More stories

  • in

    ReaLSAT, a global dataset of reservoir and lake surface area variations

    In this section, we provide quantitative evaluation for both spatial coverage and temporal dynamics of ReaLSAT dataset.Spatial coverageSince the dataset was created using satellite imagery analysis, it can provide more comprehensive coverage than existing datasets. However, using an automated process also has its challenges. It can invariably lead to the detection of spurious waterbodies because of issues in data (e.g., due to errors in GSW maps used as inputs in ReaLSAT).To provide more insights into the types of lakes and potential issues in the spatial coverage of ReaLSAT, we randomly sampled 5,000 lakes out of 435,717 that are only present in ReaLSAT (i.e., not available in the HydroLAKES dataset). A human annotator used Google’s satellite imagery base layer to categorize these lakes. Figure 5a shows the geographical distribution of these lakes, and Fig. 5b shows the distribution of different lake types in the sample set. Out of the 5,000 lakes, the human annotator identified 2,019 traditional lakes and reservoirs where sufficient water was visible in the satellite imagery. Another 551 lakes in the sample set showed signs of a bowl-like depression but with no (or very little) water visible in the satellite imagery and were labeled as ephemeral. There were 861 other lakes that were tagged as farm ponds because they showed geometric patterns of farming in the imagery. This diversity of waterbody types discovered by ReaLSAT that were previously unreported by HydroLakes highlights one of the strengths of our approach. In limnology, the origin/type of lake is a very important regulator of ecosystem dynamics. For instance, reservoirs will have faster water flow/lower residence time than natural lakes, and therefore nutrient and carbon processing rates will differ; floodplain lakes may dry periodically, leading to the denudation of sediments; and farm ponds will likely have much higher rates of nutrient loading and methane production than non-agriculturally influenced lakes. Hence, capturing a more comprehensive range of waterbody categories can enable various scientific studies where knowing the origin/lake type could provide a critical understanding of the process.Fig. 5(a) Geographic location of 5000 randomly selected lakes used for manual evaluation of lake type. (b) Allocation of the 5000 manually referenced lakes to specific lake types. Regular implies a traditional lake or reservoir. Unverifiable implies that the lake type could not be identified based on the available Google Earth imagery.Full size imageAlong with the lentic water types discovered in the sampled set, we also found that ReaLSAT identified 603 river segments missed by our morphological score filter. As stated earlier, this is an inherent challenge with automated approaches that use a fixed score threshold for eliminating river segments. Another 239 lakes were tagged as wetlands because of significant vegetation inside and around the lake polygon. There were also 97 lakes that were adjacent to rivers, which were labeled as riverine or floodplain lakes that were formed as a result of river channels meandering over time. Furthermore, there were 59 lakes where the polygons represented only a small portion of a larger lake and were labeled as partial. Finally, for 571 polygons, there was not enough evidence to tag them in any of the above categories. Since Google imagery represents only a single snapshot in time, these 571 waterbodies could not be definitively labeled as spurious (hence, they were labeled as unverifiable), highlighting a limitation of this evaluation pipeline. In particular, a vast majority of these waterbodies appear to be ephemeral based on their surface area timeseries (completely dry for extended periods of time). Hence, if the satellite imagery layer is from one of these timesteps, the annotator would not be able to confirm the presence of the lake.To assess whether we would obtain a similar distribution of different waterbody categories in existing datasets, we performed a similar evaluation on another 5,000 lakes sampled from ReaLSAT where each polygon has some overlap (greater than 1 pixel) with a polygon from HydroLAKES. In this sampled set, the annotator identified 4,030 lakes as traditional lakes or reservoirs, 370 as ephemeral, 138 as farm ponds, 6 as river segments, 66 as wetlands, 95 as riverine or floodplain lakes, 20 as partial, and 275 as unverifiable.Compared to previous distribution, this set of 5,000 waterbodies contains relatively fewer river segments and wetlands polygons in HydroLAKES, because these categories were manually identified and removed during HydroLAKES database creation6. Similary, this set contains relatively few farm ponds because HydroLAKES was created by manual curation of existing static databases and hence does not contain new farm ponds that got created over the years.Temporal dynamicsTo assess the quality of surface extent maps, we performed a quantitative evaluation on a random selection of extent maps. These extent maps were compared against reference maps created by a human annotator using a semi-automated pixel classification procedure. This strategy of creating reference maps is used extensively in the remote sensing literature (e.g. see36,37,38,39). Next, we describe our evaluation process in detail.Sample selectionThere are 462,574 lakes out of 681,137 total lakes where the label updates (corrections and imputations) by the ORBIT approach have trust scores within our chosen thresholds (as described in the methods section). To evaluate these candidate lakes effectively, we focus on lake extent maps where the ORBIT approach resulted in a different map than the underlying GSW extent based map. Hence, we remove maps where no updates were made by the ORBIT approach (neither corrections nor imputations) from the candidate pool of extent maps used for evaluation. We also remove maps where the percentage of missing labels was more than 90% because these maps tend to suffer from significant cloud coverage. Hence, it would be challenging to generate reference maps. Since the GSW dataset has a significant amount of missing data for most places in the world before 2000, we evaluated maps only from 2000 onwards. These three filters left us with a total of 51,077,278 water extent maps considered for selection. Figure 6a shows the distribution of percentage pixels updated made by the ORBIT approach in these water extent maps. To evaluate the robustness of our approach in comparison to GSW maps, we randomly selected 10,000 water extent maps such that extents with significant updates are given higher weight to reduce the skew in distribution towards extents with relative less updates (Fig. 6b).Fig. 6Distribution of updates made by the ORBIT approach. (a) distribution using candidate water extents (b) distribution using randomly selected 10000 water extent maps for evaluation.Full size imageSample pruningFrom these randomly selected water extent maps, we removed maps for which a reference map could not be generated due to clouds or the inability of the annotator to distinguish between land and water. A final set of 2,095 water extent maps were considered for evaluation. Figure 7a shows the distribution of percentage updates in the final set of evaluation extents and Fig. 7b shows the geographical distribution of these extent maps.Fig. 7Summary of the dataset used for evaluating water extent maps. (a) Distribution of updates made by the ORBIT approach in the water extent maps selected for evaluation. (b) Geographical location of the lakes in the evaluation set.Full size imageReference map generationFor these water extent maps, we created ground truth reference maps using a semi-automatic labeling process37,38,39. Specifically, the annotator selects land and water samples to train an SVM (Support Vector Machine) classification model for each image. The annotator keeps adding samples until a stable map is generated. As a final step, the annotator masks out pixels affected by clouds, cloud shadows, and any other region where the annotator is not confident about the accuracy of the reference labels. This process enables a quick and robust generation of reference maps. Supplementary Fig. S7 shows one of the reference maps in the evaluation set. While this strategy of comparing maps is different from the traditional approach of comparing pixels (often selected using stratified sampling), it provides a much more exhaustive evaluation of surface extent maps. The reference maps used for evaluation in this study are also available as part of the dataset.ComparisonTo compare the extent maps generated by ReaLSAT with the reference maps, we used accuracy as the evaluation metric, a widely used metric to measure the quality of classification maps. Accuracy is simply defined as the ratio of pixels with correct labels over a total number of pixels. Specifically, we assign 1 to water pixels and 0 to land pixels. Since GSW based extent maps contain missing labels, they are assigned a value of 0.5 to reflect the uncertainty between land and water. Accuracy is then calculated as follows:$$Accuracy=1-frac{1}{Rast C}mathop{sum }limits_{i=1}^{R}mathop{sum }limits_{j=1}^{C}left|ReferenceMap[i,j]-PredictedMap[i,j]right|$$
    (2)
    where, R is the number of rows and C is the number of columns of the map.When the accuracy of RealSAT and GSW labels are compared, a vast majority of points lie above the diagonal 1:1 line, which implies that ReaLSAT labels were more accurate overall (Fig. 8a). In Fig. 8 the points are colored based on % of pixels where GSW labels were missing. To better show the improvement in RealSAT labeling, we plot the distribution of the difference in accuracy values between the two datasets as shown in Fig. 8b. A positive value indicates that the surface extent map from the ReaLSAT dataset had better accuracy than the map from the GSW dataset and vice versa. For ease of visualization, we plot this distribution after excluding cases where the accuracy from both datasets was equal. The positively skewed distribution demonstrates the efficacy of the ORBIT approach.Fig. 8Comparison of accuracy values using GSW labels vs ReaLSAT labels. (a) Scatter plot of accuracy values using GSW labels vs ReaLSAT labels. (b) Histogram of difference in accuracy between ReaLSAT labels vs GSW labels. Positive value represents cases where ReaLSAT labels were more accurate than GSW labels. (c) Histogram of difference in accuracy values for the scenario where pixels labelled as land by both products as well as ground truth were removed to reduce the skew of surrounding land pixel on the accuracy values.Full size imageNote that the shape of a lake will influence the number of land pixels surrounding it, which might bias the accuracy values. For example, the reference map shown in Supplementary Fig. S7 contains more than 70% of land pixels. To address this bias, we also calculated accuracy values after removing pixels that were labeled as land by both datasets as well as the ground truth. This variation allows a more strict evaluation of water extent maps. Figure 8c shows the distribution of the difference in accuracy values under this scenario (after excluding cases with equal accuracy). As shown, a vast majority of the distribution is still towards positive values. Furthermore, the distribution has a larger spread towards high positive values, suggesting significant improvement made by the ORBIT approach.From Fig. 8, we can see that for some cases ReaLSAT based extent maps are less accurate relative to GSW. As described earlier, violation of assumptions made by the ORBIT approach could lead to the observed poor performance. Out of 2,095 extent maps, GSW labels show better accuracy than ReaLSAT for 323 of them. On visual analysis of errors in these maps, we found that 165 maps are slightly different only at the lake’s boundary. We categorized the remaining extent maps based on the reason behind the observed poor performance. In particular, 45 maps have poor performance due to occlusion of water surface by algae, 18 maps contain farm ponds, 8 contain mining lakes, 27 maps have unreliable bathymetry, 30 maps have issues due to the weighting factor used by ORBIT approach, and 30 maps have class conditional missing data. All the reference maps and corresponding maps from GSW and ReaLSAT are provided with the dataset.Next, we describe some of these cases in detail.Impact of algae: It can be difficult to visually differentiate surface algae or floating aquatic plants from terrestrial vegetation40, as they have similar reflectance spectra. Therefore, surface algal blooms often get incorrectly labeled as land in the reference maps. However, in most cases, the appearance and disappearance of algae on a lake are independent of the bathymetry. Thus, algae pixels get detected as physically inconsistent by the ORBIT approach, and consequently, these pixels are updated based on the labels of other pixels without algae. In many cases, while the accuracy with respect to the reference map is poor (because algae get labeled as land), ReaLSAT based extent maps are closer to the true extent of the lake. For example, Supplementary Fig. S8 illustrates the impact of algae on the extent mapping of Center Lake, Texas. In this example, the bimodal distribution of fraction values (either low or high) reveals high confidence in lake persistence (Supplementary Fig. S8b). On Oct 22, 2008, false-color composite processing of LANDSAT-5 imagery reveals a strong vegetative signal on the west side of the lake (Supplementary Fig. S8c). Since we know that this is a lake, we can assume that the west side of the lake is experiencing a large surface algal bloom with a similar reflectance to the surrounding terrestrial landscape. Because of the strong vegetative reflectance signal, the semi-automated reference mapping labels the west side of the lake as land (Supplementary Fig. S8d), as does most GSW labels (Supplementary Fig. S8e). Conversely, the ReaLSAT extent map labels the west side of the lake as water (Supplementary Fig. S8f). However, we calculate accuracy based on the semi-automated reference map (Supplementary Fig. S8d). Due to this, the GSW extent map is considered more accurate than the ReaLSAT map, even though this is not true because the reference map is incorrectly labeled. Therefore, some negative accuracy values may be a misrepresentation of reality due to surface algal blooms.Impact of variable bathymetry: Even though we tried to remove lakes with unreliable bathymetry by using score-based filters defined in an earlier section, not all cases were removed. For example, agricultural ponds often have small sections that are connected and change shape based on agricultural needs. Supplementary Fig. S9 highlights an example of labeling issues on agricultural ponds in Mexico. In this area, satellite imagery and the GSW fraction map confirm the presence of agricultural ponds (Supplementary Fig. S9a,b). These individual ponds are filled and drained based on operational decisions and do not follow a consistent pattern of growing or shrinking. Thus, the ORBIT approach can introduce spurious updates in water extent maps for these farms. In the Landsat-5 imagery from 2009–10–08, some of the ponds are dry, while others are filled (Supplementary Fig. S9c). This distribution of water is evident from a visual inspection and is confirmed in the semi-automated reference map (Supplementary Fig. S9d). Due to the similar elevations between the individual pond sections, the ORBIT approach spuriously fills the remaining sections with water based on the incorrectly learned bathymetry (Supplementary Fig. S9f). While quantification of such uncertainties is outside the scope of this paper, we hope that the wider research community can use RealSAT to address such questions. In particular, changes in bathymetry of a lake can be identified using spatial-temporal patterns in the label corrections. Specifically, if the elevation of some pixels in a lake increases after a certain time (e.g., sediment deposits leading to increase the elevation of a pixel), they will appear as physically inconsistent to the ORBIT framework, and hence the labels for these locations will be changed from land to water much more frequently after this increase in elevation.Impact of bias in errors and missing data: As mentioned earlier in the methods section, based on our observation, the confidence of water labels is higher than land labels in the GSW dataset. To account for this bias, we used a weighting factor of 3 for the water class. While this weighting factor improves the ORBIT approach’s performance in most cases, this assumption leads to an overestimation of water for some lakes. For example, Supplementary Fig. S10 compares the water extent maps with and without the weighting factor for a small reservoir in eastern Brazil. As we can see, the GSW labels contain false positives, and due to the weighting factor of 3, ORBIT prefers to update the land labels to water which further increases the number of false positives, as shown in Supplementary Fig. S10e. However, if we use a weighting factor of 1 for this example, the ORBIT approach can effectively remove many of the false positives in the GSW map, as shown in Supplementary Fig. S10f.Similarly, apart from missing data due to clouds in the GSW dataset, there can also be missing values on pixels where the GSW classification model is not confident. Hence, for some water extent maps, class-dependent missing data (compared to missing data which is class independent) adversely impact the ORBIT approach. For example, Supplementary Fig. S11 shows a water extent map for Zhongleng Reservoir in China, where missing data along the eastern edges is not independent but has resulted from ambiguous pixels around the lake where the GSW’s approach was not confident. In such a scenario, the ORBIT approach heavily relies on information from nearby timesteps to infer labels for missing pixels, leading to errors in ReaLSAT maps if there is a significant variation in lake extent in nearby timesteps, as shown in Supplementary Fig. S11e. More

