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In Niger, literature from the years 1990–2020 shows a rapid regression in the surface areas of forest, an abundant regeneration of trees in some cultivated areas, and a sharp increase in the consumption of wood energy in cities and the countryside, with this wood increasingly coming from parklands. This study, carried out in 2015–2019 on the outskirts of Niamey, aimed to assess the economic benefits for households of parkland fuelwood production and the ecological state of the parklands. Surveys were carried out among 90 farmers to assess the contribution of fuelwood to their household income. Semi-structured interviews with focus groups were conducted in 3 villages to determine farmers' strategies and practices. The inventory of the trees in the parklands was carried out in 3 villages (5000 ha per village). Most rural households have an income diversification strategy to cope with the vagaries of agricultural production. Among these revenues, the sale of fuelwood occupies on average a small place (4 to 10%). To explain their reduced use of assisted natural regeneration (ANR) for the restoration of parklands, farmers point to the difficulty in exploiting wood pruned from their trees due to conflicts of use with livestock herders, taxes and fines from environmental services agencies. Trees and shrubs in parklands have a low diversity (24 species) and low density (5–8 trees/ha). The low density of young trees indicates that during the past decade, there have been fewer efforts to enrich parklands compared to the 1980s, when ANR projects were first implemented. The 3 parklands studied are in the process of becoming severely degraded because dead old trees are no longer replaced through ANR. The Economic importance of fuelwod in family resources is not a sufficient trigger factor for farmers to restore their parklands but could support village's interest for sustainable management of natural forests. These results should serve to alert public authorities and aid organizations that research and development actions must be launched to reverse this deterioration trend in parklands.

Tropical Secondary Forests (SFs) are vulnerable forest systems growing in areas that have been subject to unsustainable human activities leading to deforestation. SFs account for swathes of tropical forest landscapes that have lost their capacity to provide a high level of goods and services. They are also located in highly dynamic and human-pressured landscapes and are vulnerable to natural and human-induced catastrophic events, such as hurricanes or fires. Without appropriate silvicultural management to increase their economic value and restore their ecological functions, they often become degraded and are sometimes cleared for more short-term economically productive activities. Given the increasing demand for tropical timber in recent decades that will continue in the near future, we suggest that active restoration geared towards wood production is an opportunity for SF conservation. Promoting sustainable wood production -i.e. associated with other environmental services- in these disturbed forest ecosystems is also a way to reduce logging pressure on the remaining intact primary tropical forests, indeed, this may be the most important reason to enhance active restoration aimed at wood production in tropical SFs worldwide. Future research in forest ecology and management should produce experimental evidence of enhanced production of wood and ecosystem services in SFs through appropriate silvicultural experimentations.

Recognizing the potential interactions and synergies between adaptation and mitigation in land-use policies in general and forest policies in particular, research on climate change policy has increasingly focused on integrating both objectives simultaneously (hereafter “interaction model”). However, while support exists for the integration of adaptation and mitigation, very few policies have successfully integrated both objectives in practice (hereafter “separation model”). In addition to the interaction and separation models, we introduce the “adaptation-first model”—an approach to climate policy integration that centers adaptation at the core of forest management, with mitigation as one benefit amongst others—and assess whether it more effectively characterizes the practical realities of forest management than the separation or interaction models. Drawing on a review of policy documents, a survey (n = 48) and interviews (n = 22) with government managers in British Columbia (BC), Canada, we analyze which of the three models have been used for integrating climate objectives into BC’s forest policy and explore views of government managers on the relationships and trade-offs between adaptation and mitigation and which model should be prioritized for their integration into forest management. Our analysis of climate-focused forest policy documents indicates that a possible shift from the separation to the interaction model is taking place in BC. However, our results also indicate that while government managers support the interaction model in principle, they perceive numerous barriers to policy integration that may prevent the shift towards the interaction model to materialize in practice. Because of the fundamental perceived differences in the levels at which adaptation and mitigation intervene in decision-making, government managers in our study were generally more comfortable with the adaptation-first model, which ultimately suggests the need to rethink how we frame climate integration into forest management and policies.

