Soil ecosystem services and human health

Brevik, Eric C.; Pereg, Lily; Steffan, Joshua J.; Burgess, Lynn C.

doi:10.1016/j.coesh.2018.07.003

Cited by 51 publications

(37 citation statements)

References 42 publications

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“…Thirteen wavelengths were finally selected and the wavelengths were 437.3 nm, 441.9 nm, 987. 4 lowest point, indicating that the selected group of spectral wavelengths is the best at this stage. Then, for the reflectance spectral curve, the training set divided by SPXY is used in SPA to perform second characteristic wavelength selection, and the selected characteristic wavelength is used for final modeling.…”

Section: Characteristic Wavelengthsmentioning

confidence: 99%

Estimation of Soil Arsenic Content with Hyperspectral Remote Sensing

Wei

Wang

et al. 2020

Sensors

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With the continuous application of arsenic-containing chemicals, arsenic pollution in soil has become a serious problem worldwide. The detection of arsenic pollution in soil is of great significance to the protection and restoration of soil. Hyperspectral remote sensing is able to effectively monitor heavy metal pollution in soil. However, due to the possible complex nonlinear relationship between soil arsenic (As) content and the spectrum and data redundancy, an estimation model with high efficiency and accuracy is urgently needed. In response to this situation, 62 samples and 27 samples were collected in Daye and Honghu, Hubei Province, respectively. Spectral measurement and physical and chemical analysis were performed in the laboratory to obtain the As content and spectral reflectance. After the continuum removal (CR) was performed, the stable competitive adaptive reweighting sampling algorithm coupled the successive projections algorithm (sCARS-SPA) was used for characteristic band selection, which effectively solves the problem of data redundancy and collinearity. Partial least squares regression (PLSR), radial basis function neural network (RBFNN), and shuffled frog leaping algorithm optimization of the RBFNN (SFLA-RBFNN) were established in the characteristic wavelengths to predict soil As content. These results show that the sCARS-SPA-SFLA-RBFNN model has the best universality and high prediction accuracy in different land-use types, which is a scientific and effective method for estimating the soil As content.

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Section: Characteristic Wavelengthsmentioning

confidence: 99%

Estimation of Soil Arsenic Content with Hyperspectral Remote Sensing

Wei

Wang

et al. 2020

Sensors

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“…They form complex chemical mixtures by reactions due to microorganisms. Very scanty toxicological information is available regarding the health effects of these chemical mixtures (Brevik and Burgess, 2014). As they have very long half-lives, many such organic chemicals are referred to as "persistent organic pollutants."…”

Section: Organic Chemicalsmentioning

confidence: 99%

“…For instance, the soil fungus Exserohilium rostratum caused a fungal meningitis outbreak in the United States in 2012 (Brevik and Burgess, 2013). Most of the protozoans that are found in soil feed on organic matter, including bacteria and algae; however, a few of these cause human parasitic diseases like diarrhea and amebic dysentery (Brevik et al, 2018). Soil serves as a common reservoir for helminthes.…”

Section: Soil Pathogensmentioning

confidence: 99%

Safety of Water Used in Food Production

Bhagwat

2019

Food Safety and Human Health

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“…Soils provide critical functions for society [1][2][3], and throughout history they have been an integral resource base for human survival and advancement. Arguably, "for most of history, few things have mattered more to human communities than their relations with soil" [4] (p. 1627).…”

Section: Introductionmentioning

confidence: 99%

A Well-Being Approach to Soil Health—Insights from Aotearoa New Zealand

et al. 2020

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This paper explores the concept of soil health from a human well-being perspective in Aotearoa New Zealand. Globally, soils play an integral role in wider society and the environment by maintaining a large range of ecosystem services and benefits. As populations and resource constraints increase and food production and food security become growing issues globally, there is a recognition of the importance of defining soil condition or soil health for sustaining all ecosystems, including services and benefits to humans, plants, animals, and micro-organisms. While the ecosystem services approach has helped to illuminate the varied services soils provide, an understanding of the complex human–soil relationships and values has been missing. Those seeking to understand and form concepts about soil health have concentrated on the more inherent biochemical, physical and economic (e.g., productivity) aspects of soils, but not on the human, social or cultural dimensions. It is argued in this paper that soils form an integral part of our social and cultural fabric and are fundamentally important to human and societal well-being. The way humans interact with, value and use soil is a critical part of determining the health and sustainability of soil ecosystems. We discuss how a well-being approach can improve understanding of soil health with respect to societal goals and needs. We believe this type of approach, which includes social and cultural dimensions, provides a more diverse and inclusive knowledge base and perspective to better inform the development of integrative policy. This would lead to improved management and decision-making of land resources and soils in Aotearoa New Zealand and globally.

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Soil ecosystem services and human health

Cited by 51 publications

References 42 publications

Estimation of Soil Arsenic Content with Hyperspectral Remote Sensing

Estimation of Soil Arsenic Content with Hyperspectral Remote Sensing

Safety of Water Used in Food Production

A Well-Being Approach to Soil Health—Insights from Aotearoa New Zealand

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