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    Successful artificial reefs depend on getting the context right due to complex socio-bio-economic interactions

    When introducing ARs as a fisheries management tool to Senegal, the Japanese management had the mindset of Japanese stakeholders, i.e., introducing fishing rights. However, after discussions with Senegalese stakeholders, it was decided that no-take areas would be delineated around ARs because the establishment of a strong fishing rights regime was not socially acceptable to the Senegalese fishing community. Japanese governance is based on the acceptance and respect of fishers towards individual, private AR concessions. In contrast, fishers in Senegal, and more widely in West Africa, are characterized by high mobility, particularly in the context of climate change and overexploitation18,19. Consequently, respect for local management regulations is lower, with open access being generally assumed. The basic concept of implementing a no-take area on the AR was not easily accepted by fishers. The immersion of AR concrete blocks was set as a top priority by managers at the expense of more complex socio-economic considerations, such as consciousness-raising activities and self-sustaining participative monitoring of the AR.The clear contradiction between the ecological knowledge of fishers and their behavior was explained by the well-known effects of open access resources on individual behavior. This phenomenon was also observed in our mathematical model. The processes in the mathematical model are in accordance with those perceived by the fishers, so that the results are also those expected by fisher’s local ecological knowledge. It is interesting to notice that the theoretical results presented here are the mathematical solutions of the model at equilibrium between fishing effort and fish population growth, i.e. after an oscillation period. It is obvious that short-term effect of fishing on the AR is always to increase the catch, but many fishers did perceive the longer-term effect of decreasing catches. The potential negative effect of the AR on catch when there is high fish attraction combined with high fishing pressure on the AR might explain the reluctance of a part of the fishers community to AR deployment (Fig. 2). In particular, the model illustrates that the AR attraction effect strongly determines the impact of the management. In general, fish attraction is the most immediate effect perceived after AR deployment11, as was true for our study16. Though the AR volume was relatively small (70 m3), the empty space between the higher blocks also contributes approximately 280 to 570 m3 of good habitat/refuge for schooling fish; therefore, it is actually difficult to accurately describe the volume that affects fish. Thus, it is difficult to say whether this AR is below or above the forecasted optimal volume in absence of fishing (120m3 with model parameters). The existence of an optimal volume for AR was also suggested by field studies as a trade off between food supply and refuge20, in line with our results. For management purposes, it is interesting to determine whether the AR is above or below this optimal level because if the volume is too small, the model predicted that any level of fishing on the AR would, in the long term, decrease the catch in the considered area. On the other hand, if the volume is above the optimal level, a small fishing effort on the AR could be authorized and would increase the total catch in the area.Field observation showed that the fish attraction effect was strong16 but precise estimation of this parameter cannot be inferred, as this would need, ideally, individual fish trajectories. Future field research on the attraction effect may permit estimating the AR attraction parameters. The model sensitivity test showed that the stronger the attraction parameter, the better the impact of the AR for the fisheries in case of no or small fishing effort on the AR (Fig. 3). But at the same time, the attraction is a strong incentive for fishers to fish on the AR, and the predicted benefit for fisheries in the fishing area rapidly vanishes when fishing effort on AR increases. This in turn provides further incentive for fishers to fish the AR, challenging the surveillance capacity. If fish attractiveness is strong and too many fishers fish on the AR, catch in the area will be concentrated on the AR, while the adjacent fishing area will be depleted, with catch levels lower than those prior to AR deployment.Specifically, in the context of generalized overfishing in Senegal21, deciding not to fish on the AR represents significant individual loss, despite being recognized as beneficial, globally22. It has been argued that this situation would rarely occur in small-scale fisheries, due to existing arrangements between individuals23. However, in the context of the highly mobile Senegalese artisanal fishing fleet and its overcapacity, as soon as the AR in Yenne was no longer subject to surveillance, it rapidly attracted fishers from other villages. Also, pre-existing arrangements between fishers might be overruled when new ARs are created, changing the structure of existing fishing grounds.At the time of the survey, the surveillance system set up by the co-management entities was not operational in our case study, because it was dependent on temporally limited external financing. These limitations are typical of short-term projects that focus on a single restricted area for a pre-determined duration, usually up to two years (e.g., NGOs, World Bank). Local fishers perceptions were globally in line with the model prediction that this AR fails to improve fisheries yield when surveillance is not in place to ensure AR regulations are observed, despite effective fish attraction and production existing in the AR.The model predicted that enhanced production on ARs could not keep pace with unrestricted access, which might be particularly true in Senegal where fishing effort rapidly reorganizes itself according to local yields24. Enhanced production due to the AR largely increases the catch if the fishing