Achieving Land Degradation Neutrality as an Integral Indicator of Land Ecosystems Adaptation to Climate Change in the Caspian Region

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

Adaptation to climate change is one of the highest priorities on national and regional agendas. Various approaches are proposed to assess the effectiveness of adaptation measures: valuation of ecosystem services, changes in total carbon stocks, ecosystem and community-based adaptation, actual climate change indicators and others. Currently, there are no indicators of the effectiveness of climate change adaptation measures in either the regulatory framework or the national statistical system of Russia. None of the eight SDG target 13 indicators are developed in the Rosstat system. In this paper, we examine the possibility of using land degradation neutrality (LDN) as an integrated indicator to assess the adaptation of terrestrial ecosystems to climate change. We studied the territories of the administrative regions of the countries bordering the Caspian Sea, for which an analysis of LDN achievement was carried out in terms of indicators of land cover dynamics, land productivity dynamics and soil organic carbon stock dynamics. Land productivity dynamics play a leading role in the overall assessment of LDN for the Caspian region. The analysis of land transitions within the identified integral classes of productivity dynamics shows that the maintenance and change of adaptive potential and degradation risks within these classes is uneven. According to our calculations, the condition of land in a significant part of the Caspian region improved in 2016–2020 compared to the baseline period 2001–2015. In general, land productivity is relatively high during this period, confirming the high potential for adaptation to climate change in recent years. Intensified exploitation of pasture systems, natural deserts and croplands leads to their increased degradation, although a significant part of them remains stable in the face of current natural and climatic changes. Some natural deserts and rangelands (due to reduced anthropogenic pressure) and arable lands (due to the application of sustainable land management practices) are improving, but their share in the region is small. Forested areas account for a significant proportion of improved land, so it can be argued that successful forest management practices are a priority and have a high adaptive capacity in the Caspian region. The observed trends in land dynamics and productivity are in good agreement with recorded and projected climate changes in the Caspian region. This allows for a generally positive assessment of the experience of using the LDN approach in the Caspian region to assess adaptation to climate change.

