Novel methods for monitoring low chlorophyll-a concentrations in the large, oligotrophic Lake Malawi/Nyasa/Niassa.

The use of remote sensing for monitoring chlorophyll-a (chla) and modelling eutrophication has advanced over the last decades. Although the application of the technology has proven successful in ocean ecosystems, there is a need to monitor chla concentrations in large, nutrient-poor inland water bodies. The main objective of this study was to explore the utility of publicly available remotely sensed Sentinel-2 (S2) imagery to quantify chla concentrations in the nutrient-deficient Lake Malawi/Niassa/Nyasa (LMNN). A secondary objective was to compare the S2 derived chla with the Global Change Observation Mission-Climate (GCOM-C) chla product that provides uninterrupted data throughout the year. In situ chla data (n = 76) from upper, middle and lower sections of LMNN served as a reference to produce remote sensing-based quantification. The line-height approach method built on color index, was applied for chla concentrations below 0.25 mg/m3. Moderate Resolution Imaging Spectroradiometer 3-band Ocean Color (MODIS-OC3) - was adopted when chla concentration exceeded 0.35 mg/m3. The MODIS-OC3 algorithm had generic model coefficients that were calibrated for each in situ sample by using GCOM-C Level 3 chla product. A weighted sum of the two algorithms was applied for chla concentrations that fell between 0.25 and 0.35 mg/m3. The above methods were then applied to the S2 data to estimate chla at each pixel. S2 showed a promising accuracy in distinguishing chla levels (MSE = 0.18) although the chla range in the lake was relatively narrow, particularly using the locally calibrated coefficients of the OC3 algorithm. Chla distribution maps produced from the S2 data revealed limited spatial variation across the LMNN with higher concentrations identified in the coastal areas. S2-derived chla and GCOM-C chla comparison showed fairly good similarity between the two datasets (MSE = 0.205). Accepting this similarity, monthly chla dynamics of the lake was profiled using the temporally reliable GCOM-C data that showed oligotrophic conditions (1.7 mg/m3 to 3.2 mg/m3) in most parts of the lake throughout the year. The study's findings advance the potential for both remote sensing approaches to provide vital information at the required spatial and temporal resolution for evidence-based policymaking and proactive environmental management in an otherwise very data deficient region.

Remote sensing of savanna woody species diversity: A systematic review of data types and assessment methods.

Despite savannas being known for their relatively sparse vegetation coverage compared to other vegetation ecosystems, they harbour functionally diverse vegetation forms. Savannas are affected by climate variability and anthropogenic factors, resulting in changes in woody plant species compositions. Monitoring woody plant species diversity is therefore important to inform sustainable biodiversity management. Remote sensing techniques are used as an alternative approach to labour-intensive field-based inventories, to assess savanna biodiversity. The aim of this paper is to review studies that applied remote sensing to assess woody plant species diversity in savanna environments. The paper first provides a brief account of the spatial distribution of savanna environments around the globe. Thereafter, it briefly defines categorical classification and continuous-scale species diversity assessment approaches for savanna woody plant estimation. The core review section divides previous remote sensing studies into categorical classification and continuous-scale assessment approaches. Within each division, optical, Radio Detection And Ranging (RADAR) and Light Detection and Ranging (LiDAR) remote sensing as applied to savanna woody species diversity is reviewed. This is followed by a discussion on multi-sensor applications to estimate woody plant species diversity in savanna. We recommend that future research efforts should focus strongly on routine application of optical, RADAR and LiDAR remote sensing of physiologically similar woody plant species in savannas, as well as on extending these methodological approaches to other vegetation environments.

Tracking conservation effectiveness in the Vhembe Biosphere Reserve in South Africa using Landsat imagery.

Biosphere reserves (BRs) seek to reconcile a sustainable relationship between human welfare and environmental integrity by adopting a landscape model that distinguishes between three interdependent management zones (core, buffer, transition). Considering the increasing human influence on landscapes in BRs, the tracking land use-land cover (LULC) dynamics is crucial for the development and planning of efficient management strategies for specific management zone. This study aimed at (i) assessing biodiversity protection around the core zones to highlight the threats facing the core zones and (ii) tracking the effect of the proclamation of the Vhembe Biosphere Reserve (VBR) on the LULC dynamics in the management zones through spatio-temporal analysis using Landsat imagery acquired from1999 to 2018. Six LULC categories (water body, forest/bush, shrubs/grass, agricultural land, bare soil, and built-up/mines) were identified and mapped using the support vector machine (SVM) classification to address both objectives. Assessment of threats around the core zones using artificial buffers (0-5, 10-15, and 15-20 km radius) created around them showed agricultural activities in the most immediate buffers (0-5 km radius). The LULC dynamics showed vegetation increase in all the management zones evidenced by the reduction of bare soil as well shrub/grass lands, and by the corresponding increase in foliage-richer forest/bush lands since the proclamation of the reserve in 2009. The findings might signify a positive outcome of vegetation increase as a consequence of the proclamation of the VBR. However, firmer conservation measures must be adopted and priority must be given to the arrangement of the management zones to strengthen biodiversity protection in the core zone.

Estimation of woody plant species diversity during a dry season in a savanna environment using the spectral and textural information derived from WorldView-2 imagery.

