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Changes in spring and autumn phenology of temperate plants in recent decades have become iconic bio-indicators of rapid climate change. These changes have substantial ecological and economic impacts. However, autumn phenology remains surprisingly little studied. Although the effects of unfavorable environmental conditions (e.g., frost, heat, wetness, and drought) on autumn phenology have been observed for over 60 y, how these factors interact to influence autumn phenological events remain poorly understood. Using remotely sensed phenology data from 2001 to 2012, this study identified and quantified significant effects of a suite of environmental factors on the timing of fall dormancy of deciduous forest communities in New England, United States. Cold, frost, and wet conditions, and high heat-stress tended to induce earlier dormancy of deciduous forests, whereas moderate heat- and drought-stress delayed dormancy. Deciduous forests in two eco-regions showed contrasting, nonlinear responses to variation in these explanatory factors. Based on future climate projection over two periods (2041–2050 and 2090–2099), later dormancy dates were predicted in northern areas. However, in coastal areas earlier dormancy dates were predicted. Our models suggest that besides warming in climate change, changes in frost and moisture conditions as well as extreme weather events (e.g., drought- and heat-stress, and flooding), should also be considered in future predictions of autumn phenology in temperate deciduous forests. This study improves our understanding of how multiple environmental variables interact to affect autumn phenology in temperate deciduous forest ecosystems, and points the way to building more mechanistic and predictive models.

Dust storms have many negative consequences, and affect all kinds of ecosystems, as well as climate and weather conditions. Therefore, classification of dust storm sources into different susceptibility categories can help us mitigate its negative effects. This study aimed to classify the susceptibility of dust sources in the Middle East (ME) by developing two novel deep learning (DL) hybrid models based on the convolutional neural network–gated recurrent unit (CNN-GRU) model, and the dense layer deep learning–random forest (DLDL-RF) model. The Dragonfly algorithm (DA) was used to identify the critical features controlling dust sources. Game theory was used for the interpretability of the DL model’s output. Predictive DL models were constructed by dividing datasets randomly into train (70%) and test (30%) groups, six statistical indicators being then applied to assess the DL hybrid model performance for both datasets (train and test). Among 13 potential features (or variables) controlling dust sources, seven variables were selected as important and six as non-important by DA, respectively. Based on the DLDL-RF hybrid model – a model with higher accuracy in comparison with CNN-GRU–23.1, 22.8, and 22.2% of the study area were classified as being of very low, low and moderate susceptibility, whereas 20.2 and 11.7% of the area were classified as representing high and very high susceptibility classes, respectively. Among seven important features selected by DA, clay content, silt content, and precipitation were identified as the three most important by game theory through permutation values. Overall, DL hybrid models were found to be efficient methods for prediction purposes on large spatial scales with no or incomplete datasets from ground-based measurements.

The ongoing decline of insect populations highlight the need for long-term ecological monitoring. As part of the “SLAM—Long Term Ecological Study of the Impacts of Climate Change on the Natural Forests of Azores” project, we investigated changes in arthropod diversity and community structure over a ten-year period (2012–2022) in the native forest of the island of Terceira (Azores). Focused on two arthropod assemblages (indigenous and non-indigenous species) monitored with SLAM traps, we asked if there was a distinguishable pattern in the diversity and structure of the studied arthropod subsets in a pristine island native forest. Species richness remained relatively constant. Endemic arthropods dominated and remained stable over time, indicating the forest’s ecological stability. In contrast, the assemblage of native non-endemic arthropods underwent changes, including increased hyperdominance and decreased biomass. The introduced arthropod assemblage showed more erratic dynamics driven by species turnover. Results suggested that temporal variation in each subset may be due to different ecological processes and that niche filtering may limit the establishment and spread of introduced arthropods. This research contributes to our understanding of the temporal dynamics of arthropods in native island forests and highlights the need for ongoing conservation efforts to protect these fragile ecosystems.

Coral reef ecosystems are under increasing pressure from local and regional stressors and a changing climate. Current management focuses on reducing stressors to allow for natural recovery, but in many areas where coral reefs are damaged, natural recovery can be restricted, delayed or interrupted because of unstable, unconsolidated coral fragments, or rubble. Rubble fields are a natural component of coral reefs, but repeated or high-magnitude disturbances can prevent natural cementation and consolidation processes, so that coral recruits fail to survive. A suite of interventions have been used to target this issue globally, such as using mesh to stabilise rubble, removing the rubble to reveal hard substrate and deploying rocks or other hard substrates over the rubble to facilitate recruit survival. Small, modular structures can be used at multiple scales, with or without attached coral fragments, to create structural complexity and settlement surfaces. However, these can introduce foreign materials to the reef, and a limited understanding of natural recovery processes exists for the potential of this type of active intervention to successfully restore local coral reef structure. This review synthesises available knowledge about the ecological role of coral rubble, natural coral recolonisation and recovery rates and the potential benefits and risks associated with active interventions in this rapidly evolving field. Fundamental knowledge gaps include baseline levels of rubble, the structural complexity of reef habitats in space and time, natural rubble consolidation processes and the risks associated with each intervention method. Any restoration intervention needs to be underpinned by risk assessment, and the decision to repair rubble fields must arise from an understanding of when and where unconsolidated substrate and lack of structure impair natural reef recovery and ecological function. Monitoring is necessary to ascertain the success or failure of the intervention and impacts of potential risks, but there is a strong need to specify desired outcomes, the spatial and temporal context and indicators to be measured. With a focus on the Great Barrier Reef, we synthesise the techniques, successes and failures associated with rubble stabilisation and the use of small structures, review monitoring methods and indicators, and provide recommendations to ensure that we learn from past projects.