In 2006, the Brazilian Forest Service (SFB) started an ambitious program to establish forest concessions so as to provide a legal framework for long-term sustainable timber production in Amazonian forests. Forest concessions in the Brazilian Amazon currently cover only 1.6 million ha (Mha) but we estimate the area of all potential concessions as 35 Mha. This paper assessed the conditions under which the present and potential concession system can ensure an annual production of 11 Mm3. yr−1 to meet the estimated present timber demand. For this we used the volume dynamics with differential equations model (VDDE) calibrated for the Amazon Basin with a Bayesian framework with data from 3500 ha of forest plots monitored for as long as 30 years after selective logging. Predictions of commercial volume recovery rates vary with location. We tested 27 different scenarios by using combinations of initial proportion of commercial volume, logging intensity and cutting cycle length. These scenarios were then applied to the current area of concessions and to the area of all potential concessions (35 Mha). Under current logging regulations and the current concession area (mean logging intensity of 15–20 m3.ha−1, a harvest cycle of 35 years and an initial commercial timber volume proportion of 20%), timber production can be maintained only for a single cutting cycle (35 years). Only the scenario with a logging intensity of 10 m3ha−1 every 60 years with a 90% initial proportion of commercial timber species can be considered as sustainable. Under this scenario, the maximum annual production with the present concession areas is 159,000 m3 (157–159), or less than 2% of the present annual production of 11 Mm3. When considering all potential concession areas (35 Mha), under current rules, the total annual production is 10 Mm3yr−1 (2–17 Mm3yr−1, 95% credibility interval) but is not maintained after the first logging cycle. Under the most sustainable scenario (see above) and a concession area of 35 Mha, the long-term sustainable annual production of timber reaches only 3.4 Mm3yr−1. Based on these results we argue that the concession system will not be able to supply the timber demand without substantial reforms in natural forest management practices and in the wood industry sector. We argue that alternative sources of timber, including plantations linked with forest restoration initiatives, must be promoted.

HIGHLIGHTSBenishangul-Gumuz Regional State (BGRS) has the highest proportion and area of natural bamboo forests in Ethiopia, mostly lowland bamboo (Oxytenanthera abyssinica).In BGRS, bamboo resources were poorly managed and wasting away.There is a lack of bamboo-focused training among foresters, and local bamboo value chains are under-developed.We characterize the existing bamboo business models, and the state and non-state actors influencing the sustainable management of bamboo resources and bamboo value chains.We identify the support needed by small-scale enterprises, including training in business and bamboo-specific technical skills, access to financing adapted to their capacity and needs, improved infrastructure and market linkages, and land use planning that accounts for the economic and environmental values of bamboo resources.SUMMARYWe document the perceptions, practices and policy options in managing lowland bamboo [Oxytenanthera abyssinica] in Benishangul Gumuz Regional State (BGRS) in Ethiopia, particularly to enable small-scale enterprises (SSE) to become more active in this field. This region hosts the largest extent of natural bamboo forests in Ethiopia. There is a recent push to realize bamboo's economic and environmental potential in Ethiopia, which puts SSEs as crucial actors. There is little or scattered published information on local perceptions and practices surrounding natural bamboo forest management and options for realizing bamboo's potential from a subnational/local perspective in Africa, including in Ethiopia. In 2018, we conducted a literature review, spatial analysis, participatory mapping, and interviewed experts working in governmental and non-governmental organizations and local stakeholders in BGRS. We find some consensus of the environmental importance of bamboo. In contrast, there is some debate at the subnational level about the economic importance of bamboo, leading to decisions favouring other land uses. Bamboo forests in this region suffer neglect, as they are perceived to be ‘owned by no one and used by everyone’ and will continue to be there without management. Lack of market-driven opportunities, bamboo-specific training among foresters, data on economic contributions of bamboo, and regulations or guidelines to support existing laws have prevented effective management of the bamboo resource. There are multiple bamboo management approaches that open economic opportunities for SSEs in the region. There needs to be more clarity on how to secure land use rights over bamboo forests, accessible financing, market linkages, business training, and low-tech/low-cost technologies to encourage the development of bamboo SSEs.

