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    Predicting distribution of malaria vector larval habitats in Ethiopia by integrating distributed hydrologic modeling with remotely sensed data

    Location of potential larval habitats and probability of occurrenceGenerally, Anopheles arabiensis mosquito takes around 15 days to develop from egg to adult, but the duration can be as short as 10 days due to selection pressures from the stressed environment such as drought, temperature anomaly, or limited food resources48,49. In this regard, we considered areas with WI exceeding 10 and 15 days to be potential larval habitats under critical and normal conditions, respectively.To determine the probability of potential larval habitat occurrence, we computed the probability of ponding occurring longer than 10 and 15 days, P(WI  > T), as shown in Eq. (2). P(WI  > T) is defined as the ratio of D(WI(x,y,t)  > T), the number of cumulated days for which the WI (i.e. persistence of ponding) of a grid cell (x,y) at time t that exceeded T days, to Dperiod, the number of days within a defined period of simulation.$$Pleft( {WI > T} right) = frac{{D(WIleft( {x,y,t} right) > T)}}{{D_{period} }},,T in left{ {10,15} right}$$
    (2)
    Figure 5 shows the results for the spatial distribution of P(WI  > T) over the three periods of simulation, namely the entire year of 2018, the dry season (i.e. January to April and November to December) and the rainy season (i.e. May to October). It can be observed that ponding was persistent throughout the year around the stream edges and the vicinity. P(WI  > 10) and P(WI  > 15) were consistently close to 1, reflecting a high potential of these areas as larval habitats.Figure 5Spatial distribution for the probability of potential larval habitat occurrence. (a–d) represent the probability of WI exceeding 10 days and 15 days for the baseline scenario and the irrigation scenario for the entire year. Similarly, (e–h) represent the probability of WI exceeding 10 days and 15 days during the dry season, and (i–l) represent the probability of WI exceeding 10 days and 15 days during the rainy season. Areas where the simulated surface water flowrate exceeded 0.01 m3/s for 90% of the time in the simulated year were masked out for all the sub-figures since Anopheles larvae have a lower chance of surviving in fast-moving water61.Full size imageFor the baseline scenario shown in Fig. 5a,b, the P(WI  > T) for the areas outside of the streams was predominantly determined by soil type. The areas characterized by Usterts (see Supplementary Fig S2) with the lowest hydraulic conductivity in the model domain were the next most at risk, with a P(WI  > T) of about 0.4–0.5. In the remaining areas, P(WI  > T) was generally 0.2 or less. Comparing Fig. 5a,b, the differences were minimal except for the steep areas at the watershed upstream boundary where P(WI  > 15) was predominantly zero. The surface water ponding was unable to last more than 15 days due to the terrain gradient.Figure 5c,d show the results for the irrigation scenario. Compared to the baseline scenario, the year-round persistent ponding around the streams and the vicinity was wider in coverage and more noticeable. Irrigation also increased P(WI  > 10) in Fig. 5c and P(WI  > 15) in Fig. 5d from 0.4–0.5 to about 0.7 and 0.6 respectively for Farm #1, Farm #2, and a significant portion of Farm #3 and Farm #4. The P(WI  > T) for the remaining area within the farms remained relatively unchanged at 0.2 and this could be attributed to the Ustoll soil type which drains easily. The increase in the probability of potential larval habitat occurrence from the baseline was more pronounced for P(WI  > 10) than P(WI  > 15) since the interval of irrigation was set at 10 days, after which the farm drained without replenishment until the next irrigation cycle.For the dry season, it can be observed in Fig. 5e,f that the stream edges were the only areas with high potential of larval habitat occurrence. In Fig. 5g,h, P(WI  > T) increased visibly in the farms after irrigation, with a distinct similarity between Farms #1/#3 and Farms #2/#4 that points to the irrigation schedule. While irrigation was alternated evenly between the two groups, Farms#1 and #3 showed a higher P(WI  > T) than Farms #2 and #4, possibly due to the timing of the irrigation relative to the rainfall. Irrigation could either coincide with rainfall or act as a supplement when there was no rainfall to augment soil moisture. Noticeably, there was an area to the northeast straddling both Farm #3 and Farm #4 where P(WI  > 10) was around 0.1 but P(WI  > 15) was almost zero, indicating that irrigation only allowed for larval habitats under critical conditions in that area during the dry season.For the rainy season, it can be observed in the baseline scenario (Fig. 5i,j) that the areas characterized by Ustert exhibited a high potential of larval habitat occurrence, apart from the stream edges. Particularly, there was an area to the north where P(WI  > T) was lower than the other parts which could be due to the relatively steeper terrain. In the irrigation scenario (Fig. 5k,l), there was no visible difference in P(WI  > T) as compared to the baseline scenario, apart from a minor increase around the western part of Farm #4.As a summary, we present the results in boxplots as shown in Fig. 6 to illustrate the effect of irrigation in different seasons for the areas inside and outside farms. The relevant statistics can be found in Table 1. The P(WI  > T) had a highly asymmetrical distribution because it was very low in most of the model domain but could be very high in the remaining areas due to the streams. For the following comparison, we will use the median as it was more representative of the distribution.Figure 6Box plots for the probability of potential larval habitat occurrence for the whole year, dry, and rainy season. Probability of WI exceeding (a) 10 days and 15 days (b) for the area inside farms and the area outside farms. The line within each box is the sample median and the top and bottom of each box are the 25th and 75th percentiles. The whiskers were drawn from the two ends of the box and demarcate the observations which were within 1.5 times the interquartile range from the top and bottom of the box.Full size imageTable 1 Summary statistics of the probability of potential larval habitat occurence for the whole year, dry season, and rainy season. Mean, 25th percentile (P25), median and 75th percentile (P75) of the probability of WI exceeding 10 days and 15 days for the (a) areas inside farms and (b) areas outside farms. The p value was derived from the Wilcoxon Rank-Sum test under the null hypothesis that irrigation did not increase the median probability of exceedance from the baseline scenario.Full size tableIn the baseline scenario, there was a higher potential for larval habitats to form inside the farms, with a median P(WI  > 10) of 0.427 and a median P(WI  > 15) of 0.400, than outside the farms, with a median P(WI  > 10) of 0.06 and a median P(WI  > 15) of 0.019. This is expected because the farms are located in an area with relatively flat terrain and a higher concentration of streams. The difference in the median P(WI  > T) inside and outside the farms was bigger in the rainy season compared to the dry season, as the higher rainfall received intensified ponding.Irrigation increased the median P(WI  > T) inside the farms drastically in the dry season, with the median P(WI  > 10) increasing from 0 to 0.442 and the median P(WI  > 15) increasing from 0 to 0.282. Although irrigation was only applied over the dry season, there was also a statistically significant increase in the median P(WI  > T) during the rainy season (p  10) increased from 0.848 to 0.864 while the median P(WI  > 15) increased from 0.794 to 0.810. This was due to irrigation contributing to the antecedent soil moisture before the onset of the rainy season, which shortened the time for the soil to become saturated and ponding to occur. On the other hand, there was no strong evidence outside the farms of an increase in the median P(WI  > T) due to irrigation (p  > 0.01). This applied