Spatial Assessment of Climate Risk in the Algerian Steppe Based on Long-Term Trends in Temperature and Precipitation (1951–2022)

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Spatial Assessment of Climate Risk in the Algerian Steppe Based on Long-Term Trends in Temperature and Precipitation (1951–2022)

https://doi.org/10.21203/rs.3.rs-8224676/v1

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This study aims to assess spatial climate risk levels in the Algerian steppe by analyzing long-term trends in temperature and precipitation between 1951 and 2022. Using the CRU TS dataset at a 0.5° × 0.5° resolution, Sen’s slope was applied to detect annual trends at each grid cell. Statistically significant trends were classified using percentile thresholds, and a 3×3 matrix was used to combine temperature and precipitation trend categories to derive five levels of climate risk, following the IPCC framework. Results reveal a generalized increase in temperature across the region, with the most pronounced warming occurring in the southern and eastern steppe areas, including Djelfa, M’Sila, Batna, and Tébessa. Precipitation trends are more spatially variable, with statistically significant declines concentrated in the northwestern steppe (e.g., Naâma and El Bayadh), while larger but non-significant decreases affect southern and eastern zones. The combined risk map identifies Biskra, Batna, and western Khenchela as the most exposed areas due to overlapping warming and drying trends. This spatially explicit approach provides a robust basis for climate risk assessment in arid ecosystems and offers valuable insights for targeted adaptation planning and land management in Algeria’s steppe regions.

Climate risk

Algerian steppe

Temperature trend

Precipitation trend

Sen’s slope

In recent decades, global climate change has profoundly altered temperature and precipitation regimes, especially in arid and semi-arid regions, which are among the most sensitive environments to climatic variability (IPCC, 2023; Gutiérrez et al., 2021). The Mediterranean basin, including North Africa, has been identified as a climate change hotspot, where rising temperatures and decreasing rainfall threaten ecosystems, livelihoods, and water security (Lionello & Scarascia, 2018zéquel et al., 2025). Within this broader context, the Algerian steppe—spanning a vast ecotone between the Sahara Desert and the Tellian Atlas—has witnessed growing ecological fragility exacerbated by both natural and anthropogenic pressures.

Changes in air temperature and rainfall patterns significantly influence hydrological processes, evapotranspiration rates, and land degradation dynamics, particularly in drylands (Huang et al., 2016; Crapart et al., 2025). The continued warming trend and shifting rainfall regimes are expected to increase the frequency and intensity of extreme climatic events, such as prolonged droughts (Oubadi et al., 2024) and heatwaves (Oubadi et al., 2025), which are already disrupting steppe agro-pastoral systems and accelerating desertification processes (Bencherif et al., 2021; Belala et al., 2018). Despite these alarming developments, climate risk assessments at fine spatial scales remain scarce across Algerian steppes, especially those based on robust long-term climatic trends.

To address this gap, this study provides a spatially explicit analysis of climate risks across the Algerian steppe zone from 1951 to 2022. Using high-resolution gridded data from the CRU TS dataset (Harris et al., 2020), the analysis estimates linear trends in temperature and precipitation using the non-parametric Sen’s slope estimator, a method well-suited for detecting monotonic trends in noisy climate records (Yue & Wang, 2004). Statistically significant trends are categorized by intensity and combined through a risk matrix adapted from IPCC risk frameworks (IPCC, 2021), enabling a nuanced classification of climate risk levels across the region.

The central objective of this study is to map and interpret climate risk patterns across the Algerian steppe based on long-term observed trends. This approach provides critical insights into the spatial heterogeneity of climate change impacts and can serve as a scientific basis for targeted adaptation planning. In doing so, the study contributes to broader efforts to understand and manage climate vulnerability in dryland socio-ecological systems, particularly under the accelerating pace of global change.