pressure on the AR remains null or very low, but it has no effect on the catch for higher fishing pressures on the AR (Fig. 3). These results were stable even if fish population growth, fish catchability, mobility and economic parameters could modulate the predicted amplitude of the catch and AR optimal volume. These results are consistent with existing theoretical studies of the impact of fisher movement to high production areas in and around MPAs25. Taking into account several species and their interactions (predation, competition) would lead to a very complex ecosystem model specific to the area (e.g. 26), with necessarily more assumptions. This model would necessarily be more difficult to share with fishers and other stakeholders. Both to simplify model structure and facilitate communication of results to stakeholders, we assumed in our model that the balance of entries exits and is in equilibrium, so that the migratory species did not affect the long-term equilibrium between fishing effort and fish abundance.The design of ARs could be adjusted to reduce the effect of illegal fishing by passively preventing both industrial and artisanal fishing activity. Complex structures are more effective for fish production and attraction27. We showed that, although production might have a limited effect on total catch, attraction can largely increase AR efficiency (total catch) if the rate of illegal fishing rate is very low or absent. Complex structures protect fish more effectively from small scale fishing gear28, including divers (Pers. Comm., Mamadou Sarr, Ouakam fishers committee). Thus, ARs should be appropriately designed to help mitigate potential issues28. Such designs might be more costly, and do not exclude the need for surveillance, but would enhance fisheries management, especially when surveillance cannot capture low levels of illegal fishing.Finally, if socio-economic and governance conditions are not met, well-intentioned AR projects will likely disturb the existing equilibrium among fishers that have different levels of access to the AR. Poor governance of marine resources has previously been described in West Africa, particularly in Senegal29, as has the failure of AR projects in a number of other developing countries9, which further deteriorate fishers trust and management plans efficiency30. In order to avoid that, NGO and governmental agencies driving ARs projects must consider that AR management induces collective costs before providing potentially collective gains. Thus, co-management that involves governmental institutions and fisher communities is required. Future management and adaptation plans for fishers, particularly in developing countries, should, therefore, focus efforts on raising long-term awareness of actors in both government institutions and fishing communities. At the level of institutional or development partners, long-term management costs should be included in the set-up of AR projects. For example, the local fishers committee of Yenne recently reported the establishment of a collective ship chandler whose profits are used to finance AR surveillance during the daytime. Subsequently, fishers noted an improvement in catches around the AR, even though illegal fishing likely continues on the AR at night (Pers. Comm. chair of local fishers committee). These observations support model predictions that low levels of illegal fishing might not disturb the positive impact of the AR. Alternatively surveillance effort could be supported by the community if benefits were managed according to ancestral traditions. Indeed, “no take area” regime on the AR would be in line with some past West African tribal laws, applied before the colonization era, which set marine area where fishing activities were restricted for occasional community celebrations. Collective processes where fishers and other stakeholders can design temporary no-take zones around the AR could increase fishers trust and compliance to the rules, fostering a positive socio-ecological feedback loop30.Hybridization of local and scientific knowledge, through the integration of natural sciences and social sciences, is key point for governance setting31,32,33. Indeed, the communication of the resulting hybrid knowledge in specific events gathering local stakeholders helps strengthen fisheries co-management for the establishment of surveillance and regulatory frameworks. This phenomenon was experienced during the public restitution of the present study with the community, fishers, children’s from local schools and governmental stakeholders. Science popularization of the study results was in French and local language (Wolof) retransmitted on national news (available at https://www.youtube.com/watch?v=yQqFU2P4XZU). Posters were exposed during the event, including pictures of local fishers interviewed and statements reflecting their own perception of how the artificial reef interacts with ecological processes and fisheries dynamics. Straightaway, stakeholders and local promoters of AR publicly expressed their concern and willingness to prioritize the setting up an efficient AR surveillance independent from external resources prior to increase AR deployments. Knowledge hybridization could produce more specific models that could be used for warning and advice, for example by considering potential impacts of ARs on species compositions3,34,35, environmental parameters36, and cascade effects on the trophic food web37. However this approach would need to be adapted to local social-ecological governance, which might require dedicated political-anthropological studies (see concept of adaptive co-management32).In summary, best practices should involve all stakeholders, consider local specificities, such as site configuration, governance, ecosystem, availability of ad hoc human and financial resources for AR surveillance, and define AR volume and design accordingly to these parameters. Thus, if plans exist to deploy ARs at large scales we recommend that legislation is strengthened, with detailed Environmental and social Impact Assessments38 to implement ARs, including considerations of long-term governance. More