Accurate estimates of commercial volume in tropical forests are key for the implementation of sustainable forest management plans. Because of the lack of local or generic volumetric equations, most forest managers and forestry services are still using traditional expansion factors (i.e., multiplication of the diameter by a given value) to estimate the volume of commercial tree species in the Amazon. Volumetric models were developed through a unique data set of 1,264 fallen trees fully measured in 150 sample plots located across a broad range of forests in Amapá, Brazil. Forest-specific volumetric models were developed and compared with a generic (i.e., across all forests) model and with published equations developed elsewhere in the Amazon. The generic equation performed well in all forest types and allowed precise predictions. The most efficient sampling design to develop volumetric models consists of measuring approximately 50 trees across four different size classes representing the whole population. The form factors (FF) developed locally generated substantial bias but performed better than the traditional FF (0.7). Overall, our results suggest that it is possible to develop accurate generic models to estimate commercial timber volume, and this study can serve as a guideline for forest managers or scientists interested in calibrating volumetric models in a cost-efficient way. Study Implications: This work provides useful information on volumetric modeling methods for Brazilian Amazon tropical forests. Most of the studies in the literature only investigate the classical modeling using regression models considering only boom metrics with or without bark, and, in this way, they provide incomplete and biased total knowledge and estimates for a given population. Therefore, detailed and accurate analyzes are crucial tools for decisionmaking. If the harvesting interventions are carried out without considering the most appropriate method to estimate the total wood stock, there may be damages or even extinction of some species, as has happened with other forest domains in Brazil and in other rainforest regions in the world. In this work, the results clearly show the importance of testing different methodologies and selecting the one best suited for a particular site, as well as carrying out techniques for the sustainable and correct management of the forest. Because the analysis procedures provide only information on how methodologies behave statistically, our results may contribute to a more refined analysis to be applied in the future in similar environments. Currently, the Brazilian forestry sector is looking for alternatives to obtain forest resources within the concept of sustainability. For the Brazilian Amazon tropical forest domain, it is extremely important to achieve a sustainable management of resources through forest management. Most studies in the literature investigate the management of tropical rainforest, whereas there is a lack of scientific information on the transition range for the cerrado. Made available in DSpace on 2020-12-16T09:06:50Z (GMT). No. of bitstreams: 1 CPAF-AP-2020-Accurate-estimation-of-commercial.pdf: 928769 bytes, checksum: dff30beaa41574825f8df54580bc8d84 (MD5) Previous issue date: 2020

Luedeling and colleagues argue that we have overestimated the restoration capacity in several regions of the world. Our model predicts the expected optimal tree cover from a combination of 10 environmental variables that were selected through a variable selection procedure to avoid overfitting issues. As detailed in table S1 of our supplementary material, these 10 variables include mean annual temperature, temperature of the wettest quarter, annual precipitation, precipitation seasonality, precipitation of the driest quarter, elevation, hillshade, soil organic carbon, sand content, and depth to bedrock. These ecological variables cover average and seasonal variation in climate and variation in topographic and edaphic conditions. As such, we have done everything that is possible to represent all of the conditions raised by Luedeling and colleagues. Of course, cold and dry conditions are among the main limitations for tree growth, and that is why we have represented these environmental constraints in our model to ensure that we do not predict that trees can exist in regions that are too cold or dry. As explained in the main text, our rigorous k-fold cross-validation (fig. S4A) revealed that our model could explain about 