The Algerian steppe zone (Fig. 1) constitutes a vast transitional belt between the fertile Tellian Atlas in the north and the hyper-arid Sahara Desert in the south. This ecoclimatic zone spans approximately 20 million hectares, covering parts of several administrative wilayas such as Naâma, El Bayadh, Djelfa, Laghouat, Saïda, and Tiaret (Aidoud et al., 2006). Characterized by its semi-arid to arid conditions, the steppe plays a critical ecological and socio-economic role as a grazing territory for extensive pastoral systems and as a buffer against desertification.

The region is marked by low and irregular precipitation (ranging from 150 to 400 mm annually), high interannual variability, and high evaporation rates, resulting in fragile ecological balances (Oubadi et al., 2024). Temperature regimes show continental patterns, with hot summers and cold winters, often with large diurnal temperature ranges. The dominant vegetation is composed of steppic grasslands and shrub species (e.g., Stipa tenacissima, Artemisia herba-alba), which are highly sensitive to climatic stresses and land-use pressure (Le Houérou, 1996).

The area is increasingly exposed to climate-related threats, including recurrent droughts, rangeland degradation, and increasing aridity. These vulnerabilities are exacerbated by overgrazing, land-use changes, and insufficient natural regeneration, making the region an important case study for assessing long-term climatic risks and their spatial dynamics (Kious et al., 2024; Oubadi & Faci, 2024).

This study relies on gridded climate data from the Climatic Research Unit Time Series (CRU TS) dataset, version 4.07, which provides monthly temperature and precipitation values at a spatial resolution of 0.5° × 0.5° (Harris et al., 2020). The dataset spans the period from 1951 to 2022 and is widely acknowledged for its accuracy, consistency, and long-term coverage, making it a reliable source for climatological analyses across diverse regions (New et al., 2000; Harris et al., 2014). The selection of the study period is justified by the temporal continuity of the data starting in 1951, with no significant gaps, allowing for robust estimation of long-term climatic trends (Moreno & Hasenauer, 2016).

For the purposes of this analysis, temperature and precipitation data were extracted for all grid points intersecting the Algerian steppe zone. To assess the trends over time, the non-parametric Sen’s slope estimator was applied to each grid point, providing a robust measure of trend magnitude that is less sensitive to outliers and non-normal distributions (Sen, 1968). The significance of these trends was evaluated using the Mann–Kendall test (Mann, 1945; Kendall, 1975) at the 5% level, a widely used method in hydrology and climate studies for detecting monotonic trends in time series (Yue & Wang, 2004).

Temperature trends were classified into three categories based on the distribution of Sen’s slope values across the region, using the 25th and 75th percentiles as thresholds to define low, moderate, and high warming intensities. Precipitation trends were similarly categorized, but with reversed interpretative logic, as negative trends (i.e., decreases in rainfall) are considered to increase climate-related risks (Huang et al., 2016; Crapart et al., 2025). For grid cells where precipitation trends were not statistically significant, a moderate class was assigned by default, to reflect intermediate risk conditions.

To synthesize the information and spatially assess climate risk levels, temperature and precipitation classes were combined using a 3×3 matrix. This matrix-based approach yielded five aggregated climate risk categories, ranging from very low to very high, following the conceptual framework of the Intergovernmental Panel on Climate Change (IPCC, 2021), which emphasizes the compound nature of climate hazards and the importance of integrating multiple climatic variables in risk assessments.

4.1. Mean Annual temperature trend

This Fig. 2 illustrates the spatial distribution of annual mean temperature trends across the Algerian steppe for the period 1951–2022, as calculated using Sen’s slope method. The results show a generalized warming trend across the entire region, with a notable spatial gradient. The strongest warming signals are observed in the central and northeastern parts of the steppe, particularly in the wilayas of Djelfa, Laghouat, and Tébessa, where the Sen’s slope values reach 0.028°C/year in some areas.

Conversely, lower but still positive trends are detected in the southwestern and western steppe, notably within the Naâma, El Bayadh, and Saïda regions. Although these areas exhibit less intense warming compared to the northeastern steppe, the consistent positive trends throughout the map confirm that no part of the steppe has been exempt from warming over the last seven decades.