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    A study of ladder-like silk foothold for the locomotion of bagworms

    Bagworm walking method using a ladder-like silk footholdWhen bagworms are reared in a plastic or glass cage, they walk not only on the floor but also on the walls or ceiling using only their three pairs of thoracic legs. The method by which they achieve this was clarified by placing a bagworm on black paper. Where the bagworm had walked, a ladder-like silk trace was observed on the black paper (Fig. 2a). Scanning electron microscopy (SEM) observation of one of the steps (or rungs) of the ladder-like trace revealed that each step was made up of a zigzag pattern of silk threads (Fig. 2b). Further magnified SEM observations revealed that the folded parts of the zigzag-spun thread were glued selectively to the substrate with adhesive whereas the remaining straight parts (hereafter, termed ‘bridges’ or ‘bridge threads’) were unglued (Fig. 2c–e).Figure 2Architecture of the ladder-like foothold. (a) A typical ladder-like foothold constructed by a bagworm on black paper, (b) an enlarged image showing one of the steps in the foothold and (c) a scanning electron microscopy image of the step shown in (b). The unglued bridge threads and a glued turn in the step shown in (c) are magnified in (d) and (e), respectively. (f) An enlarged image of four continuous steps in the foothold shown in (a). The neighbouring steps are connected via a single thread indicated by the arrows. (g) A schematic depiction of the basic architecture of the foothold; blue lines and green circles correspond to the silk thread and glued parts, respectively. (h) A photograph of a bagworm constructing a foothold on a transparent plastic board.Full size imageNotably, the steps of the foothold were not independent but rather always connected with neighbouring steps via a single thread (Fig. 2f). The overall basic construction of the foothold is schematically depicted in Fig. 2g. We found that the foothold was constructed in one continuous movement and always made of a single thread regardless of walking distance or time; therefore, a continuous thread exceeding a length of 100 m could be collected from one foothold14. We also observed bagworm climbing behaviour on a transparent plastic board, which clarified the important role of the silk trace as a foothold (Fig. 2h). During this behaviour, the bagworm used its sickle claws (Fig. 1e) to hook its second and third pairs of thoracic legs onto the first and second newest steps, respectively, and constructed the next step by spinning silk with a zigzag motion of the head and the skilful use of the first pair of thoracic legs. When the bagworm advanced one step, it always first shifted its third pair of thoracic legs to the next step before then shifting its second pair of thoracic legs to the newest step to avoid overloading this step, which may not yet be fully adhered to the surface (see Supplementary Movie S1). Because of this construction method, the interval distance between neighbouring steps is automatically determined by the interval between the thoracic legs. By repeating this process, the bagworm can advance forward slowly but steadily. This walking method was commonly observed on a horizontal floor surface, vertical wall, or horizontal ceiling. Although we have mainly described and shown observations from E. variegate here, with the exception of Supplementary Fig. S4 and Movie S1, we also observed instances of walking behaviour in other species, namely Eumeta minuscula, Mahasena aurea, Nipponopsyche fuscescens and Bambalina sp. (for a movie on E. minuscula walking behaviour, wherein it climbs a vertical wall, see Supplementary Movie S2). For at least 100 individuals of these bagworm species, we observed essentially identical walking behaviour to that described in the present study without exceptions for locomotion on substrates with slippery surfaces.Based on our observations, we asked the following question: how do bagworms selectively glue the folded parts of the foothold onto the substrate? Real-time observation of the tip of the spinneret (i.e. the spigot) through a transparent plastic board during the construction of the foothold revealed that adhesive was selectively discharged to attach the folded parts to the substrate; this process could be distinguished from the continuous spinning of the silk thread (for a movie showing construction behaviour, see Supplementary Movie S3). Figure 3a–g shows a time-sequence of foothold construction with enlarged images in the vicinity of the spinneret provided, whereas Fig. 3h depicts a schematic trace of the construction process. It was clearly noted that the bagworm discharged the adhesive only at the folded parts (shown in Fig. 3a–c,e,f; termed the ‘glued turn’) and not at the straight bridge parts (shown in Fig. 3d,g; termed the ‘unglued bridge thread’). From these time-sequence observations, we concluded that the bagworm controls the discharge of adhesive in an ‘on and off’ manner as necessary (essentially the same construction behaviours were confirmed for at least 20 individuals).Figure 3Foothold construction. (a–g) (left side) Time-sequence images taken during foothold construction and (right side) enlarged images of the vicinity of the spinneret (corresponding to the yellow rectangular area in each left-side image). The time-sequence images correspond to the parts of the schematic trace of foothold construction depicted by the red line in (h). In each right-side image and the schematic trace, the part of silk thread at which the adhesive was discharged is traced with a light-blue line. Green arrows in the right-side images show the direction of travel of the spinneret.Full size imagePassages of fibroin brins and adhesiveWe next investigated the spinning mechanism that enables continuous spinning of silk thread together with the selective discharge of adhesive via a single spigot. To this end, we observed the morphology of the bagworm from the silk gland