  • in

    High source–sink ratio at and after sink capacity formation promotes green stem disorder in soybean

    Harbach, C. J. et al. Delayed senescence in soybean: Terminology, research update, and survey results from growers. Plant Health Progress 17, 76–83 (2016).Article 

    Google Scholar 
    Hobbs, H. A. et al. Green stem disorder of soybean. Plant Dis. 90, 513–518 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hill, C. B., Hartman, G. L., Esgar, R. & Hobbs, H. A. Field evaluation of green stem disorder in soybean cultivars. Crop Sci. 46, 879–885 (2006).Article 

    Google Scholar 
    Morita, K. et al. (2006) Effect of green stem on soiled bean index at harvest of soybean by combine harvester. Hokuriku Crop Sci. 41, 107–109 (2006) (in Japanese).
    Google Scholar 
    Ogiwara, H. Delayed leaf senescence. In: Agriculture, Forestry and Fisheries Research Council of Japan, ed. Soybean-technical development for improving national food self-sufficiency ratio. Annotated bibliography of Agriculture, Forestry, and Fisheries Research, vol. 27, 291–294 (2002). (in Japanese).Crafts-Brandner, S. J. & Egli, D. B. Sink removal and leaf senescence in soybean. Plant Physiol. 85, 662–666 (1987).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Crafts-Brandner, S. J., Below, F. E., Harper, J. E. & Hageman, R. H. Effects of pod removal on metabolism and senescence of nodulating and nonnodulating soybean isolines. Plant Physiol. 75, 311–317 (1984).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Egli, D. B. & Bruening, W. P. Depodding causes green-stem syndrome in soybean. Crop Manag. 5(1), 1–9. https://doi.org/10.1094/CM-2006-0104-01-RS (2006).Article 

    Google Scholar 
    Htwe, N. M. P. S. et al. Leaf senescence of soybean at reproductive stage is associated with induction of autophagy-related genes, GmATG8c, GmATG8i and GmATG4. Plant Prod. Sci. 14, 141–147 (2011).CAS 
    Article 

    Google Scholar 
    Leopold, A. C., Niedergang-Kamien, E. & Janick, J. Experimental modification of plant senescence. Plant Physiol. 34, 570–573 (1959).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mondal, M. H., Brun, W. A. & Brenner, M. L. Effects of sink removal on photosynthesis and senescence in leaves of soybean (Glycine max L.) plants. Plant Physiol. 61, 394–397 (1978).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wittenbach, V. A. Effect of pod removal on leaf senescence in soybean. Plant Physiol. 70, 1544–1548 (1982).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wittenbach, V. A. Effect of pod removal on leaf photosynthesis and soluble protein composition of field-grown soybeans. Plant Physiol. 73, 121–124 (1983).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wittenbach, V. A. Purification and characterization of a soybean leaf storage glycoprotein. Plant Physiol. 73, 125–129 (1983).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Staswick, P. E. Developmental regulation and the influence of plant sinks on vegetative storage protein gene expression in soybean leaves. Plant Physiol. 89, 309–315 (1989).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Sato, J., Shiraiwa, T., Sakashita, M., Tsujimoto, Y. & Yoshida, R. The occurrence of delayed stem senescence in relation to trans-zeatin riboside level in the xylem exudate in soybeans grown under excess-wet and drought soil conditions. Plant Prod. Sci. 10, 460–467 (2007).Article 

    Google Scholar 
    Takehara, T. et al. Occurrence of delayed leaf senescence of soybean caused by Rhizoctonia aerial blight in Japan. Jpn. Agric. Res. Q. 50, 201–208 (2016).Article 

    Google Scholar 
    Boethel, D. J. et al. Delayed maturity associated with southern green stink bug (Heteroptera: Pentatomidae) injury at various soybean phenological stages. J. Econ. Entomol. 93, 707–712 (2000).CAS 
    PubMed 
    Article 

    Google Scholar 
    Islam, M. M. et al. Nitrogen manipulation affects leaf senescence during late seed filling in soybean. Acta Physiol. Plant. 39, 42 (2017).Article 
    CAS 

    Google Scholar 
    Yamazaki, R., Katsube-Tanaka, T. & Shiraiwa, T. Effect of thinning and shade removal on green stem disorder in soybean. Plant Prod. Sci. 21, 83–92 (2018).CAS 
    Article 

    Google Scholar 
    Yamazaki, R., Katsube-Tanaka, T., Kawasaki, Y., Katayama, K. & Shiraiwa, T. Effect of thinning on cultivar differences of green stem disorder in soybean. Plant Prod. Sci. 22, 311–318 (2019).CAS 
    Article 

    Google Scholar 
    Board, J. E. & Tan, Q. Assimilatory capacity effects on soybean yield components and pod number. Crop Sci. 35, 846–851 (1995).Article 

    Google Scholar 
    Egli, D. B. Soybean reproductive sink size and short-term reductions in photosynthesis during flowering and pod set. Crop Sci. 50, 1971–1977 (2010).Article 

    Google Scholar 
    Wells, R., Schulze, L. L., Ashley, D. A., Boerma, H. R. & Brown, R. H. Cultivar differences in canopy apparent photosynthesis and their relationship to seed yield in soybean. Crop Sci. 22, 886–890 (1982).Article 

    Google Scholar 
    Islam, M. M. et al. Nitrogen redistribution and its relationship with the expression of GmATG8c during seed filling in soybean. J. Plant Physiol. 192, 71–74 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zhao, X., Zheng, S. H. & Arima, S. Influence of nitrogen enrichment during reproductive growth stage on leaf nitrogen accumulation and seed yield in soybean. Plant Prod. Sci. 17, 209–217 (2014).CAS 
    Article 

    Google Scholar 
    Brown, A. W. & Hudson, K. A. Transcriptional profiling of mechanically and genetically sink-limited soybeans. Plant Cell Environ. 40, 2307–2318 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Tranbarger, T. J., Franceschi, V. R., Hildebrand, D. F. & Grimes, H. D. The soybean 94-kilodalton vegetative storage protein is a lipoxygenase that is localized in paraveinal mesophyll cell vacuoles. Plant Cell 3, 973–987 (1991).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Melo, B. P. et al. Revisiting the soybean GmNAC superfamily. Front. Plant Sci. 9, 1864 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kim, H. J. et al. Gene regulatory cascade of senescence-associated NAC transcription factors activated by ETHYLENE-INSENSITIVE2-mediated leaf senescence signaling in Arabidopsis. J. Exp. Bot. 65, 4023–4036 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Tucker, M. L., Burke, A., Murphy, C. A., Thai, V. K. & Ehrenfried, M. L. Gene expression profiles for cell wall-modifying proteins associated with soybean cyst nematode infection, petiole abscission, root tips, flowers, apical buds, and leaves. J. Exp. Bot. 58, 3395–3406 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Turner, G. W. et al. Experimental sink removal induces stress responses, including shifts in amino acid and phenylpropanoid metabolism, in soybean leaves. Planta 235, 939–954 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Roach, T. & Krieger-Liszkay, A. The role of the PsbS protein in the protection of photosystems I and II against high light in Arabidopsis thaliana. Biochim. Biophys. Acta Bioenerg. 1817, 2158–2165 (2012).CAS 
    Article 

    Google Scholar 
    Horton, P., Ruban, A. V. & Walters, R. G. Regulation of light harvesting in green plants. Annu. Rev. Plant Physiol. Plant Mol. Biol. 47, 655–684 (1996).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hutin, C. et al. Early light-induced proteins protect Arabidopsis from photooxidative stress. Proc. Natl. Acad. Sci. U.S.A. 100, 4921–4926 (2003).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    Wang, H. et al. Functional characterization of dihydroflavonol-4-reductase in anthocyanin biosynthesis of purple sweet potato underlies the direct evidence of anthocyanins function against abiotic stresses. PLoS ONE 8, e78484 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    Saravitz, D. M. & Siedow, J. N. The differential expression of wound-inducible lipoxygenase genes in soybean leaves. Plant Physiol. 110, 287–299 (1996).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pimenta, M. R. et al. The stress-induced soybean NAC transcription factor GmNAC81 plays a positive role in developmentally programmed leaf senescence. Plant Cell Physiol. 57, 1098–1114 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Fujimoto, M. et al. Transcriptional switch for programmed cell death in pith parenchyma of sorghum stems. Proc. Natl. Acad. Sci. U.S.A. 115, 8783–8792 (2018).Article 
    CAS 

    Google Scholar 
    Egli, D. B. Variation in leaf starch and sink limitations during seed filling in soybean. Crop Sci. 39, 1361–1368 (1999).CAS 
    Article 

    Google Scholar 
    Board, J. E. & Harville, B. G. Late-planted soybean yield response to reproductive source/sink stress. Crop Sci. 38, 763–771 (1998).Article 

    Google Scholar 
    Fatichin, Zheng, S. H., Narasaki, K. & Arima, S. Genotypic adaptation of soybean to late sowing in southwestern Japan. Plant Prod. Sci. 16, 123–130 (2013).CAS 
    Article 

    Google Scholar 
    Wakasugi, K. & Fujimori, S. Subsurface Water Level Control System “FOEAS” that promotes the full use of paddy fields. J. Jpn. Soc. Irrig. Drain. Rural Eng. 77, 705–708 (2009) (in Japanese).
    Google Scholar 
    Fehr, W. R. & Caviness, C. E. Stages of soybean development. Spec. Rep. 80. Iowa Agric. Home Econ. Exp. Stn. Iowa State Univ., Ames. (1977).Furuya, T. & Umezaki, T. Simplified distinction method of degree of delayed stem maturation of soybean plants. Jpn. J. Crop Sci. 62, 126–127 (1993) (in Japanese with English abstract).Article 

    Google Scholar 
    Kim, D. et al. TopHat2: Accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar  More

  • in

    A functional definition to distinguish ponds from lakes and wetlands

    Current scientific definitions of pondsWe compiled existing scientific definitions of ponds by conducting a backwards and forwards search of papers referenced in or subsequently referencing three seminal pond papers8,17,18 (see “Methods”). We ultimately compiled 54 pond definitions from scientific literature (data available19). The variables most often included in definitions were surface area (91% of definitions), depth (48%), permanence (48%), origin (i.e., natural or human-made; 33%), and standing water (33%; Fig. 2a). When surface area or depth were included in definitions, they were often mentioned qualitatively (e.g., “small” and “shallow”). Of the 61% of definitions that included a maximum pond surface area, the range was 0.1 to 100 ha, the median was 2 ha, and all but two definitions were ≤ 10 ha (Fig. 2b). For depth, only 17% of studies provided a maximum depth cutoff, which ranged 2 to 8 m (Fig. 2c). Of the 26 definitions mentioning permanence, 22 stated that ponds could be temporary or permanent and only three indicated that ponds are exclusively permanent waterbodies. Of the 18 definitions mentioning origin, 17 mentioned that ponds could be natural or human-made with the remaining study indicating ponds can have diverse origins.Figure 2Summary of “pond” definitions from scientific literature including (a) presence of various morphological, biological, and physical characteristics in the definition as blue bars (n = 54 definitions total). Bold black lines indicate the number of definitions with surface area and depth values. Histograms of the upper limits from “pond” definitions for (b) surface area and (c) maximum depth.Full size imageOther important factors included in definitions related to morphometry. For example, 30% of definitions mentioned the potential for plants to colonize the entire basin, which relates to high light penetration (mentioned in 11% of definitions) and/or shallow depths. For example, Wetzel11 defines ponds as having enough light penetration that macrophyte photosynthesis can occur over the entire waterbody. As such, these conditions may be comparable to the littoral region of lakes (11% of definitions). Lastly, 7% of pond definitions mentioned mixing versus stratification, whereby ponds mix more than lakes20 yet less than shallow lakes due to a smaller fetch16.To assess if there was agreement in pond definitions among papers, we examined the number of times each definition was cited. Across the 54 definitions, there were 89 citations of 48 unique papers. Ultimately, most papers (75%) were only cited only once, indicating no consensus in pond definition. The most cited paper was Biggs et al.21, which accounted for 15% of citations. The next two most cited papers were Oertli et al.17 and Sondergaard et al.18, which were seminal papers included in our backwards-forwards search, and each comprised 8% of citations.International definitionsAt an international level, there is no consensus on how to discriminate among ponds, lakes, and wetlands. In North America, wetlands are generally considered to be shallow:  More