4.2. Annual Precipitation Trend

Figure 3 displays the spatial distribution of annual precipitation trends across the Algerian steppe between 1951 and 2022, based on Sen’s slope estimates. The trends range from − 2.285 mm/year (low) to − 0.098 mm/year (high), indicating an overall tendency toward decreasing rainfall. Notably, this classification uses an inverted logic, in which smaller (less negative) but statistically significant changes are considered more alarming (High), as they correspond to consistent and detectable decreases, while larger fluctuations with no statistical significance are classified as Low.

The northwestern region, notably in the wilayas of Naâma, northern El Bayadh, and Saïda, is characterized by low Sen’s slope values, corresponding to small but statistically significant decreases in annual precipitation. These trends, although limited in magnitude, are consistent and persistent over the study period.

In contrast, the southern and eastern steppe zones, including Laghouat, Djelfa, and Tébessa, exhibit high Sen’s slope values, indicating larger decreases in precipitation. However, these trends are not statistically significant, due to strong interannual variability, and thus do not reflect a stable long-term shift.

This spatial distribution reveals a distinct contrast: areas with modest but consistent reductions in rainfall are mainly located in the northwest, while more erratic and variable declines occur in the south and east.

4.3. Temperature Trend Classes

The map in Fig. 4 depicts how annual temperature trends across the Algerian steppe have been distributed into three categories—low, moderate, and high—based on Sen’s slope values between 1951 and 2022. The classification was derived using the 25th and 75th percentiles to delimit the intensity thresholds.

A large portion of the steppe falls under the low trend class, indicating relatively modest increases in annual temperature across most of the region. In contrast, a moderate trend is only detected in a confined zone within central Laghouat, suggesting an intermediate rate of warming in that area.

Areas assigned to the high trend category are mainly located in the southwestern part of Naâma and a broad belt within the eastern steppe, including southern Djelfa, M’Sila, Biskra, Batna, Khenchela, and Tébessa. These regions exhibit the most pronounced warming signals recorded in the dataset.

The resulting distribution points to clear regional disparities in the pace of temperature change across the steppe.

4.4. Precipitation Trend Classes

Figure 5 shows the spatial categorization of precipitation trends across the Algerian steppe, calculated using Sen’s slope over the 1951–2022 period. Unlike temperature, precipitation trends were interpreted using an inverse logic: the stronger the negative slope, the greater the potential climatic risk.

The most pronounced decreases in annual precipitation appear in the southern parts of Tlemcen and Sidi Bel Abbès, as well as the northern sector of Naâma, all of which fall into the high decrease category.

Regions classified as moderate decrease extend over a wide corridor spanning the southern areas of Naâma and El Bayadh, as well as portions of Laghouat, the southeast of Djelfa, southern M’Sila, Biskra, Batna, and the western part of Khenchela.

In contrast, the remaining steppe areas show comparatively smaller declines in precipitation over time and are therefore categorized within the low decrease group.

This classification delineates zones where rainfall reduction has been more sustained or marked over the study period.

4.5. Climate Risk Levels

Figure 6. Spatial distribution of climate risk levels across the Algerian steppe (1951–2022), based on the combined classification of temperature and precipitation trends using a 3×3 matrix. The resulting categories range from very low to very high risk, following the IPCC's conceptual framework. This map highlights areas where overlapping climate trends contribute to differentiated levels of exposure and potential vulnerability.

Figure 6 presents the spatial distribution of aggregated climate risk levels across the Algerian steppe, derived from the combined classification of temperature and precipitation trends. The integration of these two variables, structured through a 3×3 matrix, results in five levels of risk—ranging from very low to very high—according to the IPCC’s framework for compound climate impacts.

The very high-risk category is limited to a few steppe areas, particularly within Biskra, Batna, and the western part of Khenchela, where the convergence of strong warming and consistent rainfall decrease is most notable.