to the spigot. Figure 4a shows the area in the vicinity of the spinneret, dissected and isolated from an E. variegata bagworm, which included a pair of silk glands and plural adhesive glands. As we previously reported21, the exterior shape of the silk gland in E. variegata (see Supplementary Fig. S1) is almost the same shape as that in the silkworm Bombyx mori and it is subdivided into three parts: the anterior (ASG), middle (MSG) and posterior (PSG) silk glands. We also previously confirmed that fibroin heavy chain (h-fib), fibroin light chain (l-fib) and fiboinhexamerin genes are expressed dominantly in the PSG, while sericin is expressed in the MSG, which strongly suggests that division-selective production of each protein exists in E. variegata (as has been shown in B. mori22). Figure 4b shows a magnified image of the spinneret including the end of the ASG. Beyond the pair of ASGs, which are merged into a common tube, a silk press and spinning tube appear before the spigot. This basic passage of silk fibroin from the ASG to the spigot is essentially the same as the passage observed in B. mori23. However, more detailed morphological observations of the inner structure of the passage revealed several obvious differences between E. variegata and B. mori.Figure 4Structural examination of the passages of fibroin brins and adhesive. (a) An optical microscope image of the area in the vicinity of a spinneret isolated from a female bagworm in the final instar stage. Indicated by arrows is a pair of silk glands (SG), one of the adhesive glands (ADG) and the spinneret (SP). (b) An optical microscope image of the passage including the (1) end of the anterior SGs (ASGs), (2) common tube, (3) silk press, (4) spinning tube and (5) spigot. (c–j) Optical microscope images showing cross-sections of the passage of fibroin brins obtained from the corresponding positions (c–j) in image (b). To focus on the fibroin brins and its passage, the surrounding outer part was removed so that a pair of fibroin brins was revealed in each image (except for image (c), which shows only one side of the ASG). Unmagnified images of (f–j), including the outer part, are shown in Supplementary Fig. S2. (k–n) 3D X-ray CT images of the spinneret: (k) overview, (l) cross-sectional top view, (m) cross-sectional side view and (n) passage of the fibroin brins and corresponding cross-sectional images at various positions. In the cross-sectional side view (m), the sheath and core parts are coloured blue and pink, respectively. (o) Image of the tip of a spigot from which adhesive is overflowing and a silk thread is emerging.Full size imageCross-sectional images along the spinneret are shown in Fig. 4c–j; these focus on the silk brins and their passage (unmagnified versions of the images in Fig. 4f–j are shown in Supplementary Fig. S2). The fibroin brins have an approximately round cross-sectional shape at the end of the ASG (Fig. 4c) and are merged at a common tube, which deforms their round shape slightly (Fig. 4d). The fibroin brins seem to be coated with a thin layer of sericin after the MSG, similar to B. mori; however, we omit the presence of the sericin layer here for convenience. The paired brins are gradually pressed between the ventral and dorsal hard cuticle plates at the silk press, and a gradual diameter decrease and shape deformation follows (Fig. 4e,f). At the exit of the silk press, each brin becomes elliptic and the diameter in the major axis decreases. Interestingly, the elliptical shape and 1.7-axial ratio for the major and minor axes of the fibroin brin cross-section in bagworm silk, which we previously reported14, are already determined at this stage in the silk press; afterwards, the diameter decreases without any change in the axial ratio of the elliptical cross-section. Notably, the two elliptical fibroin brins are aligned side-by-side so that their major axes are in line horizontally (to resemble a figure of ‘∞’) at the spinning press, and these are followed by the spinning tube (Fig. 4e–h). However, the alignment is twisted by 90° in one direction (to resemble a figure of ‘8’) before the brins are spun from the spigot (Fig. 4i,j).We found that the spinning tube was surrounded by a hard exoskeleton. Using 3D-X-ray CT observations, we produced clear images of the exterior and interior morphologies of the spinning tube enveloped by exoskeleton (Fig. 4k–m; the exterior shape observed from the dorsal-, ventral- and lateral-sides by optical microscopy is provided in Supplementary Fig. S3). The spigot was not cut perpendicularly to the spinning tube but rather with a slope of around 20°; consequently, it was elliptic. X-ray CT clearly showed the core-sheath structure of the spinneret and a wide expanse of sheath parts (Fig. 4m) between the exterior shell and interior spinning tube (Fig. 4l,m). Using optical microscope observations of the cross-sections, we found that at least three pairs of adhesive ducts were running in the sheath space (Supplementary Fig. S2E). Therefore, while the silk brins pass through the central narrow spinning tube, the plural adhesive ducts pass through the outer space independently of the silk thread. Finally, the adhesive enters a ladle-like reservoir located at the spigot and is released together with the silk thread (Fig. 4o). The presence of definitive routes connecting the adhesive passage and the spigot were not clearly observed in our X-ray CT images, probably due to the small structural scale relative to the space resolution used in our analysis (i.e. 0.31 μm). We speculate that the adhesive merges into the spigot via a fine, porous sponge-like structure, and we indicate assumed routes in Fig. 4l,m. X-ray CT observations also revealed a sophisticated structural design involving gradual twists in the silk brins by 90° from ‘∞’ to ‘8’ (Fig. 4n and Supplementary Movie S4). Essentially identical spinneret structures were observed by X-ray CT images for all of eight observed individuals from the third to final instars of E. variegata. More

