Feasibility and effectiveness of global intact forest landscape protection through forest certification: the conservation burden of intact forest landscapes

Intact Forest Landscapes (IFLs) are defined as forested areas of at least 500 km2 that show no signs of remotely sensed human activity. They are considered to be of high conservation value due to their role in maintaining biodiversity and mitigating climate change. In 2014, the members of the Forest Stewardship Council (FSC), one of the major global certification schemes for responsible forest management, took a conservation stand by restricting logging in FSC-certified IFLs. However, this move raised concerns about the economic viability of FSC-certified logging in these areas. To address these challenges, in 2022, FSC proposed an integrated landscape approach, considering local conditions and stakeholders’ needs to balance IFL protection, economic sustainability, and community interests. Here, we leverage publicly available management unit (MU) data, to provide a global quantitative overview of IFLs designated for timber production. We use the concept of ‘conservation burden’ for the extent that MUs overlap with IFLs, representing the impact that IFL protection has on forest management operations if logging is disallowed. Our data indicates that currently FSC-certified MUs affect 0.6% of global IFLs. Too restrictive policies for logging in IFLs may discourage FSC-certification in global IFLs. Considering the environmental and social benefits of FSC certification, it warrants careful examination whether the benefits of protecting a limited subset of FSC-certified IFLs outweighs the cost of potentially reduced growth of the total FSC-certified area. Our data can provide a basis to facilitate stakeholder engagement for landscape-level IFL management

Degradação florestal na Amazônia: como ultrapassar os limites conceituais, científicos e técnicos para mudar esse cenário.

Os dez pontos-chave identificados nesse documento enfatizam a importância de reconhecer a degradação florestal como uma ameaça séria à conservação da Floresta Amazônica. O combate aos impactos da degradação merece tanta atenção quanto o desmatamento quando se considera a abrangência espacial dos eventos de queimadas, exploração predatória de madeira e fragmentação das florestas. Ao contrário dos desmatamentos, os efeitos da degradação são mais difíceis de perceber, podem ocorrer de forma lenta e, em longo prazo, terminam por ameaçar a biodiversidade e comprometer serviços ecológicos importantes nas florestas. O combate à degradação florestal requer um esforço coordenado do governo e da sociedade. Os cientistas têm muito a contribuir com o desenvolvimento de metodologias, indicadores, sistemas de classificação e estimativas dos impactos. A integração dos diversos setores é fundamental para implementar medidas sistemáticas de monitoramento, controle e incentivos para impedir a degradação florestal na Amazônia.bitstream/item/132200/1/DOC413.pd

Real‐time alerts from AI‐enabled camera traps using the Iridium satellite network: A case‐study in Gabon, Central Africa

Efforts to preserve, protect and restore ecosystems are hindered by long delays between data collection and analysis. Threats to ecosystems can go undetected for years or decades as a result. Real-time data can help solve this issue but significant technical barriers exist. For example, automated camera traps are widely used for ecosystem monitoring but it is challenging to transmit images for real-time analysis where there is no reliable cellular or WiFi connectivity. We modified an off-the-shelf camera trap (Bushnell™) and customised existing open-source hardware to create a ‘smart’ camera trap system. Images captured by the camera trap are instantly labelled by an artificial intelligence model and an ‘alert’ containing the image label and other metadata is then delivered to the end-user within minutes over the Iridium satellite network. We present results from testing in the Netherlands, Europe, and from a pilot test in a closed-canopy forest in Gabon, Central Africa. All reference materials required to build the system are provided in open-source repositories. Results show the system can operate for a minimum of 3 months without intervention when capturing a median of 17.23 images per day. The median time-difference between image capture and receiving an alert was 7.35 min, though some outliers showed delays of 5-days or more when the system was incorrectly positioned and unable to connect to the Iridium network. We anticipate significant developments in this field and hope that the solutions presented here, and the lessons learned, can be used to inform future advances. New artificial intelligence models and the addition of other sensors such as microphones will expand the system's potential for other, real-time use cases including real-time biodiversity monitoring, wild resource management and detecting illegal human activities in protected areas

Real‐time alerts from AI‐enabled camera traps using the Iridium satellite network: A case‐study in Gabon, Central Africa

Efforts to preserve, protect and restore ecosystems are hindered by long delays between data collection and analysis. Threats to ecosystems can go undetected for years or decades as a result. Real‐time data can help solve this issue but significant technical barriers exist. For example, automated camera traps are widely used for ecosystem monitoring but it is challenging to transmit images for real‐time analysis where there is no reliable cellular or WiFi connectivity.We modified an off‐the‐shelf camera trap (Bushnell™) and customised existing open‐source hardware to create a ‘smart’ camera trap system. Images captured by the camera trap are instantly labelled by an artificial intelligence model and an ‘alert’ containing the image label and other metadata is then delivered to the end‐user within minutes over the Iridium satellite network. We present results from testing in the Netherlands, Europe, and from a pilot test in a closed‐canopy forest in Gabon, Central Africa. All reference materials required to build the system are provided in open‐source repositories.Results show the system can operate for a minimum of 3 months without intervention when capturing a median of 17.23 images per day. The median time‐difference between image capture and receiving an alert was 7.35 min, though some outliers showed delays of 5‐days or more when the system was incorrectly positioned and unable to connect to the Iridium network.We anticipate significant developments in this field and hope that the solutions presented here, and the lessons learned, can be used to inform future advances. New artificial intelligence models and the addition of other sensors such as microphones will expand the system's potential for other, real‐time use cases including real‐time biodiversity monitoring, wild resource management and detecting illegal human activities in protected areas

