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In this study, as shown in the conceptual image described in Fig. 2, we supposed that the cause to promote sediment production rate from forest areas to rivers is understory coverage rate decreasing. As the locations of the survey, we selected three granite low mountain forest areas in Japan; Hiei mountain, Kagami mountain, and Suzuka mountain. These places were the similar environmental conditions, forest woods, understory plants, the incline which almost less than 35°, and the latitude which is N35°04′-05′ at catchments of the river which inflow to Lake Biwa. We surveyed Shiga prefecture where is almost Lake Biwa basin in the western area of Japan. The forest area of Shiga prefecture is about 200,000 ha (about 60% occupied the prefecture area). About 80,000 ha of them are the artificial forest of cedar and cypress. Most of the planted forests are of an age that can be cut down and used. The locations of the field survey, we selected three low mountain forest areas on granite area and almost the same latitude in Lake Biwa basin; Hiei mountain, Kagami mountain, and Suzuka mountain (Fig. 3).Figure 2The concept ecosystem image diagram of the relationship between understory coverage rate and sediment production in the low mountain forest area. The understory disturbs sediments moving. The concept image diagram was drawn by T. Mizuno using Microsoft PowerPoint.Full size imageFigure 3The location map of the field survey forest of the low mountain on granite are between N35 06′ from N35 04′, where are the basin of Lake Biwa near Kyoto in the western area of Japan. The location map was based on the Digital Topographic Map 25,000 published by the Geospatial Information Authority of Japan (https://maps.gsi.go.jp), and was edited and processed by T. Mizuno using Microsoft PowerPoint.Full size imageFor the sediment production rate, annual actual measurement data of sediment receiving boxes, sediment receiving weirs, and dams were used. For the understory coverage rate, the Miura method was used18. The almost physical flow of forest surfaces is expressed in the form of a function of exponentiation19. Therefore, in the meta-analysis of all field data, the Poisson regression analysis (log function) of the generalized linear mixed-effects regression model was used. The dependent variable was the sediment production rate, the explanatory variable was the understory coverage rate and the random effect was the rain intensity. Because the rainfall intensity has a large effect on the surface flow of the forest when the amount of rainfall exceeds 90 (mm) on the moist soil4. Therefore, assuming that the maximum annual rainfall of 72 h is strongly related to sediment movement, it was used as an index of rainfall intensity. All-year data of Hiei, Kagami, and Suzuka of the maximum annual rainfall of 72 h exceeded 90 (mm). The rainfall intensity was categorized 6 levels; 100–200 (mm), 200–300 (mm), 300–400 (mm), 400–500 (mm), 500–600 (mm) and 600–700 (mm). Each rainfall intensity was inserted as the random effect in the Poisson regression analysis model. Statistical analysis software used R20 and performed calculations using the lme4 package21.Detail method of field survey of Hiei mountain forest (St.1)We carried out a field survey on the sediment production rate on a forest slope in the Hiei mountain forest owned by Enryakuji temple which was recorded world heritage. The stream order of the survey site is the zero-order basin of the Omiya River. The survey point was set in the forest of Sakamoto-Cho, Otsu City (Latitude and longitude notation; 35° 5′ 29ʺ N, 135° 50′ 10ʺ E) located in the uppermost stream of the Omiya River in the southwestern part of Shiga Prefecture. The bedrocks were mainly granite rock and the soil was brown forest soil. The altitude was about 760 (m), the slope direction was east, and the slope was 32°–35°. The main forest wood was the Japanese cypress (Chamaecyparis obtusa), which was about 100 years old, and the forest floor was relatively bright with moderate forest density. Besides, dwarf bamboo flourished on the forest floor of the study site and nearby forests until around 2005. At present, there are many areas where understory vegetation has disappeared due to deer feeding damage. At the survey point, the surface of the forest floor had become bare. On the forest slope where the understory vegetation had disappeared, we made a 5.0 (m) × 5.0 (m) survey area surrounded by a protective fence with a height of about 2.0 (m) to prevent deer feeding damage. At the lower end of the survey area, five sediment receiving boxes with a width of 25 (cm) and a height of 15 (cm) were installed at intervals of about 1.0 (m) along the contour lines. The survey started in June 