  • in

    Pleistocene drivers of Northwest African hydroclimate and vegetation

    de Menocal, P. B. Plio-Pleistocene African climate. Science 270, 53–59 (1995).ADS 
    Article 

    Google Scholar 
    de Menocal, P. B. African climate change and faunal evolution during the Pliocene-Pleistocene. Earth Planet. Sci. Lett. 220, 3–24 (2004).ADS 
    Article 
    CAS 

    Google Scholar 
    Donges, J. F. et al. Nonlinear detection of paleoclimate-variability transitions possibly related to human evolution. Proc. Natl Acad. Sci. U.S.A. 108, 20422–20427 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Maslin, M. A. et al. East african climate pulses and early human evolution. Quat. Sci. Rev. 101, 1–17 (2014).ADS 
    Article 

    Google Scholar 
    Larrasoaña, J. C., Roberts, A. P. & Rohling, E. J. Dynamics of Green Sahara periods and their role in hominin evolution. PLoS One 8, 76514 (2013).ADS 
    Article 
    CAS 

    Google Scholar 
    Castañeda, I. S. et al. Wet phases in the Sahara/Sahel region and human migration patterns in North Africa. Proc. Natl Acad. Sci. USA. 106, 20159–20163 (2009).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    United Nations World Food Programme. Scaling up for resilient individuals, communities and systems in the Sahel Operational Reference Note. (2018).Barbier, B., Yacouba, H., Karambiri, H., Zoromé, M. & Somé, B. Human vulnerability to climate variability in the sahel: Farmers’ adaptation strategies in northern burkina faso. Environ. Manag. 43, 790–803 (2009).ADS 
    Article 

    Google Scholar 
    Mohamed, A. Ben Climate change risks in Sahelian Africa. Reg. Environ. Chang. 11, 109–117 (2011).Article 

    Google Scholar 
    Biasutti, M. Forced Sahel rainfall trends in the CMIP5 archive. J. Geophys. Res. Atmos. 118, 1613–1623 (2013).ADS 
    Article 

    Google Scholar 
    Roudier, P., Sultan, B., Quirion, P. & Berg, A. The impact of future climate change on West African crop yields: what does the recent literature say? Glob. Environ. Chang 21, 1073–1083 (2011).Article 

    Google Scholar 
    Keeling, R. F. & Keeling, C. D. Atmospheric monthly in situ CO2 data—Mauna Loa Observatory, Hawaii. In Scripps CO2 Program Data. UC San Diego Library Digital Collections. https://doi.org/10.6075/J08W3BHW (2017).Brandt, M. et al. An unexpectedly large count of trees in the West African Sahara and Sahel. Nature 587, 78–82 (2020).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Tiedemann, R., Sarnthein, M. & Shackleton, N. J. Astronomic timescale for the Pliocene Atlantic δ18O and dust flux records of Ocean Drilling Program Site 659. Paleoceanography 9, 619–638 (1994).ADS 
    Article 

    Google Scholar 
    de Menocal, P. B., Ruddiman, W. F. & Pokras, E. M. Influences of high‐ and low‐latitude processes on African terrestrial climate: Pleistocene eolian records from equatorial atlantic Ocean Drilling Program Site 663. Paleoceanography 8, 209–242 (1993).ADS 
    Article 

    Google Scholar 
    Kuechler, R. R., Dupont, L. M. & Schefuß, E. Hybrid insolation forcing of Pliocene monsoon dynamics in West Africa. Clim. Past 14, 73–84 (2018).Article 

    Google Scholar 
    Rose, C. et al. Changes in northeast African hydrology and vegetation associated with pliocene-pleistocene sapropel cycles. Philos. Trans. R. Soc. B Biol. Sci. 371, 20150243 (2016).Article 
    CAS 

    Google Scholar 
    Tierney, J. E., Pausata, F. S. R. & De Menocal, P. B. Rainfall regimes of the Green Sahara. Sci. Adv. 3, e1601503 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Tierney, J. E. & Russell, J. M. Abrupt climate change in southeast tropical Africa influenced by Indian monsoon variability and ITCZ migration. Geophys. Res. Lett. 34, 1–6 (2007).Article 
    CAS 

    Google Scholar 
    Skonieczny, C. et al. Monsoon-driven Saharan dust variability over the past 240,000 years. Sci. Adv. 5, eaav1887 (2019).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McGee, D. et al. The magnitude, timing and abruptness of changes in North African dust deposition over the last 20,000 yr. Earth Planet. Sci. Lett. 371–372, 163–176 (2013).ADS 
    Article 
    CAS 

    Google Scholar 
    Bosmans, J. H. C., Hilgen, F. J., Tuenter, E. & Lourens, L. J. Obliquity forcing of low-latitude climate. Clim. Past 11, 1335–1346 (2015).Article 

    Google Scholar 
    Bosmans, J. H. C., Drijfhout, S. S., Tuenter, E., Hilgen, F. J. & Lourens, L. J. Response of the North African summer monsoon to precession and obliquity forcings in the EC-Earth GCM. Clim. Dyn. 44, 279–297 (2014).Article 

    Google Scholar 
    Mantsis, D. F. et al. The response of large-scale circulation to obliquity-induced changes in meridional heating gradients. J. Clim. 27, 5504–5516 (2014).ADS 
    Article 

    Google Scholar 
    Rachmayani, R., Prange, M. & Schulz, M. Intra-interglacial climate variability: model simulations of Marine Isotope Stages 1, 5, 11, 13, and 15. Clim. Past 12, 677–695 (2016).Article 

    Google Scholar 
    Chou, C. & Neelin, J. D. Mechanisms limiting the northward extent of the northern summer monsoons over North America, Asia, and Africa. J. Clim. 16, 406–425 (2003).ADS 
    Article 

    Google Scholar 
    Bischoff, T., Schneider, T. & Meckler, A. N. A conceptual model for the response of tropical rainfall to orbital variations. J. Clim. 30, 8375–8391 (2017).ADS 
    Article 

    Google Scholar 
    Ehleringer, J. R., Cerling, T. E. & Helliker, B. R. C4 photosynthesis, atmospheric CO2, and climate.Bond, W. J. & Midgley, G. F. A proposed CO2-controlled mechanism of woody plant invasion in grasslands and savannas. Glob. Chang. Biol. 6, 865–869 (2000).ADS 
    Article 

    Google Scholar 
    Lehmann, C. E. R., Archibald, S. A., Hoffmann, W. A. & Bond, W. J. Deciphering the distribution of the savanna biome. N. Phytol. 191, 197–209 (2011).Article 

    Google Scholar 
    Vallé, F., Dupont, L. M., Leroy, S. A. G. G., Schefuß, E. & Wefer, G. Pliocene environmental change in West Africa and the onset of strong NE trade winds (ODP Sites 659 and 658). Palaeogeogr. Palaeoclimatol. Palaeoecol. 414, 403–414 (2014).Article 

    Google Scholar 
    Leroy, S. & Dupont, L. Development of vegetation and continental aridity in northwestern Africa during the Late Pliocene: the pollen record of ODP site 658. Palaeogeogr. Palaeoclimatol. Palaeoecol. 109, 295–316 (1994).Article 

    Google Scholar 
    Huang, Y., Dupont, L., Sarnthein, M., Hayes, J. M. & Eglinton, G. Mapping of C4 plant input from North West Africa into North East Atlantic sediments. Geochim. Cosmochim. Acta 64, 3505–3513 (2000).ADS 
    CAS 
    Article 

    Google Scholar 
    Buitenwerf, R., Bond, W. J., Stevens, N. & Trollope, W. S. W. Increased tree densities in South African savannas: >50 years of data suggests CO2 as a driver. Glob. Chang. Biol. 18, 675–684 (2012).ADS 
    Article 

    Google Scholar 
    Stevens, N., Lehmann, C. E. R., Murphy, B. P. & Durigan, G. Savanna woody encroachment is widespread across three continents. Glob. Chang. Biol. 23, 235–244 (2017).ADS 
    PubMed 
    Article 

    Google Scholar 
    Stevens, N., Erasmus, B. F. N., Archibald, S. & Bond, W. J. Woody encroachment over 70 years in South African savannahs: overgrazing, global change or extinction aftershock? Philos. Trans. R. Soc. B Biol. Sci. 371, (2016).Kgope, B. S., Bond, W. J. & Midgley, G. F. Growth responses of African savanna trees implicate atmospheric [CO2] as a driver of past and current changes in savanna tree cover. Austral. Ecol. 35, 451–463 (2010).Article 

    Google Scholar 
    Scheff, J., Seager, R., Liu, H., Coats, S. & Observatory, L. E. Are glacials dry? Consequences for paleoclimatology and for greenhouse warming. J. Clim. 30, 6593–6609 (2017).ADS 
    Article 

    Google Scholar 
    Bragg, F. J. et al. Stable isotope and modelling evidence for CO2 as a driver of glacial-interglacial vegetation shifts in southern Africa. Biogeosciences 10, 2001–2010 (2013).ADS 
    CAS 
    Article 

    Google Scholar 
    Bhattacharya, T., Tierney, J. E., Addison, J. A. & Murray, J. W. Ice-sheet modulation of deglacial North American monsoon intensification. Nat. Geosci. 11, 848–852 (2018).ADS 
    CAS 
    Article 

    Google Scholar 
    DiNezio, P. N. et al. Glacial changes in tropical climate amplified by the Indian Ocean. Sci. Adv. 4, 1–12 (2018).Article 

    Google Scholar 
    Kuechler, R. R., Schefuß, E., Beckmann, B., Dupont, L. & Wefer, G. NW African hydrology and vegetation during the Last Glacial cycle reflected in plant-wax-specific hydrogen and carbon isotopes. Quat. Sci. Rev. 82, 56–67 (2013).ADS 
    Article 

    Google Scholar 
    Raymo, M. E. & Nisancioglu, K. H. The 41 kyr world: Milankovitch’s other unsolved mystery. Paleoceanography 18, 1011 (2003).Davis, B. A. S. & Brewer, S. Orbital forcing and role of the latitudinal insolation/temperature gradient. Clim. Dyn. 32, 143–165 (2009).Article 

    Google Scholar 
    Bosmans, J. H. C. et al. Precession and obliquity forcing of the freshwater budget over the Mediterranean. Quat. Sci. Rev. 123, 16–30 (2015).ADS 
    Article 

    Google Scholar 
    McGee, D., Broecker, W. S. & Winckler, G. Gustiness: the driver of glacial dustiness? Quat. Sci. Rev. 29, 2340–2350 (2010).ADS 
    Article 

    Google Scholar 
    Bradtmiller, L. I. et al. Changes in biological productivity along the northwest African margin over the past 20,000 years. Paleoceanography 31, 185–202 (2016).ADS 
    Article 

    Google Scholar 
    Guan, K., Wood, E. F. & Caylor, K. K. Multi-sensor derivation of regional vegetation fractional cover in Africa. Remote Sens. Environ. 124, 653–665 (2012).ADS 
    Article 

    Google Scholar 
    Ehleringer, J. R., Cerling, T. E. & Helliker, B. R. C4 photosynthesis, atmospheric CO2, and climate. Oecologia 112, 285–299 (1997).ADS 
    PubMed 
    Article 

    Google Scholar 
    Sage, R. F. The evolution of C4 photosynthesis. N. Phytol. 161, 341–370 (2004).CAS 
    Article 

    Google Scholar 
    Lloyd, J. et al. Contributions of woody and herbaceous vegetation to tropical savanna ecosystem productivity: a quasi-global estimate. Tree Physiol. 28, 451–468 (2008).PubMed 
    Article 