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    Brazilian road proposal threatens famed biodiversity hotspot

    NEWS
    17 August 2021

    Brazilian road proposal threatens famed biodiversity hotspot

    Scientists and environmentalists say the road, slated to pass through Iguaçu National Park, could harm research projects and precious ecosystems.

    Meghie Rodrigues

    Meghie Rodrigues

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    Protesters oppose the Caminho do Colono at Iguaçu Falls.Credit: Marcos Labanca

    Brazil’s National Congress could soon vote on a bill proposing to construct a road through the country’s Iguaçu National Park. If the proposal moves ahead, researchers fear that it will threaten the park’s lush forest, a biodiversity hotspot that is home to almost 1,600 animal species, including endangered animals such as the purple-winged ground dove.Environmentalists and researchers have fought off construction of the 17.5-kilometre road for years, arguing that it will not only bring pollution to the park, but also poachers, who would threaten animals such as jaguars and tapirs. Even research in the park could be affected. In a portion of the park that dips into Argentina, for example, “poachers often steal our cameras”, says Julia Pardo, a mammal conservation and ecology researcher at the Subtropical Biology Institute in Misiones, Argentina.
    ‘Apocalyptic’ fires are ravaging the world’s largest tropical wetland
    Under the leadership of President Jair Bolsonaro, Brazil’s government has weakened protection of the country’s forests in favour of industries such as mining, logging and ranching. The lower house of Brazil’s Congress, the Chamber of Deputies, put the bill on a fast track in June, allowing it to skip regular debate among its committees and head straight for a vote — a move that has researchers worried.If passed, the legislation would establish a dangerous precedent that could weaken environmental law in Brazil, says Sylvia Torrecilha, a biologist at the Secretariat of Environment, Economic Development, Production and Family Agriculture in Mato Grosso do Sul. In addition to cutting Iguaçu Park in two with a road that will connect towns to its north and south (see ‘Contested route’), the bill seeks to create a new type of protected area — the estrada-parque, or park road — within Brazil’s System of Natural Conservation Units, which regulates environmentally protected areas. Approving the construction of the ‘Caminho do Colono’ (the Settler’s Road) in Iguaçu could literally pave the way for creating through-ways in other parks and conservation areas in Brazil, says Torrecilha.Normally, the idea of a park road is to preserve the green areas along an already-existing scenic route, she says, not to bring commercial or economic advancement to a state — the argument lawmakers have made in favour of the road. The proposal, from its very beginning, is “inappropriate”, she adds.A historical routeEstablished in 1939, Iguaçu National Park is famous for the waterfall — one of the world’s largest — on the border with Argentina along its southwestern tip. But it is also notable because it contains the largest remaining patch of Atlantic Forest in southern Brazil. Although less well-known than the Amazon rainforest, the Atlantic Forest is rich in plant and animal species, and originally stretched along the coast of southeastern Brazil and down to Argentina and Paraguay. However, the forest is rapidly disappearing: it has lost almost 90% of its tree cover, accelerated by deforestation from urbanization, and agricultural and industrial activities in the twentieth century. Because of these attributes, the park was designated as a World Heritage site by the United Nations cultural organization UNESCO in 1986.

    If the legislation is successful, it would actually enable the creation of the Caminho do Colono for the second time. The government of Paraná, the state where Iguaçu National Park is located, transformed an existing walking path into an unpaved version of the road during the 1950s. “Nobody cared much at the time because there wasn’t much difference between the inside and the outside of the park, as the Atlantic Forest stretched all over the place,” says former park chief Ivan Baptiston. “With all the deforestation of the last decades, nowadays, the scenario is a lot different.”In 1986 — the same year the park received its UNESCO World Heritage Site designation — Brazil’s Federal Prosecutor’s Office filed a civil suit to close the road, and the following year, a federal judge officially closed it. Since then, vegetation has overtaken the route, and some local residents have tried and failed to force it back open, claiming economic hardships associated with not being able to travel efficiently through the area.
    ‘We are being ignored’: Brazil’s researchers blame anti-science government for devastating COVID surge
    The new bill states that re-establishing the road would offer a “solution to a logistical problem in Paraná state”. Sponsored by Nelsi Coguetto Maria, a member of the Chamber of Deputies, the proposal also says it “answers a decades-old outcry of Paraná inhabitants, salvaging the region’s history and its socioeconomic, environmental and tourism relations.”Environmentalists have criticized Coguetto Maria for backing the bill. And local media outlets have reported that his family stands to potentially gain from the Caminho do Colono; two of his sons are partners in construction companies that could pave the road. Coguetto Maria’s office did not respond to Nature’s queries about this, or about researchers’ concerns over the road. When the Chamber of Deputies approved fast-tracking of the bill, he argued that the Brazil of today is “responsible”, and has the “competence and capacity to build an ecologically correct road”, pointing out that the road existed as a walking path before the park was even created.Research interruptedFor many conservationists and researchers, the economic argument to open the road doesn’t hold water. The damage caused to the park’s highly valued Atlantic Forest would far outweigh the potential economic gains for the surrounding towns1, they say. Furthermore, the species protected by the park are irreplaceable, they add. Iguaçu is the only location in the world where the jaguar population is increasing instead of declining. If the road opens, says Pardo, pressure on the animals will skyrocket. “Easy access is the main enabler for poachers,” she says.

