from the citizen science database of eBird. The complete dataset of Indian peafowl from 2001-2017 was used to prepare the distribution maps in different years as well as to obtain information on the species' location, and the number of a social group in India. Some potential reported sites were verified during 2013–2017 by visiting the distinct locations. From 2001 to 2017 we found 71,632 records from 15,151 contributors across 26 states/union territories of India. Percentage of individuals observed was 38% (in 2017), 27% (in 2016) and 16% (in 2015) whereas 0% was recorded in 2002, 2006 and 2007. The citizen science data obtained thus has the potential for increasing our understanding of current peafowl distribution patterns, and for categorizing important sites for conservation/protections and to perform occupancy and habitat modeling of Indian peafowl species in India.

Habitat and Distribution Modeling of Prehistoric Hippos (Hippopotamus sivalensis spp.) During Pleistocene in Java Island

Currently, there are only 2 extant species of hippos including common (Hippopotamus amphibius) and pygmy hippos (Choeropsis liberiensis) . But in prehistoric times, there were several species. During Pleistocene these species were known to migrate to Java Island from Asian Continent and the species was Hippopotamus sivalensis spp. In this regard, this study aimed to model the habitat of H. sivalensis spp., ecology, and biodiversity of Hippopotamus sivalensis spp. based on the fossil record. The model was developed based on the Principal Component Analysis (PCA) method using the R statistical package. The results showed that there were 7 populations of H. sivalensis spp. that lived at various altitudes with an average of 177 m above sea level (95% CI : 123-232 m). According to PCA, there were at least 2 separate populations of H. sivalensis spp. One population occupies the forest while another occupies a habitat close to the coast. Currently the habitat for H. sivalensis spp. already changed. Based on habitat modeling, H. sivalensis spp. inhabit streams with submerged aquatic plants and shrubs and trees growing along river banks.

Data Gap Classification for Terrestrial Laser Scanning-Derived Digital Elevation Models

Extensive gaps in terrestrial laser scanning (TLS) point cloud data can primarily be classified into two categories: occlusions and dropouts. These gaps adversely affect derived products such as 3D surface models and digital elevation models (DEMs), requiring interpolation to produce a spatially continuous surface for many types of analyses. Ultimately, the relative proportion of occlusions in a TLS survey is an indicator of the survey quality. Recognizing that regions of a scanned scene occluded from one scan position are likely visible from another point of view, a prevalence of occlusions can indicate an insufficient number of scans and/or poor scanner placement. Conversely, a prevalence of dropouts is ordinarily not indicative of survey quality, as a scanner operator cannot usually control the presence of specular reflective or absorbent surfaces in a scanned scene. To this end, this manuscript presents a novel methodology to determine data completeness by properly classifying and quantifying the proportion of the site that consists of point returns and the two types of data gaps. Knowledge of the data gap origin can not only facilitate the judgement of TLS survey quality, but it can also identify pooled water when water reflections are the main source of dropouts in a scene, which is important for ecological research, such as habitat modeling. The proposed data gap classification methodology was successfully applied to DEMs for two study sites: (1) A controlled test site established by the authors for the proof of concept of classification of occlusions and dropouts and (2) a rocky intertidal environment (Rabbit Rock) presenting immense challenges to develop a topographic model due to significant tidal fluctuations, pooled water bodies, and rugged terrain generating many occlusions.

In search of Makara, an Extirpated Freshwater Crocodile Crocodylus siamensis (Schneider, 1801) of Java Island, Using Temple Reliefs, ᴪ AIC and Habitat Modeling

Ancient reliefs in temple can provide information of past ecosystem along with biodiversity including Makara relief representing crocodile figure. In here, this study aims to identify and model the population of freshwater Crocodylus siamensis as portrayed in reliefs in 6 temples. The result shows that the crocodile reliefs in temples were having similar pattern to the freshwater Crocodylus siamensis fossils in term of locality. The temples and the fossils were located in the inland and near the rivers. While the temple locality patterns were in contrast to the locations where extant saltwater Crocodylus porosus has occurred. These contradictions strengthen the possibility that the crocodile portrayed in reliefs was made based on the C. siamensis occurrences. Based on the analysis, it is estimated that the C. siamensis once has occupied river and wetland in Java and its presence has been recorded in the reliefs. This occurrence at least happened from 1280 to 700 BC. From assessments of habitats near the temples using ᴪ AIC, most surrounding habitats have high detection probability and occupancy for C. siamensis from ᴪ 0.500 (95%CI:0.058-0.941). to ᴪ 1.000 (95%CI:0.000-1.000).

Multiscale consensus habitat modeling for landscape level conservation prioritization

Globally, wide-ranging carnivore populations are imperiled due to human-caused habitat fragmentation. Where populations are fragmented, habitat quantification is often the first step in conservation. Presence-only species distribution models can provide robust results when proper scales and data are considered. We aimed to identify habitat for a fragmented carnivore population at two scales and aid conservation prioritization by identifying potential future habitat fragmentation. We used location data and environmental variables to develop a consensus model using Maxent and Mahalanobis distance to identify black bear (Ursus americanus floridanus) habitat across Florida, USA. We compared areas of habitat to areas of predicted sea level rise, development, and protected areas. Local-scale models performed better than state-scale models. We identified 23,798 km2 of habitat at the local-scale and 45,703 km2 at the state-scale. Approximately 10% of state- and 14% of local-scale habitat may be inundated by 2100, 16% of state- and 7% of local-scale habitat may be developed, and 54% of state- and 15% of local-scale habitat is unprotected. Results suggest habitat is at risk of fragmentation. Lack of focused conservation and connectivity among bear subpopulations could further fragmentation, and ultimately threaten population stability as seen in other fragmented carnivore populations globally.

Suitable Habitat Modeling of Prehistoric Antelope-like Bovid Duboisia Santeng in Java Island in The Early Pleistocene

The migration routes have facilitated the distribution of mammals from south east Asian mainland to the Sundaland including Java island in the early Pleistocene. One of species that has migrated through that route is antelope-like bovid Duboisia santeng. In the present study, the potential distribution areas and the suitable habitats of D. santeng have been projected and modeled. The modeled habitat was a forest river basin sizing 302.91 Ha in the central of Java island. The model has classified and reconstructed the habitat suitability ranged from low to high back to Pleistocene. The surrounding areas of forest were mostly classified as medium and low related to the limited tree covers. Most suitable habitats were identified in the middle of forest river basin where the tree covers were presented