    Google Scholar 
    Archibald, S. & Hempson, G. P. Competing consumers: contrasting the patterns and impacts of fire and mammalian herbivory in Africa. Philos. Trans. R. Soc. B Biol. Sci. 371, 20150309 (2016).Elderfield, H. et al. Evolution of ocean temperature. Science 337, 704–709 (2012).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Hooghiemstra, H., Lézine, A. M., Leroy, S. A. G., Dupont, L. & Marret, F. Late Quaternary palynology in marine sediments: a synthesis of the understanding of pollen distribution patterns in the NW African setting. Quat. Int. 148, 29–44 (2006).Article 

    Google Scholar 
    Dupont, L. M. Vegetation zones in NW Africa during the brunhes chron reconstructed from marine palynological data. Quat. Sci. Rev. 12, 189–202 (1993).ADS 
    Article 

    Google Scholar 
    Dallmeyer, A., Claussen, M., Lorenz, S. J. & Shanahan, T. The end of the African humid period as seen by a transient comprehensive Earth system model simulation of the last 8000 years. Clim 16, 117–140 (2020).ADS 

    Google Scholar 
    Collins, J. A. et al. Interhemispheric symmetry of the tropical African rainbelt over the past 23,000 years. Nat. Geosci. 4, 42–45 (2011).ADS 
    CAS 
    Article 

    Google Scholar 
    Pastouret, L., Chamley, H., Delibrias, G., Duplessy, J. & Thiede, J. Late quaternary climatic changes in western tropical africa deduced from deep-sea sedimentation off the Niger delta. Oceanol. Acta 1, 217–232 (1978).CAS 

    Google Scholar 
    Tierney, J. E., Lewis, S. C., Cook, B. I., LeGrande, A. N. & Schmidt, G. A. Model, proxy and isotopic perspectives on the East African Humid Period. Earth Planet. Sci. Lett. 307, 103–112 (2011).ADS 
    CAS 
    Article 

    Google Scholar 
    COHMAP members. Climatic changes of the last 18,000 years: observations and model simulations. Science 241, 1043–1052 (1988).Article 

    Google Scholar 
    Street-Perrott, F. A., Marchand, D. S., Roberts, N. & Harrison, S. P. Global lake-level variations from 18,000 to 0 years ago: a palaeoclimate analysis. U.S. Department of Energy Technical Report 46, 20545 (1989).de Menocal, P. B. & Tierney, J. E. Green Sahara: African humid periods paced by Earth’ s orbital changes. Nat. Educ. Knowl. 3(10):12 (2012).Sage, R. F. & Kubien, D. S. Quo vadis C4? An ecophysiological perspective on global change and the future of C4 plants. Photosynth. Res. 77, 209–225 (2003).CAS 
    PubMed 
    Article 

    Google Scholar 
    Sarnthein, M., Tetzlaff, G., Koopmann, B., Wolter, K. & Pflaumann, U. Glacial and interglacial wind regimes over the eastern subtropical Atlantic and North-West Africa. Nature 293, 193–196 (1981).ADS 
    Article 

    Google Scholar 
    Rowland, G. H. et al. The spatial distribution of aeolian dust and terrigenous fluxes in the tropical Atlantic ocean since the last glacial maximum. Paleoceanogr. Paleoclimatol. 36, 1–17 (2021).Article 

    Google Scholar 
    Polissar, P. J., Rose, C., Uno, K. T., Phelps, S. R. & DeMenocal, P. Synchronous rise of African C4 ecosystems 10 million years ago in the absence of aridification. Nat. Geosci. 12, 657–660 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Jullien, E. et al. Low-latitude “dusty events” vs. high-latitude “icy Heinrich events”. Quat. Res. 68, 379–386 (2007).Article 

    Google Scholar 
    Pye, K. Aeolian Dust and Dust Deposits. (Academic Press, 1987).Skonieczny, C. et al. A three-year time series of mineral dust deposits on the West African margin: sedimentological and geochemical signatures and implications for interpretation of marine paleo-dust records. Earth Planet. Sci. Lett. 364, 145–156 (2013).ADS 
    CAS 
    Article 

    Google Scholar 
    Malaizé, B. et al. The impact of African aridity on the isotopic signature of Atlantic deep waters across the Middle Pleistocene Transition. Quat. Res. 77, 182–191 (2012).Article 
    CAS 

    Google Scholar 
    Lisiecki, L. E. & Raymo, M. E. A Pliocene-Pleistocene stack of 57 globally distributed benthic δ 18O records. Paleoceanography 20, 1–17 (2005).
    Google Scholar 
    Polissar, P. J. & D’Andrea, W. J. Uncertainty in paleohydrologic reconstructions from molecular D values. Geochim. Cosmochim. Acta 129, 146–156 (2014).ADS 
    CAS 
    Article 

    Google Scholar 
    Eggleston, S., Schmitt, J., Bereiter, B., Schneider, R. & Fischer, H. Evolution of the stable carbon isotope composition of atmospheric CO2 over the last glacial cycle. Paleoceanography 31, 434–452 (2016).ADS 
    Article 

    Google Scholar 
    Tierney, J. E. & deMenocal, P. B. Abrupt shifts in Horn of Africa hydroclimate since the last glacial maximum. Science 342, 843–846 (2013).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Schrag, D. P. et al. The oxygen isotopic composition of seawater during the Last Glacial Maximum. Quat. Sci. Rev. 21, 331–342 (2002).ADS 
    Article 

    Google Scholar 
    Vogts, A., Moossen, H., Rommerskirchen, F. & Rullkötter, J. Distribution patterns and stable carbon isotopic composition of alkanes and alkan-1-ols from plant waxes of African rain forest and savanna C3 species. Org. Geochem. 40, 1037–1054 (2009).CAS 
    Article 

    Google Scholar 
    Garcin, Y. et al. Reconstructing C3 and C4 vegetation cover using n-alkane carbon isotope ratios in recent lake sediments from Cameroon, Western Central Africa. Geochim. Cosmochim. Acta 142, 482–500 (2014).ADS 
    CAS 
    Article 

    Google Scholar 
    White, F. The Vegetation of Africa. (UNESCO 1983).Ritchie, J. C., Eyles, C. H. & Haynes, C. V. Sediment and pollen evidence for an early to mid-Holocene humid period in the eastern Sahara. Nature 314, 352–355 (1985).ADS 
    Article 

    Google Scholar 
    Watrin, J. et al. Plant migration and plant communities at the time of the ‘green Sahara’. Comptes Rendus—Geosci. 341, 656–670 (2009).ADS 
    Article 

    Google Scholar 
    Hély, C. et al. Holocene changes in African vegetation: tradeoff between climate and water availability. Clim 10, 681–686 (2014).ADS 

    Google Scholar 
    Lézine, A. M. Timing of vegetation changes at the end of the Holocene Humid Period in desert areas at the northern edge of the Atlantic and Indian monsoon systems. Comptes Rendus—Geosci. 341, 750–759 (2009).ADS 
    Article 

    Google Scholar 
    Dupont, L. M. & Hooghiemstra, H. The Saharan-Sahelian boundary during the Brunhes chron. Acta Bot. Neerl. 38, 405–415 (1989).Article 

    Google Scholar 
    Sachse, D. et al. Molecular paleohydrology: interpreting the hydrogen-isotopic composition of lipid biomarkers from photosynthesizing organisms. Annu. Rev. Earth Planet. Sci. 40, 221–249 (2012).ADS 
    CAS 
    Article 

    Google Scholar 
    Dansgaard, W. Stable isotopes in precipitation. Tellus 16, 436–468 (1964).ADS 
    Article 

    Google Scholar 
    Worden, J. et al. Importance of rain evaporation and continental convection in the tropical water cycle. Nature 445, 528–532 (2007).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Risi, C., Bony, S. & Vimeux, F. Influence of convective processes on the isotopic composition (δ18O and δD) of precipitation and water vapor in the tropics: 2 Physical interpretation of the amount effect. J. Geophys. Res. Atmos. 113, D19306 (2008).ADS 
    Article 
    CAS 

    Google Scholar 
    Risi, C. et al. What controls the isotopic composition of the African monsoon precipitation? Insights from event-based precipitation collected during the 2006 AMMA field campaign. Geophys. Res. Lett. 35, L24808 (2008).ADS 
    Article 
    CAS 

    Google Scholar 
    Badewien, T., Vogts, A. & Rullkötter, J. n-Alkane distribution and carbon stable isotope composition in leaf waxes of C3 and C4 plants from Angola. Org. Geochem. 89–90, 71–79 (2015).Bezabih, M., Pellikaan, W. F., Tolera, A. & Hendriks, W. H. Evaluation of n-alkanes and their carbon isotope enrichments (d 13 C) as diet composition markers. Anim. Int. J. Anim. Biosci. 5, 57–66 (2011).CAS 
    Article 

    Google Scholar 
    Kristen, I. et al. Biomarker and stable carbon isotope analyses of sedimentary organic matter from Lake Tswaing: evidence for deglacial wetness and early Holocene drought from South Africa. 143–160 https://doi.org/10.1007/s10933-009-9393-9 (2010).Magill, C. R., Ashley, G. M. & Freeman, K. H. Water, plants, and early human habitats in eastern Africa. Proc. Natl Acad. Sci. 110, 1175–1180 (2013).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Cheddadi, R., Carré, M., Nourelbait, M., François, L. & Rhoujjati, A. Early Holocene greening of the Sahara requires Mediterranean winter rainfall. 1–7 https://doi.org/10.1073/pnas.2024898118 (2021).Niedermeyer, E. M. et al. Orbital- and millennial-scale changes in the hydrologic cycle and vegetation in the western African Sahel: insights from individual plant wax δD and δ13C. Quat. Sci. Rev. 29, 2996–3005 (2010).ADS 
    Article 

    Google Scholar 
    Adkins, J., deMenocal, P. & Eshel, G. The ‘African humid period’ and the record of marine upwelling from excess 230Th in Ocean Drilling Program Hole 658C. Paleoceanography 21, 1–14 (2006).Article 

    Google Scholar 
    Mcgee, D. Glacial—interglacial precipitation changes. Annu. Rev. Mar. Sci. 12, 525–557 (2020).Weldeab, S., Lea, D. W., Schneider, R. R. & Andersen, N. 155,000 Years of West African monsoon and ocean thermal evolution. Science 316, 1303–1307 (2007).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Schefuß, E., Schouten, S. & Schneider, R. R. Climatic controls on central African hydrology during the past 20,000 years. Nature 437, 1003–1006 (2005).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Weijers, J. W. H., Schefuß, E., Schouten, S. & Damsté, J. S. S. Coupled thermal and hydrological evolution of tropical Africa over the last deglaciation. Science 315, 1701–1704 (2007).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Lezine, A. M. & Cazet, J. P. High-resolution pollen record from core KW31, Gulf of Guinea, documents the history of the lowland forests of West Equatorial Africa since 40,000 yr ago. Quat. Res. 64, 432–443 (2005).Article 

    Google Scholar 
    Marret, F., Scourse, J. D., Versteegh, G., Fred Jansen, J. H. & Schneider, R. Integrated marine and terrestrial evidence for abrupt Congo River palaeodischarge fluctuations during the last deglaciation. J. Quat. Sci. 16, 761–766 (2001).Article 

    Google Scholar 
    Dupont, L. & Behling, H. Land-sea linkages during deglaciation: High-resolution records from the eastern Atlantic off the coast of Namibia and Angola (ODP site 1078). Quat. Int. 148, 19–28 (2006).Article 

    Google Scholar 
    Maley, J. & Brenac, P. Vegetation dynamics, palaeoenvironments and climatic changes in the forests of western Cameroon during the last 28,000 years B.P. Rev. Palaeobot. Palynol. 99, 157–187 (1998).Article 

    Google Scholar 
    Giresse, P., Maley, J. & Brenac, P. Late Quaternary palaeoenvironments in the Lake Barombi Mbo (West Cameroon) deduced from pollen and carbon isotopes of organic matter. Palaeogeogr. Palaeoclimatol. Palaeoecol. 107, 65–78 (1994).Article 

    Google Scholar 
    Maley, J. The African rain forest vegetation and palaeoenvironments during late quaternary. Clim. Change 19, 79–98 (1991).ADS 
    Article 

    Google Scholar 
    Talbot, M. R. & Johannessen, T. A high resolution paleoclimatic record for the last 27,500 years in tropical West Africa from the carbon and nitrogen isotopic composition of lacustrine organic matter. Earth Planet. Sci. Lett. 110, 23–37 (1992).Anhuf, D. et al. Paleo-environmental change in Amazonian and African rainforest during the LGM. Palaeogeogr. Palaeoclimatol. Palaeoecol. 239, 510–527 (2006).Article 

    Google Scholar 
    Elenga, H. et al. Pollen-based biome reconstruction for southern Europe and Africa 18,000 yr BP. J. Biogeogr. 27, 621–634 (2000).Article 

    Google Scholar 
    Gasse, F., Chalié, F., Vincens, A., Williams, M. A. J. & Williamson, D. Climatic patterns in equatorial and southern Africa from 30,000 to 10,000 years ago reconstructed from terrestrial and near-shore proxy data. Quat. Sci. Rev. 27, 2316–2340 (2008).ADS 
    Article 