    Iguaçu Falls is located along the border of Argentina and Brazil, on the Iguaçu River.Credit: Thiago Trevisan/Alamy

    Cars using the road will also cause air, soil, water and even sound pollution, says Victor Prasniewski, a conservation biologist at the Federal University of Mato Grosso in Brazil. Sound pollution, in particular, changes communication patterns among a number of species. “Birds that attract females by singing will be forced to sing louder or longer to get noticed,” says Prasniewski, who published a paper last year2 listing the potential negative impacts of the Caminho do Colono.“These changes can affect the reproduction and even the evolution of some birds,” says Carlos Araújo, a bioacoustics ecologist at Argentina’s Subtropical Biology Institute. “The building of a road would be catastrophic to research in my field,” he says.He works on a large-scale monitoring project looking for the purple-winged ground-dove, the last confirmed sighting of which was more than three decades ago. “It’s a rare animal, and we leave recorders spread over the forest to try and catch her singing. We often capture helicopter noise, which disturbs our work.” Cars and trucks on the road would create similar low-frequency noise, he says. “It will be a lot harder to find birds like this dove.”
    Brazil’s lawmakers renew push to weaken environmental rules
    For some, the argument that the road will enhance tourism in Paraná doesn’t make sense either. Reopening the road, says Carmel Croukamp Davies, chief executive of Parque das Aves, a private bird sanctuary and shelter near the park, could threaten Iguaçu’s UNESCO World Heritage title if it damages the park’s biodiversity and severs the Atlantic Forest. Visitors come because they want to experience nature, she adds: “Whoever doesn’t understand the impact of a proposal like this doesn’t understand an inch of tourism nor biodiversity.”With Brazil’s Congress having returned from holiday earlier this month, the bill could soon be put to a vote. And when it is, environmentalists worry it will be passed, given how many representatives within the Chamber of Deputies currently align with Bolsonaro. Then it would face the Senate, and finally, Bolsonaro, who is expected to ultimately approve it.

    doi: https://doi.org/10.1038/d41586-021-02199-x

    References1.Ortiz, R. A. Ambientalia 1, 141–160 (2009).
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    2.Prasniewski, V. M. et al. Ambio 49, 2061–2067 (2020).
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    Dayara bugyal restoration model in the alpine and subalpine region of the Central Himalaya: a step toward minimizing the impacts