Pieces are in place, but need coordination and policy focus The massive investment of resources devoted to monitoring and assessment of economic and societal indicators in the United States is neither matched by nor linked to efforts to monitor and assess the ecosystem services and biodiversity that support economic and social well-being. Although national-scale assessments of biodiversity ( 1 ) and ecosystem indicators ( 2 ) have been undertaken, nearly a decade has elapsed since the last systematic assessment ( 2 ). A 2011 White House report called for a national biodiversity and ecosystem services assessment ( 3 ), but the initiative has stalled. Our aim here is to stimulate the process and outline a credible framework and pathway for an ongoing assessment of ecosystem functioning (see the photo). A national assessment should engage diverse stakeholders from multiple sectors of society and should focus on metrics and analyses of direct relevance to policy decisions, from local to national levels. Although many technical or science-focused components are in place, they need to be articulated, distilled, and organized to address policy issues.

In the context of the continuous degradation of the global environment, ecological restoration has become a primary task in global environmental governance. In this process, remote sensing technology, as an advanced monitoring and analysis tool, plays a key role in monitoring ecological restoration. This article reviews the application of remote sensing technology in ecological restoration monitoring. Based on a comprehensive analysis of the literature in the field of ecological remote sensing, it systematically summarizes the major in-orbit spaceborne and airborne sensors and their related products. This article further proposes a series of evaluation indicators for ecological restoration from four aspects: forests, soil, water, and the atmosphere, and elaborates on the calculation methods for these indicators. In addition, this paper also summarizes the methods for evaluating the effectiveness of ecological restoration, including subjective evaluation, objective evaluation, and comprehensive evaluation methods. Finally, we analyze the challenges faced by remote sensing technology in evaluating ecological restoration effectiveness, such as issues with the precision of indicators extraction, the limitations of spatial resolution, and the diversity of evaluation methods. This review also looks forward to future ecological restoration technologies, such as the potential applications of integrated aerospace and terrestrial remote sensing, multi-data fusion, and machine learning technologies. This study reveals the effectiveness of remote sensing technology in ecological restoration monitoring, aiming to provide efficient tools and innovative strategies for future remote sensing monitoring and assessment of ecological restoration.

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series, even more exciting results can be expected, especially about range shifts. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented.

The tri-spine horseshoe crab, Tachypleus tridentatus , is a threatened species that inhabits coastal areas from South to East Asia. A Conservation management system is urgently required for managing its nursery habitats, i.e., intertidal flats, especially in Japan. Habitat suitability maps are useful in drafting conservation plans; however, they have rarely been prepared for juvenile T . tridentatus . In this study, we examined the possibility of constructing robust habitat suitability models (HSMs) for juveniles based on topographical data acquired using unmanned aerial vehicles and the Structure from Motion (UAV-SfM) technique. The distribution data of the juveniles in the Tsuyazaki and Imazu intertidal flats from 2017 to 2019 were determined. The data were divided into a training dataset for HSM construction and three test datasets for model evaluation. High accuracy digital surface models were built for each region using the UAV-SfM technique. Normalized elevation was assessed by converting the topographical models that consider the tidal range in each region, and the slope was calculated based on these models. Using the training data, HSMs of the juveniles were constructed with normalized elevation and slope as the predictor variables. The HSMs were evaluated using the test data. The results showed that HSMs exhibited acceptable discrimination performance for each region. Habitat suitability maps were built for the juveniles in each region, and the suitable areas were estimated to be approximately 6.1 ha of the total 19.5 ha in Tuyazaki, and 3.7 ha of the total 7.9 ha area in Imazu. In conclusion, our findings support the usefulness of the UAV-SfM technique in constructing HSMs for juvenile T . tridentatus . The monitoring of suitable habitat areas for the juveniles using the UAV-SfM technique is expected to reduce survey costs, as it can be conducted with fewer investigators over vast intertidal zones within a short period of time.

The Grain for Green Project (GGP) is an essential ecological system protection and restoration measure which can effectively improve the ecological environment. Constructing ecological monitoring system and obtaining ecological parameters can scientifically evaluate the ecological benefits of the GGP, consolidate the existing achievements, take the road of high-quality development, and promote the construction of a national ecological civilization. Firstly, an index system was constructed based on the factors driving forest ecosystem functions, involving climate (thermal and moisture conditions), vegetation types, and typical ecological zones. Then, GIS spatial analysis technology and the merging criteria index method were used to identify GGP ecological function monitoring zones. Finally, according to the scale of the project, the spatial distribution of existing stations, typical ecological zones, and the density of monitoring stations, the eco-efficiency monitoring stations, were arranged in an overall way, which constitutes the GGP ecological monitoring network. The results showed that the ecological function monitoring zones of GGP included 77 divisions, and 99 ecological monitoring stations (20 compatible level-1 stations, 31 compatible level-2 stations, 18 professional level-1 stations, and 30 professional level-2 stations) were arranged. Among them, 83 are located in national major ecosystem protection and restoration engineering areas (NMEPREA), 79 in national ecological fragile areas (NEFA), 41 in national ecological barrier areas (NEBA), and 58 in national key ecological function areas (NKEFA). The proportion of types of NMEPREA, NEFA, NEBA, and NKEFA covered by monitoring is 66.7%, 100%, 100%, and 76%, respectively. The ecological monitoring system of GGP can not only meet the monitoring needs of the GGP but also effectively monitor the effectiveness of protection and restoration of typical ecological zones. In addition, this study can provide a methodological basis for other countries or ecological projects to build a more scientific and reasonable ecological monitoring system.