Monitoring climate change and anthropogenic pressure at Lake Tanganyika

Plisnier, Pierre‐Denis; Muderhwa, Nshombo; Mgana, Huruma; Ntakimazi, Gaspard

doi:10.1016/j.jglr.2018.05.019

Cited by 56 publications

(29 citation statements)

References 52 publications

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“…For instance, records of Chla in Lake Tanganyika (Bergamino et al., ; Horion et al., ) have shown variations at seasonal and inter‐annual scales, related to variations of the mixed layer depending on meteorological and climatic conditions, which determine water column processes in African Great Lakes (Nicholson, ; O'Reilly, Alin, Plisnier, Cohen, & McKee, ; MacIntyre, ; Tierney et al., ; Tierney, Smerdon, Anchukaitis, & Seager, ). However, the lack of continuity in records (Plisnier, Nshombo, Mgana, & Ntakimazi, ) hampers straightforward interpretation of changes involved and, too often, methodological differences between past and recent surveys further complicate data processing and interpretation. Therefore, studies on tropical lakes have mostly relied on paleolimnological approaches based on various sediment archives, such as fossil diatoms (Haberyan & Hecky, ) or phytoplankton pigments (Saulnier‐Talbot et al., ), with a time resolution of decades to centuries.…”

Section: Introductionmentioning

confidence: 99%

Long‐term change of phytoplankton in Lake Kivu: The rise of the greens

Rugema¹,

Darchambeau

Sarmento

et al. 2019

Freshwater Biology

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Phytoplankton time‐series enable the observation of recurrent seasonal patterns on community composition, but drastic shifts in community structure are rarely observed, unless linked to anthropogenic impacts (e.g. changes in nutrient inputs). Here, we report a unique case of non‐seasonal, multiannual regime shift of phytoplankton community structure in Lake Kivu, East Africa, and explore the possible causes for such changes. We recorded phytoplankton biomass every 2 weeks over a period of 12 years (from 2002 to 2015). Phytoplankton community previously dominated by cyanobacteria and diatoms changed considerably from 2012, with a conspicuous rise in the biomass of green algae (from 3 to 33% lake‐wide), and a decline of cryptophytes and cyanobacteria along with an increase in total chlorophyll a concentration. Concomitantly, we observed significant differences in the mixed layer depth between the two periods, resulting from changes in the thermal gradient. The euphotic zone depth was also reduced in 2012–2015, probably from the higher phytoplankton biomass. Moreover, mean particulate nitrogen and phosphorus increased as well as the particulate N:P ratio. Desmids (Cosmarium laeve) now dominate the mixolimnion, probably due to atelomixis, observed in high‐frequency temperature measurements. We believe that decadal or multidecadal variability of climate on the Indian Ocean may be the reason for this regime shift in thermal stratification, with a strong impact in phytoplankton community structure. In conclusion, our study demonstrates that tropical lakes may be subject to non‐seasonal fluctuations that generate multiannual regime shifts. These regime shifts have probably never been reported previously because of the lack of long phytoplankton time‐series in low latitudes.

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Section: Introductionmentioning

confidence: 99%

Long‐term change of phytoplankton in Lake Kivu: The rise of the greens

Rugema¹,

Darchambeau

Sarmento

et al. 2019

Freshwater Biology

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“…Extreme climatic and weather events in recent decades have been a critical global issue due to the severity of the impacts on natural environments, economy, and on human life [1][2][3]. These extreme events are unpredictable and destructive, especially, on agriculture production.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Recent Trends of Two Climate Parameters over Two Eco-Regions of Ethiopia

Gedefaw

Yan

Wang

et al. 2019

Water

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The changes in climatic variables in Ethiopia are not entirely understood. This paper investigated the recent trends of precipitation and temperature on two eco-regions of Ethiopia. This study used the observed historical meteorological data from 1980 to 2016 to analyze the trends. Trend detection was done by using the non-parametric Mann-Kendall (MK), Sen's slope estimator test, and Innovative Trend Analysis Method (ITAM). The results showed that a significant increasing trend was observed in the Gondar, Bahir Dar, Gewane, Dembi-Dolo, and Negele stations. However, a slightly decreasing trend was observed in the Sekoru, Degahabur, and Maichew stations regarding precipitation trends. As far as the trend of temperature was concerned, an increasing trend was detected in the Gondar, Bahir Dar, Gewane, Degahabur, Negele, Dembi-Dolo, and Maichew stations. However, the temperature trend in Sekoru station showed a sharp decreasing trend. The effects of precipitation and temperature changes on water resources are significant after 1998. The consistency in the precipitation and temperature trends over the two eco-regions confirms the robustness of the changes. The findings of this study will serve as a reference for climate researchers, policy and decision makers.

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“…A global consensus has been reached that NWHSs are significant components in global ecosystem protection which is so exceptional as to transcend national boundaries and to be of common importance for present and future generations of all humanity [1]. However, in recent years, NWHSs have been experiencing unprecedented pressures due to climate change, natural disaster, and human activities [4][5][6][7][8][9]. The World Heritage Committee summarized a list of factors affecting the heritage values of World Heritage properties.…”

Section: Introductionmentioning

confidence: 99%

Ecological Environment Assessment in World Natural Heritage Site Based on Remote-Sensing Data. A Case Study from the Bayinbuluke

et al. 2019

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Ecological environment assessment would be helpful for a rapid and systematic understanding of ecological status and would contribute to formulate appropriate strategies for the sustainability of heritage sites. A procedure based on spatial principle component analysis was employed to measure the ecological status in Bayinbuluke; exploratory spatial data analysis and geo-detector model were introduced to assess the spatio-temporal distribution characteristics and detect the driving factors of the ecological environment. Five results are presented: (1) During 2007–2018, the average values of moisture, greenness, and heat increased by 51.72%, 23.10%, and 4.99% respectively, and the average values of dryness decreased by 56.70%. However, the fluctuation of each indicator increased. (2) The ecological environment of Bayinbuluke was improved from 2007 to 2018, and presented a distribution pattern that the heritage site was better than the buffer zone, and the southeast area was better than the northwest area. (3) The ecological environment presented a significant spatial clustering characteristic, and four types of spatial associations were proposed for assessing spatial dependence among the samples. (4) Elevation, protection partition, temperature, river, road, tourism, precipitation, community resident, and slope were statistically significant with respect to the changes in ecological status, and the interaction of any two factors was higher than the effect of one factor alone. (5) The remote-sensing ecological index (RSEI) could reflect the vegetation growth to a certain extent, but has limited ability to respond to species structure. Overall, the framework presented in this paper realized a visual and measurable approach for a detailed monitoring of the ecological environment and provided valuable information for the protection and management of heritage sites.

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Monitoring climate change and anthropogenic pressure at Lake Tanganyika

Cited by 56 publications

References 52 publications

Long‐term change of phytoplankton in Lake Kivu: The rise of the greens

Long‐term change of phytoplankton in Lake Kivu: The rise of the greens

Analysis of the Recent Trends of Two Climate Parameters over Two Eco-Regions of Ethiopia

Ecological Environment Assessment in World Natural Heritage Site Based on Remote-Sensing Data. A Case Study from the Bayinbuluke

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