to both rainy and dry seasons.Stability of larval habitatsIn the previous section, we showed that irrigation did not have a significant impact on areas outside the farms. Here, we evaluated the stability of the potential larval habitats specifically for the areas inside farms based on the distribution of the maximum duration of ponding for each grid cell within the year as shown in the histogram (Fig. 7a). The total number of cells corresponding to each bin interval of 15 days was expressed as a fraction of the total number of cells in the area inside farms.Figure 7The fraction of area inside the irrigated farms for each potential larval habitat types under the baseline and irrigation scenarios. (a) Shows the histogram of the maximum duration of ponding within the year for the grid cells in each type of habitats expressed as a fraction of the total area of the farms. The bin size was 15 days. Temporary, semi-permanent, and permanent larval habitats were typically characterized by ponding duration of 15–90 days, 90–180 days, and 180 days and above, respectively. The baseline scenario is represented in blue and the irrigation scenario is represented in orange. The darker orange bin is a result of the two overlapping. (b) Shows the comparison of the fractional area occupied by non-habitats (less than 15 days) as well as potential temporary, semi-permanent, and permanent larval habitats inside the farms. Each grid cell within the farm was categorized based on its maximum ponding duration.Full size imageFrom the baseline scenario, 13.2% of the area was not favorable for larval habitats because the maximum duration of ponding in those areas was less than 15 days. The most common maximum ponding duration was between 150 and 165 days, which accounted for more than 20% of the area. This was followed by 15–30 days and 360 days and above which made up 17.6% and 13.8% of the area respectively. With irrigation, there was a general increase in the maximum ponding durations. The most common maximum ponding duration was 360 days and above, accounting for 18% of the area. Noticeably, the area with maximum ponding duration between 210–225 days increased fourfold to 10%. The remaining increase was for 285 days and above. Counter-intuitively, the area that was not conducive as larval habitats (i.e. maximum ponding duration less than 15 days) also increased slightly by 0.6%. This was because irrigation raised the overland flowrate in these areas, mostly near streams, and made them unfavorable for breeding.In Fig. 7b, we grouped the maximum ponding durations into stability periods corresponding to temporary (2 weeks to 3 months), semi-permanent (3–6 months), and permanent (6 months and above) habitats based on field observations from a study at the site35. Temporary habitats such as puddles retain water for a short period while permanent habitats such as stream edges and swamps hold water much longer and are more stable. For the baseline scenario, semi-permanent habitats were the most common, occupying 33.1% of the area, while permanent and temporary habitats also accounted for 29.6% and 24.1% of the area respectively. After irrigation, there was a significant shift from semi-permanent habitats, which reduced to 22.9% of the area, to permanent habitats which increased to 41% of the area. There was also a slight reduction in the extent of temporary habitats to 22.4% of the area.Temporal pattern of potential larval habitatsTo shed light on the temporal patterns, we evaluated F(WI  > T), the fractional coverage of potential larval habitats inside farm, for each day throughout the year. We only focused on the area inside farms since irrigation does not have a significant impact on the area outside farms. As shown in Eq. (3), F(WI  > T) is defined as the ratio of C(WI  > T), the number of cells for which the WI (i.e. persistence of ponding) exceeded T days, to Cfarm, the number of cells within the farm area. T is set as 10 days and 15 days, corresponding to critical and normal conditions respectively.$$Fleft( {WI > T} right) = frac{{Cleft( { WIleft( {x,y,t} right) ge T} right)}}{{C_{farm} }},,T in left{ {10,15} right}$$
    (3)
    In Fig. 8a, F(WI  > 10) increased steeply on January 10 as WI started increasing from 0 at the beginning of the year. For the baseline scenario, the fractional coverage decreased minimally from 0.18 throughout the dry season despite the sporadic spike in precipitation. At the onset of the rainy season, the peak rainfall event of the year from May 5th to May 11th caused a sharp increase in F(WI  > 10) from 0.15 to 0.61 and thereafter, the relentless rainfall maintained the fractional coverage at about 0.6. Throughout the rainy season, there were four recurring peaks at a frequency of about 2 months. Post-rainy season, F(WI  > 10) dropped gradually to below 0.2 after the last peak at the end of October.Figure 8Daily variations in the extent of the potential larval habitats for the year. Time series of the fractional coverage of areas with Wetness Index (WI) exceeding (a) 10 days and (b) 15 days.Full size imageFor the irrigation scenario, F(WI  > 10) increased during the dry season from January to March with visible cyclical variations between 0.2 and 0.4 due to the rotation of irrigation among the four farms. Subsequently, the spike in rainfall at the end of March combined with the higher antecedent soil moisture from irrigation brought forward the step increase in the fractional coverage to April from May in the baseline scenario. As irrigation stopped at the end of April, F(WI  > 10) gradually dropped back to the same level as the baseline scenario at the end of June. In the dry season from November to December, the fractional coverage started to deviate from the baseline scenario again with cyclical fluctuations, gradually decreasing towards the end of the year.In Fig. 8b, F(WI  > 15) remained largely the same for the dry season but the peaks were moderated in the rainy season, compared to F(WI  > 10). There was one less peak at the end of May in the early rainy season because the watershed did not accumulate enough rainfall for the persistence of the ponded areas to exceed 15 days. Specifically, for the irrigation scenario, the increase in fractional coverage during the dry season was moderated and less sensitive to the spikes in rainfall. Similarly, irrigation resulted in the early onset of the steep increase in F(WI  > 15) in April following the spike in rainfall at the end of March. Also, it took two months after the end of irrigation in April for the fractional coverage to return to the same level as the baseline.From F(WI  > 10) and F(WI  > 15), we calculated the corresponding monthly mean, MF(WI  > 10), and MF(WI  > 15) as well as the 95th confidence interval as shown in Fig. 9. In Fig. 9a, MF(WI  > 10) in the baseline was the highest for the months between June and September, constituting a four-month window in which at least 50% of the area was conducive for larval habitat formation. Of the four months, the highest monthly mean fractional coverage was in July at 79.9%. Irrigation extended the window to include the months of April and May. The monthly mean fractional coverage increased 4.5 times to 64.3% in April and 1.4 times to 63.7% in May. The MF(WI  > 10) for the rest of the months in the window (i.e. June to September) remained one of the highest but the increase due to irrigation was not statistically significant (p  > 0.01). July remained as the month with the highest monthly mean fractional coverage at 80.0%. In Fig. 9b, MF(WI  > 15) was generally slightly lower than MF(WI  > 10) for both the baseline and irrigation scenarios but the general trends were the same.Figure 9Monthly variation in the extent of the potential larval habitats for the year. Monthly mean fractional coverage of areas with a probability of WI exceeding 10 days (a) and 15 days (b). The 95% confidence interval is indicated at the top of each bar chart. The asterisks (*) next to the month on the x-axis indicate that irrigation increased the fractional coverage of the potential larval habitats for the month from the baseline scenario based on a 2-sample t-test (p  More