2015, and the samples captured in the sediment receiving box were collected approximately once every two to four weeks, and after heavy rain appropriately. The collected sediment sample was air-dried, dried at 70 °C for 24 h or more, fractionated into sediment and litter, and the weight of each was measured. The sediment production rate was converted with a specific gravity of 1.8 (tons) per 1.0 (m3). As for the understory coverage rate, vegetation growth, litter, sediment, and gravel were evaluated by the point-counting by the Miura method18 in a range of 50 (cm) × 50 (cm) above each sediment receiving a box every autumn. Also, we checked the vegetation overgrowth around the field survey area. As the rainfall data used in the analysis, the observation data (observatory name: Hiei) closest to the survey site was used from the water quality hydrology database of the Ministry of Land, Infrastructure, Transport, and Tourism. The boxplot of the annual sediment production rate (m3/km2/year) was made by using soft-wares R3.6.120.Detail method of field survey of Kagami mountain (St.2)We collected data about the sediment production rate of the forest with 60% or more of the understory coverage rate in the Kagami mountain forest where no deer has been confirmed. The stream order of the survey site was a 0–3 order basin within the catchment area of the Hino River. The investigation point of sediment outflow from the forest was conducted at the forest mountain stream in Oshinohara, Yasu City (Latitude and longitude notation; 35° 4′ 2ʺ N, 136° 4′ 3ʺ E). The bedrock is granite, and the soil is brown forest soil. The catchment area of the study site is 20.0 ha, the altitude is about 150–280 (m), the slope of the mountain stream is north, and the slope of the mountain stream is about 11°. The main forest wood was the Japanese cypress (Chamaecyparis obtusa) and deciduous broad-leaved trees such as oak. No deer feeding damage to adult trees and understory was observed high density in the survey area. Mainly understory is the fern plant (Gleichenia japonica). Now the understory coverage rate is 60% or more anywhere. Sediment and litter that flowed out of the forest were collected from the upper part of the concrete weir (2.4 (m) wide × 1.2 (m) tall) installed at the downstream end of the survey site. We collected approximately once every two to four weeks after heavy rain in five years from 2015 to 2019. The collected sediment sample was air-dried for about 1 week, then dried at 70 °C for 24 h or more, and the weight of gravel and litter was measured. The boxplot of the annual sediment production rate (m3/km2/year) was made by using soft-wares R3.6.120.Detail method of data collection of Suzuka mountain (St.3)We collected data about the sediment production rate of the forest with both cases under 30% and 30%-60% of the understory coverage rate in the Suzuka mountain by using the Eigenji dam annual sediment deposit data. The elevation of the Eigenji Dam dam is 274 (m), and the maximum elevation of the catchment area of the Eigenji Dam is 1247 (m). The Eigenji dam is the stream order which is a 0–6 order basin within the catchment area of the Echi River. The Eigenji Dam was built in 1973 on the Echi River in Higashi-Omi City, Shiga Prefecture (Latitude and longitude notation; 35° 4′ 35ʺ N, 136° 20′ 7ʺ E), the catchment area is 131.5 km2. The catchment area is almost the forest area of the Suzuka mountain. The main bedrock of the Eigenji dam is granite, and the main bedrocks of the catchment are granite and sedimentary rock. The soil is brown forest soil. The slope of the watershed area is 10–20°. The report of Shiga prefecture referred to the damage caused by overgrazing by deer began to increase around 201022,23. In 2011, a large decrease in understory was confirmed in the entire watershed of the Eigenji Dam24. The boxplot of the annual sediment deposition (m3/km2/year) was made by dividing the period’s case 1 is when a 30–60% understory coverage rate from 1982 to 2009 and case 2 is when under 30% understory coverage rate from 2010 to 2015 by using soft-wares R3.6.120.Detail explains of the random effect of the equation of meta-analysisThe Poisson regression analysis (log function) of the generalized linear mixed-effects regression model was used. The dependent variable was the sediment production rate, the explanatory variable was the understory coverage rate and the random effect was the rainfall intensity. The rain intensity was categorized 6 levels; 100–200 (mm), 200–300 (mm), 300–400 (mm), 400–500 (mm), 500–600 (mm) and 600–700 (mm). Each rain intensity was inserted as a random effect in the Poisson mixed-effect regression analysis model. Statistical analysis software used R and performed calculations using the lme4 package21. More