Full Text

Restricted Access

About the authors

G. S. Kust

Institute of Geography of the Russian Academy of Sciences

Author for correspondence.
Email: kust@igras.ru
Russian Federation, Moscow

V. A. Lobkovsky

Institute of Geography of the Russian Academy of Sciences

Email: kust@igras.ru
Russian Federation, Moscow

O. V. Andreeva

Institute of Geography of the Russian Academy of Sciences

Email: kust@igras.ru
Russian Federation, Moscow

D. S. Shklyaeva

Institute of Geography of the Russian Academy of Sciences

Email: kust@igras.ru
Russian Federation, Moscow

References

  1. Akbari M., Baubekova A., Roozbahani A., Gafurov A., Shiklomanov A., Rasouli K., Ivkina N., Klöve B., Torabi Haghighi A. Vulnerability of the Caspian Sea shoreline to changes in hydrology and climate. Environ. Res. Lett., 2020, vol. 15, no. 11, art. 115002. https://doi.org/10.1088/1748–9326/abaad8
  2. Andreeva O.V., Kust G.S. Land assessment in Russia based on the concept of land degradation neutrality. Reg. Res. Russ., 2020, vol. 10, no. 4, pp. 593–602. https://doi.org/10.1134/S2079970520040127
  3. Andreeva O.V., Kust G.S., Lobkovsky V.A. Sustainable land management and land degradation neutrality. Her. Russ. Acad. Sci., 2022, vol. 92, pp. 285–296. https://doi.org/10.1134/S1019331622030066
  4. Andreeva O.V., Lobkovsky V.A., Kust G.S., Zonn I.S. The concept of sustainable land management: Modern state, models and typology development. Arid Ecosys., 2021, vol. 11, pp. 1–10. https://doi.org/10.1134/S2079096121010029
  5. Behzadi F., Yousefi H., Javadi S., Moridi A., Hashemy S., Mehdy S., Neshat A. Meteorological drought duration–severity and climate change impact in Iran. Theor. Appl. Climatol., 2022, vol. 149, pp. 1297–1315. https://doi.org/10.1007/s00704-022-04113-5
  6. Belyaeva M.V., Andreeva O.V., Kust G.S., Lobkovskiy V.A. Experience in assessment of land degradation dynamics of the south of European part of Russia using the methodology of Land Degradation Neutrality. Ekosis.: Ekol. Dinamika, 2020, vol. 4, no. 3, pp. 145–165. (In Russ.). https://doi.org/10.24411/1993-3916-2021-10135
  7. Belyaeva M.V., Kust G.S., Andreeva O.V. Assessment of the land degradation neutrality in the Samara region by global and regional indicators. Vestn. Mosk. Univ., Ser. 17: Pochvoved., 2023, no. 3, pp. 16–27. (In Russ.). https://doi.org/10.55959/MSU0137-0944-17-2023-78-3-16-27
  8. Cherenkova E.A., Bardin M.Y., Platova T.V., Semenov V.A. Influence of North Atlantic SST Variability and Changes in Atmospheric Circulation on the Frequency of Summer Droughts in the East European Plain. Russ. Meteorol. Hydrol., 2020, vol. 45, pp. 819–829. https://doi.org/10.3103/S1068373920120018
  9. Cherenkova E.A., Sidorova M.V. Climatic shift of seasonal variations in moisture in the Ural River basin in recent decades. Probl. Reg. Ekol., 2022, no. 5, pp. 93–98. (In Russ.).
  10. Hu Yu., Han Yu., Zhang Yu. Land desertification and its influencing factors in Kazakhstan. J. Arid Environ., 2020, vol. 180, art. 104203. https://doi.org/10.1016/j.jaridenv.2020.104203
  11. Javari M. Trend and homogeneity analysis of precipitation in Iran. Climate, 2016, vol. 4, no. 3, art. 44. https://doi.org/10.3390/cli4030044
  12. Kust G., Andreeva O., Cowie A. Land degradation neutrality: Concept development, practical applications and assessment. J. Environ. Manage., 2017, vol. 195, no. 1, pp. 16–24. https://doi.org/10.1016/j.jenvman.2016.10.043
  13. Kust G., Andreeva O., Lobkovskiy V., Telnova N. Uncertainties and policy challenges in implementing Land Degradation Neutrality in Russia. Environ. Sci. Policy, 2018, vol. 89, pp. 348–356. https://doi.org/10.1016/j.envsci.2018.08.010
  14. Kust G., Andreeva O., Shklyaeva D. Application of the concept of land degradation neutrality for remote monitoring of agricultural sustainability of irrigated areas in Uzbekistan. Sensors, 2023, vol. 23, art. 6419. https://doi.org/10.3390/s23146419
  15. Kust G.S., Andreeva O.V., Shklyaeva D.S., Lobkovskiy V.A. Towards the possibilities of achieving the land degradation neutrality in the countries of the Caspian Region (on the example of Russia, Kazakhstan and Turkmenistan). In Proc. of Sci. Conf. on Climate Change in the Caspian Sea Region, 27–28 October 2021. 2021, pp. 273–276.
  16. Kuzucuoǧlu C., Leroy S. Geographic and geomorphologic context of Caspian Sea level fluctuations over the Late Pleistocene and Holocene. Quaternaire, 2023, vol. 34, no. 2, pp. 71–92.
  17. Limareva N., Cabos N., William D., Izquierdo A., Sein D. The climate change of the Caucasus as a result of the global warming. Sovrem. Nauka Innov., 2017, no. 2, pp. 15–26. (In Russ.).
  18. Molavi-Arbshahi M., Arpe K., Leroy S. Precipitation and temperature of the southwest Caspian Sea region during the last 55 years: Their trends and teleconnections with large-scale atmospheric phenomena. Int. J. Climatol., 2016, vol. 36, pp. 2156–2172. https:// doi.org/10.1002/joc.4483
  19. Natsional’nyi doklad “Global’nyi klimat i pochvennyi pokrov Rossii: otsenka riskov i ekologo-ekonomicheskikh posledstvii degradatsii zemel’. Adaptivnye sistemy i tekhnologii ratsional’nogo prirodopol’zovaniya (sel’skoe i lesnoe khozyaistvo)” [National Report “Global Climate and Soil Cover in Russia: Assessment of Risks and Environmental and Economic Consequences of Land Degradation. Adaptive Systems and Technologies for Rational Environmental Management (Agriculture and Forestry)”]. Moscow: GEOS Publ., 2018. 357 p.
