The present and future of grassland restoration

Restoration Ecology, Год журнала: 2021, Номер 29(S1)

Опубликована: Март 16, 2021

Grasslands contribute greatly to biodiversity and human livelihoods; they support 70% of the world's agricultural area, but are heavily degraded by land use. Grassland restoration research management receives less attention than forests or freshwater habitats, although grasslands critical for sustaining ecosystems multifunctionality capacity biodiversity. In this article, we introduce a Special Issue which considers major trends prospects in grassland restoration. We identified three key topics: First, must confront widespread seed site limitations, new monitoring methods, including remote sensing techniques, projects. Second, highlight that restored typically require ongoing disturbance is required determine optimal approaches implementing during Third, global regional agendas should be harmonized with site‐level goals, syntheses current knowledge needs guide across scales. also identify gaps filled, challenges face future: (1) need careful target vegetation selection climate‐adaptive restoration; (2) lack dynamics several regions types, drylands (sub)tropical regions; (3) increased importance species arrival sequence, high stochasticity establishment; finally (4) issues post‐restoration guarantee long‐term sustainability sites. A generation projects bridge these necessary mitigate environmental spanning localities globe as commence UN Decade on Ecosystem Restoration.

Язык: Английский

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A Review of Estimation Methods for Aboveground Biomass in Grasslands Using UAV

Remote Sensing, Год журнала: 2023, Номер 15(3), С. 639 - 639

Опубликована: Янв. 21, 2023

Grasslands are one of the world’s largest ecosystems, accounting for 30% total terrestrial biomass. Considering that aboveground biomass (AGB) is most essential ecosystem services in grasslands, an accurate and faster method estimating AGB critical managing, protecting, promoting sustainability. Unmanned aerial vehicles (UAVs) have emerged as a useful practical tool achieving this goal. Here, we review recent research studies employ UAVs to estimate grassland ecosystems. We summarize different methods establish comprehensive workflow, from data collection field processing. For purpose, 64 articles were reviewed, focusing on several features including study site, species composition, UAV platforms, flight parameters, sensors, measurement, indices, processing, analysis methods. The results demonstrate there has been increase scientific evaluating use estimation grasslands during period 2018–2022. Most carried out three countries (Germany, China, USA), which indicates urgent need other locations where ecosystems abundant. found RGB imaging was commonly used suitable at moment, terms cost–benefit processing simplicity. In 50% studies, least vegetation index AGB; Normalized Difference Vegetation Index (NDVI) common. popular linear regression, partial squares regression (PLSR), random forest. Studies spectral structural showed models incorporating both types outperformed utilizing only one. also observed limited spatially temporally. example, small number papers conducted over years multiple places, suggesting protocols not transferable time points. Despite these limitations, light rapid advances, anticipate will continue improving may become commercialized farming applications near future.

Язык: Английский

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Prediction and uncertainty in restoration science

Restoration Ecology, Год журнала: 2021, Номер 32(8)

Опубликована: Март 16, 2021

Restoration outcomes are notoriously unpredictable and this challenges the capacity to reliably meet goals. To harness ecological restoration's full potential, significant advances predictive must be made in restoration ecology. We outline a process for predicting outcomes, based on model of iterative forecasting. then describe six that impede capabilities and, each, an agenda overcoming challenge. Key include lack clear goals, insufficient knowledge why vary, difficulty quantifying known drivers variation prior initiation projects, uncertainty, need scale up local understanding guide large‐scale efforts, temporally variable conditions hinder long‐term forecast accuracy. Meeting these will require research resolve key outcomes; however, there is also critical begin forecasting efforts ecology immediately. Although early may limited practical utility, iterating between development evaluation data needs, minimize lead predictions practitioners can confidently embrace. In turn, robust help enhance cost‐effectiveness, policy decisions see out promise Decade Ecosystem Restoration.

Язык: Английский

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Digital whole-community phenotyping: tracking morphological and physiological responses of plant communities to environmental changes in the field

Frontiers in Plant Science, Год журнала: 2023, Номер 14

Опубликована: Май 9, 2023

Plant traits are informative for ecosystem functions and processes help to derive general rules predictions about responses environmental gradients, global change perturbations. Ecological field studies often use ‘low-throughput’ methods assess plant phenotypes integrate species-specific community-wide indices. In contrast, agricultural greenhouse or lab-based employ ‘high-throughput phenotyping’ individuals tracking their growth fertilizer water demand. ecological studies, remote sensing makes of freely movable devices like satellites unmanned aerial vehicles (UAVs) which provide large-scale spatial temporal data. Adopting such community ecology on a smaller scale may novel insights the phenotypic properties communities fill gap between traditional measurements airborne sensing. However, trade-off resolution, resolution scope respective study requires highly specific setups so that fit scientific question. We introduce small-scale, high-resolution digital automated phenotyping as source quantitative trait data in provides complementary multi-faceted communities. customized an system its mobile application ‘digital whole-community (DWCP), capturing 3-dimensional structure multispectral information demonstrated potential DWCP by recording experimental land-use treatments over two years. captured changes morphological physiological response mowing thus reliably informed land-use. manually measured community-weighted mean species composition remained largely unaffected were not these treatments. proved be efficient method characterizing communities, complements other trait-based ecology, indicators states, forecast tipping points associated with irreversible ecosystems.