71% of the variation in tree cover without bias (fig. S3, B and C). This means that our model is unbiased at a global scale, but we do not explain 100% of the potential tree cover variation. It is consequently possible to find places where we overestimate or underestimate the potential tree cover—particularly in areas where uncertainties are high, as shown in fig S6. Delzeit and colleagues claim that we overestimate the area available for tree restoration because the expansion of croplands in upcoming decades will reduce the land available for restoration, and because pasture lands are considered as potential land for restoration in our assessment. We agree that, if we continue to expand agricultural land area, there will be a reduction in the land available for restoration. As stated in our analysis, our model estimates the area that is currently available for restoration under present conditions. Of course, any changes in the area of land use will necessarily affect this global total. We exemplified this in our attempts to show how future changes in climate might reduce the area available for restoration. We hope that our analysis can also serve as a stepping stone for future research to evaluate how changes in agricultural land use will affect the potential restoration area. It is true that we included rangelands in the area available for restoration. Of course, much of this land is used for the grazing of animals and so may not be available for complete forest restoration. However, as mentioned in the Report, several studies suggest that it is possible to increase the current tree cover in these areas without limiting food production ([ 1 ][1], [ 2 ][2]), especially when forest cover is relatively low, as is the case for most of the pasture land in our model. Because we removed all urban and agricultural land (i.e., we considered a potential increase of tree cover of 0% in cropland and urban areas), our numbers are likely to underestimate the total area that could currently be covered by trees. Indeed, both croplands and cities constitute great opportunities to increase the current tree cover and to play a major role in mitigating climate change ([ 3 ][3]–[ 5 ][4]). We maintain that our global estimate of the land available for restoration is a conservative one, and we encourage local land owners to use our forest restoration potential map in combination with more detailed local-scale estimates of land use when designing effective restoration strategies. Sheil and colleagues point out that restoring ecosystems might have either positive or negative consequences regarding hydrology. We agree that these effects must be considered as a priority in upcoming research in restoration ecology. 1. [↵][5]1. K.-H. Erb et al ., Nature 553, 73 (2017). [OpenUrl][6] 2. [↵][7]1. K.-H. Erb et al ., Nat. Commun. 7, 11382 (2016). [OpenUrl][8][CrossRef][9][PubMed][10] 3. [↵][11]1. A. Albrecht, 2. S. T. Kandji , Agric. Ecosyst. Environ. 99, 15 (2003). [OpenUrl][12] 4. 1. P. K. Ramachandran Nair, 2. B. Mohan Kumar, 3. V. D. Nair , J. Plant Nutr. Soil Sci. 172, 10 (2009). [OpenUrl][13] 5. [↵][14]1. G. Manoli et al ., Nature 573, 55 (2019). [OpenUrl][15] [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-5 [5]: #xref-ref-1-1 "View reference 1 in text" [6]: {openurl}?query=rft.jtitle%253DNature%26rft.volume%253D553%26rft.spage%253D73%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [7]: #xref-ref-2-1 "View reference 2 in text" [8]: {openurl}?query=rft.jtitle%253DNat.%2BCommun.%26rft.volume%253D7%26rft.spage%253D11382%26rft_id%253Dinfo%253Adoi%252F10.1038%252Fncomms11382%26rft_id%253Dinfo%253Apmid%252F27092437%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [9]: /lookup/external-ref?access_num=10.1038/ncomms11382&link_type=DOI [10]: /lookup/external-ref?access_num=27092437&link_type=MED&atom=%2Fsci%2F366%2F6463%2F317.atom [11]: #xref-ref-3-1 "View reference 3 in text" [12]: {openurl}?query=rft.jtitle%253DAgric.%2BEcosyst.%2BEnviron.%26rft.volume%253D99%26rft.spage%253D15%26rft.atitle%253DCARBON%2BSEQUESTRATION%2BIN%2BTROPICAL%2BAGROFORESTRY%2BSYSTEMS%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [13]: {openurl}?query=rft.jtitle%253DJ.%2BPlant%2BNutr.%2BSoil%2BSci.%26rft.volume%253D172%26rft.spage%253D10%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [14]: #xref-ref-5-1 "View reference 5 in text" [15]: {openurl}?query=rft.jtitle%253DNature%26rft.volume%253D573%26rft.spage%253D55%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx