Data-driven planning adjustments of the functional zoning of Houhe National Nature Reserve

Prediction of potential suitable habitats in the 21st century and GAP analysis of priority conservation areas of Chionanthus retusus based on the MaxEnt and Marxan models

Chionanthus retusus (C. retusus) has a high economic and medicinal value, but in recent years it has been included in the list of China's major protected plants and China's Red List of Biodiversity due to the serious destruction of its wild germplasm resources. Based on 131 sample points of C. retusus, this study simulated potential habitats and spatial changes of C. retusus in the 21st century using the Maxent model combined with the geographic information system ArcGIS, predicted prioritized protected areas by the Marxan model, and assessed current conservation status through GAP analysis. The results showed that (1) when the regularization multiplier was 1.5 and the feature combinations were linear, quadratic, and fragmented, the area under the curve of the subjects in the training and test sets were both above 0.9, the true skill statistic value was 0.80, and the maximum Kappa value was 0.62, meaning that the model had high accuracy; (2) Temperature seasonality, annual precipitation, min temperature for coldest month, and precipitation of wettest month had relatively strong influences on species' ranges. (3) The moderately and optimally suitable habitats of C. retusus were primly located in the areas of southwestern Shanxi, central Hebei, western Henan, Shandong, Shaanxi, Anhui and Hubei; (4) Under different future climate scenarios, the area of each class of suitable habitat will increase for varied amounts compared to the current period, with a general trend of expansion to the south; (5) The C. retusus priority protected areas were mainly located in most of Shandong, southern Liaoning, southwestern Shanxi, western Henan, and central Hebei, and its conservation vacancy area was relatively large compared to its protected area. These results will provide scientific strategies for implementing long-term conservation of C. retusus in China and similar regions under warming conditions in the 21st century.

Optimizing functional zoning for Dalingshan Forest Park in China through microcosmic human disturbance evaluation

Human disturbance stands as a prominent factor influencing the ecological environment within natural protected areas. Presently, the issue of balancing human activities and ecological preservation has emerged as a critical concern in the construction of China's natural protected area system. Functional zoning serves as the cornerstone of natural protected area management and represents a pivotal tool in achieving this equilibrium. This study endeavors to introduce a set of functional zoning methods for natural protected areas based on human disturbance assessments. Utilizing Dalingshan Forest Park in Dongguan city which is known for its significant human disturbances as a case study, field surveys were conducted to identify various types of small-scale and understory-hidden human disturbances, such as residential areas, roads, tourist areas, forestry areas, and energy facilities. Subsequently, a microcosmic human disturbance model tailored to forested areas was developed using the analytic hierarchy process. By integrating the findings of macrocosmic human disturbance assessments conducted concurrently by the research group, a functional zoning plan for Dalingshan Forest Park was proposed. The results show that ecological conservation zones within the park should be established in three specific areas, primarily in regions with low-level microcosmic human disturbance (levels 1 and 2) and terrain fluctuations ≥110 m. In contrast, the rational use zone is notably influenced by tourist infrastructure and road networks, predominantly located in regions with high human activity, such as popular tourist destinations and areas with road classifications and vehicular traffic. The microcosmic human disturbance assessment method proposed in this study enhances the rationality and accuracy of natural protected area functional zoning. It provides a more scientifically grounded research approach for similar studies concerning natural protected area functional zoning and contributes valuable insights for the further advancement of China's efforts in the integration and optimization of natural protected areas.

Priority conservation area of Larix gmelinii under climate change: application of an ensemble modeling

Larix gmelinii (Rupr.) Kuzen is a major tree species with high economic and ecological value in the Greater Khingan Mountains coniferous forest of Northeast China. Reconstructing the priority Conservation Area of Larix gmelinii under Climate could provide a scientific basis for its germplasm conservation and management. The present study used ensemble and Marxan model simulations to predict species distribution areas and delineate priority conservation areas for Larix gmelinii in relation to productivity characteristics, understory plant diversity characteristics, and climate change impacts. The study revealed that the Greater Khingan Mountains and the Xiaoxing'an Mountains, with an area of approximately 300 974.2 km², were the most suitable for L. gmelinii. The stand productivity of L. gmelinii in the most suitable area was significantly higher than that in the less suitable and marginally suitable areas, but understory plant diversity was not dominant. The increase in temperature under future climate change scenarios will reduce the potential distribution and area under L. gmelinii; the species will migrate to higher latitudes of the Greater Khingan Mountains, while the degree of niche migration will gradually increase. Under the 2090s-SSP585 climate scenario, the most suitable area for L. gmelinii will completely disappear, and the climate model niche will be completely separated. Therefore, the protected area of L. gmelinii was demarcated with a target of the productivity characteristics, understory plant diversity characteristics and climate change sensitive area, and the current key protected area was 8.38 × 10⁴ km². Overall, the study's findings will lay a foundation for the protection and rational development and utilization of cold temperate coniferous forests dominated by L. gmelinii in the northern forested region of the Greater Khingan Mountains.

