Habitat suitability mapping of stone pine (Pinus pinea L.) under the effects of climate change

Modeling potential distribution and above-ground biomass of Scots pine (Pinus sylvestris L.) forests in the Inner Anatolian Region, Türkiye

Scots pine (Pinus sylvestris L.) holds a substantial position as a tree species designated for biomass energy within European forests, covering a significant part of Türkiye's forests. We used the machine learning technique, namely, maximum entropy (MaxEnt), to estimate the suitable areas for Scots pine and to investigate its potential future distribution under various climate change scenarios in Inner Anatolian Region, Türkiye. The distribution data of Scots pine was utilized, and a set of 20 variables was chosen from spectral, topographic, and bioclimatic datasets to train the MaxEnt model. A map depicting the potential distribution of Scots pine in the area was generated, and alterations in its spatial distribution under SSP2-4.5 and SSP5-8.5 climate change scenarios were predicted. The results showed that the most effective factors for the distribution of Scots pine in the region were normalized difference vegetation index (NDVI), Red band of the imagery, and Bio19 variables, and the contribution percentages were 45.6%, 18.5%, and 18.1%, respectively. Current conditions have indicated that 81.11% of the region is not suitable for Scots pine. Highly suitable areas for Scots pine constituted 0.88% of the total area in the east and southeast parts of the region. Considering the SSP2-4.5 and SSP5-8.5 scenarios, it has been determined that there may be a partial increase in highly suitable areas. The above-ground biomass (AGB) data generated based on potential distribution areas were predicted between 0.04 and 168.76 t ha-1, and the areas with dense biomass over 120 t ha-1 were identified in the west, north, and northeast parts of the region. While actual AGB of Scots pine was 6.92 MT, its potential AGB was estimated 125.93 MT in total area. The difference may well be attributed to the wide potential distribution of Scots pine stands in the area apart from the current forest lands. Nevertheless, this research contributes to the holistic management of forests and provides substantial values for formulating well-suited silvicultural interventions, developing sustainable forest management strategies, and furthering research aimed at estimating biomass reserves.

Predicting of the current and future geographical distribution of Laurus nobilis L. under the effects of climate change

Today, climate change affects all living things on earth. It also leads to serious losses in terms of biodiversity, ecosystem services, and human welfare. In this context, Laurus nobilis L. is a very important species for Turkey, and the Mediterranean countries. This research aimed to simulate the current distribution of the suitable habitat for L. nobilis in Turkey and to predict its possible range shifts in future climate scenarios. To predict the geographical distribution of L. nobilis, the study used the maximum-entropy algorithm-based MaxEnt 3.4.1 with seven bioclimatic variables created using the Community Climate System Model 4.0 (CCSM4) and the prediction models RCP4.5-8.5 for the years 2050-2070. The results indicated that the most important bioclimatic variables that shape the distribution of L. nobilis are BIO11-mean temperature of coldest quarter, and BIO7-annual temperature range. Two climate change scenarios predicted that the geographical distribution of L. nobilis would increase slightly and then decrease in the future. However, the spatial change analysis showed that the general geographical distribution area of L. nobilis did not change significantly, but the "moderate," "high," and "very high" suitable habitats changed towards "low" suitable habitats. These changes were particularly effective in Turkey's Mediterranean region, which shows that climate change is instrumental in determining the future of the Mediterranean ecosystem. Therefore, suitability mapping and change analysis of potential future bioclimatic habitats can help in planning for land use, conservation, and ecological restoration of L. nobilis.

Analysis of the Potential Range of Anticlea sibirica L. (Kunth) and Its Changes under Moderate Climate Change in the 21st Century

The study shows the analysis of the current potential range and the modeling of its changes in the hemiboreal species Anticlea sibirica. The models show the habitat suitability for A. sibirica under moderate climatic changes (RCP4.5) in the middle and second half of the 21st century. For modeling, we used MaxEnt software with the predictors being climate variables from CHELSA Bioclim and a digital elevation model. The modeling has shown that climate change can be favorable for the spread of A. sibirica to the northeastern part of its range by expanding highly suitable habitats in mountainous landscapes along the coast of the Sea of Okhotsk. In the rest of the range, the total area of suitable habitats will decrease. In areas with extremely deteriorating growing conditions, the species will persist in low-competition habitats such as rocky outcrops, riverbanks, and screes. The predicted change in the distribution of A. sibirica indicates a possible strong transformation of the vegetation cover in Siberia and the Urals, even under moderate climate change.

A Model-Based Assessment for the Ability of National Nature Reserves to Conserve the Picea Species in China under Predicted Climate Conditions

Climate change has a profound impact on the conservation and management of the Picea species, and establishing more nature reserves would be an effective way to conserve wild species in general. Based on a novel computational method using ecological niche modeling to predict the potential geographical distribution of species and a spatial decision support system, the planning process could predict the future distribution of the Picea species and thus select appropriate nature reserves. In this research, we utilized systematic conservation planning to define priority conservation areas for the Picea species in China according to future climate predictions. We hypothesized that: (1) the distribution of the Picea species could be changed under predicted climate conditions in China; (2) the current national nature reserves had sufficient capacity to conserve Picea species under predicted climate conditions in China; and (3) there were still deficiencies in the planned conservation for the Picea species based on predicted climate predictions in China. The results of a spatial analysis showed that the predicted climate would have an impact on the area of distribution of the Picea species. Current nature reserves have a strong potential to conserve the Picea species. However, the conservation of the Picea species in the existing nature reserves was not adequate. There were still many Picea specimens outside the reserve that would be threatened. This research systematically improved the research on the Picea species, and it also scientifically identified the suitable growth and conserved areas of the Picea species in China to provide an empirical basis for the conservation and management of the Picea species.