A high-risk level is also evident across several zones, including the southern parts of Naâma and El Bayadh, as well as Djelfa and Tébessa, which show notable trends for both climatic variables.

In contrast, a low-risk zone emerges in the northern section of the western steppe, extending eastward to include the northern part of Djelfa, where both temperature and precipitation changes remain limited.

The moderate risk level, representing intermediate combinations of temperature and rainfall trends, occupies the majority of the steppe landscape.

This spatial distribution of risk reflects the interplay between warming intensity and rainfall reduction across different ecological zones within the Algerian steppe.

The results of this study reveal pronounced spatial heterogeneity in both temperature and precipitation trends across the Algerian steppe over the 1951–2022 period. The generalized warming observed throughout the region confirms earlier regional and global assessments identifying the Mediterranean basin and North Africa as highly vulnerable to climate change (Lionello & Scarascia, 2020; IPCC, 2021; Gutiérrez et al., 2021). The central and eastern steppe zones, including areas such as Djelfa, M’Sila, and Tébessa, appear to be warming at a faster rate, a pattern also noted by Oubadi et al. (2025) in their analysis of heatwave intensification in Algeria. This localized acceleration in warming may be linked to regional-scale feedbacks involving land cover degradation, reduced albedo, and increasing atmospheric heat retention.

This spatial heterogeneity may be explained by variations in altitude, land cover, and exposure to Saharan heat advection. The intensification of warming in the central and eastern steppe could further exacerbate ecological degradation, including loss of vegetation cover, increased evapotranspiration, and soil moisture deficits. These findings align with global and regional climate assessments highlighting the vulnerability of arid and semi-arid ecosystems to even small increases in temperature (Huang et al., 2016; IPCC, 2021).

On the other hand, the analysis of precipitation trends presents a more complex picture. While a broad decline in rainfall is detected, its magnitude and statistical significance vary greatly. The most statistically consistent reductions are found in the northwestern steppe—particularly in Naâma, Saïda, and northern El Bayadh— long-term cumulative effects on already fragile water and soil systems. This aligns with the findings of Belala et al. (2018), who reported marked impacts of rainfall shifts on vegetation dynamics in the Algerian steppes. Conversely, areas in the southern and eastern steppe recorded sharper declines in precipitation, but these were often non-significant, suggesting that high interannual variability continues to dominate rainfall behavior in those regions, as also observed by Bencherif et al. (2021).

The combined climate risk map—based on a cross-analysis of temperature and precipitation trends—highlights a pattern of compound vulnerability. Zones such as Biskra, Batna, and western Khenchela emerge as the most at-risk, as they are exposed to both accelerated warming and persistent declines in rainfall. This pattern corroborates similar risk zonations proposed in previous steppe-focused studies (Oubadi & Faci, 2024; Kious et al., 2024). Meanwhile, the northern steppe, stretching from southern Tlemcen to northern Djelfa, retains a relatively low risk profile due to limited trends in both climate variables.

From a methodological perspective, the integration of Sen’s slope and the IPCC-inspired 3×3 matrix provides a transparent and replicable framework for multi-variable climate risk assessment in data-scarce drylands. Comparable approaches have been applied in studies across other semi-arid zones globally (Huang et al., 2016; Crapart et al., 2025), demonstrating the robustness of this combination of trend detection and categorical risk mapping.

Nevertheless, this study is not without limitations. The analysis is based on gridded observational data and does not incorporate projected future scenarios. Furthermore, the current risk assessment does not yet integrate socio-economic exposure or ecosystem resilience indicators, which are essential to translate climatic risk into vulnerability assessments. Addressing these limitations would require combining this spatial climate analysis with land degradation metrics, vegetation monitoring, and local vulnerability indices.

This study provides a comprehensive spatial assessment of climate risk across the Algerian steppe based on long-term observed trends in temperature and precipitation between 1951 and 2022. The findings highlight widespread warming throughout the region and a general tendency toward declining rainfall, with marked spatial disparities in both magnitude and significance.