    Restoration response evaluationMulti-criteria response analysis has been a crucial part of restoration evaluation work as a proper practical achievement which always includes multiple objectives defined by diverse stakeholders. In current work, a new framework was designed for restoration response evaluation by assessing three categories, direct management measure (M), environmental desirability (E) and socio-economic feasibility (SE). In total, 9 sub-categories and 22 individual variables were considered for evaluation of the present work41 (Table 6).Table 6 Response evaluation parameters.Full size tableDirect management measure (M) evaluationDuring the starting phase of the work, excessive grazing, uncontrolled tourism and continuous soil erosion were identified as major drivers behind the degradation of Dayara bugyal. Therefore, in the first category of the evaluation work, direct management measures to control the above-mentioned activities were analysed. The disturbances were controlled by managing both anthropogenic (M1) and natural (M2) processes. Under anthropogenic control process, grazing (A1) and tourism (A2) control activities were measured and soil erosion (B1) control activities was considered under natural control sub-category.Livestock carrying capacityLivestock carrying capacity of the pastureland was a measure for proper control of the estimation of grazing capacity. Forage yield of the area was calculated by considering the shoot production of 10 dominant palatable species of the area. Sample plant materials at the end of the growing season, were oven-dried at 80 (^circ)C till it reached at constant weight and then weighed in the laboratory. Thereafter, density of individual plant was measured by laying 30 quadrates of 1 × 1 m randomly placed within 50 × 50 m grid in the herb community (Eq. 1)42. Total 80 grids were sampled for analysis of 40 hectare degraded grazing land of the Dayara alpine pasture from the Papad Gad and Swari Gad area. Thereafter, 10 dominant palatable species covering ~ 33% of the total dry weight of the palatable and unpalatable species were considered for forage production calculation. Peak biomass was calculated by summing up the peak biomass of each individual to get the forage yield (Eq. 2). Finally, standard dry forage yield and proper rangeland carrying capacity was calculated by using Eqs. (3) and (4)43 as follows.$${text{Density }} = frac{{text{Total number of individuals of a species in all quadrates}}}{{text{Total number of quadrates laid}}}$$
    (1)
    $$Y = Y{text{p}} times A$$
    (2)
    where, Y = forage yield in a certain area (kg), Yp i = forage yield per unit area (kg/km2), A = land area of rangeland (km2) (i.e., total grazing area of the Dayara occupies 3.235 km2).$$F = mathop sum limits_{i = 1}^{n} Y_{{text{i}}} times {text{ U}}_{{text{i}}} times {text{ C}}_{{text{i}}}$$
    (3)
    where F = yield of standard dry forage (kg), Yi = forage yield (kg), Ui = utilizable rate (%), Ci = conversion coefficient.Utilization rate 50% and conversion coefficient 1 for meadow was considered for current work43 .$$Cc = frac{{text{F}}}{{{text{I}} times {text{D}}}}$$
    (4)
    where, Cc = proper livestock numbers that meadow can bear, F = yield of standard dry forage (kg), I = daily intake for an animal unit (7.5 kg/day, Table 7)*, D = Grazing days (May to September, 153 days).Table 7 Animal unit and forage requirement.Full size table*One animal consumes 3% of its body weight as dry forage44. Animal unit conversion was done after Rawat (2020)45.Tourists’ Carrying Capacity (TCC)The general formula of carrying capacity assessment for protected areas was first proposed by Cifuentes (1992), which was further applied in different fields46. The approach is to establish the capacity of an area for maximum visits based on existing physical, biological, and management conditions through the physical carrying capacity (PCC), and real carrying capacity (RCC). TCC is divided into the following levels:Physical Carrying Capacity (PCC)The PCC is the maximum number of tourists that can physically accommodate into or onto a specific area, over a particular time. The PCC (Eq. 5) may be estimated as follows:$${text{PCC }} = {text{ A}}/{text{Au}} times {text{ Rf}}$$
    (5)
    where, PCC = physical carrying capacity; A = Available area for tourists use ; 15%-18% area of the total geographical area is considered for the present work according to the expert opinion and URDPFI guidelines for hill towns47.Au = Area required per tourist; in general, it is considered 3 m2. However in the present work, 5 m2 area is considered for one person based on nature of the area is relatively more sensitive to degradation.Rf = Daily open period / average time of visit.Average opening time = 6 h (according to the field survey, tourists like timing for a day visit between 9 AM to 3 PM), time required by one tourist to visit the Dayara bugyal = 3 h.Rf = 6 h/3 h = 2.Real Carrying Capacity (RCC) (Eq. 6)Maximum permissible number of tourists to a specific site could be determined once the Correction factors (CF) becomes possible to derive out of the particular characteristics of the site. CF is applied to the PCC as follows.$${text{RCC }} = {text{ PCC }} times , left( {{text{Cf1}} times {text{ Cf2}} times {text{ Cf3}} times {text{ Cf4}} times cdots {text{Cfn}}} right)$$
    (6)
    where RCC = Real Carrying Capacity, PCC = Physical Carrying Capacity, Cf = Correction factors.Correction factors are calculated using the following formula.$${text{Cfx }} = { 1 }{-}{text{ Lmx }}/{text{ Tmx}}$$where Cfx = Correction factors of variable x, Lmx = Limiting magnitude of variable x, Tmx = Total magnitude of variable x.Tourism is dependent on nature. In the present work, number of days with heavy rain ( > 250 mm per day) and snowfall ( > 8 cm per day) were considered as limiting variables that control tourism for the area. The calculations were done by analyzing the rainfall and snowfall data from 2017 to 2019 considering March to November as rainfall months and December to February as snowfall months. Total numbers of days in the months were considered as total variables (Tmx) and the days with heavy rain/snow fall were considered as limiting variables (Lmx). For example, during 2017 to 2019 total number of days from March to November were 909 days (Tmx) and in 369 heavy rainfall occurred, therefore, Cf1 was 0.59 (1—Lmx/Tmx). Similarly, during this time heavy snowfall occurred for 51 days out of 186 days, and Cf2 was 0.72.Measurement of soil erosion controlEco-friendly bio-degradable coir geo-textile (9000 sq m) purchased from Coir Board of India, locally available pine needle (240 tonne) along with bamboo were roped in, to create a series of check dams and channels to control soil erosion, gully formation and vegetation loss. Prior to commencement, the leveling of uneven surfaces was done before laying the coir geo-textile. The open degraded sites in different patches of the bugyal, the eroded lateral sites of the gullies were then covered with geo-textile to control soil erosion. Total 38 check dams in the Swari Gad area were examined for draining soil holding capacity. After one year of the treatment, total mass of debris