Modelling the susceptibility of wetland plant species under climate change in the Mekong Delta, Vietnam

Developing and Validating Species Distribution Models for Wetland Plants Across Europe

Drainage, agricultural conversion, and climate change threaten wetlands and their unique biodiversity. Species distribution models (SDMs) can help to identify effective conservation measures. However, existing SDMs for wetland plants are often geographically limited, miss variables representing hydrological conditions, and neglect moss species, essential to many wetlands. Here, we developed and validated SDMs for 265 vascular plant and moss species characteristic of European wetlands, using environmental variables representing climate, soil, hydrology, and anthropogenic pressures. We validated the spatial predictions of the SDMs through cross-validation and against independent data from the Global Biodiversity Information Facility (GBIF). Further, we validated the niche optima of the species, as obtained from the modelled species response curves, with empirical niche optima. The spatial validation revealed good predictive power of the SDMs, especially for diagnostic mosses, for which we obtained median cross-validated values of the area under the curve (AUC) and true skill statistic (TSS) of 0.93 and 0.73, respectively, and a median true positive rate (TPR) based on GBIF records of 0.77. SDMs of diagnostic vascular plants performed well, too, with median AUC, TSS, and TPR of 0.91, 0.69, and 0.67, respectively. SDMs of non-diagnostic plants had the lowest performance, with median AUC, TSS, and TPR values of 0.84, 0.53, and 0.62, respectively. Correlations between modelled and empirical niche optima were typically in the expected direction. Climate variables, particularly the mean temperature of the coldest month, were the strongest predictors of species occurrence. At the same time, groundwater table depth was a significant predictor for diagnostic vascular plants but not for mosses. We concluded that our SDMs are suitable for predicting broad-scale patterns of wetland plant species distributions as governed by climatic conditions. Alternative or additional variables or a different modelling approach might be needed to represent better the local heterogeneity in the hydrological conditions of wetlands.

Simulation of mangrove suitable habitat in the Guangdong-Hong Kong-Macao Area under the background of climate change

Climate change has resulted in great influence on the geographical distribution of species. Mangrove forests are one of the most precious ecosystems on the planet, yet they are being threatened by the habitat destruction and degradation under the situation of global warming. Seeking suitable areas for planting mangroves to tackle climate change has been gradually popular in ecological restoration. In this study, we applied the Maximum Entropy algorithm to assess the contribution of environmental factors on mangrove distribution, simulated mangrove suitable habitat for present and future (scenario of SSP245-2070s), and used kernel density analysis for identifying priority of mangrove reserve construction. Results indicate that mean diurnal range and elevation made the highest contribution on mangrove distribution. At present, the mangrove habitat suitability along the western coast of the Guangdong-Hong Kong-Macao Area (GHMA) was the highest while that along the eastern coast was the lowest. By 2070s, mangrove suitable areas would show a decreasing trend under SSP245 scenario. High suitable areas (HSAs) would change fastest and shift to northeast in the same direction as dominant environmental factors. For further mangrove restoration, it is advisable to select sites with high suitability density in the future but low reclamation density at present as prior mangrove reserves, and these sites distribute along the northeastern and northwestern coast of Zhanjiang, Yangjiang and Jiangmen, the Pearl River Estuary and Honghai Bay of Shanwei. Meanwhile, regions with lower suitability density but higher reclamation density could be listed as secondary mangrove reserves.

Predicting the growth suitability of Larix principis-rupprechtii Mayr based on site index under different climatic scenarios

Larix principis-rupprechtii Mayr (larch) is one of the main afforestation and timber production species used in North China. Climate change has led to a change in its suitable distribution and growth. However, the impact of climate change on its growth suitability is not clear. In this study, using forest resource inventory data and spatially continuous environmental factor data (temperature, precipitation, topography, and soil) in Hebei and Shanxi Provinces, China, the random forest model (RF) was used to simulate the larch site index (SI) and growth suitability under three shared socioeconomic pathways (SSPs: SSP1-2.6, SSP2-4.5, and SSP5-8.5) for the current and future (2021-2040, 2041-2060 and 2080-2100). The results revealed that (1) RF had excellent performance in predicting the regional SI (R² = 0.73, MAE = 0.93 m, RMSE = 1.35 m); (2) the main factors affecting the productivity of larch were the mean temperature of the warmest quarter (BIO10), elevation (ELEV), mean diurnal range (BIO2), and annual precipitation (BIO12); and (3) larch currently had a higher SI in the Bashang areas and in the high-altitude mountains. The areas characterized as unsuitable, poorly suitable, moderately suitable, and highly suitable accounted for 15.45%, 42.12%, 31.94%, and 10.49% of the total area, respectively. (4) Future climate warming had an obvious inhibitory effect on the SI, and the effect strengthened with increasing radiation intensity and year. (5) The moderately suitable and highly suitable areas of larch growth showed a downward trend under future climate scenarios. By the end of this century, the suitable growth areas would decrease by 14.14% under SSP1-2.6, 15.17% under SSP2-4.5, and 19.35% under SSP5-8.5. The results revealed the impact of climate change on larch growth suitability, which can provide a scientific basis for larch forest management.