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CORRESPONDENCE
13 July 2021

Italy: Forest harvesting is the opposite of green growth

Roberto Cazzolla Gatti

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Gianluca Piovesan

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Alessandro Chiarucci

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Roberto Cazzolla Gatti

Tomsk State University, Russia.

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Gianluca Piovesan

University of Tuscia, Viterbo, Italy.

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Alessandro Chiarucci

University of Bologna, Italy.

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We question plans to step up the harvesting of forest biomass, as set out in Italy’s Fourth Report on the State of Natural Capital. Rather than supporting a transition to a green economy, this could translate into more logging and perturbation of forest ecosystems.The loss of trees in Italy’s forests in recent years (go.nature.com/3yzvdp9) is only partly explained by disturbances such as Storm Vaia in 2018, and salvage logging thereafter. The dominant driver is the production of wood fuel (D. Pettenella et al. Forest@ 18, 1–4; 2021), mainly from coppice. This probably removes about 50% of estimated annual growth (see go.nature.com/3xr1mzc).The new biomass policy could threaten the functionality of forest ecosystems unless it includes measurable targets and a reliable monitoring system for tracking the impacts of removing wood. In a geographically complex country, rich in biodiversity, this could undermine progress towards the European Union’s 2030 biodiversity strategy.For Italy’s forests to contribute to the economy, provide ecosystem services, halt biodiversity loss and mitigate climate change, the country needs ecological planning, data monitoring, forest protection, restoration and rewilding.

Nature 595, 353 (2021)
doi: https://doi.org/10.1038/d41586-021-01923-x

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The authors declare no competing interests.

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Flow velocity thresholdThere were 92 Chinese sturgeon signals from 2016 to 2019, which were identified with the DIDSON dual-frequency video sonar system. The distribution map of Chinese sturgeon signals was shown in Fig. 1. The number of monitored signals in 2016 was significantly higher than in 2017–2019. The latest wild reproduction of the Chinese sturgeon occurred in 2016. Overall, most Chinese sturgeon signals were distributed within 500 m downstream from Gezhouba Dam, and there were more in the right side(facing downstream) than in the left side. The flow field of each sturgeon signal was simulated by the model, and the velocity of each signal location was obtained. According to the statistical analysis of the flow velocity values, the frequency of the sturgeon signal at different flow velocity values was shown in Fig. 2. The results show that most signals were concentrated in areas with flow velocities of 0.6–1.5 m/s, which accounted for 88.1% of the signals; areas with flow velocities below 0.6 m/s accounted for 4.3% of the signals, and areas with flow velocities above 1.5 m/s accounted for 7.6%. Therefore, 0.6–1.5 m/s was selected as the preferred flow velocity range of the Chinese sturgeon for spawning activity. This result was approximately consistent with the ranges proposed by most other researchers. The low limit of the velocity range was lower than that of other researchers. There may be two reasons for this result: the first was that the bottom velocity we analysed was lower than the surface velocity and vertical average velocity under the same conditions; the second was that our research time was after 2016, and the discharge during the spawning period was relatively low, so the velocity of the Chinese sturgeon signal was also relatively low.Figure 1Distribution map of Chinese sturgeon signals, where ○ indicates Chinese sturgeon signals monitored in 2016, ∆ indicates those in 2017, □ indicates those in 2018, and ✩ indicates those in 2019. Map generated in ArcGIS Pro (https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview).Full size imageFigure 2Plots of the frequency for the different flow velocity ranges of Chinese sturgeon signals.Full size imageDifferent opening modes with identical dischargeThe discharge of 6150 m3/s on November 24, 2016, when the latest wild reproduction of Chinese sturgeon occurred, was used to study the flow velocity distribution with different opening modes. The specific opening mode cases are shown in Table 1. Case 1 was the actual situation, and the Dajiang Plant featured 7 open units: #8, #11, #13, #14, #16, #19, and #21. According to the amounts of electricity generated by Dajiang Plant and Erjiang Plant on that day, the proportion of the Dajiang River flow was 58.8%, and the average discharge of each unit was 516.6 m3/s. Case 2 and case 3 featured 7 open units with the same discharge, but in case 2, units #15–21 were continuously open on the right-side (facing downstream), and in case 3, units #8–14 were continuously open near the left side. Case 4 and case 5 were the most concentrated conditions with the discharge of 6150 m3/s because the maximum through-discharge for each unit in the Dajiang Plant is 825 m3/s19. In these cases, at least 5 units were open with an average discharge of 723 m3/s per unit. Case 4 involved continuously opening units #8–12 on the left side, and case 5 involved continuously opening units #17–21 on the right side. Case 6 involved simultaneously opening 14 units on Dajiang River, and the average discharge of each unit was 258.3 m3/s.Table 1 Calculation cases with different opening modes of units under the identical discharge.Full size tableFigure 3 shows the flow fields of the spawning ground under different opening modes with identical discharge. By comparing the areas with a velocity threshold range of 0.6–1.5 m/s in different cases, the most favourable opening mode was determined. In case 1, the velocity at the outlet of the units was higher than the 1.5 m/s velocity threshold, but the discharge of each unit was only 516.6 m3/s, so the high-velocity range was limited, and most areas were suitable. In case 2 and case 3, there was a large difference in proportions of suitable area. Because the left side was deeper than the right side, the flow velocity on the right side was higher under the same discharge, and case 3 more easily exceeded the flow threshold, which resulted in a larger unsuitable area. Case 2 was more suitable than case 1, which also demonstrated that opening the left-side units was more favourable. In case 4 and case 5, the proportions of suitable area were small. Because the units were concentrated, the discharge of each unit was too high, and the outlet velocity was more than 2 m/s, so a large area of high velocity appeared downstream of the units with backflow under the shut-down units. The proportion of suitable area in case 5 was larger than those in case 4 and case 3, which further indicates that opening the left-side units was more favourable than opening the right-side units. Case 6 was greater than that of any other case. Because the discharge of each unit was only 258.3 m3/s, the velocity of the unit outlet was less than 1.5 m/s, and almost all areas were suitable except for the small areas on both sides. The suitable-velocity area was the largest when all units of the Dajiang Plant of Gezhouba Dam were open; therefore, for a given discharge, it was best to open all units.Figure 3Flow field of the spawning ground in different opening modes with identical discharge, where the numbers at the top of each picture are the numbers of units to open, and the arrows indicate the direction of the water flow. Maps generated in Tecplot360 EX 2020 R1 (https://www.tecplot.com/products/tecplot-360/).Full size imageDifferent discharges under identical opening modeThe velocity distribution of the spawning field is affected by the opening mode of the units and discharge of Gezhouba Dam. To study the effect of different discharges, 14 cases were simulated, as shown in Table 2. All units of the Dajiang Plant were considered open because the proportion of suitable area was expected to be maximal under such circumstances. From 1982 to the present, the discharge during the spawning day of Chinese sturgeon under Gezhouba Dam has a wide range: the highest discharge was 27,290 m3/s in 1990, and the lowest discharge was 5590 m3/s in 2012. However, the highest design discharge of the Gezhouba Dam units is 17,930 m3/s20. Once the design discharge is exceeded, the spillway on Erjiang River discharges water, and the velocity distribution of the study area is not affected. Therefore, case 1 represents the lowest discharge of 5590 m3/s, and case 2 represents a discharge of 6000 m3/s. For each subsequent case, the discharge was increased by 1000 m3/s to case 13 with the highest flow of 17,930 m 3/s. In case 14, all units reached the design discharge, and the discharge of each unit was 825 m3/s19.Table 2 Calculation cases with the same opening mode under different discharges.Full size tableFigure 4 shows the proportion of suitable-velocity area with all units open under different discharges. According to the calculation results, the proportion of suitable area slightly fluctuated at approximately 96.2% for discharges of 5590–11,000 m3/s. Because the discharge of each unit was low, the velocity of the unit outlet was low, and most areas were within the velocity threshold. Therefore, it is advantageous to open all units when the discharge is low. After the discharge reached 12,000 m3/s, the proportion of suitable area rapidly decreased. Because the discharge of each unit was high, on the right side of Dajiang River, the velocity of the unit outlet exceeded the velocity threshold and increased with increases in discharge, and the range of effect gradually increased. In the last case, the proportion of suitable area was only 6% when the units reached the designed discharge of 825 m3/s. Because the discharge of each unit was too high, almost all areas exceeded the velocity threshold except for small areas on both sides. Therefore, at discharges below 12,000 m3/s, opening all units is favourable, and at discharge above 12,000 m3/s, a higher discharge corresponds to more unfavourable conditions.Figure 4Proportions of the suitable-velocity area with all units opened under different discharges.Full size imageOptimal scheme under high-flow conditionsHigh-flow conditions at Gezhouba Dam are considered those that exceed 12,000 m3/s because of the substantive decline in suitable habitat area at higher discharges. Because opening the units on the left side of the Dajiang Plant provides a more uniform, suitable habitat, we evaluated 20 cases with a left-side opening mode under different discharge, as shown in Table 3. Because the highest discharge of each unit in the Dajiang Plant is 825 m3/s, at least 9 units must be open when the discharge is 12,000 m3/s. Case 1 was designed to open 9 units on the left, i.e., units #13–21, and the discharge of each unit was 784 m3/s. Cases 2–5 increased by 1 unit from left to right until 13 units were opened. For discharges of 13,000 m3/s, 14,000 m3/s, 15,000 m3/s, and 16,000 m3/s, at least 10, 10, 11, and 12 units were opened. When the discharge was 17,000 m3/s and 17,930 m3/s, at least 13 units were open.Table 3 Calculation cases with different opening modes under high-flow conditions.Full size tableFigure 5 shows the proportions of suitable area for different opening modes under high-flow conditions. The calculation results show that when the discharge was 12,000 m3/s, 13,000 m3/s, and 14,000 m3/s, the proportion of suitable area showed a parabolic trend with the increase in number of units. When the discharge was 12,000 m3/s, the proportion of suitable area with 11 open units on the left was the largest, which was 8.7% larger than the value for all open units and 15% larger than the value for the lowest number of open units. When the discharge was 13,000 m3/s, 12 open units on the left had the largest proportion of suitable-flow-velocity area. When the discharge was 14,000 m3/s, the proportions of suitable area produced by opening 12 and 13 units on the left were the largest. The proportion of suitable area of the lowest number of open units was usually minimal because the discharge of each unit was too high, which resulted in a large area of high velocity that was not suitable for Chinese sturgeon to spawn. Because of the underwater topography, opening the left-side units was more favourable than opening the right-side units, so for all open units, the proportions of suitable area will be lower, and the number of units opened in the middle will be the most advantageous. For a discharge of 15,000 m3/s, with the increase in number of units, the proportion of suitable area increased, and there was no parabolic trend because the discharge of each unit exceeded 678 m3/s; thus, on the left side, there was a large area of high velocity, and the effect extended very far, which was not suitable for Chinese sturgeon.Figure 5Proportions of the suitable area for different opening modes under high-flow conditions, where 12,000–09 on the x-axis indicates that the discharge is 12,000 m3/s, and 9 units are open on the left.Full size image More

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