Multiperiod Dynamic Programming Algorithm for Optimizing a Nature Reserve

Zoning adjustments are a key method of improving the conservation efficiency of a nature reserve. Existing studies typically consider the one-period programming method and ignore dynamic ecological changes during the programming of a nature reserve. In this study, a scientific method for nature reserve (NR) programming, namely the multiperiod dynamic programming (MDP) algorithm, is proposed. The MDP algorithm designs an NR over three periods and does so by using ecological suitability values for each grid area. Ecological suitability values for each period were determined based on existing data on rare aquatic animals with Maxent software and cellular automata (CA). CA were used to determine the actual protection effect and to adjust each period’s ecological suitability values through comparisons with the sites’ surroundings. The maximization of ecological suitability values was used as an objective function; these values were assumed to indicate protection benefits. The objective function of the MDP also includes grid perimeters and numerical minimization for spatial compactness. Moreover, we designed three MDP constraints for the dynamic programming, including base constraints, distinguishing constraints, and multiperiod constraints. In the base and distinguishing constraints, we require a grid square to be a core, buffer, or unselected square, and we require the core and buffer grids to be spatially connected. For the multiperiod constraints, we used virtual points to ensure spatial continuity in different periods while attaining high ecological suitability. Our main contributions are as follows: (1) the novel MDP algorithm combining ecological attributes and multiperiod dynamic planning to optimize NR planning; (2) the use of virtual points to avoid selecting invalid grids and to ensure spatial continuity with significant protection benefits; and (3) the definition of ecological suitability values and use of CA to simulate dynamic changes over the three periods. The results reveal that the MDP algorithm results in a reserve with greater protection benefits than current reserves with superior spatial distribution due to multiperiod programming. The proposed MDP algorithm is a novel method for the scientific optimization and adjustment of nature reserves.

Vegetation Monitoring of Protected Areas in Rugged Mountains Using an Improved Shadow-Eliminated Vegetation Index (SEVI)

It is significant to study the vegetation of protected areas in rugged mountains where the vegetation grows naturally with minimal eco-society environmental stress from anthropogenic activities. The shadow-eliminated vegetation index (SEVI) was used to monitor the vegetation of protected areas, since it successfully removes topographic shadow effects. In order to auto achieve the best adjustment factor for SEVI calculation from regional area images, we developed a new calculation algorithm using block information entropy (BIE-algorithm). The BIE-algorithm auto-detected typical blocks (subareas) from slope images and achieved the best adjustment factor from a block where the SEVI obtained the highest information entropy in an entire scene. Our obtained regional SEVI result from two scenes of Landsat 8 OLI images using the BIE-algorithm exhibited an overall flat feature with the impression of the relief being drastically removed. It achieved balanced values among three types of samples: Sunny area, self-shadow, and cast shadow, with SEVI means of 0.73, 0.77, and 0.75, respectively, and the corresponding SEVI relative errors of self-shadow and cast shadow were only 4.99% and 1.84%, respectively. The linear regression of SEVI vs. the cosine of the solar incidence angle was nearly horizontal, with an inclination of −0.0207 and a coefficient of determination of 0.0042. The regional SEVI revealed that the vegetation growth level sequence of three protected areas was Wuyishan National Park (SEVI mean of 0.718) > Meihuashan National Nature Reserve (0.672) > Minjiangyuan National Nature Reserve (0.624) > regional background (0.572). The vegetation growth in the protected areas was influenced by the terrain slope and years of establishment of the protected area and by the surrounding buffer zone. The homogeneous distribution of vegetation in a block is influenced by many factors, such as the actual vegetation types, block size, and shape, which need consideration when the proposed BIE-algorithm is used.