    Google Scholar 
    Wu, H., Guiot, J., Brewer, S. & Guo, Z. Climatic changes in Eurasia and Africa at the last glacial maximum and mid-Holocene: reconstruction from pollen data using inverse vegetation modelling. Clim. Dyn. 29, 211–229 (2007).Article 

    Google Scholar 
    Harrison, S. P. & Prentice, C. I. Climate and CO2 controls on global vegetation distribution at the last glacial maximum: analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations. Glob. Chang. Biol. 9, 983–1004 (2003).ADS 
    Article 

    Google Scholar 
    Prentice, I. C., Cleator, S. F., Huang, Y. H., Harrison, S. P. & Roulstone, I. Reconstructing ice-age palaeoclimates: quantifying low-CO2 effects on plants. Glob. Planet. Change 149, 166–176 (2017).ADS 
    Article 

    Google Scholar 
    Prentice, I. C., Villegas-Diaz, R. & Harrison, S. P. Accounting for atmospheric carbon dioxide variations in pollen-based reconstruction of past hydroclimates. Glob. Planet. Change 103790 https://doi.org/10.1016/j.gloplacha.2022.103790 (2022).Abell, J. T., Winckler, G., Anderson, R. F. & Herbert, T. D. Poleward and weakened westerlies during Pliocene warmth. Nature 589, 70–75 (2021).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Winckler, G., Anderson, R. F. & Schlosser, P. Equatorial Pacific productivity and dust flux during the mid-Pleistocene climate transition. Paleoceanography 20, 1–10 (2005).Article 

    Google Scholar 
    McGee, D. & Mukhopadhyay, S. Extraterrestrial He in sediments: from recorder of asteroid collisions to timekeeper of global environmental changes. in Advances in Isotope Geochemistry 155–176 (Springer, 2013). https://doi.org/10.1007/978-3-642-28836-4_7Costa, K. & McManus, J. Efficacy of 230Th normalization in sediments from the Juan de Fuca Ridge, northeast Pacific Ocean. Geochim. Cosmochim. Acta 197, 215–225 (2017).ADS 
    CAS 
    Article 

    Google Scholar 
    Nier, A. O. & Schlutter, D. J. Extraction of helium from individual interplanetary dust particles by step-heating. Meteoritics 27, 166–173 (1992).ADS 
    CAS 
    Article 

    Google Scholar 
    McGee, D. et al. Tracking eolian dust with helium and thorium: impacts of grain size and provenance. Geochim. Cosmochim. Acta 175, 47–67 (2016).ADS 
    CAS 
    Article 

    Google Scholar 
    Bhattacharya, A. Application of the Helium Isotopic System to Accretion of Terrestrial and Extraterrestrial Dust Through the Cenozoic. (Harvard University, 2012).Ebisuzaki, W. A method to estimate the statistical significance of a correlation when the data are serially correlated. J. Clim. 10, 2147–2153 (1997).ADS 
    Article 

    Google Scholar 
    Torrence, C. & Compo, G. P. A practical guide to wavelet analysis. Bull. Am. Meteorol. Soc. 79, 61–78 (1998).ADS 
    Article 

    Google Scholar 
    Grinsted, A., Moore, J. C. & Jevrejeva, S. Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Process. Geophys. 11, 515–533 (2004).Article 

    Google Scholar 
    Berger, A. L. Long-term variations of daily insolation and Quaternary climatic changes. J. Atmos. Sci. 35, 2361–2367 (1978).ADS 
    Article 

    Google Scholar 
    Berger, A. & Loutre, M. F. Insolation values for the climate of the last 10 million years. Quat. Sci. Rev. 10, 297–317 (1991).ADS 
    Article 

    Google Scholar 
    Eisenman, I. & Huybers, P. J. daily_insolation. (2006).Thyng, K. M., Greene, C. A., Hetland, R. D., Zimmerle, H. M. & DiMarco, S. F. True colors of oceanography. Oceanography 29, 9–13 (2016).Article 

    Google Scholar 
    Lüthi, D. et al. High-resolution carbon dioxide concentration record 650,000–800,000 years before present. Nature 453, 379–382 (2008).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Rommerskirchen, F. et al. A north to south transect of Holocene southeast Atlantic continental margin sediments: relationship between aerosol transport and compound-specific δ13C land plant biomarker and pollen records. Geochem. Geophys. Geosyst. 4, (2003).Zhao, M., Dupont, L., Eglinton, G. & Teece, M. n-Alkane and pollen reconstruction of terrestrial climate and vegetation for N.W. Africa over the last 160 kyr. Org. Geochem. 34, 131–143 (2003).CAS 
    Article 

    Google Scholar 
    Küechler, R. R. A Revised Orbital Forcing Concept of West African Climate and Vegetation Variability During the Pliocene and the Last Glacial Cycle-Molecular Isotopic Approach and Proxy Calibration. (University of Bremen, 2015). More

  • in

    Linking metabolites in eight bioactive forage species to their in vitro methane reduction potential across several cultivars and harvests

    Haque, M. N. Dietary manipulation: A sustainable way to mitigate methane emissions from ruminants. J. Anim. Sci. Technol. 60, 1–10. https://doi.org/10.1186/s40781-018-0175-7(2018) (2018).Article 

    Google Scholar 
    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 (in press).Lauder, A. R. et al. Offsetting methane emissions—An alternative to emission equivalence metrics. Int. J. Greenh. 12, 419–429. https://doi.org/10.1016/j.ijggc.2012.11.028 (2013).CAS 
    Article 

    Google Scholar 
    Hill, J., McSweeney, C., Wright, A. G., Bishop-Hurley, G. & Kalantar-Zadeh, K. Measuring methane production from ruminants. Trends Biotechnol. 34, 26–35. https://doi.org/10.1016/j.tibtech.2015.10.004 (2016).CAS 
    Article 
    PubMed 

    Google Scholar 
    Van Zanten, H. H. E. et al. Defining a land boundary for sustainable livestock consumption. Glob Change Biol. 24, 4185–4194. https://doi.org/10.1111/gcb.14321 (2018).ADS 
    Article 

    Google Scholar 
    Naumann, H. D., Tedeschi, L. O., Zeller, W. E. & Huntley, N. F. The role of condensed tannins in ruminant animal production: Advances, limitations and future directions. Rev. Bras. de Zootec. 46, 929–949. https://doi.org/10.1590/S1806-92902017001200009 (2017).Article 

    Google Scholar 
    Mueller-Harvey, I. Unravelling the conundrum of tannins in animal nutrition and health. J. Sci. Food Agric. 86, 2010–2037. https://doi.org/10.1002/jsfa.2577 (2006).CAS 
    Article 

    Google Scholar 
    Burggraaf, V. T. et al. Morphology and agronomic performance of white clover with increased flowering and condensed tannin concentration. N. Z. J. Agric. Res. 49, 147–155. https://doi.org/10.1080/00288233.2006.9513704 (2006).CAS 
    Article 

    Google Scholar 
    Einarsson, R. et al. Crop production and nitrogen use in European cropland and grassland 1961–2019. Sci. Data 8, 288. https://doi.org/10.1038/s41597-021-01061-z (2021).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Salminen, J.-P. & Karonen, M. Chemical ecology of tannins and other phenolics: we need a change in approach. Funct. Ecol. 25, 325–338. https://doi.org/10.1111/j.1365-2435.2010.01826.x (2011).Article 

    Google Scholar 
    Zeller, W. E. Activity, purification, and analysis of condensed tannins: current state of affairs and future endeavors. Crop Sci. 59, 886–904. https://doi.org/10.2135/cropsci2018.05.0323 (2019).CAS 
    Article 

    Google Scholar 
    Barbehenn, R. V. & Peter Constabel, C. Tannins in plant–herbivore interactions. Phytochemistry 72, 1551–1565. https://doi.org/10.1016/j.phytochem.2011.01.040 (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    Chung, Y. H. et al. Enteric methane emission, diet digestibility, and nitrogen excretion from beef heifers fed sainfoin or alfalfa1. J. Anim. Sci. 91, 4861–4874. https://doi.org/10.2527/jas.2013-6498 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    Christensen, R. G. et al. Effects of feeding birdsfoot trefoil hay on neutral detergent fiber digestion, nitrogen utilization efficiency, and lactational performance by dairy cows1. J. Dairy Sci. 98, 7982–7992. https://doi.org/10.3168/jds.2015-9348 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    Jonker, A. & Yu, P. The occurrence, biosynthesis, and molecular structure of proanthocyanidins and their effects on legume forage protein precipitation, digestion and absorption in the ruminant digestive tract. Int. J. Mol. Sci. 18, 1105. https://doi.org/10.3390/ijms18051105 (2017).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    Barry, T. N. & McNabb, W. C. The implications of condensed tannins on the nutritive value of temperate forages fed to ruminants. Br. J. Nutr. 81, 263–272. https://doi.org/10.1017/S0007114599000501 (1999).CAS 
    Article 
    PubMed 

    Google Scholar 
    Verma, S., Taube, F. & Malisch, C. S. Examining the variables leading to apparent incongruity between antimethanogenic potential of tannins and their observed effects in ruminants—A review. Sustainability 13, 2743. https://doi.org/10.3390/su13052743 (2021).CAS 
    Article 

    Google Scholar 
    Malisch, C. S. et al. Large variability of proanthocyanidin content and composition in Sainfoin (Onobrychis viciifolia). J. Agric. Food Chem. 63, 10234–10242. https://doi.org/10.1021/acs.jafc.5b04946 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Verma, S., Salminen, J.-P., Taube, F. & Malisch, C. S. Large inter- and intraspecies variability of polyphenols and proanthocyanidins in eight temperate forage species indicates potential for their exploitation as nutraceuticals. J. Agric. Food Chem. 69, 12445–12455. https://doi.org/10.1021/acs.jafc.1c03898 (2021).CAS 
    Article 
    PubMed 

    Google Scholar 
    Lorenz, H., Reinsch, T., Kluß, C., Taube, F. & Loges, R. Does the admixture of forage herbs affect the yield performance, yield stability and forage quality of a grass clover ley?. Sustainability 12, 5842. https://doi.org/10.3390/su12145842 (2020).Article 

    Google Scholar 
    Hofer, D. et al. Yield of temperate forage grassland species is either largely resistant or resilient to experimental summer drought. J. Appl. Ecol. 53, 1023–1034. https://doi.org/10.1111/1365-2664.12694 (2016).Article 

    Google Scholar 
    Mueller-Harvey, I. et al. Benefits of condensed tannins in forage legumes fed to ruminants : Importance of structure, concentration and diet compsition. Crop Sci. 59, 861–885. https://doi.org/10.2135/cropsci2017.06.0369 (2017).CAS 
    Article 

    Google Scholar 
    Loza, C. et al. Assessing the potential of diverse forage mixtures to reduce enteric methane emissions in vitro. Animals 11, 1126. https://doi.org/10.3390/ani11041126 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Min, B. R. et al. Dietary mitigation of enteric methane emissions from ruminants: A review of plant tannin mitigation options. Anim. Nutr. 6, 231–236. https://doi.org/10.1016/j.aninu.2020.05.002 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    van Gastelen, S., Dijkstra, J. & Bannink, A. Are dietary strategies to mitigate enteric methane emission equally effective across dairy cattle, beef cattle, and sheep?. J. Dairy Sci. 102, 6109–6130. https://doi.org/10.3168/jds.2018-15785 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    Hatew, B. et al. Relationship between in vitro and in vivo methane production measured simultaneously with different dietary starch sources and starch levels in dairy cattle. Anim. Feed Sci. Technol. 202, 20–31. https://doi.org/10.1016/j.anifeedsci.2015.01.012 (2015).CAS 
    Article 

    Google Scholar 
    Storm, I. M. L. D., Hellwing, A. L. F., Nielsen, N. I. & Madsen, J. Methods for measuring and estimating methane emission from ruminants. Animals 2, 160–183. https://doi.org/10.3390/ani2020160 (2012).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dewhurst, R. J., Delaby, L., Moloney, A., Boland, T. & Lewis, E. Nutritive value of forage legumes used for grazing and silage. Irish J. Agric. Food Res. 48, 167–187 (2009).CAS 

    Google Scholar 
    Hakl, J., Fuksa, P., Konečná, J. & Šantrůček, J. Differences in the crude protein fractions of lucerne leaves and stems under different stand structures. Grass Forage Sci. 71, 413–423. https://doi.org/10.1111/gfs.12192 (2016).CAS 
    Article 

    Google Scholar 
    Jayanegara, A., Makkar, H. & Becker, K. The use of principal component analysis in identifying and integrating variables related to forage quality and methane production. J. Indones. Trop. Anim. 34, 241–247. https://doi.org/10.14710/jitaa.34.4.241-247 (2009).Article 