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    Author Correction: Disturbance suppresses the aboveground carbon sink in North American boreal forests

    AffiliationsDepartment of Earth System Science, University of California, Irvine, CA, USAJonathan A. Wang & James T. RandersonDepartment of Earth and Environment, Boston University, Boston, MA, USAJonathan A. Wang, Alessandro Baccini & Mark A. FriedlThe Woodwell Climate Research Center, Falmouth, MA, USAAlessandro Baccini & Mary FarinaDepartment of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT, USAMary FarinaAuthorsJonathan A. WangAlessandro BacciniMary FarinaJames T. RandersonMark A. FriedlCorresponding authorCorrespondence to
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    Supplementation of Lactobacillus early in life alters attention bias to threat in piglets

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    Nature-based solutions can help cool the planet — if we act now

    Women in northern Mumbai, India, have planted mangrove saplings to protect the area against rising sea levels.Credit: Mahendra Parikh/Hindustan Times via Getty

    Projects that manage, protect and restore ecosystems are widely viewed as win–win strategies for addressing two of this century’s biggest global challenges: climate change and biodiversity loss. Yet the potential contribution of such nature-based solutions to mitigating climate change remains controversial.Decision-makers urgently need to know: what role do nature-based solutions have in the race to net-zero emissions and stop further global temperature increases?Analyses of nature-based solutions often focus on how much carbon they can remove from the atmosphere. Here, we provide a new perspective by modelling how these solutions will affect global temperatures — a crucial metric as humanity attempts to limit global warming.Our analysis shows that nature-based solutions can have a powerful role in reducing temperatures in the long term. Land-use changes will continue to act long past the point at which net-zero emissions are achieved and global temperatures peak (known as peak warming), and will have an important role in planetary cooling in the second half of this century. Before then, nature-based solutions can provide real but limited mitigation benefits. Crucially, the more ambitious the climate target, the shorter the time frame for such solutions to have an effect on peak warming.In other words, nature-based solutions must be designed for longevity. This means paying closer attention to their long-term carbon-sink potential, as well as their impacts on biodiversity, equity and sustainable development goals. It also means continuing to limit global warming through other methods, from decarbonization to geological storage of carbon dioxide.Our model reinforces the conclusion that an ambitious scaling-up of nature-based solutions needs to be implemented fast and thoughtfully — and not at the expense of other measures.Win–winsThe world is currently likely to hit 3 °C of warming above pre-industrial levels by 2100 (although recent policy announcements from the United States and China could reduce this). The 2015 Paris climate agreement aims to limit the global temperature rise this century to well below 2 °C, and, ideally, to 1.5 °C. There is no date for either goal, beyond the “end of this century”. The metric that matters most is the peak temperature, with more-aggressive efforts required to stay below 1.5 °C of warming than for the 2 °C target.
    Emissions: world has four times the work or one-third of the time
    It is impossible to achieve the needed reduction in peak warming solely through cuts to greenhouse gases, because emissions from certain sectors, such as agriculture and some heavy industry, cannot be driven to zero any time soon. For this reason, we also need to remove greenhouse gases from the atmosphere on an unprecedented scale1.There are various options for doing this. For example, when biomass vegetation is burnt for energy, the emitted CO2 can be retained and stored underground. This process, known as bioenergy with carbon capture and storage (BECCS), requires vast areas of land — compromising food security and biodiversity — as well as time to develop on a large scale. Other options involve industrial machines that capture CO2 from the air; these are currently nascent, expensive technologies.A subset of nature-based solutions can be used specifically to limit warming. These ‘natural climate solutions’ aim to reduce atmospheric greenhouse-gas concentrations in three ways. One is to avoid emissions by protecting ecosystems and thus reducing carbon release; this includes efforts to limit deforestation. Another is to restore ecosystems, such as wetlands, so that they sequester carbon. The third is to improve land management — for timber, crops and grazing — to reduce emissions of carbon, methane and nitrous oxide, as well as to sequester carbon (see ‘Three steps to natural cooling’).

    Source: S. Jenkins et al. Geophys. Res. Lett. 45, 2795–2804 (2018).

    Decades of work provide strong evidence that nature-based solutions can deliver many local ecological and socio-economic benefits2. Restoring a forest next to a stream, for example, might reduce flooding, improve carbon storage and support fisheries. Growing recognition of such benefits means that interest in nature-based solutions is soaring: they can help people adapt to climate change, achieve sustainable development goals, protect biodiversity and mitigate climate change3.Quantifying nature’s roleThere is still debate around how much nature-based solutions can contribute to achieving net-zero targets by mid-century. This is because results have been estimated across a range of objectives, time frames and model assumptions4,5 (see Supplementary information; SI). Some researchers say that tree restoration is the most effective climate-change solution we have available6 (this in itself has been robustly contested); others argue that nature-based solutions won’t be nearly as fast or as effective as is often stated7.Part of the reason for the impasse is this: many well-known papers discuss the annual carbon uptake possibilities of nature-based solutions; they do not discuss their cooling impact year on year. Because the Paris agreement is framed in terms of temperature, we argue that this gap is critical: researchers need to know how nature-based solutions will affect global temperature.To model this, we consider an ambitious but realistic scenario — an update to previous estimates by one of our co-authors (B.W.G)4,8,9. This scenario considers only those projects for nature-based solutions that are constrained by many factors: they are cost-effective (costing less than US$100 per tonne of CO2 equivalent); ensure adequate global production of food and wood-based products; and involve sufficient biodiversity conservation. They also respect land tenure rights and don’t change the amount of sunlight reflected from Earth, or albedo (see SI). In our scenario, nature-based solutions that avoid emissions ramp up quickly — by 2025 — and absorb carbon while avoiding emissions at a rate of 10 gigatonnes of CO2 per year (Gt CO2 yr−1). This rises to 20 Gt CO2 yr−1 in the most ambitious scenario (peak warming of 1.5 °C by 2055), in which we assume a higher price of carbon. The 10-Gt value is cost-contained. But we also account for 30 years of higher-priced nature-based solutions in the 1.5 °C scenario (up to $200 per tonne of CO2 equivalent; see SI). For comparison, 10 Gt CO2 yr−1 is more than the emissions from the entire global transportation sector.

    Instituto Terra, an initiative in Aimorés, Brazil, is restoring a devastated ecosystem.Credit: Christian Ender/Getty

    Achieving 10 Gt CO2 yr−1 of mitigation in this way would involve stopping the destruction of ecosystems worldwide (including 270 million hectares of deforestation); restoring 678 million hectares of ecosystems (more than twice the size of India); and improving the management of around 2.5 billion hectares of land by mid-century4. This is ambitious, but it is important to note that the bulk of land required (85%) comes from improving management of existing lands for agriculture, grazing and production forest without displacing yields of food, wood-based products or fuel (see ‘Three steps to natural cooling’).These estimates come with caveats (see SI). The role of nature-based solutions could be larger if one considers, for example, their impacts on other greenhouse gases besides CO2. This could represent an additional amount of roughly 1–3 Gt CO2 equivalent yr−1 of climate mitigation. Alternatively, the contribution of such solutions might be smaller in the long term, if the carbon drawdown from land-based interventions decreased over time. This could happen if these natural sinks became saturated or were affected by climate impacts such as forest fires. These caveats are not included in our estimates.We then modelled how this level of nature-based solutions would affect global temperature up to 2100 (see ‘The long game’ and SI). We looked at illustrative pathways from the Intergovernmental Panel on Climate Change, in which peak warming is constrained to 1.5 °C or 2 °C, and ran these scenarios with the added contribution of nature-based solutions as described. These pathways include BECCS, but no nature-based solutions beyond some avoided deforestation.Taking the temperatureOur analysis shows that implementing this level of nature-based solutions could reduce the peak warming by an additional 0.1 °C under a scenario consistent with a 1.5 °C rise by 2055; 0.3 °C under a scenario consistent with a 2 °C rise by 2085; and 0.3 °C under a 3 °C-by-2100 scenario (see ‘The long game’).

    Adapted from Fig. SPM.1 of Ref. 1

    The most significant contribution nature-based solutions can make to mitigating the peak temperature is in the 2 °C scenario. In a more ambitious 1.5 °C scenario, there isn’t enough time for nature-based solutions to have as great an impact on peak warming. In the 3 °C scenario, several issues constrain the impact of nature-based solutions, including the limited ability of ecosystems to absorb carbon in a warmer world.Overall, the mitigation potential of nature-based solutions remains small compared to what can be achieved by decarbonizing the economy. Yet, assuming that decarbonization takes place, nature-based solutions can still suppress a chunk of the warming (see SI).Crucially, nature-based solutions cool the planet long after the peak temperature is reached. In the 1.5 °C scenario, they take a total of 0.4 °C off warming by 2100 — four times their suppression to the 2055 peak temperature (see SI, Table S2).
    Restoring natural forests is the best way to remove atmospheric carbon
    Achieving these significant long-term benefits requires several things. Nature-based solutions of good quality must be scaled up rapidly — and not at the expense of other robust strategies. Long-term geological storage of CO2, for example, will need to be ramped up significantly in the next decade as technologies mature and prices fall. The long-term benefits of nature-based solutions also depend on warming being held in check. The increased frequency and intensity of impacts such as wildfires can undermine ecosystems and their capacity to store carbon or provide other benefits to society.Ecosystems that are protected and carefully managed — such as intact peatlands and old-growth tropical rainforests — are very likely to continue to store carbon for thousands of years. These are also more resilient to climate extremes and pathogens.The right metricsRestoration of forest cover is widely considered the most viable near-term opportunity for carbon removal. Unfortunately, some of this enthusiasm has been used to promote plantation forestry — growing trees of a limited variety of ages and species (for example, in monoculture plantations) does not have the same carbon benefits as maintaining an intact forest ecosystem10.One serious problem is that some nature-based solutions, as currently implemented, can have unintended and unwanted consequences. For example, an area of 34,007 hectares of intact forest ecosystem in Cambodia became a logging concession, with much of it replaced with an acacia monoculture. This was the first large-scale reforestation project to be funded in Cambodia in the context of climate-change mitigation. The project resulted in unethical ecological devastation, affecting 1,900 families in the area11.Similarly, Chilean government subsidies for new plantations of pine and eucalyptus have resulted in plantations expanding by 1.3 million hectares since 1986, with an associated sequestration of about 5.6 million tonnes of carbon. However, regulations stating that expansion cannot happen at the expense of native biodiverse forests were not enforced, resulting in large-scale reductions in native forest cover. Clearing of the original forest has resulted in a net decrease of approximately 0.05 million tonnes of stored carbon since 198612.These examples show how a singular focus on rapid carbon sequestration as the metric of success for land-based climate mitigation can result in perverse outcomes. Activities should be evaluated and monitored with the right metrics, to account for the multitude of benefits they provide in the long term.
    Adopt a carbon tax to protect tropical forests
    To ensure long-term resilience, projects involving nature-based solutions should adhere to four high-level principles (see nbsguidelines.info). First, nature-based solutions are not an alternative to decarbonization; second, they need to involve a wide range of ecosystems; third, they should be designed in partnership with local communities while respecting Indigenous and other rights; and, finally, they must support biodiversity, from the level of the gene to the ecosystem. In addition, the Oxford principles13 for high-quality offsets call for safe and durable CO2 removal and storage for every tonne of CO2 emitted. Metrics of success should include those for carbon dynamics, biodiversity across multiple trophic levels, and socio-economic factors such as women’s empowerment and youth employment.There are many examples of good-practice projects (see also case studies by the University of Oxford’s Nature-based Solutions Initiative, where N.S. and C.A.J.G. work). For example, mangrove forests in eastern India that have been protected from deforestation since 1985 have been shown to protect coastal regions from the negative impacts of cyclones much better than artificial defences do, while also soaking up carbon14. In Sierra Leone’s tropical rainforest, cocoa agroforestry — where cocoa is planted with trees for shade, alongside pineapples, chillies and maize (corn) as an additional source of food and income — has been shown to produce cocoa sustainably while diminishing forest clearance. One agroforestry project in the Gola Rainforest National Park, initiated 30 years ago, has increased biodiversity and the profitability of crops while saving an estimated 500,000 tonnes of carbon each year through sequestration and avoiding deforestation.Invest wiselyThis much is clear: we urgently need to increase investment in high-quality nature-based solutions. They currently receive a small proportion of existing climate-mitigation financing4,15, which does not reflect their potential.Carbon markets are increasingly relied on to finance nature-based solutions. But carbon offsets on the voluntary market are of variable quality. It can be unclear whether projects really represent a carbon sink, whether they are permanent or if they safeguard social and ecological factors. Offsets that adhere to standards can allow organizations to deliver lower-cost and hence larger climate-mitigation outcomes through nature-based solutions; however, budgets to emit fossil fuels should be ratcheted down rapidly to avoid delaying decarbonization from continued greenhouse-gas emissions.
    Account for depreciation of natural capital
    Nature-based solutions need both public and private finance; in particular, governments need to reward ecosystem stewardship while taxing polluters and ramping up regulation to ensure that companies meet strict social and environmental safeguards.The United Nations Framework Convention on Climate Change (UNFCCC) needs to provide clear guidelines on national-level accounting for nature-based solutions. This will guide the targets set in the Paris agreement’s Nationally Determined Contributions, and the monitoring, reporting and verification methodologies required to comply with these targets.The next UNFCCC meeting, COP26, is due to be held in Glasgow, UK, this November and provides an opportunity for national reporting systems to tighten national carbon accounting related to nature-based solutions. This would ensure that such solutions make a real, long-term contribution to carbon mitigation and could set metrics to ensure high biodiversity levels and maximize human well-being. One pressing issue for COP26 is Article 6 of the Paris agreement, which established a “mechanism to contribute to the mitigation of greenhouse gas emissions and support sustainable development”. A tightly regulated compliance market defined in Article 6 will provide the grounding for a tightly regulated voluntary offsetting market.COP26 also presents the chance to harmonize the goals of the UNFCCC and those of the Convention on Biological Diversity. For example, nature-based solutions projects are likely to be required to adhere to the principle of free prior informed consent of local people: local communities need to be involved at all stages of project planning and management. Similarly, nature-based solutions should be required to protect and enhance biodiversity. This work can build on existing social and biodiversity standards3.Our economy must be decarbonized at unprecedented rates to achieve net-zero targets by mid-century. Carbon must also be removed from the atmosphere to counter emissions that are hard to eliminate, using nature-based solutions and other means. To transform social and economic systems to deliver resilience in the face of ongoing climate impacts, the world must invest now in nature-based solutions that are ecologically sound, socially equitable and designed to pay dividends over a century or more. Properly managed, these could benefit many generations to come. More

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    The impact of stopping and starting indoor residual spraying on malaria burden in Uganda

    Uganda has been exceptionally successful in scaling-up coverage of LLINs. Following the mass distribution campaigns to deliver free LLINs in 2013–14 and 2017–18, 90 and 83% of households, respectively reported ownership of at least one LLIN7,14. However, despite this success, the burden of malaria remains high in much of the country. Uganda had the third highest number of malaria cases reported in 2019, with reported case incidence increasing since 20142. If Uganda is to achieve the goals established by the World Health Organization’s Global Technical Strategy for malaria including reducing malaria case incidence by at least 90% by 2030 as compared with 201515, additional malaria control measures will be needed. This report highlights the critical role of IRS in substantially reducing the burden of malaria in areas where transmission remains high despite deployment of LLINs. Withdrawing IRS after 5 years of sustained use in three districts in northern Uganda was associated with a more than fivefold increase in malaria cases within 10 months. Restarting IRS with a single round in nine districts in Northern Uganda ~3 years after IRS had been stopped was associated with a transient but important (more than a fivefold) decrease in malaria cases within 8–12 months, returning to pre-IRS levels after 23 months. Initiating and sustaining IRS in five districts in Eastern Uganda was associated with a gradual reduction in malaria cases reaching almost a sevenfold reduction after 4–5 years.Robust evidence supports the widespread use of LLINs for malaria control. In a systematic review of clinical trials conducted between 1987 and 2001, insecticide treated nets reduced all cause child mortality by 17% and the incidence of uncomplicated P. falciparum malaria by almost half16. However, there is concern that the effectiveness of LLINs may be diminishing due to widespread resistance to pyrethroids which until recently were the only class of insecticides approved for LLINs. Similar to many other African countries, high-level resistance to pyrethroids among the principle Anopheles vectors has been reported recently throughout Uganda17,18,19. In addition, behavioral changes in vector biting activity following the introduction of LLINs have been reported which could present new challenges for malaria control20,21,22. Finally, the effectiveness of LLINs may be further compromised by poor adherence and waning coverage in the setting of free distribution campaigns done intermittently. In Uganda, less than 18% of households reported adequate coverage (defined as at least one LLIN per two residents) 3 years after the 2013–14 distribution campaign23 and adequate coverage decreased from 71% to 51% between 6 and 18 months following the 2017–18 distribution campaign24. Although the World Health Organization recommends mass distribution campaigns every 3 years, mounting evidence suggests that LLINs should be distributed more frequently to sustain high coverage25,26,27,28,29,30,31.Given concerns about the current effectiveness of pyrethroid-based LLINs and the persistently high burden of malaria despite aggressive scale-up of LLINs in countries like Uganda, additional malaria control measures are needed. IRS is an attractive option. Historically, IRS programs were used to dramatically reduce and even eliminate malaria in many parts of the world. Thus, while there is some evidence for the impact of IRS in the absence of LLINs32, it is surprising that the evidence base from contemporary controlled trials on the impact of adding IRS to LLINs for vector control is limited. A recent systematic review of cluster randomized controlled trials conducted in sub-Saharan Africa since 2008, reported that adding IRS using a “pyrethroid-like” insecticide to LLINs did not provide any benefits, while adding IRS with a “non-pyrethroid-like” insecticide produced mixed results5. Among the four trials comparing IRS plus LLINs with LLINs alone, three evaluated IRS with a carbamate (bendiocarb) and one evaluated a long-lasting organophosphate, pirimiphos-methyl (Actellic 300CS®)33,34,35,36. Only two trials (both using bendiocarb) assessed malaria incidence; one from Sudan found a 35% reduction when adding IRS to LLINs34, while another from Benin found no benefit of adding IRS33. All four trials assessed parasite prevalence, with an overall non-significant trend towards a lower prevalence when adding IRS to LLINs (RR = 0.67, 95% CI 0.35–1.28)5. However, when the analyses were restricted to include only the two studies with LLIN usage over 50%, adding IRS reduced parasite prevalence by over 50% (RR = 0.47, 95% CI 0.33–0.67)5. Of note, none of the trials that evaluated the impact of adding IRS with a “non-pyrethroid-like” insecticide assessed outcomes beyond 2 years. More recently, a number of observational studies have reported benefits of using IRS with pirimiphos-methyl (Actellic 300CS®). In the Mopti Region of Mali, delivery of a single round of IRS with Actellic 300CS® was associated with a 42% decrease in the peak incidence of laboratory-confirmed malaria cases reported at public health facilities37. In the Koulikoro Region of Mali, villages that received a single round of IRS with Actellic 300CS® combined with LLINs observed a greater than 50% decrease in the incidence of malaria compared to villages that only received LLINs38. In the Northern Region of Ghana, districts that received IRS with Actellic 300CS® reported 26–58% fewer cases of laboratory-confirmed malaria cases reported at public health facilities over a 2-year period, compared to districts that did not receive IRS39. In Northern Zambia, implementation of IRS with Actellic 300CS® targeting only high burden areas over a 3 year period was associated with a 25% decline in parasite prevalence during the rainy season, but no decline during the dry season40. In Western Kenya, the introduction of a single round of IRS with Actellic 300CS® was associated with a 44–65% decrease in district level malaria case counts over a 10 month period compared to pre-IRS levels41. In addition, several recent reports have documented dramatic resurgences of malaria following the withdrawal of IRS with bendiocarb in Benin42, and the withdrawal of IRS with Actellic 300CS® in Mali and Ghana37,39.The results from this study provides additional support for the critical role IRS can play in reducing the burden of malaria in African countries with high LLINs coverage. A strength of the study was its use of a large, rigorously collected dataset. Data were collected over nearly 7 years through an enhanced health facility-based surveillance system covering 14 districts in Uganda where IRS was being withdrawn, re-started, and initiated. This enhanced surveillance system facilitated laboratory testing and provided prospectively collected, individual-level data, allowing for analyses of quantitative changes in laboratory-confirmed cases of malaria over time, controlling for temporal changes in rainfall, seasonal effects, diagnostic practices, and health seeking behavior. Previous work by our group documented a marked decrease in malaria TPRs after 4 years of sustained IRS with bendiocarb in one district of Northern Uganda followed by a rapid resurgence over an 18-month period after IRS was withdrawn11. In this study we expand on these findings by including data from three districts and covering a 31-month period following the withdrawal of IRS. We were able to quantify more than a fivefold increase in malaria cases which was sustained over the 10–31 months following the withdrawal of IRS. This marked resurgence occurred despite the fact the first universal LLIN distribution campaign was timed to occur right after IRS was withdrawn. Given the dramatic nature of the resurgence, the Ugandan government was able to procure funding for a single round of IRS with Actellic 300CS® ~3 years after IRS was withdrawn in 10 districts of Northern Uganda. In this study, we assessed the impact of this single round in nine of these districts. This single round was associated with over a fivefold decrease in malaria cases after 8–12 months, with malaria cases returning to pre-IRS levels after almost 2 years. These data suggest that IRS with longer-acting formulations such as Actellic 300CS® administered every 2 years could be considered as a strategy for mitigating the risk of resurgence following sustained IRS and/or enabling countries to expand coverage when resources are limited, but formal assessment and a cost-effectiveness analyses are needed. This study also evaluated the impact of 5 years of sustained IRS in five districts of Eastern Uganda, starting first with bendiocarb and then switching to Actellic 300CS® after 18 months. Rounds of IRS were initially associated with marked decreases in malaria cases followed by peaks before subsequent rounds until the fourth and fifth years after IRS was initiated when there was a sustained decrease of almost sevenfold compared to pre-IRS level. Given the before-and-after nature of our study design, it is not clear whether the maximum sustained benefits of IRS seen after 4–5 years were due to the cumulative effect of multiple rounds of IRS, the switch from bendiocarb to Actellic 300CS®, improvements in implementation (although campaigns occurred regularly and coverage was universally high across rounds, see Supplementary Table 4), the second universal LLIN distribution campaign which occurred in this area in 2017, and/or other factors.This study had several limitations. First, we used an observational study design, with measures of impact based on comparisons made before-and-after key changes in IRS policy. Although cluster randomized controlled trials are the gold standard study design for estimating the impact of IRS, it could be argued that withholding IRS would be unethical, given what is known about its impact in Uganda. Second, our estimates of impact could have been confounded by secular trends in factors not accounted for in our analyses. However, we feel that our overall conclusions are robust given the large amount of data available from multiple sites over an extended period with multiple complementary objectives providing consistent findings. Third, we could not assess the impact of IRS independent of LLIN use and did not have access to measures of IRS or LLIN coverage from our study populations. It is possible that some of the impacts we observed were from LLIN distributions in combination with IRS campaigns. However, we were able to provide a “real world” assessment of IRS in a setting where LLIN use is strongly supported by repeated universal distribution campaigns that are becoming increasingly common in sub-Saharan Africa. Similarly, we cannot draw conclusions on the impact of different IRS compounds given all sites received the same formulations consecutively. The results from Objective 3 indicate that malaria incidence dropped substantially in the years that districts stopped receiving bendiocarb and began receiving Actellic 300CS®. However, we cannot conclude whether this reduction was a result of this change or rather the cumulative impact of sustained IRS campaigns, as it has been suggested that in very high transmission settings, several years of IRS may be needed to maximize impact on measures of morbidity.43,44 Finally, our study outcome was limited to case counts of laboratory-confirmed malaria captured at health facilities. Thus, we were unable to measure the impact of IRS on other important indicators such as measures of vector distribution, parasite prevalence, or mortality.There is a growing body of evidence that combining LLINs with IRS using “non-pyrethroid-like” insecticides, especially the long acting organophosphate Actellic 300CS®, is highly effective at reducing the burden of malaria in Uganda, and elsewhere in Africa. Despite these encouraging findings, IRS coverage in Africa has been moving in the wrong direction. The proportion of those at risk protected by IRS in Africa peaked at just over 10% in 2010. However, the spread of pyrethroid resistance has led many control programs to switch to more expensive formulations resulting in a 53% decrease in the number of houses sprayed between years of peak coverage and 2015 across 18 countries supported by the US President’s Malaria Initiative45 and an overall reduction in the proportion protected by IRS in Africa to less than 2% in 20192. Given the lack of recent progress in reducing the global burden of malaria coupled with challenges in funding, renewed commitments are needed to address the “high burden to high impact” approach now being advocated by the World Health Organization2. IRS is a widely available tool that could be scaled up, however demands currently exceed the availability of resources. Additional work is needed to optimize the use of IRS, prevent further spread of insecticide resistance, and better evaluate the cost-effectiveness of IRS in the context of other control interventions. More

