Developing an early warning land degradation indicator based on geostatistical analysis of Ecosystem Functional Types dynamics

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators Pub Date : 2024-11-09 DOI:10.1016/j.ecolind.2024.112815

Cristina Domingo-Marimon , Małgorzata Jenerowicz-Sanikowska , Lluís Pesquer , Marek Ruciński , Michał Krupiński , Edyta Woźniak , Anna Foks-Ryznar , Mohammad Abdul Quader

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Abstract

Identifying and quantifying ecosystem degradation and recovery is of critical importance for ecosystem health, biodiversity, food security and the livelihoods of local communities. Remote sensing datasets and techniques, particularly land cover maps, provide crucial data for capturing spatial and temporal changes, supporting informed decision-making and targeted interventions. However, these maps often emphasize structural rather than functional attributes and, also due to their thematic and temporal resolution, may not detect early degradation signs. This study evaluates the effectiveness of Ecosystem Functional Attributes (EFAs) and Ecosystem Functional Types (EFTs) as early warning indicators of ecosystem degradation. Using Sentinel-2 derived Normalized Difference Vegetation Index (NDVI) data from 2016 to 2022, we conducted qualitative and quantitative EFA/EFT analysis on two fragile protected areas, Moyowosi Game Reserve (Kigoma region, Tanzania) and the Sheikh Jamal Inani National Park (Cox’s Bazar district, Bangladesh). Firstly, EFA analysis characterized vegetation productivity and seasonality, revealing temporal trends and spatial patterns of change. Secondly, EFTs served as indicators of change levels. Our findings showed significant insights into productivity shifts due to human activities and climate anomalies, identifying specific temporal events and turning points. Variogram-based geostatistical analysis highlighted changes in vegetation diversity’s spatial distribution. Integrating EFA/EFT analysis with geostatistical methods proved effective for early detection of land degradation, surpassing traditional land cover change analysis. Hence, the presented approach forms a robust framework for an early warning system, aimed at monitoring and evaluating environmentally fragile areas and aiding decision-makers in mitigating environmental degradation and promoting sustainable land management.

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基于对生态系统功能类型动态的地质统计分析，开发土地退化预警指标

识别和量化生态系统退化和恢复对生态系统健康、生物多样性、粮食安全和当地社区的生计至关重要。遥感数据集和技术，尤其是土地覆被图，为捕捉空间和时间变化、支持知情决策和有针对性的干预措施提供了重要数据。然而，这些地图通常强调的是结构属性而非功能属性，而且由于其专题和时间分辨率的原因，可能无法发现早期退化迹象。本研究评估了生态系统功能属性（EFAs）和生态系统功能类型（EFTs）作为生态系统退化预警指标的有效性。利用哨兵-2 获得的归一化差异植被指数（NDVI）数据，我们对两个脆弱的保护区--莫约沃西野生动物保护区（坦桑尼亚基戈马地区）和谢赫-贾迈勒-伊纳尼国家公园（孟加拉国科克斯巴扎尔地区）--进行了定性和定量的 EFA/EFT 分析。首先，EFA 分析描述了植被生产力和季节性，揭示了变化的时间趋势和空间模式。其次，EFTs 可作为变化水平的指标。我们的研究结果表明，人类活动和气候异常导致的生产力变化具有重要意义，并确定了特定的时间事件和转折点。基于变异图的地理统计分析凸显了植被多样性空间分布的变化。事实证明，将 EFA/EFT 分析与地质统计方法相结合，可以有效地早期发现土地退化，超过了传统的土地覆被变化分析。因此，所提出的方法形成了一个强大的预警系统框架，旨在监测和评估环境脆弱地区，帮助决策者减缓环境退化，促进可持续土地管理。

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来源期刊

Ecological Indicators 环境科学-环境科学

CiteScore

11.80

自引率

8.70%

发文量

1163

审稿时长

78 days

期刊介绍： The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.