    Google Scholar 
    Maccarana, L. et al. Methodological factors affecting gas and methane production during in vitro rumen fermentation evaluated by meta-analysis approach. J. Anim. Sci. Biotechnol. 7, 35–35. https://doi.org/10.1186/s40104-016-0094-8 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Baruah, L., Malik, P. K., Kolte, A. P., Dhali, A. & Bhatta, R. Methane mitigation potential of phyto-sources from Northeast India and their effect on rumen fermentation characteristics and protozoa in vitro. Vet. World 11, 809–818. https://doi.org/10.14202/vetworld.2018.809-818 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hassanat, F. & Benchaar, C. Assessment of the effect of condensed (acacia and quebracho) and hydrolysable (chestnut and valonea) tannins on rumen fermentation and methane production in vitro. J. Sci. Food Agric. 93, 332–339. https://doi.org/10.1002/jsfa.5763 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    Naumann, H. et al. Relationships between structures of condensed tannins from texas legumes and methane production during in vitro rumen digestion. Molecules 23, 2123. https://doi.org/10.3390/molecules23092123 (2018).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    Jayanegara, A., Makkar, H. P. S. & Becker, K. Addition of purified tannin sources and polyethylene glycol treatment on methane emission and rumen fermentation in vitro. Media Peternakan 38, 57–63. https://doi.org/10.5398/medpet.2015.38.1.57 (2015).Article 

    Google Scholar 
    Jayanegara, A., Goel, G., Makkar, H. P. S. & Becker, K. Divergence between purified hydrolysable and condensed tannin effects on methane emission, rumen fermentation and microbial population in vitro. Anim. Feed Sci. Technol. 209, 60–68. https://doi.org/10.1016/j.anifeedsci.2015.08.002 (2015).CAS 
    Article 

    Google Scholar 
    Hatew, B. et al. Diversity of condensed tannin structures affects rumen in vitro methane production in sainfoin (Onobrychis viciifolia) accessions. Grass Forage Sci. 70, 474–490. https://doi.org/10.1111/gfs.12125 (2015).CAS 
    Article 

    Google Scholar 
    Huyen, N. T. et al. Structural features of condensed tannins affect in vitro ruminal methane production and fermentation characteristics. J. Agric. Sci. 154, 1474–1487. https://doi.org/10.1017/S0021859616000393 (2016).CAS 
    Article 

    Google Scholar 
    Salami, S. A. et al. Characterisation of the ruminal fermentation and microbiome in lambs supplemented with hydrolysable and condensed tannins. FEMS Microbiol. Ecol. https://doi.org/10.1093/femsec/fiy061 (2018).Article 
    PubMed 

    Google Scholar 
    Salminen, J. P., Karonen, M. & Sinkkonen, J. Chemical ecology of tannins: Recent developments in tannin chemistry reveal new structures and structure-activity patterns. Chem.-Eur. J. 17, 2806–2816. https://doi.org/10.1002/chem.201002662 (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    Bezabih, M., Pellikaan, W. F., Tolera, A., Khan, N. A. & Hendriks, W. Chemical composition and in vitro total gas and methane production of forage species from the Mid Rift Valley grasslands of Ethiopia. Grass Forage Sci. 69, 635–643. https://doi.org/10.1111/gfs.12091 (2013).CAS 
    Article 

    Google Scholar 
    Navarrete, S., Kemp, P. D., Pain, S. J. & Back, P. J. Bioactive compounds, aucubin and acteoside, in plantain (Plantago lanceolata L.) and their effect on in vitro rumen fermentation. Anim. Feed Sci. Technol. 222, 158–167. https://doi.org/10.1016/j.anifeedsci.2016.10.008 (2016).CAS 
    Article 

    Google Scholar 
    Basha, N. A., Scogings, P. F. & Nsahlai, I. V. Effects of season, browse species and polyethylene glycol addition on gas production kinetics of forages in the subhumid subtropical savannah, South Africa. J. Sci. Food Agric. 93, 1338–1348. https://doi.org/10.1002/jsfa.5895 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    O’Donovan, L. & Brooker, J. D. Effect of hydrolysable and condensed tannins on growth, morphology and metabolism of Streptococcus gallolyticus (S. caprinus) and Streptococcus bovis. Microbiology 147, 1025–1033. https://doi.org/10.1099/00221287-147-4-1025 (2001).CAS 
    Article 
    PubMed 

    Google Scholar 
    Bhatta, R. et al. Difference in the nature of tannins on in vitro ruminal methane and volatile fatty acid production and on methanogenic archaea and protozoal populations. J. Dairy Sci. 92, 5512–5522. https://doi.org/10.3168/jds.2008-1441 (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Naumann, H. D. et al. Effect of molecular weight and concentration of legume condensed tannins on in vitro larval migration inhibition of Haemonchus contortus. Vet. Parasitol. 199, 93–98. https://doi.org/10.1016/j.vetpar.2013.09.025 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    Jayanegara, A., Goel, G., Makkar, H.P.S., & Becker, K. Reduction in
    methane emissions from ruminants by plant secondary metabolites: Effects of polyphenols and saponins. Food and Agriculture Organization of the United Nations (FAO) Rome, Italy, 151–157. ISBN 978-92-5-106697-3 (2010).Hatew, B. et al. Impact of variation in structure of condensed tannins from sainfoin (Onobrychis viciifolia) on in vitro ruminal methane production and fermentation characteristics. J. Anim. Physiol. Anim. Nutr. 100, 348–360. https://doi.org/10.1111/jpn.12336 (2016).CAS 
    Article 

    Google Scholar 
    Waghorn, G. C., Douglas, G. B., Niezen, J. H., McNabb, W. C. & Foote, A. G. Forages with condensed tannins-their management and nutritive value for ruminants. Proc. N. Z. Grassl. Assoc., 60, 89−98 (1998).Woodward, S. L., Waghorn, G. C. & Lassey, K. Early indications that feeding Lotus will reduce methane emissions from ruminants. Proc. N. Z. Soc. Anim. Prod. 61, 23–26 (2001).
    Google Scholar 
    Molle, G. et al. Responses to condensed tannins of flowering sulla (Hedysarum coronarium L.) grazed by dairy sheep: Part 1: Effects on feeding behaviour, intake, diet digestibility and performance. Livest. Sci. 123, 138–146. https://doi.org/10.1016/j.livsci.2008.11.018 (2009).Article 

    Google Scholar 
    Orlandi, T., Kozloski, G. V., Alves, T. P., Mesquita, F. R. & Ávila, S. C. Digestibility, ruminal fermentation and duodenal flux of amino acids in steers fed grass forage plus concentrate containing increasing levels of Acacia mearnsii tannin extract. Anim. Feed Sci. Technol. 210, 37–45. https://doi.org/10.1016/j.anifeedsci.2015.09.012 (2015).CAS 
    Article 

    Google Scholar 
    Patra, A. K. & Yu, Z. Effects of adaptation of in vitro rumen culture to garlic oil, nitrate, and saponin and their combinations on methanogenesis, fermentation, and abundances and diversity of microbial populations. Front. Microbiol. https://doi.org/10.3389/fmicb.2015.01434 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Niderkorn, V. et al. Effect of increasing the proportion of chicory in forage-based diets on intake and digestion by sheep. Animal 13, 718–726. https://doi.org/10.1017/S1751731118002185 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    Lee, J., Hemmingson, N., Minneé, E. & Clark, C. Management strategies for chicory (Cichorium intybus) and plantain (Plantago lanceolata): Impact on dry matter yield, nutritive characteristics, and plant density. Crop Pasture Sci. 66, 168. https://doi.org/10.1071/CP14181 (2015).CAS 
    Article 

    Google Scholar 
    Cong, W.-F., Jing, J., Rasmussen, J., Søegaard, K. & Eriksen, J. Forbs enhance productivity of unfertilised grass-clover leys and support low-carbon bioenergy. Sci. Rep. 7, 1422. https://doi.org/10.1038/s41598-017-01632-4 (2017).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sanderson, M. A., Labreveux, M., Hall, M. H. & Elwinger, G. F. Nutritive value of chicory and English plantain forage. Crop Sci. 43, 1797. https://doi.org/10.2135/cropsci2003.1797 (2003).CAS 
    Article 

    Google Scholar 
    Van Soest, P. J., Robertson, J. B. & Lewis, B. A. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J. Dairy Sci. 74, 3583–3597. https://doi.org/10.3168/jds.S0022-0302(91)78551-2 (1991).Article 
    PubMed 

    Google Scholar 
    Engström, M. T. et al. Rapid qualitative and quantitative analyses of proanthocyanidin oligomers and polymers by UPLC-MS/MS. J. Agric. Food Chem. 62, 3390–3399. https://doi.org/10.1021/jf500745y (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    Menke, K. & Steingass, H. Estimation of the energetic feed value obtained from chemical analysis and in vitro gas production using rumen fluid. Anim. Res. Dev. 28, 7–55 (1988).
    Google Scholar 
    R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).Venables, B. & Ripley, B. Generalised linear models. In Modern Applied Statistics With S.(4th edition) 183–208 (Springer, 2013). More

  • in

    Common and distinctive genomic features of Klebsiella pneumoniae thriving in the natural environment or in clinical settings

    Genome’s collection and phylogenetic analysisThe study examined the genomes of 139 isolates, 61 of environmental samples (ENV) and 78 clinical (CLI) (Supplementary Table 1, Supplementary Fig. 1), with origin in 21 countries: USA (23/139, 17%), UK, Portugal and Spain (each 15/139, 33%), China (14/139, 10%), Germany (13/139, 9%), Thailand (11/139, 8%) and other countries (each  More

  • in

    Honey bee symbiont buffers larvae against nutritional stress and supplements lysine

    Dolezal AG, Toth AL. Feedbacks between nutrition and disease in honey bee health. Curr Opin Insect Sci. 2018;26:114–9.PubMed 
    Article 

    Google Scholar 
    Scofield HN, Mattila HR. Honey bee workers that are pollen stressed as larvae become poor foragers and waggle dancers as adults. PLoS ONE. 2015;10:e0121731.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    McFall-Ngai M, Hadfield MG, Bosch TCG, Carey HV, Domazet-Lošo T, Douglas AE, et al. Animals in a bacterial world, a new imperative for the life sciences. Proc Natl Acad Sci USA. 2013;110:3229–36.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Akman Gündüz E, Douglas AE. Symbiotic bacteria enable insect to use a nutritionally inadequate diet. Proc R Soc B Biol Sci. 2009;276:987–91.Article 
    CAS 

    Google Scholar 
    Wu D, Daugherty SC, Van Aken SE, Pai GH, Watkins KL, Khouri H, et al. Metabolic Complementarity and Genomics of the Dual Bacterial Symbiosis of Sharpshooters. PLoS Biol 2006;4:e188.Bing X, Attardo GM, Vigneron A, Aksoy E, Scolari F, Malacrida A, et al. Unravelling the relationship between the tsetse fly and its obligate symbiont Wigglesworthia: transcriptomic and metabolomic landscapes reveal highly integrated physiological networks. Proc R Soc B Biol Sci. 2017; 284:20170360.Itoh H, Jang S, Takeshita K, Ohbayashi T, Ohnishi N, Meng X-Y, et al. Host–symbiont specificity determined by microbe–microbe competition in an insect gut. Proc Natl Acad Sci USA. 2019;116:22673–82.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Flórez LV, Scherlach K, Miller IJ, Rodrigues A, Kwan JC, Hertweck C, et al. An antifungal polyketide associated with horizontally acquired genes supports symbiont-mediated defense in Lagria villosa beetles. Nat Commun. 2018;9:2478.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Kaltenpoth M, Göttler W, Herzner G, Strohm E. Symbiotic bacteria protect wasp larvae from fungal infestation. Curr Biol. 2005;15:475–9.CAS 
    PubMed 
    Article 

    Google Scholar 
    Oliver KM, Degnan PH, Hunter MS, Moran NA. Bacteriophages encode factors required for protection in a symbiotic mutualism. Science 2009;325:992–4.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Shin SC, Kim SH, You H, Kim B, Kim AC, Lee KA, et al. Drosophila microbiome modulates host developmental and metabolic homeostasis via insulin signaling. Science 2011;334:670–4.CAS 
    PubMed 
    Article 

    Google Scholar 
    Dedeine F, Vavre F, Fleury F, Loppin B, Hochberg ME, Boulétreau M. Removing symbiotic Wolbachia bacteria specifically inhibits oogenesis in a parasitic wasp. Proc Natl Acad Sci USA. 2001;98:6247–52.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Koropatnick TA, Engle JT, Apicella MA, Stabb EV, Goldman WE, McFall-Ngai MJ. Microbial factor-mediated development in a host-bacterial mutualism. Science 2004;306:1186–8.CAS 
    PubMed 
    Article 