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    Comparison of sample types from white-tailed deer (Odocoileus virginianus) for DNA extraction and analyses

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    Leaf trait variation in species-rich tropical Andean forests

    Study sites and examined tree speciesThe study was conducted at three sites in the Andes of southern Ecuador along an elevation gradient at ca. 1000 m (Bombuscaro, Podocarpus NP), ca. 2000 m (San Francisco Reserve) and ca. 3000 m elevation (Cajanuma, Podocarpus NP) in the Provinces of Loja and Zamora-Chinchipe. All sites are located in protected forest areas. At each elevation three permanent 1-ha plots were established in 2018, choosing representative portions of old-growth forest without visible signs of human disturbance (Appendix A1).The forest types at the three sites differ in floristic composition, species richness and structural characteristics49: The premontane rain forest (below 1300 m) at the lowermost site reaches 40 m in height with common tree families being Fabaceae, Moraceae, Myristicaceae, Rubiaceae, and Sapotaceae. It is replaced at 1300–2100 m by smaller-statured lower montane rain forest with Euphorbiaceae, Lauraceae, Melastomataceae, and Rubiaceae as characteristic tree families, and above 2100 m by upper montane rain forest with a canopy height that rarely exceeds 8–10 m. Dominant tree families of the latter forest type are Aquifoliaceae, Clusiaceae, Cunoniaceae, and Melastomataceae. Tree species turnover is complete between premontane and upper montane forest, while a few tree species are shared between lower montane and premontane or upper montane forest types.The climate is tropical humid with a precipitation peak from June to August and a less humid period from September to December. Mean annual temperature decreases with elevation from 20 °C at 1000 m to 9.5 °C at 3000 m, while annual precipitation increases from around 2000 mm at the two lowermost sites to 4500 mm at 3000 m. Typically, there are no arid months with More

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    Field studies on breeding sites of Culicoides Latreille (Diptera: Ceratopogonidae) in agriculturally used and natural habitats

