Novel Model Based on Artificial Neural Networks to Predict Short-Term Temperature Evolution in Museum Environment

The environmental microclimatic characteristics are often subject to fluctuations of considerable importance, which can cause irreparable damage to art works. We explored the applicability of Artificial Intelligence (AI) techniques to the Cultural Heritage area, with the aim of predicting short-term microclimatic values based on data collected at Rosenborg Castle (Copenhagen), housing the Royal Danish Collection. Specifically, this study applied the NAR (Nonlinear Autoregressive) and NARX (Nonlinear Autoregressive with Exogenous) models to the Rosenborg microclimate time series. Even if the two models were applied to small datasets, they have shown a good adaptive capacity predicting short-time future values. This work explores the use of AI in very short forecasting of microclimate variables in museums as a potential tool for decision-support systems to limit the climate-induced damages of artworks within the scope of their preventive conservation. The proposed model could be a useful support tool for the management of the museums.

Long-term changes in populations of rainforest birds in the Australia Wet Tropics bioregion: A climate-driven biodiversity emergency

Many authors have suggested that the vulnerability of montane biodiversity to climate change worldwide is significantly higher than in most other ecosystems. Despite the extensive variety of studies predicting severe impacts of climate change globally, few studies have empirically validated the predicted changes in distribution and population density. Here, we used 17 years (2000–2016) of standardised bird monitoring across latitudinal/elevational gradients in the rainforest of the Australian Wet Tropics World Heritage Area to assess changes in local abundance and elevational distribution. We used relative abundance in 1977 surveys across 114 sites ranging from 0-1500m above sea level and utilised a trend analysis approach (TRIM) to investigate elevational shifts in abundance of 42 species. The local abundance of most mid and high elevation species has declined at the lower edges of their distribution by >40% while lowland species increased by up to 190% into higher elevation areas. Upland-specialised species and regional endemics have undergone dramatic population declines of almost 50%. The “Outstanding Universal Value” of the Australian Wet Tropics World Heritage Area, one of the most irreplaceable biodiversity hotspots on Earth, is rapidly degrading. These observed impacts are likely to be similar in many tropical montane ecosystems globally.

Mapping Tourism Potential Based on Urban Heritage Tourism in Medan City

The city of Medan is the third-largest city in Indonesia and has historical buildings or heritage that can be revitalized as a cultural heritage with tourism potential that can be developed. However, until now, the colonial heritage buildings have been destroyed up to 70%. This research method uses a tourism anthropology approach with a qualitative research type that focuses on tourist destinations. The research location is a heritage area, a colonial heritage building in the Merdeka Square segment, Maimoon segment, Benteng segment, Youth segment, Polonia segment, and Sambu segment. The study results reveal that Medan has a heritage in the form of historic buildings that have the potential to be developed and represent the identity of the city of Medan. The potential for tourism development can be carried out in 3 (three) potential areas, namely: 1) The youth segment, which includes Gedung Juang 45, which currently functions as the Sumatran Money Museum, Tip Top Restaurant, and Tjong A Fie Mansion. 2) the Maimoon segment, which includes: Maimoon Palace and the Great Mosque. 3) The Merdeka Square segment includes City Hall, which currently functions as the Grand City Hall, Hotel De Boer (currently called Grand Inna Hotel), and the London Sumatra building. Through urban tourism based on urban heritage tourism, tourists can be invited to appreciate and interpret the objects observed. It serves as education and recreation for the community. This activity is also a means of preserving the wealth and identity of the city of Medan.

A spatial analysis of seagrass habitat and community diversity in the Great Barrier Reef World Heritage Area

The Great Barrier Reef World Heritage Area (GBRWHA) in north eastern Australia spans 2500 km of coastline and covers an area of ~ 350,000 km2. It includes one of the world’s largest seagrass resources. To provide a foundation to monitor, establish trends and manage the protection of seagrass meadows in the GBRWHA we quantified potential seagrass community extent using six random forest models that include environmental data and seagrass sampling history. We identified 88,331 km2 of potential seagrass habitat in intertidal and subtidal areas: 1111 km2 in estuaries, 16,276 km2 in coastal areas, and 70,934 km2 in reef areas. Thirty-six seagrass community types were defined by species assemblages within these habitat types using multivariate regression tree models. We show that the structure, location and distribution of the seagrass communities is the result of complex environmental interactions. These environmental conditions include depth, tidal exposure, latitude, current speed, benthic light, proportion of mud in the sediment, water type, water temperature, salinity, and wind speed. Our analysis will underpin spatial planning, can be used in the design of monitoring programs to represent the diversity of seagrass communities and will facilitate our understanding of environmental risk to these habitats.