    Google Scholar 
    Chun CK, Troll JV, Koroleva I, Brown B, Manzella L, Snir E, et al. Effects of colonization, luminescence, and autoinducer on host transcription during development of the squid-vibrio association. Proc Natl Acad Sci USA. 2008;105:11323–8.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Shikuma NJ, Pilhofer M, Weiss GL, Hadfield MG, Jensen GJ, Newman DK. Marine tubeworm metamorphosis induced by arrays of bacterial phage tail-like structures. Science 2014;343:529–33.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Freiberg C, Fellay R, Bairoch A, Broughton WJ, Rosenthal A, Perret X. Molecular basis of symbiosis between Rhizobium and legumes. Nature 1997;387:394–401.CAS 
    PubMed 
    Article 

    Google Scholar 
    Médigue C, Masson-Boivin C, Gilbert LB, Cruveiller S, Gris C, Batut J, et al. Experimental evolution of a plant pathogen into a legume symbiont. PLoS Biol. 2010;8:e1000280.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Brucker RM, Bordenstein SR. Speciation by symbiosis. Trends Ecol Evol. 2012;27:443–51.PubMed 
    Article 

    Google Scholar 
    Moran NA, McCutcheon JP, Nakabachi A. Genomics and evolution of heritable bacterial symbionts. Annu Rev Genet. 2008;42:165–90.CAS 
    PubMed 
    Article 

    Google Scholar 
    Moran NA, Tran P, Gerardo NM. Symbiosis and insect diversification: an ancient symbiont of sap-feeding insects from the bacterial phylum Bacteroidetes. Appl Environ Microbiol. 2005;71:8802–10.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lee FJ, Miller KI, McKinlay JB, Newton ILG. Differential carbohydrate utilization and organic acid production by honey bee symbionts. FEMS Microbiol Ecol. 2018;94:fiy113.CAS 
    Article 

    Google Scholar 
    Lee FJ, Rusch DB, Stewart FJ, Mattila HR, Newton ILG. Saccharide breakdown and fermentation by the honey bee gut microbiome. Environ Microbiol. 2015;17:796–815.CAS 
    PubMed 
    Article 

    Google Scholar 
    Zheng H, Nishida A, Kwong WK, Koch H, Engel P, Steele MI, et al. Metabolism of toxic sugars by strains of the bee gut symbiont Gilliamella apicola. MBio 2016;7:e01326–16.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kešnerová L, Mars RAT, Ellegaard KM, Troilo M, Sauer U, Engel P. Disentangling metabolic functions of bacteria in the honey bee gut. PLoS Biol. 2017;15:e2003467.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Gallai N, Salles JM, Settele J, Vaissière BE. Economic valuation of the vulnerability of world agriculture confronted with pollinator decline. Ecol Econ. 2009;68:810–21.Article 

    Google Scholar 
    Brodschneider R, Gray A, Adjlane N, Ballis A, Brusbardis V, Charrière JD, et al. Multi-country loss rates of honey bee colonies during winter 2016/2017 from the COLOSS survey. J Apic Res. 2018;57:452–7.Article 

    Google Scholar 
    Kulhanek K, Steinhauer N, Rennich K, Caron DM, Sagili RR, Pettis JS, et al. A national survey of managed honey bee 2015-6 annual colony losses in the USA. J Apic Res. 2017;56:328–40.Article 

    Google Scholar 
    Goulson D, Nicholls E, Botías C, Rotheray EL. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 2015;347:1255957.PubMed 
    Article 
    CAS 

    Google Scholar 
    Dolezal AG, Carrillo-Tripp J, Judd TM, Allen Miller W, Bonning BC, Toth AL. Interacting stressors matter: Diet quality and virus infection in honeybee health. R Soc Open Sci. 2019;6:81803.Article 
    CAS 

    Google Scholar 
    St Clair AL, Zhang G, Dolezal AG, O’Neal ME, Toth AL, et al. Diversified farming in a monoculture landscape: effects on honey bee health and wild bee communities. Environ Entomol. 2020;49:753–64.Article 

    Google Scholar 
    Naug D. Nutritional stress due to habitat loss may explain recent honeybee colony collapses. Biol Conserv. 2009;142:2369–72.Article 

    Google Scholar 
    Taha EKA, Al-Kahtani S, Taha R. Protein content and amino acids composition of bee-pollens from major floral sources in Al-Ahsa, eastern Saudi Arabia. Saudi J Biol Sci. 2019;26:232–7.CAS 
    PubMed 
    Article 

    Google Scholar 
    de Groot AP. Amino acid requirements for growth of the honeybee (Apis mellifica L.). Experientia 1952;8:192–4.Article 

    Google Scholar 
    Brodschneider R, Crailsheim K. Nutrition and health in honey bees. Apidologie 2010;41:278–94.Article 

    Google Scholar 
    Keller I, Fluri P, Imdorf A. Pollen nutrition and colony development in honey bees – Part II. Bee World. 2005;86:27–34.Article 

    Google Scholar 
    Huang Z. Pollen nutrition affects honey bee stress resistance. Terr Arthropod Rev. 2012;5:175–89.Article 

    Google Scholar 
    van Dooremalen C, Stam E, Gerritsen L, Cornelissen B, van der Steen J, van Langevelde F, et al. Interactive effect of reduced pollen availability and Varroa destructor infestation limits growth and protein content of young honey bees. J Insect Physiol. 2013;59:487–93.PubMed 
    Article 
    CAS 

    Google Scholar 
    Feldhaar H, Straka J, Krischke M, Berthold K, Stoll S, Mueller MJ, et al. Nutritional upgrading for omnivorous carpenter ants by the endosymbiont Blochmannia. BMC Biol. 2007;5:48.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Sannino DR, Dobson AJ, Edwards K, Angert ER, Buchon N. The Drosophila melanogaster gut microbiota provisions thiamine to its host. MBio 2018;9:e00155–18.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hammer TJ, Moran NA. Links between metamorphosis and symbiosis in holometabolous insects. Philos Trans R Soc B Biol Sci. 2019;374:20190068.CAS 
    Article 

    Google Scholar 
    Kowallik V, Mikheyev AS. Honey bee larval and adult microbime life stages are effectively decoupled with vertical transmisson overcoming early life perturbations. mBio 2021;12:e02966–21.CAS 
    PubMed Central 
    Article 

    Google Scholar 
    Storelli G, Defaye A, Erkosar B, Hols P, Royet J, Leulier F. Lactobacillus plantarum promotes Drosophila systemic growth by modulating hormonal signals through TOR-dependent nutrient sensing. Cell Metab. 2011;14:403–14.CAS 
    PubMed 
    Article 

    Google Scholar 
    Wright GA, Nicolson SW, Shafir S. Nutritional physiology and ecology of honey bees. Annu Rev Entomol. 2017;63:327–44.PubMed 
    Article 
    CAS 

    Google Scholar 
    Tarpy DR, Mattila HR, Newton ILG. Development of the honey bee gut microbiome throughout the queen-rearing process. Appl Environ Microbiol. 2015;81:3182–91.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Corby-Harris V, Snyder LA, Schwan MR, Maes P, McFrederick QS, Anderson KE. Origin and effect of Alpha 2.2 Acetobacteraceae in honey bee larvae and description of Parasaccharibacter apium gen. nov., sp. nov. Appl Environ Microbiol. 2014;80:7460–72.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Vojvodic S, Rehan SM, Anderson KE. Microbial gut diversity of Africanized and European honey bee larval instars. PLoS ONE. 2013;8:72106.Article 
    CAS 

    Google Scholar 
    Kwong WK, Medina LA, Koch H, Sing KW, Soh EJY, Ascher JS, et al. Dynamic microbiome evolution in social bees. Sci Adv. 2017;3:e1600513.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Cohen O, Ashkenazy H, Belinky F, Huchon D, Pupko T. GLOOME: Gain loss mapping engine. Bioinformatics 2010;26:2914–5.CAS 
    PubMed 
    Article 

    Google Scholar 
    Price MN, Deutschbauer AM, Arkin AP. GapMind: Automated annotation of amino acid biosynthesis. mSystems 2020;5:e00291–20.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Schmehl DR, Tomé HVV, Mortensen AN, Martins GF, Ellis JD. Protocol for the in vitro rearing of honey bee (Apis mellifera L.) workers. J Apic Res. 2016;55:113–29.Article 

    Google Scholar 
    Li H, Tennessen JM. Preparation of Drosophila larval samples for gas chromatography-mass spectrometry (GC-MS)-based metabolomics. J Vis Exp. 2018;136:e57847.
    Google Scholar 
    Rortais A, Arnold G, Halm MP, Touffet-Briens F. Modes of honeybees exposure to systemic insecticides: Estimated amounts of contaminated pollen and nectar consumed by different categories of bees. Apidologie 2005;36:71–83.CAS 
    Article 

    Google Scholar 
    Buttstedt A, Mureşan CI, Lilie H, Hause G, Ihling CH, Schulze SH, et al. How honeybees defy gravity with royal jelly to raise queens. Curr Biol. 2018;28:1095–1100.CAS 
    PubMed 
    Article 

    Google Scholar 
    Fratini F, Cilia G, Mancini S, Felicioli A. Royal jelly: An ancient remedy with remarkable antibacterial properties. Microbiol Res. 2016;192:130–41.CAS 
    PubMed 
    Article 

    Google Scholar 
    Fontana R, Mendes MA, De Souza BM, Konno K, César LMM, Malaspina O, et al. Jelleines: A family of antimicrobial peptides from the royal jelly of honeybees (Apis mellifera). Peptides 2004;25:919–28.CAS 
    PubMed 
    Article 

    Google Scholar 
    Rokop ZP, Horton MA, Newton ILG. Interactions between cooccurring lactic acid bacteria in honey bee hives. Appl Environ Microbiol. 2015;81:7261–70.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Crailsheim K, Brodschneider R, Aupinel P, Behrens D, Genersch E, Vollmann J, et al. Standard methods for artificial rearing of Apis mellifera larvae. J Apic Res. 2013;52:1–16.Article 

    Google Scholar 
    Smith EA, Newton ILG. Genomic signatures of honey bee association in an acetic acid symbiont. Genome Biol Evol. 2020;12:1882–94.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kaftanoglu O, Linksvayer TA, Page RE. Rearing honey bees, Apis mellifera, in vitro 1: Effects of sugar concentrations on survival and development. J Insect Sci. 2011;11:96.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Aupinel P, Fortini D, Dufour H, Tasei J-N, Michaud B, Odoux J-F, et al. Improvement of artificial feeding in a standard in vitro method for rearing Apis mellifera larvae. Bull Insectol. 2005;58:107–11.
    Google Scholar 
    Hansen AK, Moran NA. Aphid genome expression reveals host-symbiont cooperation in the production of amino acids. Proc Natl Acad Sci USA. 2011;108:2849–54.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McCutcheon JP, McDonald BR, Moran NA. Convergent evolution of metabolic roles in bacterial co-symbionts of insects. Proc Natl Acad Sci USA. 2009;106:15394–9.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Shigenobu S, Watanabe H, Hattori M, Sakaki Y, Ishikawa H. Genome sequence of the endocellular bacterial symbiont of aphids Buchnera sp. Aps Nat. 2000;407:81–86.CAS 

    Google Scholar 
    Gil R, Silva FJ, Zientz E, Delmotte F, González-Candelas F, Latorre A, et al. The genome sequence of Blochmannia floridanus: Comparative analysis of reduced genomes. Proc Natl Acad Sci USA. 2003;100:9388–93.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McCutcheon JP, Moran NA. Extreme genome reduction in symbiotic bacteria. Nat Rev Microbiol. 2012;10:13–26.CAS 
    Article 

    Google Scholar 
    Wernegreen JJ, Lazarus AB, Degnan PH. Small genome of Candidatus Blochmannia, the bacterial endosymbiont of Camponotus, implies irreversible specialization to an intracellular lifestyle. Microbiology 2002;148:2551–6.CAS 
    PubMed 
    Article 

    Google Scholar 
    McCutcheon JP, Moran NA. Parallel genomic evolution and metabolic interdependence in an ancient symbiosis. Proc Natl Acad Sci USA. 2007;104:19392–7.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bennett GM, Mccutcheon JP, Macdonald BR, Romanovicz D, Moran NA. Differential genome evolution between companion symbionts in an insect-bacterial symbiosis. mBio 2014;5:e01697–14.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Husnik F, Nikoh N, Koga R, Ross L, Duncan RP, Fujie M, et al. Horizontal gene transfer from diverse bacteria to an insect genome enables a tripartite nested mealybug symbiosis. Cell 2013;153:1567.CAS 
    PubMed 
    Article 

    Google Scholar 
    Bao XY, Yan JY, Yao YL, Wang Y, Bin, Visendi P, Seal S, et al. Lysine provisioning by horizontally acquired genes promotes mutual dependence between whitefly and two intracellular symbionts. PLOS Pathog. 2021;17:e1010120.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Cotte JF, Casabianca H, Giroud B, Albert M, Lheritier J, Grenier-Loustalot MF. Characterization of honey amino acid profiles using high-pressure liquid chromatography to control authenticity. Anal Bioanal Chem. 2004;378:1342–50.CAS 
    PubMed 
    Article 