    In total, 13 culicoid species were found in the present study, with 45.5% of the collected specimens belonging to the Obsoletus Complex while species only occasionally present in previous collections in Germany, accounted for approximately 25% of the sampled individuals. Thus, the species composition is only partly in accordance to earlier studies on the German Culicoides fauna according to which 70 to over 90% of the specimens belonged to the Obsoletus Complex and up to 20% represented members of the Pulicaris Complex, while other culicoid species were present in negligible numbers only12,13. However, previous studies were based on UV-light trap catches12,13,14,15 and targeted active culicoid specimens16. The results obtained in this study are very specific as they represent the species compositions associated with the respective breeding substrates.The gender ratio differed strongly between species, revealing no pattern applicable to all species. The dominance of female Culicoides emerging from breeding sites corresponds to earlier results17,18, even though the sex ratio in the present study showed a much higher proportion of females with 70.7% or a female:male ratio of 2.4:1 than the above studies with 55.6%17 or a female:male ratio of 1.06:118.The evaluation of the diversity of each biotope (excluding the ungrazed meadow where no Culicoides were found) revealed clear differences between the agriculturally used habitats and the more natural biotopes. The Shannon–Weaver index depicted very low diversity for all three studied meadows where biting midges were found. The two meadows (with cattle and sheep) of region 2 reached the lowest possible diversity. This seems plausible as only one species was sampled within each biotope. The meadow with cattle of region 1 revealed at least two species. The Evenness factor of 0.24 depicts the dominance of one of them. The low number of species and unbalanced number of specimens within the biotope result in a low Shannon–Weaver index of 0.24, which describes the poor level of biodiversity.The Simpson index measures the probability that two individuals, randomly selected from a sample, belong to the same species. As only one species was sampled on each meadow from region 2, the probability to choose two specimens which belong to one species is 100% (displayed by the value of D = 1.0). The meadow with cattle of region 2 revealed at least two culicoid species, but the dominance of one species leads to a high Simpson index of 0.92 as well.Opposite to the very low biodiversity of all meadows, the four more natural biotopes of region 3 show an overall high level of biodiversity: according to the Shannon–Weaver index, the level of biodiversity is highest within the AFS (H = 2.96). Compared to the other biotopes of region 3, the AFS revealed by far the highest numbers of culicoid species and specimens. This and the relatively high Evenness factor (E = 0.89) lead to the high H value. The Shannon–Weaver indices for CW and MA are 1.91 and 1.92, respectively. Based on the low numbers of species and specimens in both biotopes, the relatively high H value is mainly caused by its high Evenness values of 0.95 (CW) and 0.96 (MA), respectively. Therefore, the almost equal numbers of all present species leads to the relatively high biodiversity, rather than a high number of species.The Shannon–Weaver index of the DW is the lowest of the four biotopes of region 3 with H = 1.42 and rates this biotope as the one with the lowest diversity of region 3. Though the number of species equal the one of the CW and MA, the higher number of specimens and especially the much lower Evenness factor of 0.71 reduces the H value.Other than the Shannon–Weaver index, the Simpson index rates both, the AFS and the MA, as the two most diverse biotopes. With values of D = 0.13, the probability to randomly select two species of the same species is rather low in both biotopes. As the AFS revealed more than double as many species than the MA, the lower number of caught specimens of the MA must have led to the same biodiversity rate.Study 1—Influence of domestic animals on meadows: up to date, dung-breeding Culicoides have been investigated more thoroughly18,19,20 than most other culicoid species. Most studies have focused on examining selectively either dungheaps or cowpats, rather than conducting a direct comparison between grazed and ungrazed meadows under field conditions. In the present study, we were able to show that the ungrazed meadow seems to be an unsuitable breeding habitat for Culicoides. Therefore, it seems plausible that the suitability of meadows as culicoid breeding sites can be largely, if not completely, attributed to the influence of livestock pasturing.The strong dominance of Obsoletus Complex specimens sampled on grazed meadows is not surprising as this species complex is known to contain typical dung-breeders19,20. The high potential of manure as a breeding substrate has been demonstrated before21,22 and explains the high quantity of Culicoides developing on meadows used by cattle in the present study. While 0.83 midges/sample were found on the meadow with cattle in region 1, only 0.21 midges/sample were collected on the meadow with cattle in region 2. The quantitative differences between these two study sites might be caused by the differing time periods of sampling (April to July for region 1 and August to October for region 2). Previous studies observed population peaks of Obsoletus Complex midges in October, though23, giving reason to expect even higher numbers of midges for region 2 than for region 1, particularly so, as region 2 is an agriculturally dominated area with a higher abundance of potential blood hosts and more suitable breeding habitats than region 1.Compared to the much higher total number of midges emerging from cowpats, sheep dung produced only two specimens. The very low number of midges originating from sheep faeces might be due to the very quick decomposition and desiccation of the rather small droppings, which likely reduces the quality of these remains as culicoid breeding sites. Therefore, it can be assumed that, contrary to pastures with cattle dung, sheep-runs might not play an essential role in promoting the distribution of Culicoides. For modeling approaches, it should be considered, though, that this might only apply to single scattered pieces of faeces as the longer persistence of higher volumes of sheep dung, i.e. on muckheaps, might very likely raise its quality as potential breeding sites as observed by21.All grazed meadows revealed very few culicoid species. Besides members of the Obsoletus Complex, only one individual of C. comosioculatus was found. The present investigation represents a case study though as merely one habitat of each type was sampled. More research to confirm the present results is therefore strongly recommended, even more, as ceratopogonid communities of terrestrial ecosystems have been barely investigated24, with the consequence that breeding sites of Culicoides spp. are still poorly known25.Study 2—Quality of forest-dominated biotopes as culicoid breeding sites: In the present study, the AFS turned out to be very productive as a culicoid breeding site in regards to the number of caught specimens and species diversity. Ten of the 13 collected species were found in the AFS. This is 2.5 times as many species as in the three other biotopes of region 3, which contained four species each in different compositions. Therefore, species-specific requirements for larval development seem to be met for more culicoid species in the AFS than in any of the other study sites.The measured pH values are in accordance to soil analyses conducted in German forests26. As the top layers usually are the most acidic ones, the chosen depth of soil sampling in the present study (upper 0–5 cm) persistently produced low pH values. Additionally, the used solvent (CaCl2) is less sensitive to fast changing weather conditions, but also lowers the measured pH value significantly compared to distilled water26—a solvent often used in earlier studies analyzing the distribution of Ceratopogonidae.The wide variances of the soil factors, especially moisture and organic content, were mainly caused by unequal soil conditions within each biotope rather than changes over time (unpublished data). Nevertheless, the statistical analysis revealed that all four biotopes of region 3 were significantly different from each other regarding the three soil factors. Comparing the means of each soil factor revealed that the AFS contained a higher level of soil moisture, a less acidic pH value and a higher organic content than the other three biotopes of region 3. We could show that significantly more midges (0.4 Culicoides/sample) developed in the AFS compared to the three other biotopes of region 3 with 0.12 (DW), 0.07 (CW) and 0.06 (MA) Culicoides per sample.Previous studies have assumed that the level of moisture be a crucial factor for ceratopogonid development17,20. Also, some studies determined the organic