  20. Natsional’nyi doklad “Global’nyi klimat i pochvennyi pokrov Rossii: opustynivanie i degradatsiya zemel’, institutsional’nye, infrastrukturnye, tekhnologicheskie mery adaptatsii (sel’skoe i lesnoe khozyaistvo)”. T. 2 [National Report “Global Climate and Land Cover in Russia: Desertification and Land Degradation, Institutional, Infrastructural, and Technological Adaptation Measures (Agriculture and Forestry). Vol. 2]. Moscow: MBA Publ., 2019. 476 p.
  21. Orr B.J., Cowie A.L., Castillo Sanchez V.M. et al. Scientific conceptual framework for land degradation neutrality. A report of the science-policy interface. Bonn: UN Convention to Combat Desertification (UNCCD), 2017. 129 p.
  22. Pearce-Higgins J.W., Antao L.H., Bates R.E., Bowgen K.M., Bradshaw C.D., Duffield S.J. et al. A framework for climate change adaptation indicators for the natural environment. Ecol. Indic., 2022, vol. 136, art. 108690. http://doi.org/10.1016/j.ecolind.2022.108690
  23. Phillips L.B., Hansen A.J., Flather C.H. Evaluating the species energy relationship with the newest measures of ecosystem energy: NDVI versus MODIS primary production. Remote Sens. Environ., 2008, vol. 112, no. 12, pp. 4381–4392.
  24. Prirodopol’zovanie i ustoichivoe razvitie. Mirovye ekosistemy i problemy Rossii [Environmental Management and Sustainable Development. World Ecosystems and Problems of Russia]. Moscow: KMK Publ., 2006. 448 p.
  25. Rabbaniha M. Assessment of climate change impacts on the Caspian Sea Iranian coastal wetlands, using by GIS. 2013.
  26. Romanovskaya A.A. Needs and development paths for adaptation monitoring. Probl. Ekol. Monitor. Modelir. Ekosis., 2018, vol. 29, no. 1, pp. 107–126. (In Russ.).
  27. Samant R., Prange M. Climate-driven 21st century Caspian Sea level decline estimated from CMIP6 projections. Commun. Earth Environ., 2023, vol. 4, art. 357. https://doi.org/10.1038/s43247-023-01017-8
  28. Sanz M.J., Vente J. de, Chotte J.-L., Bernoux M., Kust G., Ruiz I., Almagro M., Alloza J.-A., Vallejo R., Castillo V., Hebel A., Akhtar-Schuster M. Sustainable Land Management contribution to successful land-based climate change adaptation and mitigation. A Report of the Science-Policy Interface. Bonn: UN Convention to Combat Desertification (UNCCD), 2017. 178 p.
  29. Sapanov M.K. Impact of climate change on water content in the northern Caspian region. Arid Ekosys., 2010, vol. 16, no. 5, pp. 25–30. (In Russ.).
  30. Schiemann R., Lüthi D., Vidale P., Schär C. The precipitation climate of Central Asia – intercomparison of observational and numerical data sources in a remote semiarid region. Int. J. Climatol., 2008, vol. 28, pp. 295–314.
  31. Semenov V.A., Cherenkova E.A. Evaluation of the Atlantic Multidecadal Oscillation Impact on Large-Scale Atmospheric Circulation in the Atlantic Region in Summer. Dokl. Earth Sci., 2018, vol. 478, pp. 263–267. https://doi.org/10.1134/S1028334X18020290
  32. Sims N.C., Newnham G.J., England J.R., et al. Good Practice Guidance. SDG Indicator 15.3.1, Proportion of Land That Is Degraded Over Total Land Area. Version 2.0. Bonn: UN Convention to Combat Desertification (UNCCD), 2021. 148 p.
  33. Slavko V.D., Andreeva O.V., Kust G.S. Assessment of land cover dynamics in order to establish a neutral balance of land degradation at the local level (for decertified lands of the dry steppe Trans-Volga region). Arid Ekosys., 2023, vol. 29, no. 1, pp. 59–69. (In Russ.).
  34. Titkova T.B. Climate changes in the Caspian and Turgai semi-deserts in the 20th century. Izv. Akad. Nauk, Ser. Geogr., 2003, no. 1, pp. 106–112. (In Russ.).
  35. Titkova T.B., Cherenkova E.A., Zolotokrylin A.N. Current trends in changes in soil moisture and evaporation in the south of European Russia based on satellite data and reanalysis data. In Materialy 20-i Mezhdun. Konf. “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa” [Proc. of the 20th Int. Conf. “Modern Problems of Earth Remote Sensing from Space”]. Moscow: IKI RAN, 2022, p. 460. (In Russ.). https://doi.org/10.21046/20DZZconf-2022a
  36. Titkova T.B., Zolotokrylin A.N. Monitoring of lands affected by desertification in the Republic of Kalmykia. Sovrem. Probl. Distants. Zondir. Zemli Kosmosa, 2022, vol. 19, no. 2, pp. 130–141. (In Russ.). https://doi.org/10.21046/2070-7401-2022-19-2-130-141
  37. UN, 2015. United Nations. A/RES/70/1. General Assembly. Resolution adopted by the General Assembly. Transforming our world: the 2030 Agenda for Sustainable Development. 2015. 35 p.
  38. Vahdati K., Massah Bavani A.R., Khosh-Khui M., Fakour P., Sarikhani S. Applying the AOGCM-AR5 models to the assessments of land suitability for walnut cultivation in response to climate change: A case study of Iran. PLoS ONE, 2019, vol. 14, no. 6, art. e0218725. https://doi.org/10.1371/journal.pone.0218725
  39. Zhang W., Xiang F., Qin W., Jiang W. Vegetation dynamics and the relations with climate change at multiple time scales in the Yangtze River and Yellow River Basin, China. Ecol. Indic., 2020, vol. 110, art. 105892. https://doi.org/10.1016/j.ecolind.2019.105892
  40. Zolotokrylin A.N., Cherenkova E.A., Titkova T.B. Aridization of drylands in the European part of Russia: Secular trends and links to droughts. Izv. Akad. Nauk, Ser. Geogr., 2020, vol. 84, no. 2, pp. 207–217. (In Russ.). https://doi.org/10.31857/S258755662002017X