Remote sensing techniques are useful in the monitoring of woody plant species diversity in different environments including in savanna vegetation types. However, the performance of satellite imagery in assessing woody plant species diversity in dry seasons has been understudied. This study aimed to assess the performance of multiple Gray Level Co-occurrence Matrices (GLCM) derived from individual bands of WorldView-2 satellite imagery to quantify woody plant species diversity in a savanna environment during the dry season. Woody plant species were counted in 220 plots (20 m radius) and subsequently converted to a continuous scale of the Shannon species diversity index. The index regressed against the GLCMs using the all-possible-subsets regression approach that builds competing models to choose from. Entropy GLCM yielded the best overall accuracy (adjusted R2: 0.41-0.46; Root Mean Square Error (RMSE): 0.60-0.58) in estimating species diversity. The effect of the number of predicting bands on species diversity estimation was also explored. Accuracy generally increased when three-five bands were used in models but stabilised or gradually decreased as more than five bands were used. Despite the peak accuracies achieved with three-five bands, performances still fared well for models that used fewer bands, showing the relevance of few bands for species diversity estimation. We also assessed the effect of GLCM window size (3×3, 5×5 and 7×7) on species diversity estimation and generally found inconsistent conclusions. These findings demonstrate the capability of GLCMs combined with high spatial resolution imagery in estimating woody plants species diversity in a savanna environment during the dry period. It is important to test the performance of species diversity estimation of similar environmental set-ups using widely available moderate-resolution imagery.

Expected spatial patterns of alien woody plants in South Africa's protected areas under current scenario of climate change.

Although protected areas (PAs) are declared to provide sanctuaries for biodiversity, they are increasingly threatened by the synergistic effects of anthropic factors, invasive alien species and climate change. Consequently, interventions are required to minimize the impacts of these threats on PAs' integrity. To inform these interventions in the South African context and under the current climate change scenario, we tested for geographic patterns of alien woody species across the network of 1,453 PAs using three alien invasion indices - alien species abundance, invaded area ratio and alien species richness. Our analysis shows that, under current climate change scenario, none of the PAs would be effective in shielding against alien plants and PAs that are geographically close tend to share similar invasion patterns. In addition, PAs that are hotspots of alien species are also geographically clustered but these findings are biome-dependent. Our outlier analysis reveals not only an island of disproportionately rich PAs in alien species, but also identifies some alien-poor PAs. We suggest that PAs that are hotspots of alien species as well as outliers of disproportionately rich PAs in alien species should be priority in monitoring and invasion control programmes in the context of the ongoing climate change.

Preserving the tree of life of the fish family Cyprinidae in Africa in the face of the ongoing extinction crisis 1.

Our understanding of how the phylogenetic tree of fishes might be affected by the ongoing extinction risk is poor. This is due to the unavailability of comprehensive DNA data, especially for many African lineages. In addition, the ongoing taxonomic confusion within some lineages, e.g., Cyprinidae, makes it difficult to contribute to the debate on how the fish tree of life might be shaped by extinction. Here, we combine COI sequences and taxonomic information to assemble a fully sampled phylogeny of the African Cyprinidae and investigate whether we might lose more phylogenetic diversity (PD) than expected if currently threatened species go extinct. We found evidence for phylogenetic signal in extinction risk, suggesting that some lineages might be at higher risk than others. Based on simulated extinctions, we found that the loss of all threatened species, which approximates 37% of total PD, would lead to a greater loss of PD than expected, although highly evolutionarily distinct species are not particularly at risk. Pending the reconstruction of an improved multi-gene phylogeny, our results suggest that prioritizing high-EDGE species (evolutionary distinct and globally endangered species) in conservation programmes, particularly in some geographic regions, would contribute significantly to safeguarding the tree of life of the African Cyprinidae.

Predicting the effect of climate change on a range-restricted lizard in southeastern Australia.

Climate change is ranked as one of the most severe threats to global biodiversity. This global phenomenon is particularly true for reptiles whose biology and ecology are closely linked to climate. In this study, we used over 1,300 independent occurrence points and different climate change emission scenarios to evaluate the potential risk of changing climatic conditions on the current and future potential distribution of a rock-dwelling lizard; the velvet gecko. Furthermore, we investigated if the current extent of protected area networks in Australia captures the full range distribution of this species currently and in the future. Our results show that climate change projections for the year 2075 have the potential to alter the distribution of the velvet gecko in southeastern Australia. Specifically, climate change may favor the range expansion of this species to encompass more suitable habitats. The trend of range expansion was qualitatively similar across the different climate change scenarios used. Additionally, we observed that the current network of protected areas in southeast Australia does not fully account for the full range distribution of this species currently and in the future. Ongoing climate change may profoundly affect the potential range distribution of the velvet gecko population. Therefore, the restricted habitat of the velvet geckos should be the focus of intensive pre-emptive management efforts. This management prioritization should be extended to encompass the increases in suitable habitats observed in this study in order to maximize the microhabitats available for the survival of this species.

Utility of ASTER and Landsat for quantifying hydrochemical concentrations in abandoned gold mining.

The effect of mining on water resources is severe and requires careful monitoring and management. Remote sensing has been used to characterize water quality indicators in efforts to fight mine-induced contamination. Much focus has however been placed on producing a qualitative classification of water qualities. Moreover, the number of variables considered in most studies is relatively small for a large number of hydrochemical constituents common in water bodies associated with gold mining activities. This study is aimed at quantifying a comprehensive list of field- and laboratory-measured chemical constituents of water samples from abandoned mines using remotely-sensed data. Akaike's Information Criterion was used to estimate each of the constituents using statistical values derived from individual bands of ASTER and Landsat data as predictors. Fairly good accuracies were obtained for constituents such as redox potential (Eh), major anions and cations. In contrast, trace elements correlated poorly with ASTER and Landsat bands, due mainly to a sampling anomaly. The performances of the two images in estimating the constituents were comparable. These findings suggest the potential of multispectral, moderate spatial resolution remote sensing for quantifying different hydrochemical properties of water bodies in mining environments. Further studies are however encouraged to enhance accuracies and reliability using a greater number of samples than was used in this study to capture the variability present in the population.