Write, draw, show, and tell: a child-centred dual methodology to explore perceptions of out-of-school physical activity

Background Research to increase children’s physical activity and inform intervention design has, to date, largely underrepresented children’s voices. Further, research has been limited to singular qualitative methods that overlook children’s varied linguistic ability and interaction preference. The aim of this study was to use a novel combination of qualitative techniques to explore children’s current views, experiences and perceptions of out-of-school physical activity as well as offering formative opinion about future intervention design. Methods Write, draw, show and tell (WDST) groups were conducted with 35 children aged 10–11 years from 7 primary schools. Data were analysed through a deductive and inductive process, firstly using the Youth Physical Activity Promotion Model as a thematic framework, and then inductively to enable emergent themes to be further explored. Pen profiles were constructed representing key emergent themes. Results The WDST combination of qualitative techniques generated complimentary interconnected data which both confirmed and uncovered new insights into factors relevant to children’s out-of-school physical activity. Physical activity was most frequently associated with organised sports. Fun, enjoyment, competence, and physical activity provision were all important predictors of children’s out-of-school physical activity. Paradoxically, parents served as both significant enablers (i.e. encouragement) and barriers (i.e. restricting participation) to physical activity participation. Some of these key findings would have otherwise remained hidden when compared to more traditional singular methods based approaches. Conclusions Parents are in a unique position to promote health promoting behaviours serving as role models, physical activity gatekeepers and choice architects. Given the strong socialising effect parents have on children’s physical activity, family-based physical activity intervention may offer a promising alternative compared to traditional school-based approaches. Parents' qualitative input is important to supplement children’s voices and inform future family-based intervention design. The WDST method developed here is an inclusive, interactive and child-centred methodology which facilitates the exploration of a wide range of topics and enhances data credibility

Long-term thermal sensitivity of Earth’s tropical forests

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

The pace of life for forest trees

This is the author accepted manuscript. The final version is available from the American Association for the Advancement of Science via the DOI in this record Data availability statement: The plot-level input data and R code that are needed to replicate our analyses are available at https://github/Lalasia/pace_of_life.com and doi.org/10.5281/zenodo.11615767 (56). The tree-by-tree observations used to generate the plot-level input data are also published with this paper. However, this file does not include data from networks with sensitive species or a need for indigenous data sovereignty. These data are available upon request for research purposes by emailing the following networks: Alberta Agriculture and Forestry Division https://www.alberta.ca/permanent-sample-plots-program, email: [email protected], Saskatchewan Minister of Environment Forest Service Branch https://www.saskatchewan.ca/contact-us, ForestGeo https://forestgeo.si.edu/explore-data ((20–22), and ForestPlots https://forestplots.net/en/using-forestplots/in-the-field, email: [email protected] (18, 19).Tree growth and longevity trade-offs fundamentally shape the terrestrial carbon balance. Yet, we lack a unified understanding of how such trade-offs vary across the world's forests. By mapping life history traits for a wide range of species across the Americas, we reveal considerable variation in life expectancies from 10 centimeters in diameter (ranging from 1.3 to 3195 years) and show that the pace of life for trees can be accurately classified into four demographic functional types. We found emergent patterns in the strength of trade-offs between growth and longevity across a temperature gradient. Furthermore, we show that the diversity of life history traits varies predictably across forest biomes, giving rise to a positive relationship between trait diversity and productivity. Our pan-latitudinal assessment provides new insights into the demographic mechanisms that govern the carbon turnover rate across forest biomes.European Union Horizon 2020Royal SocietyNatural Environment Research Council (NERC

Methods for wildlife monitoring in tropical forests: Comparing human observations, camera traps, and passive acoustic sensors

Wildlife monitoring is essential for conservation science and data-driven decision-making. Tropical forests pose a particularly challenging environment for monitoring wildlife due to the dense vegetation, and diverse and cryptic species with relatively low abundances. The most commonly used monitoring methods in tropical forests are observations made by humans (visual or acoustic), camera traps, or passive acoustic sensors. These methods come with trade-offs in terms of species coverage, accuracy and precision of population metrics, available technical expertise, and costs. Yet, there are no reviews that compare the characteristics of these methods in detail. Here, we comprehensively review the advantages and limitations of the three mentioned methods, by asking four key questions that are always important in relation to wildlife monitoring: (1) What are the target species?; (2) Which population metrics are desirable and attainable?; (3) What expertise, tools, and effort are required for species identification?; and (4) Which financial and human resources are required for data collection and processing? Given the diversity of monitoring objectives and circumstances, we do not aim to conclusively prescribe particular methods for all situations. Neither do we claim that any one method is superior to others. Rather, our review aims to support scientists and conservation practitioners in understanding the options and criteria that must be considered in choosing the appropriate method, given the objectives of their wildlife monitoring efforts and resources available. We focus on tropical forests because of their high conservation priority, although the information put forward is also relevant for other biomes