Язык: Английский

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UAV-derived models of vegetation characteristics do not transfer to extreme drought and wet conditions across a northern Arizona landscape

Landscape Ecology, Год журнала: 2025, Номер 40(3)

Опубликована: Март 7, 2025

Язык: Английский

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Prairie management practices influence biodiversity, productivity and surface–atmosphere feedbacks

New Phytologist, Год журнала: 2025, Номер unknown

Опубликована: Май 14, 2025

Summary Grassland restoration efforts aim to reestablish vegetation cover and maintain ecosystem services. However, there is a lack of systematic evaluation the effects grassland management strategies on biodiversity, productivity surface–atmosphere feedbacks affecting climate. Through multiyear experiment in tallgrass prairie site Nebraska, USA, we investigated how different practices affected using combination situ measurements airborne hyperspectral thermal remote sensing. Our findings indicated that treatments diversity, energy balance. Higher diversity plots had higher plant growth, albedo, canopy water content lower surface temperature, indicating clear processes influencing mass energy. The coherent responses multiple sensing indices illustrate potential cobenefits enhance biodiversity mitigate climate change through feedbacks, offering new strategy address challenges loss ecosystems.

Язык: Английский

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Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral‐ and three‐dimensional information from UAV‐based aerial imagery

Remote Sensing in Ecology and Conservation, Год журнала: 2022, Номер 8(4), С. 536 - 550

Опубликована: Март 4, 2022

Abstract The alpine treeline ecotone is expected to move upwards in elevation with global warming. Thus, mapping ecotones crucial monitoring potential changes. Previous remote sensing studies have focused on the usage of satellites and aircrafts for ecotone. However, can be highly heterogenous, thus use imagery higher spatial resolution should investigated. We evaluate using unmanned aerial vehicles (UAVs) collection ultra‐high land covers. acquired field reference data from 32 sites along a 1100 km latitudinal gradient Norway (60–69°N). Before classification, we performed superpixel segmentation UAV‐derived orthomosaics assigned cover classes segments: rock, water, snow, shadow, wetland, tree‐covered area five within ridge‐snowbed gradient. calculated features providing spectral, textural, three‐dimensional vegetation structure, topographical shape information classification. To influence acquisition time during growing season geographical variations, four sets classifications: global, seasonal‐based, regional‐based seasonal‐regional‐based. found no differences overall accuracy (OA) between different classifications, model observations irrespective timing region had an OA 73%. When accounting similarities closely related gradient, increased 92.6%. spectral visible, red‐edge near‐infrared bands most important predict classes. Our results show that UAVs efficient ecotones, get accurate maps. This overcome constraints short field‐season or low‐resolution data.

Язык: Английский

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Pasture Biomass Estimation Using Ultra-High-Resolution RGB UAVs Images and Deep Learning

Remote Sensing, Год журнала: 2023, Номер 15(24), С. 5714 - 5714

Опубликована: Дек. 13, 2023

The continuous assessment of grassland biomass during the growth season plays a vital role in making informed, location-specific management choices. implementation precision agriculture techniques can facilitate and enhance these decision-making processes. Nonetheless, depends on availability prompt precise data pertaining to plant characteristics, necessitating both high spatial temporal resolutions. Utilizing structural spectral attributes extracted from low-cost sensors unmanned aerial vehicles (UAVs) presents promising non-invasive method evaluate traits, including above-ground height. Therefore, main objective was develop an artificial neural network capable estimating pasture by using UAV RGB images canopy height models (CHM) growing over three common types paddocks: Rest, bale grazing, sacrifice. Subsequently, this study first explored variation color-related features derived statistics CHM image values under different levels growth. Then, ANN model trained for accurate volume estimation based rigorous employing statistical criteria ground observations. demonstrated level precision, yielding coefficient determination (R2) 0.94 root mean square error (RMSE) 62 (g/m2). evaluation underscores critical ultra-high-resolution photogrammetric CHMs red, green, blue (RGB) capturing meaningful variations enhancing model’s accuracy across diverse paddock types, rest, sacrifice paddocks. Furthermore, sensitivity areas with minimal or virtually absent period is visually generated maps. Notably, it effectively discerned low-biomass regions grazing paddocks reduced impact compared other types. These findings highlight versatility range scenarios, well suited deployment various environmental conditions.

Язык: Английский

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Drought effects on tree mortality and regeneration in northern California

Forest Ecology and Management, Год журнала: 2024, Номер 563, С. 121969 - 121969

Опубликована: Май 20, 2024

The 2012–2016 California drought was the most severe in state's recorded history, contributing to death of millions trees. Through sampling 54 (0.25 ha) plots northern and employing standard dendrochronological techniques this study compared tree mortality regeneration patterns before, during, after California's recent record-setting both montane costal environments. This evaluated 1) influence habitat competitive covariates on trends using ridge regression analysis; 2) seedling/sapling establishment dates dendrochronology Superposed Epoch Analysis explore climate forest demographics. Results showed two related climatic environments: (1) years with high rates were positively associated water deficit (CWD) 1–2 preceding during dates; (2) significantly below-average CWD year. In sites, pre-drought greater at wet sites than dry drought-related canopy openness. coastal environments, maximum temperature topographic position (e.g., upper slope sites). Drought-related occurred primarily trees smaller 40 cm diameter breast height (DBH, 1.37 m) forests, exclusively 80 DBH or Our findings also indicate that current demographic will likely reduce diversity future, especially For example, environments white pine species (Pinus lambertiana P. monticola) other weighted towards advanced shade-tolerant fir (Abies) (median age 34 years). These highlight effects fire exclusion, need for targeted management, including reducing density returning process, aimed decreasing mortality, increasing shade-intolerant pines). Management should preferentially retain medium large trees, which demonstrated less vulnerability enhance resilience forests.

Язык: Английский

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Understanding spatio-temporal complexity of vegetation using drones, what could we improve?

Journal of Environmental Management, Год журнала: 2024, Номер 373, С. 123656 - 123656

Опубликована: Дек. 10, 2024

Язык: Английский

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