The role of climatic changes and financial development to the ASEAN agricultural output: a novel long-run evidence for sustainable production

This paper examines the impact of climate variables and financial development on agricultural value-added and cereal production in selected Southeast Asian economies from 1970 to 2016. The current research applies second-generation advanced techniques to accomplish robust and reliable outcomes. The findings from the FM-OLS estimation disclose that climatic factors, for instance, CO2e and average temperature, impact both agricultural value-added and cereal production negatively, and financial development has an inverted U-shaped influence on both agricultural value-added and cereal production. Meanwhile, other important factors, including cropped area, income level, and rural labor force, significantly improve agricultural value-added and cereal production. Furthermore, the FM-OLS estimator's D-H panel causality test outcomes are reliable. The findings of our study reveal that both the short- and long-run risks of climatic changes to the agricultural sector pose a large-scale threat to food security in Southeast Asian economies. As a result, a robust and stable financial development in terms of governance of climate change finance in the agriculture sector must be achieved to enhance farmers' ability to adapt to current and future climate change adverse impacts.

Changes in Mangrove Carbon Stocks and Exposure to Sea Level Rise (SLR) under Future Climate Scenarios

Mangrove ecosystems are threatened by a variety of anthropogenic changes, including climate change. The main aim of this research is to quantify the spatial variation in the different mangrove carbon stocks, aboveground carbon (AGC), belowground carbon (BGC), and soil carbon (SOC), under future climate scenarios. Additionally, we sought to identify the magnitude of sea-level rise (SLR) exposure with the view of identifying the mangrove regions most likely to face elevated inundation. Different representative concentration pathways (RCPs) ranging from the most optimistic (RCP 2.6) to medium emissions (RCP 4.5) and the most pessimistic (RCP 8.5) were considered for 2070. We used the Marine Ecoregions of the World (MEOW), a biogeographical classification of coastal ecosystems, to quantify the variation in future carbon stocks at a regional scale and identify areas of potential carbon stock losses and gains. Here, we showed that the mangroves of Central and Western Indo-Pacific islands (Andamans, Papua New Guinea, and Vanuatu), the west African coast, and northeastern South America will be the worst hit and are projected to affect all three carbon stocks under all future scenarios. For instance, the Andaman ecoregion is projected to have an 11–25% decline in SOC accumulation, while the Western Indo-Pacific realm is projected to undergo the sharpest declines, ranging from 10% to 12% under all three scenarios. Examples of these areas are those in Amazonia and the eastern part of South Asia (such as in the Northern Bay of Bengal ecoregion). Based on these findings, conservation management of mangroves can be conducted.

Modeling the Climate Suitability of Northernmost Mangroves in China under Climate Change Scenarios

Mangroves are important wetland ecosystems on tropical and subtropical coasts. There is an urgent need to better understand how the spatial distribution of mangroves varies with climate change factors. Species distribution models can be used to reveal the spatial change of mangroves; however, global models typically have a horizontal resolution of hundreds of kilometers and more than 1 km, even after downscaling. In the present study, a maximum entropy model was used to predict suitable areas for the northernmost mangroves in China in the 2050s. An approach was proposed to improve the resolution and credibility of suitability predictions by incorporating land-use potential. Predictions were made based on two CMIP6 scenarios (i.e., SSP1-2.6 and SSP5-8.5). The results show that the northern edge of the natural mangrove distribution in China would migrate from 27.20° N to 27.39° N–28.15° N, and the total extent of suitable mangrove habitats would expand. By integrating 30 m resolution land-use data to refine the model’s predictions, under the SSP1-2.6 scenario, the suitable habitats of mangroves are predicted to be 13,435 ha, which would increase by 33.9% compared with the current scenario. Under the SSP5-8.5 scenario, the suitable area would be 23,120 ha, with an increased rate of 96.5%. Approximately 40–44% of the simulated mangrove patches would be adjacent to aquacultural ponds, cultivated, and artificial land, which may restrict mangrove expansion. Collectively, our results showed how climate change and land use could influence mangrove distributions, providing a scientific basis for adaptive mangrove habitat management despite climate change.

Remote Sensing Approach for Monitoring Coastal Wetland in the Mekong Delta, Vietnam: Change Trends and Their Driving Forces

Coastal wetlands in the Mekong Delta (MD), Vietnam, provide various vital ecosystem services for the region. These wetlands have experienced critical changes due to the increase in regional anthropogenic activities, global climate change, and the associated sea level rise (SLR). However, documented information and research on the dynamics and drivers of these important wetland areas remain limited for the region. The present study aims to determine the long-term dynamics of wetlands in the south-west coast of the MD using remote sensing approaches, and analyse the potential factors driving these dynamics. Wetland maps from the years 1995, 2002, 2013, and 2020 at a 15 m spatial resolution were derived from Landsat images with the aid of a hybrid classification approach. The accuracy of the wetland maps was relatively high, with overall accuracies ranging from 86–93%. The findings showed that the critical changes over the period 1995/2020 included the expansion of marine water into coastal lands, showing 129% shoreline erosion; a remarkable increase of 345% in aquaculture ponds; and a reduction of forested wetlands and rice fields/other crops by 32% and 73%, respectively. Although mangrove forests slightly increased for the period 2013/2020, the overall trend was also a reduction of 5%. Our findings show that the substantial increase in aquaculture ponds is at the expense of mangroves, forested wetlands, and rice fields/other crops, while shoreline erosion significantly affected coastal lands, especially mangrove forests. The interaction of a set of environmental and socioeconomic factors were responsible for the dynamics. In particular, SLR was identified as one of the main underlying drivers; however, the rapid changes were directly driven by policies on land-use for economic development in the region. The trends of wetland changes and SLR implicate their significant effects on environment, natural resources, food security, and likelihood of communities in the region sustaining for the long-term. These findings can assist in developing and planning appropriate management strategies and policies for wetland protection and conservation, and for sustainable development in the region.