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Fig. 1. Land cover of the study region as of 2020

Download (933KB)
Indexing metadata
3. Fig. 2. Land cover types of the study area, % of total area

Download (144KB)
Indexing metadata
4. Fig. 3. Ranking of first-order administrative-territorial units in the countries of the Caspian region according to the NBDZ index calculated for the period of 2016-2020 (base period: 2001-2015)

Download (196KB)
Indexing metadata
5. Fig. 4. ‘Trends’ in land productivity: averaged data for the period of 2016-2020

Download (265KB)
Indexing metadata
6. Fig. 5. ‘Efficiency’ of land productivity: comparison of averaged NDVI values for the period of 2016-2020 with NDVI values of territories similar in natural characteristics

Download (231KB)
Indexing metadata
7. Fig. 6. ‘Level’ of land productivity: averaged data for the period of 2016-2020 compared to the baseline period (2001-2015)

Download (308KB)
Indexing metadata
8. Fig. 7. Integral assessment of land productivity dynamics for the period of 2016-2020 compared to the base period (2001-2015)

Download (260KB)
Indexing metadata
9. Fig. 8. Main impacts of climate change in the Caspian region

Download (329KB)
Indexing metadata
10. Fig. 9. Temperature and precipitation in the Caspian Sea region

Download (309KB)
Indexing metadata

Copyright (c) 2024 Russian Academy of Sciences

Согласие на обработку персональных данных с помощью сервиса «Яндекс.Метрика»

1. Я (далее – «Пользователь» или «Субъект персональных данных»), осуществляя использование сайта https://journals.rcsi.science/ (далее – «Сайт»), подтверждая свою полную дееспособность даю согласие на обработку персональных данных с использованием средств автоматизации Оператору - федеральному государственному бюджетному учреждению «Российский центр научной информации» (РЦНИ), далее – «Оператор», расположенному по адресу: 119991, г. Москва, Ленинский просп., д.32А, со следующими условиями.

2. Категории обрабатываемых данных: файлы «cookies» (куки-файлы). Файлы «cookie» – это небольшой текстовый файл, который веб-сервер может хранить в браузере Пользователя. Данные файлы веб-сервер загружает на устройство Пользователя при посещении им Сайта. При каждом следующем посещении Пользователем Сайта «cookie» файлы отправляются на Сайт Оператора. Данные файлы позволяют Сайту распознавать устройство Пользователя. Содержимое такого файла может как относиться, так и не относиться к персональным данным, в зависимости от того, содержит ли такой файл персональные данные или содержит обезличенные технические данные.

3. Цель обработки персональных данных: анализ пользовательской активности с помощью сервиса «Яндекс.Метрика».

4. Категории субъектов персональных данных: все Пользователи Сайта, которые дали согласие на обработку файлов «cookie».

5. Способы обработки: сбор, запись, систематизация, накопление, хранение, уточнение (обновление, изменение), извлечение, использование, передача (доступ, предоставление), блокирование, удаление, уничтожение персональных данных.

6. Срок обработки и хранения: до получения от Субъекта персональных данных требования о прекращении обработки/отзыва согласия.

7. Способ отзыва: заявление об отзыве в письменном виде путём его направления на адрес электронной почты Оператора: info@rcsi.science или путем письменного обращения по юридическому адресу: 119991, г. Москва, Ленинский просп., д.32А

8. Субъект персональных данных вправе запретить своему оборудованию прием этих данных или ограничить прием этих данных. При отказе от получения таких данных или при ограничении приема данных некоторые функции Сайта могут работать некорректно. Субъект персональных данных обязуется сам настроить свое оборудование таким способом, чтобы оно обеспечивало адекватный его желаниям режим работы и уровень защиты данных файлов «cookie», Оператор не предоставляет технологических и правовых консультаций на темы подобного характера.

9. Порядок уничтожения персональных данных при достижении цели их обработки или при наступлении иных законных оснований определяется Оператором в соответствии с законодательством Российской Федерации.

10. Я согласен/согласна квалифицировать в качестве своей простой электронной подписи под настоящим Согласием и под Политикой обработки персональных данных выполнение мною следующего действия на сайте: https://journals.rcsi.science/ нажатие мною на интерфейсе с текстом: «Сайт использует сервис «Яндекс.Метрика» (который использует файлы «cookie») на элемент с текстом «Принять и продолжить».