By combining classified trends of temperature and precipitation through a structured matrix approach, five distinct levels of climate risk were identified. The most vulnerable zones—where warming and drying tendencies intersect—are concentrated in the southern and eastern steppe, particularly in Biskra, Batna, and Khenchela. Conversely, the northern steppe regions, including northern Djelfa and southern Tlemcen, appear to be less exposed to compound climatic stress.

These results emphasize the urgent need for geographically targeted adaptation strategies in the steppe regions most at risk. In this regard, the approach adopted in this study offers a practical tool to support local decision-making and spatial prioritization in climate resilience planning.

Future research should integrate socio-economic indicators and ecosystem response metrics to further refine climate vulnerability assessments. Likewise, extending the analysis to include future climate scenarios would be essential to anticipate and manage the long-term evolution of climate risks under different emissions pathways.

Declaration of competing interest

The author declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Conflict of interest

The author declare that they have no conflicts of interest.

Author Contributions Statement

M.O. conceived the study, designed the methodology, collected and analyzed the data, interpreted the results, and wrote the manuscript. M.O. reviewed and approved the final version of the manuscript.

Funding: I received no financial support for the research, authorship, and/or publication of this article.

Data Availability Statement

This study is based on publicly available gridded climate data from the Climatic Research Unit Time Series (CRU TS) version 4.07 dataset. The CRU TS dataset, which includes monthly temperature and precipitation fields at 0.5° × 0.5° spatial resolution, can be freely accessed from the CRU Data Repository:

https://crudata.uea.ac.uk/cru/data/hrg/

No individual or sensitive data were collected or generated in this study.

All processed datasets and analytical scripts used to compute Sen’s slope estimations, Mann–Kendall trend tests, and climate risk classifications are available from the corresponding author (M.O.) upon reasonable request.