    Google Scholar 
    Baker HG. Non-sugar chemical constituents of nectar. Apidologie 1977;8:349–56.Article 

    Google Scholar 
    Nyholm SV, McFall-Ngai MJ. The winnowing: Establishing the squid – Vibrios symbiosis. Nat Rev Microbiol. 2004;2:632–42.CAS 
    PubMed 
    Article 

    Google Scholar 
    Kikuchi Y, Hosokawa T, Fukatsu T. Insect-microbe mutualism without vertical transmission: a stinkbug acquires a beneficial gut symbiont from the environment every generation. Appl Environ Microbiol. 2007;73:4308–16.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Itoh H, Jang S, Takeshita K, Ohbayashi T, Ohnishi N, Meng XY, et al. Host–symbiont specificity determined by microbe–microbe competition in an insect gut. Proc Natl Acad Sci USA. 2019;116:22673–82.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Oono R, Anderson CG, Denison RF. Failure to fix nitrogen by non-reproductive symbiotic rhizobia triggers host sanctions that reduce fitness of their reproductive clonemates. Proc R Soc B Biol Sci. 2011;278:2698–703.Article 

    Google Scholar 
    Brown BP, Wernegreen JJ. Genomic erosion and extensive horizontal gene transfer in gut-associated Acetobacteraceae. BMC Genom. 2019;20:1–15.CAS 
    Article 

    Google Scholar 
    Vitreschak AG, Rodionov DA, Mironov AA, Gelfand MS. Riboswitches: the oldest mechanism for the regulation of gene expression? Trends Genet. 2004;20:44–50.CAS 
    PubMed 
    Article 

    Google Scholar 
    Meijuan X, Rao Z, Yang J, Dou W, Xu Z. The effect of a LYSE exporter overexpression on L-arginine production in Corynebacterium crenatum. Curr Microbiol. 2013;67:271–8.Article 
    CAS 

    Google Scholar 
    Indurthi SM, Chou H-T, Lu C-D. Molecular characterization of lysR-lysXE, gcdR-gcdHG and amaR-amaAB operons for lysine export and catabolism: a comprehensive lysine catabolic network in Pseudomonas aeruginosa PAO1. Microbiology 2016;162:876–88.CAS 
    Article 

    Google Scholar 
    Pathania A, Sardesai AA. Distinct paths for basic amino acid export in Escherichia coli: YbjE (LysO) mediates export of L-lysine. J Bacteriol. 2015;197:2036–47.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Miller DL, Smith EA, Newton ILG. A bacterial symbiont protects honey bees from fungal disease. mBio 2021;12:e00503–21.CAS 
    PubMed Central 
    Article 

    Google Scholar  More

  • in

    Sustainable small-scale fisheries can help people and the planet

    More than three billion people rely on the ocean to make a living, most of whom are in developing countries. For some 17% of the world’s population, fisheries and aquaculture provide the main source of animal protein. For the least-developed countries, fish contributes about 29% of animal protein intake; in other developing countries, it accounts for 19%1.As the global population increases, the demand for seafood is expected to rise, too. Already, Africa and Asia have seen fish production double over the past few decades. Globally, fish consumption is set to rise by around 15% by 20302.Although ocean ecosystems are strained by climate change, overfishing and more, studies nevertheless suggest that seafood can be expanded sustainably to meet future food demands3. Last year, international efforts promoting this approach included the Blue Food Assessment (a joint initiative of 25 research institutions) and the United Nations Food Systems Summit.Success will depend on small-scale fisheries. Small operations tend to deliver both food and income directly to the people who need them most, and locals have a strong incentive to make their practices sustainable. What’s more, these fisheries can be remarkably efficient. Almost everything that hand-to-mouth fisheries catch is consumed. By contrast, around 20% of the fish caught by industrial fleets is estimated to be wasted, mainly because of unwanted by-catch4. So, whereas large-scale operators land more fish, small-scale fisheries provide a larger share of the fish that is actually consumed.Small fishers rarely have the right resources to expand their operations, or even to survive. If they do scale up, they might lose some of their current advantages or engage in the same harmful practices as do large commercial fisheries. Managed with care, however, small fisheries could provide win–wins for livelihoods and the environment. Making this happen should be high on the agenda at the UN Ocean Conference in Lisbon this month.As someone who has studied food security and policymaking for decades, here I suggest ways to support and strengthen artisanal fishing operations.Small reformsThe potential and importance of small-scale fisheries has been increasingly recognized over the past decade. In 2014, the UN Food and Agriculture Organization (FAO) provided voluntary guidelines to support sustainable small-scale fisheries, aimed at improving food security and eradicating poverty. A forthcoming report by the FAO, Duke University in Durham, North Carolina, and the non-profit organization WorldFish, headquartered in Penang, Malaysia, will conclude a remarkable initiative to collate case studies, questionnaire results and data sets to help get fishers a seat at policymakers’ tables. The UN General Assembly has declared 2022 the International Year of Artisanal Fisheries and Aquaculture.Most nations already have management policies for marine ecosystems that provide for small-scale fisheries. In India, Indonesia, Malaysia and Sri Lanka, for example, there is a ban on trawling within about 8 kilometres of the coastline to prevent industrial fishers from scooping up large catches, which protects those regions for local fishers. Countries such as Costa Rica ease access by exempting small-scale fisheries from licences, and Angola exempts subsistence and artisanal fishers from paying licensing fees5.But this is not enough. Small-scale fishers’ rights to access are often poorly defined, ineffectively enforced or unfairly distributed4. The boundaries of exclusive economic zones (EEZs) — the parts of the coast belonging to a given nation — are often poorly policed, and large-scale vessels regularly swoop in and take sea life through bottom trawling, something that small fishers seldom practice. Large-scale bottom-trawlers account for 26% of the global fisheries catch, with more than 99% of that occurring in the EEZs of coastal countries6. Even when there are well-meaning policies to protect local fishers, foreign vessels can take advantage. For instance, a 2018 investigation by the Environmental Justice Foundation in London found that around 90% of Ghana’s industrial fishing fleet was linked to Chinese ownership, despite Ghanaian laws expressly forbidding foreign ownership or control of its boats. Clearer definitions of the terms fisher, fishing and fishing vessel to make provisions for small-scale operators could help, in part, to avoid such abuse.Government subsidies also require reform. One estimate found that large-scale fishers receive about three-and-a-half times more subsidies than small-scale fishers do7. This widens the existing advantages of large operations in terms of vessels and gear, infrastructure (including cold storage), processing capacity and access to cheap fuel. By giving large-scale fishers the capacity to catch even more, it can have the perverse effect of encouraging overfishing8. Instead, subsidies and other funds should be directed towards small-scale fishers to let them expand their access to markets, while keeping them from adopting the negative practices of large-scale operations.More for consumptionThe total global loss and waste from fisheries is estimated at between 30% and 35% annually1. This could increase as smaller operations broaden their markets. A 2015 estimate of the Volta Basin coast in West Africa attributed 65% of fish-production losses to a lack of technology and good manufacturing practices, and to a lack of infrastructure such as decent roads and cold storage9. The study found that fish were rarely lost to physical damage during the process; most waste resulted from spoilage. Such losses limit the sale of fish locally and to distant markets.Public and private investment in cold-storage facilities and processing equipment (such as for drying, fermentation, pickling or smoking) could help. Current funding for fishery conservation projects comes from development partners, regional banks, the World Bank, private foundations and other agencies — with some entities also providing microloans to small-scale fisheries — but these efforts are uncoordinated and inadequate.One promising strategy is to pair international or national funding with direct contracts for feeding programmes linked to schools, hospitals and similar facilities. Such arrangements would provide small fisheries with large, consistent markets and storage infrastructure that boosts local consumption and does not incentivize overfishing.

    Artisanal fishers at a fish-processing cooperative in Santa Rosa de Salinas, Ecuador.Credit: Camilo Pareja/AFP/Getty

    Other strategies pair local fishers with conservation efforts. As fishing operations scale up, fish entrails and other waste cannot simply be thrown into the sea: care must be taken not to contaminate the environment. One option is to fund ecosystem-restoration projects that also benefit local fisheries. For example, the Mikoko Pamoja (Mangroves Together) project in Gazi Bay, Kenya, restores and conserves degraded mangrove forests, which act as nurseries for young fish. The restoration thus earns saleable carbon credits while enhancing nearby fishery grounds for the local community.Consumers could support small fisheries by buying local, because shorter supply chains mean more income for the fishers. The use of ecolabels — which seek to promote sustainably managed fisheries by certifying that a product has a reduced environmental impact — could also encourage consumer adoption, and help consumers to make informed choices.However, such certification is costly to obtain and maintain, and requires compliance, monitoring and reporting. Certification can distort market opportunities, effectively excluding small enterprises from entering international markets. These programmes can also have unintended consequences: most certification programmes focus on environmental sustainability and pay less attention to social responsibility elements, such as fairness in access to resources, markets and wages.Instead, simple incentive programmes could be implemented by funders, managers and local governments trying to promote sustainable fisheries. For example, local markets could display a rating system for individual fishers or small entrepreneurs. This could include various elements of sustainability other than environmental ones — such as providing information on the type of fishing gear, location of the catch and freshness. Promoting the rating as a social responsibility concept would inform consumers of the need to support sustainable fisheries. The rating system could be conducted by community members trained in inspection and enforcement.Local controlDiverse efforts are needed to protect small fisheries’ access and to boost local consumption and reduce waste, and must be tailored to local community conditions. The 2021 UN Food Systems Summit was a ‘people’s summit’ that elevated roles for Indigenous peoples and civil-society groups, yet the voice of fishing communities was notably absent.Few governments take an integrated approach to the development, implementation and enforcement of policies. For example, policies governing urban development tend not to consider the implications on the ocean, fish and fishers. In the late 2000s, for instance, fishers were initially denied access to traditional public fishing zones along the beach front in Durban, South Africa, following upgrades to the port and the development of a private marina and hotel. (Fishers later reclaimed some of the zones after protests and engagement with the authorities10.)Cooperatives can help on several fronts: by coordinating fishing activities, sharing information (about weather, sea conditions or fish movement) and advocating effectively for human and social rights. For instance, CoopeSoliDar, a small-scale fisheries management cooperative in San José, Costa Rica, has helped to strengthen collective action to sustainably use molluscs, alleviate poverty and strengthen the representation of women and young people in community decision-making. Governments can help by creating a legal framework to establish cooperatives and include them in decisions to manage marine resources.Local communities can also stand up for themselves. For example, a class action by a group of 5,000 artisanal fishers in South Africa in 2004 argued against a policy they said did not give them recognition or access to food and fishing rights that were established in the country’s constitution. The court ruled in the group’s favour in 2007, and the resulting legal framework granted small-scale fishers collective community fishing rights, recognizing community members as bona fide fishers11.Integrated inputsSmall fisheries do not operate in isolation. Unlike terrestrial resources, the ocean is an extensive, global commons without clear territorial boundaries. Issues as diverse as climate change, ocean acidification, overfishing and pollution by nutrients and plastics and other chemicals all affect local fishers. But such system interactions get scant attention when fisheries policies focus on a single seafood stock or individual fishing area.Whereas the concept of integrated land management has been part of the development agenda for a few decades, integrated marine management is only now emerging. To work, it must involve all relevant stakeholders, including small-scale fishers.A context-specific strategy in the Seychelles is a leading example of such integration. Communities, financing partners and the government worked together to create the Seychelles Marine Spatial Plan Initiative, which protects 30% of the archipelago’s waters and boosts climate resilience. The Seychelles faces significant threats from rising sea levels and warmer air and water temperatures that put fisheries, infrastructure, tourism and its rich biodiversity at risk.In an example in the Coral Triangle region (encompassing Indonesia, Malaysia, Papua New Guinea, the Philippines, the Solomon Islands and East Timor), local communities gave their input to a marine protection plan. This led to a greater understanding of how practices such as overfishing and taking undersized stock sustains marine and coastal resources, and how managing these helps to address food security, climate change and threats to marine biodiversity. Such cooperation between fishing communities and governments in managing marine protected areas is essential to the preservation of future fish stocks (see go.nature.com/3xvkqxj).Fishers should be actively engaged in relevant meetings held by the UN and national and local councils, so that they can weigh in on matters that affect fishing access, their livelihoods and environmental concerns. Both fishers and organizers must help to build empowerment mechanisms to make sure their voices are heard, such as providing translation services and scheduling meetings at accessible locations. This is important not just for the fishers’ human rights, but also because much can be learnt from artisanal fishers’ local knowledge.Moves that would, for instance, restrict the fishing season or areas so that stocks or biodiversity can recover should include compensation mechanisms that will secure fishers’ cooperation and livelihoods. Social-protection measures such as food and income assistance can also help to tide fishers over.When fish swim in schools, they move more efficiently, forage better and are protected from predators. The same might be said for small-scale fishers, but those networks should extend to local and international communities, too. Collaborative problem-solving and an integrated food system can deliver seafood protein, sustainably, to a world that increasingly needs it. More