content as pivotal17,27. Our statistical analysis revealed that each soil factor has an impact on the probability of Culicoides to occur. Due to high correlations between the various measured soil factors, it could not be clarified, though, whether they influence the number of specimens, too. But as many culicoid species are known to lay their eggs in batches and previous egg-laying encourages females to oviposit at the same site28, an increase in the probability of biting midge presence should indirectly result in a higher number of specimens, too.The aggregation of larvae in terrestrial habitats29 typically results in a high number of samples completely devoid of midges and an overall low number of specimens sampled by emergence traps30. Thus, the obtained low numbers of collected specimens are not surprising. Nevertheless, emergence traps are still considered to be the best tool for the investigation of breeding site productivity, as it offers a safe assignment of species to their specific developmental sites24,29,31.The Culicoides collected in this study are discussed on species level in regards to existing literature.Culicoides achrayi was found in the AFS. A swamp as a breeding site32 and soil located in stagnant water22 have previously been described for this species. We confirm June as the time of emergence32 and add that C. achrayi co-exists with C. pulicaris.Culicoides albicans was collected in the AFS and DW. Specimens hatched from late April to mid-June, representing one generation per year. We confirm co-habitation with C. pictipennis and C. kibunensis11,33 and the preference for very humid substrates which has been described for the wettest parts of boglands5,34 and for artificially waterlogged soil11. Our results show, that C. albicans larvae can tolerate medium moisture levels, too. The mean organic content of their developmental sites reached from moderate to high, and the pH values lay between strong and ultra-acidic.Culicoides comosioculatus was found on the meadow with cattle dung in mid-June. As only one individual (a gravid female with the presumed intention to oviposit) was collected and no literature regarding breeding sites of this species could be found, our finding only indicates that this species might possibly develop in animal dung although in extremely low numbers.Culicoides grisescens was found within the AFS, the CW and the DW from late May until mid-July. Kremer35 listed soils of swamps and boggy grasslands as developmental sites. We collected C. grisescens in three different biotopes with wide variances of the mean moisture level, mean organic content and mean pH value, which reveals the wide tolerance range of this species towards these three soil factors.Culicoides impunctatus was collected in the AFS and the CW from late May to mid-July, representing one generation per year. This finding differs from earlier observations of two generations per year in Scotland36. Previous studies described breeding sites as acidic, oligotrophic grasslands, swamps, boglands or marshes, often of a peaty consistence5,10,33,34,37 and with soil pH values of 5.0–6.5 (dissolved in distilled water)37. This matches the pH values of the AFS in the present study (lower, but dissolved in CaCl2), but excludes the much lower pH values of the CW. The range considered suitable for C. impunctatus larvae should therefore be extended downwards to as low as pH 2.9–3.9 (CaCl2). We found C. impunctatus in two biotopes comprising a wide variance regarding soil moisture and organic content, which illustrates the wide tolerance range of this species. Individuals of C. impunctatus co-exist with Obsoletus Complex specimens as both were collected within the same sample in the AFS.Culicoides kibunensis was collected in the AFS and MA, which matches earlier observations depicting swamps of eutrophic fresh water bodies17,34, soil of stagnant water bodies22 and acidic grasslands in considerable distances to swamps33 as breeding sites. The AFS and MA revealed pH values between 3.4 and 5.4. Soil moisture and organic content displayed wide variances. All specimens hatched from late May to mid-June. Culicoides kibunensis was found to co-exist with C. albicans as observed by Kettle33. Earlier observations of co-habitations with C. obsoletus s.s. and C. pallidicornis5,34 could not be confirmed.Obsoletus Complex members were present in all study sites except for the ungrazed meadow. In the grazed meadows, Obsoletus Complex midges emerged almost throughout the entire sampling period except for the month of September. Two peaks were observed, one in June/July and a smaller one in October. As in the grazed meadows, the biotopes of region 3 also revealed two generations, but emerging at a slightly earlier time of the year with one peak in May/June and the other one in September/October.Members of the Obsoletus Complex are known to be generalists regarding their choice of breeding sites. Only the identified member species, C. chiopterus and C. obsoletus s.s., are considered here.Culicoides chiopterus was exclusively found on meadows grazed by cattle, which is in accordance to several earlier studies as this species is described as a dung-breeding species developing in cowpats and horse droppings5,34,35,38.Culicoides obsoletus s.s. was mostly sampled in the AFS. Only one individual was collected on a meadow grazed by cattle. Previous descriptions of breeding sites differed widely. Acidic grasslands in considerable distance to bogs/swamps33 and leaf litter compost5,35 could not be confirmed in the present study, although the MA and AFS were of a comparable character. While Uslu and Dik17 could not find any C. obsoletus s.s. in wet organic matter-rich soil, we collected most specimens of this species in the AFS and can therefore confirm previous findings11,29,32,39. The time of C. obsoletus s.s. activity in Germany (April–October) as described by Havelka32 agrees with our observations.Culicoides pallidicornis was found in the MA in late June. This species revealed the smallest variances of all sampled biting midge species regarding the three soil factors, using soil with pH values of 3.6–5.0 (CaCl2) and a relatively low level of moisture. This contradicts earlier observations where C. pallidicornis developed in the mud of eutrophic fresh-water swamps5. While C. pallidicornis larvae are known to co-exist with C. kibunensis5, we can add C. subfagineus to share the same developmental site.Culicoides pictipennis was collected in the DW and, to a minor part, in the AFS. The preferred physicochemical breeding conditions were ultra to extremely acidic with a medium moisture level and a moderate to slightly increased organic content. This differs from previous studies, which have found this species to develop only at the margin of stillwater bodies like pools and ponds, and the littoral of lakes or in artificially waterlogged soil11,32,34. Havelka32 observed C. pictipennis between May and June, while in our investigation the first specimen emerged as early as mid-April. We can confirm the co-existence of C. pictipennis and C. albicans as previously observed by Harrup11.Culicoides pulicaris was sampled in the AFS from late June until September, which agrees with observations denoting May to September as the activity time of this species32. Culicoides pulicaris seems to prefer breeding substrates with a high moisture level and a high organic content, as previously described17,32,34. We can add that C. pulicaris breeds in soil showing pH values at least between 4.0 and 5.4. We collected C. pulicaris together with C. achrayi and found it to simultaneously emerge from one biotope with C. obsoletus s.s. Additionally, we can confirm the co-existence of C. pulicaris with C. punctatus5,40, since both species have similar breeding habitat preferences11.Culicoides punctatus was sampled in the AFS and, to a minor part, in the CW. Time of emergence was from mid-June to late September, which is in accordance with earlier observations listing April-August and October as times of activity32. In the present study, a strong preference for swampy conditions with soil of high moisture, high organic content and a strong to very strong acidity was found. This is in agreement to previous findings11,32,41. The co-existence of C. punctatus with C. pulicaris is well known5,40 and can be confirmed once more. Additionally, we found C. punctatus to co-occur with C. subfasciipennis.Culicoides subfagineus was caught in the MA in late June. The soil was oligotrophic and contained a relatively low moisture level with pH values between 3.6 and 5.0. The first record of this species in Germany was in 2014, when C. subfagineus was observed to attack cattle42.Culicoides subfasciipennis was sampled in mid-June in the AFS. The time and choice of breeding site are in accordance to previous findings17,32. Breeding conditions for the only individual collected revealed a medium soil moisture factor, a pH value of 5.2 and a medium organic content. The species was found to co-develop with C. punctatus. More