stored by each check dams was evaluated using core density method. The core density of bulk soil in each check dam was determined in triplicates, using an iron core of 2.5 cm radius and 30 cm height. The mass of draining soil checked by each check dam was calculated as under48:$${text{Md }} = {text{ V }} times , rho {text{b}}$$where, Md = The mass of debris in each check dam, V = Volume of check dam, ρb = Mean core density of bulk of soil in each check dam.Environmental desirability (E) assessmentIn this part, environmental desirability, the direct ecological outputs of the work were considered under this category, as habitat enhancement is the most crucial component of the activity. The sub-component considered under the category included vegetation structure (vegetation diversity, vegetation cover) and ecological progress (soil chemical properties)20. Vegetation sampling was done by considering 30 randomly placed quadrates of 1 × 1 m inside 9 sample plots of 5-50 m along three different zones of the treated water channel areas using vertical belt transact method49. The zones were: (i) geo-coir treated area, (ii) untreated degraded area, (iii) reference untreated non-degraded area along with both sides of the water channels wherein total vegetation density (Eq. 1) was analysed following the methodology of Misra (1968) and Mueller-Dombois & Ellenberg (1974)50,51.Soil samplingSoil samples (30 cm depth) were collected from the experimental site in triplicates using random sampling method from all the three investigation zones, namely, Untreated undegraded zone (R), Geo-coir Treated Zone (GTZ) and Untreated Degraded Zone (UTZ). Fresh samples were taken from each plot (50 random soil cores per replicate per investigation zones) and were mixed thoroughly as one composite sample for further study. Here, it is to mention that utmost care was taken to collect each replicate as composite soil sample to appropriately represent the investigation zones of varied topography. Hence, total 9 soil samples (3 samples per investigation zones) were collected to determine its physico-chemical characteristics. After collection, the soil samples were preserved in a portable storage box and transported to the lab immediately. After air drying and grinding, it was passed through 2-mm sieve, and selected soil properties viz. soil organic carbon (SOC) (%), soil pH, total nitrogen (N), phosphorus (P), potassium (K) contents (%), and water holding capacity (WHC) (%) were determined.Soil physico-chemical analysisThe SOC content in soil was determined by wet oxidation method using K2Cr2O752. The soil pH was measured with a suspension of soil in water at a 1:2.5 (soil : water) soil-to-solution ratio using a glass electrode. Calibration of the pH meter was done with the help of two buffer solutions of pH 7.0 and 9.253. The WHC of the soil was determined by measuring the ratio of total water in the wet soil to the weight of the air-dried soil using a Keen– Rackzowski box54. Total N was analysed following the micro Kjeldahl method55. Total phosphorous (TP) was determined using the HClO4-H2SO4 method56 and total potassium (TK) was measured by Flame Photometer (NaOH melting)57.Socio-economic feasibility (SE) assessmentTo investigate the opinion of local residents about the restoration initiative, village survey was conducted in two adjacent villages of the Dayara bugyal, Barsu (2232 m) and Raithal (2258 m). Participants had to indicate the degree of the work in above mentioned three scales (M, E and SE). The questionnaire comprising of questions covered perception about the above discussed six categories (Supplementary S10). Total 60 respondents from different households were randomly selected from each village. The sample consisted of villagers as well as administrative staff. The informants were randomly chosen across 3 different age groups, 20–40, 40–60 and  > 60 year58. Economic feasibility was the first class and parameters considered under this category included cost-effectiveness of the material used, economic efficiency, i.e., benefit–cost ratio and economic impact of the generated income. In addition, social acceptability is the next category, where two sub-parameters were considered, procedural equity (inclusivity and participatory) in response to planning and designing and social preference that covers over current practices, access to resources and services. In the fourth category, technical feasibility was considered which included three subcategories. Adoption lag means waiting period required to adopt the response, replicability of the response and technical sophistication associated with response. In sixth category, cultural acceptability was considered to deal with alignment of the work with cultural, spiritual and aesthetic heritage values, beliefs and social norms and use of traditional (indigenous and local) knowledge and practices. In the last category, political feasibility was considered, where existing policy/legislation and governance mechanism (clarity on roles/responsibilities of stakeholders) was analysed. Each restoration response is ranked using a relative effectiveness or performance rating scale of low (L), moderate (M), or high (H). These effectiveness response ratings for each sub-criterion also reflect no (or minimal), some (or moderate) and major (or substantial) improvement, respectively, relative to the initial condition (pre-response).Index score calculationRestoration success index was calculated, by considering three categories, viz., direct management measure (M), environmental desirability (E), and socio-economic feasibility (SE). In the first scoring part, all the 22 individual variables were evaluated for calculation of “variable index”, by assigning index score between 0 and 3, where 0 rated for ‘not satisfactory’ and 3 rated for ‘satisfactory’. For first two categories, i.e., direct management measure (M), environmental desirability (E), and direct field values were considered. The last category, socio-economic feasibility was indexed depending on village questionnaire survey. The second score “category index” was calculated by adding all variable index and divided by number of independent variables within that category. Finally, the “restoration evaluation index” was evaluated by summing all category scores, dividing by the maximum possible score (16) and multiplying by 10059 (Fig. 8). Ecosystem differences between reference, degraded and restored sites category and ecosystem index scores were determined using unpaired one way ANOVA by using categories viz., direct management measure (M) and environmental desirability (E). To estimate the most affected variable between references, degraded and restored sites, discriminant function analysis (DFA) was carried out, using the field values of all measured independent variables under second category.Figure 8Detailed outline of the scoring process applied for restoration evaluation index calculation for the Dayara bugyal.Full size image More

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    High taxonomic resolution surveys and trait-based analyses reveal multiple benthic regimes in North Sulawesi (Indonesia)

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