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Simple Summary: Based on the "Hutchinson niche hypothesis" and the "Eltonian Noise Hypothesis" about ecological niches, as well as the "resource dependent hypothesis" about biotic interactions, this study integrated climate data, host plants, and empirical expert maps to predict potential distributions based on the Maxent and random forest (RF) models. Utilizing the species richness of host plants as a surrogate for biotic interactions was a simple and effective way to significantly improve the predictive performance of Species Distribution Models (SDMs). Given climate change, their distribution is significantly shrinking, increasing their threatened level in the future. Abiotic factors could not only directly affect the distribution of T. aureus but also indirectly impact it through host plants. This was evident in the delayed response of T. aureus to climate change compared to its host plants, which is called the "hysteresis effect" caused by biotic interactions. Considering its narrow altitude range, vulnerability to climate change, host plant specialization, and the survival status of its highly dependent host plants, we recommended designating T. aureus as currently vulnerable. The accurate prediction of the niche and the potential distribution of a species is a fundamental and key content for biodiversity related research in ecology and biogeography, especially for protected species. Biotic interactions have a significant impact on species distribution but are often overlooked by SDMs. Therefore, it is crucial to incorporate biotic interaction factors into SDMs to improve their predictive performance. The Teinopalpus aureus Mell, 1923 is endemic to high altitudes in southern East Asia, renowned for its exceptional beauty and rarity. Despite the significant conservation value, its spatial distribution remains unclear. This study integrated climate data, host plants, and empirical expert maps to predict its potential distribution. The results indicated that utilizing the species richness of host plants as a surrogate for biotic interactions was a simple and effective way to significantly improve the predictive performance of the SDMs. The current suitable distribution of T. aureus and its host plants is highly fragmented, primarily concentrated in the Nanling and Wuyi Mountains, and consisting of numerous isolated small populations. Given climate change, their distribution is significantly shrinking, increasing the threatened level in the future. Especially for the population of T. aureus hainani Lee, the likelihood of extinction is extremely high. Abiotic factors not only directly affect the distribution of T. aureus but also indirectly impact it through the host plants. This was evident in the delayed response of T. aureus to climate change compared to its host plants, which is called the "hysteresis effect" caused by biotic interactions. Overall, we tentatively suggest regarding T. aureus as a vulnerable species. In the future, multiple measures could be taken to indirectly protect the feeding and habitat resources of T. aureus by conserving host plants, thereby enhancing its survival prospects. [ABSTRACT FROM AUTHOR]

Climate change is altering the geographical distribution and abundance of species. Abundant genetic variation generally indicates a stronger adaptability and evolutionary potentiality, especially in case of sharply changing climates or environments. With the past global climate fluctuations, especially the climate oscillation since the Quaternary, the global temperature changes related to glaciation, many relict plant species have formed possible refugia in humid subtropical/warm temperate forests, thus retaining a high level of genetic diversity patterns. Based on the contraction and expansion of the geographical distribution of Taxus wallichiana Zucc. in the past driven by climate change, combined with the contemporary genetic diversity modeling, the distribution performance of Taxus wallichiana Zucc. in future climate change was predicted. The areas of highly suitable habitat will increase with climate change in the future. There were continuous and stable high suitable areas of T. wallichiana in the southeastern Tibet and northwestern Yunnan as long-term stable climate refugia. We made the genetic landscape surface of T. wallichiana complex and discovered geographical barriers against gene flow. Genetic barriers spatially isolated the center of genetic diversity into three regions: west (east Himalaya), middle (Yunnan plateau, Sichuan basin, Shennongjia, and the junction of Guizhou and Guangxi provinces), and east (Mt. Huangshan and Fujian). Southern Tibet was isolated from other populations. The central and western Yunnan, the Sichuan basin, and surrounding mountains were isolated from the southern China populations. We found that the positive correlationships between the present species genetic diversity and suitability index during LGM, MH, and 2070. This infers that T. wallichiana has provisioned certain genetic diversity and has strong evolutionary potential under conditions of climate change. [ABSTRACT FROM AUTHOR]

Invasion by non-native tree species is an environmental and societal challenge requiring predictive tools to assess invasion dynamics. The frequent scale mismatch between such tools and on-ground conservation is currently limiting invasion management. This study aimed to reduce these scale mismatches, assess the success of non-native tree invasion and determine the environmental factors associated to it. A hierarchical scaling approach combining species distribution models (SDMs) and satellite mapping at very high resolution (VHR) was developed to assess invasion by Acacia dealbata in Peneda-Gerês National Park, the only national park in Portugal. SDMs were first used to predict the climatically suitable areas for A. dealdata and satellite mapping with the random-forests classifier was then applied toWorldView-2 very-high resolution imagery to determine whether A. dealdata had actually colonized the predicted areas (invasion success). Environmental attributes (topographic, disturbance and canopy-related) differing between invaded and non-invaded vegetated areas were then analyzed. The SDM results indicated that most (67%) of the study area was climatically suitable for A. dealbata invasion. The onset of invasion was documented to 1905 and satellite mapping highlighted that 12.6% of study area was colonized. However, this species had only colonized 62.5% of the maximum potential range, although was registered within 55.6% of grid cells that were considerable unsuitable. Across these areas, the specific success rate of invasion was mostly below 40%, indicating that A. dealbata invasion was not dominant and effective management may still be possible. Environmental attributes related to topography (slope), canopy (normalized difference vegetation index (ndvi), land surface albedo) and disturbance (historical burnt area) differed between invaded and non-invaded vegetated area, suggesting that landscape attributes may alter at specific locations with Acacia invasion. Fine-scale spatial-explicit estimation of invasion success combining SDM predictions with VHR invasion mapping allowed the scale mismatch between predictions of invasion dynamics and on-ground conservation decision making for invasion management to be reduced. Locations with greater potential to suppress invasions could also be defined. Uncertainty in the invasion mapping needs to be accounted for in the interpretation of the results. [ABSTRACT FROM AUTHOR]

Oxytropis ochrocephala Bunge is an herbaceous perennial poisonous weed. It severely affects the production of local animal husbandry and ecosystem stability in the source region of Yellow River (SRYR), China. To date, however, the spatiotemporal distribution of O. ochrocephala is still unclear, mainly due to lack of high-precision observation data and effective methods at a regional scale. In this study, an efficient sampling method, based on unmanned aerial vehicle (UAV), was proposed to supply basic sampling data for species distribution models (SDMs, BIOMOD in this study). A total of 3232 aerial photographs were obtained, from 2018 to 2020, in SRYR, and the potential and future distribution of O. ochrocephala were predicted by an ensemble model, consisting of six basic models of BIOMOD. The results showed that: (1) O. ochrocephala mainly distributed in the southwest, middle, and northeast of the SRYR, and the high suitable habitat of O. ochrocephala accounted for 3.19%; (2) annual precipitation and annual mean temperature were the two most important factors that affect the distribution of O. ochrocephala, with a cumulative importance of 60.45%; and (3) the distribution probability of O. ochrocephala tends to increase from now to the 2070s, while spatial distribution ranges will remain in the southwest, middle, and northeast of the SRYR. This study shows that UAVs can potentially be used to obtain the basic data for species distribution modeling; the results are both beneficial to establishing reasonable management practices and animal husbandry in alpine grassland systems. [ABSTRACT FROM AUTHOR]