Aidoud, A., Le Floc’h, E., & Le Houérou, H. N. (2006). Les steppes arides du Nord de l’Afrique : écologie, dégradation et restauration. Sécheresse, 17(1–2), 19–30.
Belala, F., Hirche, A., Muller, S.D. et al. Rainfall patterns of Algerian steppes and the impacts on natural vegetation in the 20^th century. J. Arid Land 10, 561–573 (2018). https://doi.org/10.1007/s40333-018-0095-x
Bencherif, S., Dahmani, M. B., Burgas, D., & Manzano, P. (2021). Current social and rangeland access trends among pastoralists in the Western Algerian steppe. Land, 10 (7), 674. https://doi.org/10.3390/land10070674
Crapart, C., Anquetin, S., Blanchet, J., & Diedhiou, A. (2025). Global projections of aridity index for mid and long-term future based on CMIP6 scenarios. EGUsphere, 2025,1-32.https://doi.org/10.5194/egusphere-2024-3710.
Gutiérrez, J.M., R.G. Jones, G.T. Narisma, L.M. Alves, M. Amjad, I.V. Gorodetskaya, M. Grose, N.A.B. Klutse, S. Krakovska, J. Li, D. Martínez-Castro, L.O. Mearns, S.H. Mernild, T. Ngo-Duc, B. van den Hurk, and J.-H. Yoon, 2021: Atlas. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1927–2058, doi: 10.1017/9781009157896.021.
Harris, I., Jones, P. D., Osborn, T. J., & Lister, D. H. (2014). Updated high-resolution grids of monthly climatic observations - the CRU TS3.10 Dataset. International Journal of Climatology, 34(3), 623-642. https://doi.org/10.1002/joc.3711
Harris, I., Osborn, T. J., Jones, P., & Lister, D. (2020). Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Scientific Data, 7, 109. https://doi.org/10.1038/s41597-020-0453-3
Huang, J., Yu, H., Guan, X., Wang, G., & Guo, R. (2016). Accelerated dryland expansion under climate change. Nature Climate Change, 6(2), 166-171. https://doi.org/10.1038/nclimate2837
Huang, J., Yu, H., Guan, X., Wang, G., & Guo, R. (2016). Accelerated dryland expansion under climate change. Nature Climate Change, 6, 166-171.https://doi.org/10.1038/nclimate2837
IPCC (2021): Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, In press, doi:10.1017/9781009157896.
IPCC (2023): Summary for Policymakers. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland, pp. 1-34, doi :10.59327/IPCC/AR6-9789291691647.001
Jézéquel, A., Faranda, D., Drobinski, P., & Lionello, P. (2025). Extreme Event Attribution in the Mediterranean. International Journal of Climatology, e8799. https://doi.org/10.1002/joc.8799
Kendall MG (1975). Rank correlation methods, 4th edn. Charles Griffin, London
Kious, C., Maatoug, M. H., Bouacha, M. I., & Maatoug, Z. Z. (2024). Monitoring vegetation cover trends in the steppe region of western Algeria using MODIS imagery. SAINS TANAH-Journal of Soil Science and Agroclimatology, 21(1), 15-21. https://doi.org/10.20961/stjssa.v21i1.80849
Le Houérou, H. N. (1996). Climate change, drought and desertification. Journal of Arid Environments, 34(2), 133–185. https://doi.org/10.1006/jare.1996.0099
Lionello, P., Scarascia, L. The relation between climate change in the Mediterranean region and global warming. Reg Environ Change 18, 1481–1493 (2018). https://doi.org/10.1007/s10113-018-1290-1
Mann, H.B. (1945). Nonparametric Tests Against Trend. Econometrica 13, 245–259. https://doi.org/10.2307/1907187
Miloud Oubadi, & Mohammed Faci. (2024). Spatio-Temporal Changes of Aridity in the Province of Naâma (Western Algeria). Annals of Arid Zone, 63(3), 41-49. https://doi.org/10.56093/aaz.v63i3.147766
Moreno, A., & Hasenauer, H. (2016). Spatial downscaling of European climate data. International Journal of Climatology, 36(3), 1444-1458. https://doi.org/10.1002/joc.4436
New, M., Hulme, M., & Jones, P. (2000). Representing twentieth-century space-time climate variability. Part II: Development of 1901-96 monthly grids of terrestrial surface climate. Journal of Climate, 13(13), 2217-2238. https://doi.org/10.1175/1520-0442(2000)013<2217:RTCSTC>2.0.CO;2
Oubadi, M., Faci, M. & Pham, Q.B. Drought and aridity trends on the Algerian steppe. Theor Appl Climatol 155, 1541–1551 (2024). https://doi.org/10.1007/s00704-024-04865-2
Oubadi, M., Faci, M. Analysis of the evolution of heatwaves recordings in Algeria during the period 1979–2023. Theor Appl Climatol 156, 218 (2025). https://doi.org/10.1007/s00704-025-05456-5
Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall's tau. Journal of the American Statistical Association, 63(324), 1379-1389. https://doi.org/10.1080/01621459.1968.10480934
Yue, S., & Wang, C. Y. (2004). The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resources Management,18(3),201-218. https://doi.org/10.1023/B:WARM.0000043140.61082.60
Yue, S., & Wang, C. Y. (2004). The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resources Management, 18(3), 201-218. https://doi.org/10.1023/B:WARM.0000043140.61082.60

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You are reading this latest preprint version

Spatial Assessment of Climate Risk in the Algerian Steppe Based on Long-Term Trends in Temperature and Precipitation (1951–2022)

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Version 1

Abstract

Figures

1. Introduction

2. Study Area

3. Methodology

4. Results

4.1. Mean Annual temperature trend

4.2. Annual Precipitation Trend

4.3. Temperature Trend Classes

4.4. Precipitation Trend Classes

4.5. Climate Risk Levels

5. Discussion

6. Conclusion

Declarations

References

Status:

Version 1