Selecting agri-environmental indicators for monitoring and assessment of environmental management in the example of landscape parks in Poland

Kubacka, Marta; Bródka, Sylwia; Macias, Andrzej

doi:10.1016/j.ecolind.2016.07.004

Cited by 12 publications

(6 citation statements)

References 35 publications

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“…Intensive changes in agriculture, production techniques, forestry, construction or industry, transport and tourism management, and on a wider scale, in the world economy have resulted in the need to monitor the landscape and study its changes being discussed more and more often [17,18]. Changes are analyzed, both in relation to urban and suburban landscapes [19,20], agricultural and forest landscapes [21][22][23], or protected areas [24][25][26]. It is worth noting that, as a result of more and more intensive landscape changes, the main objective of landscape change research has changed.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Landscape Transformations within Landscape Parks in Poland in the 21st Century

Krajewski

2019

Sustainability

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One of the most problematic forms of nature protection in Poland relates to landscape parks. They include the most valuable landscapes, but the areas within the landscape park still have economic uses. Therefore, the monitoring of landscape changes within landscape parks is necessary in order to properly manage these forms of protection. The main objective of the study was to monitor the scale and nature of landscape transformations within the boundaries of landscape parks in Poland during the period 2000–2018 and to assess the possibility of using the landscape change index (LCI) to monitor the intensity of landscape transformations within this type of protected area. Preliminary analyses of the transformations within all landscape parks in Poland showed an upward trend, both in terms of the number of types of identified landscape changes as well as their area. In spite of the large diversity and degree of transformation in landscape parks, several dominant processes can be observed. The largest number and area of changes during each of the analyzed periods were found in transformations within forest landscapes (temporary and permanent deforestation and forest maturation), which constitute the dominant type of land cover within most of the landscape parks. In open landscapes, changes mainly relate to afforestation and natural succession in meadows, pastures, and arable land, as well as the transformation of arable land into mining areas. Twelve case studies, covering all landscape parks in Lower Silesia, have shown that the LCI is an excellent tool for monitoring the intensity of landscape changes, but it is dependent on the accuracy of the source data. The analyses confirmed that, during the study periods, the changes in all 12 Lower Silesian landscape parks were at a low level, but their particular intensification took place in the years from 2012 to 2018. The highest LCI was found in the area where a natural disaster had occurred (air tornado), which destroyed huge areas of forest in landscape parks. After changes in the forest landscape, the most frequently identified type of change in 2006–2012 was the transformation of non-forest landscapes into forest landscapes. The main reason for such changes was the expansion of forest into abandoned arable land, meadows, and pastures. The use of the Corine Land Cover database to calculate the LCI and monitor the intensity of landscape change revealed a low usability of the database for the year 2000 and a high usability for data from 2006 to 2018.

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Section: Introductionmentioning

confidence: 99%

Monitoring of Landscape Transformations within Landscape Parks in Poland in the 21st Century

Krajewski

2019

Sustainability

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“…In the first stage, the theme of interest was defined and the concepts that best represent this theme were explored in the titles, abstracts, and keywords of the scientific documents. In the second stage, databases were consulted and 115 documents were collected from the Scopus (58), Web of Science (39), and Science Direct (18) platforms. After excluding duplicate publications, we analyzed the content of the 63 publications available in English.…”

Section: Methodsmentioning

confidence: 99%

“…Water balance, decreased availability, nutrient concentration, presence of toxic components, and salinization of water stand out as state indicators [39,51]. Among the documents that considered impact, the main indicators used were dissolved oxygen, electrical conductivity, hydrogen potential (pH), increased biochemical oxygen demand, and chlorophyll concentration [8,68].…”

Section: Dpsir Structure Parameters and Componentsmentioning

confidence: 99%

The Drivers-Pressures-State-Impact-Response Model to Structure Cause−Effect Relationships between Agriculture and Aquatic Ecosystems

et al. 2021

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Different segments of society have shown interest in understanding the effects of human activities on ecosystems. To this end, the aim of this article is to analyze the scientific literature on the application of the Drivers-Pressures-State-Impact-Response (DPSIR) conceptual model to identify the parameters used to describe the causal interactions that occur between agriculture and aquatic ecosystems at the watershed scale. In this way, descriptive indicators were established for the data of 63 publications collected through Scopus, Web of Science, and Science Direct. The results confirm the great heterogeneity in the interpretation of the pressure, state, and impacts components. Part of this discrepancy can be attributed to the use of different indicators, as the model is flexible and generic. Overall, the DPSIR is a tool used not only in the scientific field, but also has demonstrated its potential to guide public policy formulation, planning, and decision-making in water resource management.

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“…In theory, targeting decisions are based on carefully defined objectives and priority criteria [13,14] and quantitative indicators of those criteria [15][16][17]. In practice, poorly defined criteria and insufficient indicator data often result in ineffective targeting and suboptimal outcomes [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Spatial Targeting of Agricultural Support Measures: Indicator-Based Assessment of Coverages and Leakages

LaFevor

Ponette‐González

Larson

et al. 2021

Land

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Agricultural support programs distribute payments to farms based on a diverse set of policy objectives. Adequate targeting of this support to priority areas is key to efficient and effective policy. We evaluated the targeting strategy of a national-level program in Mexico that distributed support based on seven criteria that prioritized poor smallholder farming communities at high risk of cropland failure. We used a series of logistic models to assess the coverage and leakage rates of the program’s targeting strategy and found rates of about 80 and 20 percent, respectively. We also found significant differences between the targeting priorities specified in program rules and the observed distribution of support measures. In general, the program favored arid and semi-arid regions at high risk of soil erosion but neglected smallholder farms in high-poverty regions with elevated rates of cropland failure. Our findings highlight the continued lack of financial support for smallholder agriculture in Mexico, despite program rules and priority statements that stress the vulnerability of this sector. This study also illustrates the important role of spatial targeting in better aligning agricultural support payments with stated policy priorities. This alignment is often overlooked in ex-post assessment, but it is critical for improving targeting precision, equity, and overall policy effectiveness.

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Selecting agri-environmental indicators for monitoring and assessment of environmental management in the example of landscape parks in Poland

Cited by 12 publications

References 35 publications

Monitoring of Landscape Transformations within Landscape Parks in Poland in the 21st Century

Monitoring of Landscape Transformations within Landscape Parks in Poland in the 21st Century

The Drivers-Pressures-State-Impact-Response Model to Structure Cause−Effect Relationships between Agriculture and Aquatic Ecosystems

Spatial Targeting of Agricultural Support Measures: Indicator-Based Assessment of Coverages and Leakages

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