Matheus Henrique Nunes

Bio: Matheus Henrique Nunes is an academic researcher from University of Helsinki. The author has contributed to research in topics: Canopy & Environmental science. The author has an hindex of 11, co-authored 29 publications receiving 283 citations. Previous affiliations of Matheus Henrique Nunes include University of São Paulo & University of Cambridge.

The major barriers to evidence-informed conservation policy and possible solutions.

Abstract: Conservation policy decisions can suffer from a lack of evidence, hindering effective decision-making. In nature conservation, studies investigating why policy is often not evidence-informed have tended to focus on Western democracies, with relatively small samples. To understand global variation and challenges better, we established a global survey aimed at identifying top barriers and solutions to the use of conservation science in policy. This obtained the views of 758 people in policy, practice, and research positions from 68 countries across six languages. Here we show that, contrary to popular belief, there is agreement between groups about how to incorporate conservation science into policy, and there is thus room for optimism. Barriers related to the low priority of conservation were considered to be important, while mainstreaming conservation was proposed as a key solution. Therefore, priorities should focus on convincing the public of the importance of conservation as an issue, which will then influence policy-makers to adopt pro-environmental long-term policies.

Artificial Intelligence Procedures for Tree Taper Estimation within a Complex Vegetation Mosaic in Brazil

Abstract: Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along the stem and subsequently merchantable volume. Artificial intelligence approaches can be useful techniques in minimizing estimation errors within complex variations of vegetation. We evaluated the performance of Random Forest® regression tree and Artificial Neural Network procedures in modelling stem taper. Diameters and volume outside bark were compared to a traditional taper-based equation across a tropical Brazilian savanna, a seasonal semi-deciduous forest and a rainforest. Neural network models were found to be more accurate than the traditional taper equation. Random forest showed trends in the residuals from the diameter prediction and provided the least precise and accurate estimations for all forest types. This study provides insights into the superiority of a neural network, which provided advantages regarding the handling of local effects.

Co-producing a Research Agenda for Sustainable Palm Oil

Abstract: The rise of palm oil as the world's most consumed vegetable oil has coincided with exponential growth in palm oil research activity. Bibliometric analysis of research outputs reveals a distinct imbalance in the type of research being undertaken, notably a disproportionate focus on biofuel and engineering topics. Recognizing the expansion of oil palm agriculture across the tropics and the increasing awareness of environmental, social, and economic impacts, we seek to reorientate the existing research agenda toward one that addresses the most fundamental and urgent questions defined by the palm oil stakeholder community. Following consultation with 659 stakeholders from 38 countries, including palm oil growers, government agencies, non-governmental organizations, and researchers, the highest priority research questions were identified within 13 themes. The resulting 279 questions, including 26 ranked as top priority, reveal a diversity of environmental and social research challenges facing the industry, ranging from the ecological and ecosystem impacts of production, to the livelihoods of plantation workers and smallholder communities. Analysis of the knowledge type produced from these questions underscores a clear need for fundamental science programmes, and studies that involve the consultation of non-academic stakeholders to develop “transformative” solutions to the oil palm sector. Stakeholders were most aligned in their choice of priority questions across the themes of policy and certification related themes, and differed the most in environmental feedback, technology and smallholder related themes. Our recommendations include improved regional academic leadership and coordination, greater engagement with private and public stakeholders in Africa, and Central and South America, and enhanced collaborative efforts with researchers in the major consuming countries of India and China.

The giant trees of the Amazon basin

Abstract: © The Ecological Society of America Front Ecol Environ doi:10.1002/fee.2085 Our analysis of 594 airborne laser transects (375 ha each; WebFigure 1) obtained from airborne laser scanning (ALS) surveys conducted within the Amazon basin led to the discovery of a tree with a height of 88.5 m (Figure 1). It is surrounded by seven other trees taller than 80 m and many more above 75 m (WebFigure 2). The tree is located in a remote region, between Pará and Amapá states, at a straightline distance of 360 km from the Atlantic Ocean, 280 km from the Amazon River delta, and 220 km from the closest city; it lies approximately 220 m above sea level (WebFigure 3). Additional details about the ALS surveys and data processing are provided in WebPanel 1. The region is accessible only via military helicopters or in small boats up the Jari River, a rapidly flowing watercourse containing numerous waterfalls and carnivorous fish that make navigation dangerous and slow. The tallest extant trees on Earth, greater than 90 m, are located in North America, Southeast Asia, and Australia, in regions with average annual temperatures of 7.0°– 15.4°C in temperate forests, and 22°–29°C neighbors (Cramer 2011). Besides physiological and environmental constraints, disturbances such as windstorms, fires, pests, pathogens, and (increasingly) chain saws threaten the continued existence of giant trees. Tall trees are susceptible to uprooting and breakage by wind because they are more exposed and so experience higher wind load (Laurance et al. 2000). Large trees are particularly important as a source of inspiration to the general public, often playing a key role in campaigns to conserve forests. Furthermore, their dynamics are important for the maintenance of plant and animal diversity (Lindenmayer and Laurance 2016), and they contribute disproportionately to biomass and productivity (Lutz et al. 2018). Given that Amazonia represents the world’s largest tropical forest, covering 5.3 million km (Ter Steege et al. 2013) and contributing 17% of the terrestrial vegetation carbon stock (Feldpausch et al. 2012), the discovery of giant trees improves our understanding of their effects on global carbon dynamics and on biodiversity. Rose F. 1992. Temperate forest management: its effects on bryophytes and lichen florals and habitats. In: Bates JW and Farmer AM (Eds). Bryophytes and lichens in a changing environment. Oxford, UK: Clarendon Press. Sillett SC, McCune B, Peck JE, et al. 2000. Dispersal limitations of epiphytic lichens result in species dependent on oldgrowth forests. Ecol Appl 10: 789–99. Tibell L. 1992. Crustose lichens as indicators of forest continuity in boreal coniferous forests. Nord J Bot 12: 427–50. Verheyen K, Honnay O, Motzkin G, et al. 2003. Response of forest plant species to landuse change: a lifehistory traitbased approach. J Ecol 91: 563–77.

Recovery of logged forest fragments in a human-modified tropical landscape during the 2015-16 El Niño

Abstract: The past 40 years in Southeast Asia have seen about 50% of lowland rainforests converted to oil palm and other plantations, and much of the remaining forest heavily logged. Little is known about how fragmentation influences recovery and whether climate change will hamper restoration. Here, we use repeat airborne LiDAR surveys spanning the hot and dry 2015-16 El Nino Southern Oscillation event to measure canopy height growth across 3,300 ha of regenerating tropical forests spanning a logging intensity gradient in Malaysian Borneo. We show that the drought led to increased leaf shedding and branch fall. Short forest, regenerating after heavy logging, continued to grow despite higher evaporative demand, except when it was located close to oil palm plantations. Edge effects from the plantations extended over 300 metres into the forests. Forest growth on hilltops and slopes was particularly impacted by the combination of fragmentation and drought, but even riparian forests located within 40 m of oil palm plantations lost canopy height during the drought. Our results suggest that small patches of logged forest within plantation landscapes will be slow to recover, particularly as ENSO events are becoming more frequent. It is unclear whether tropical forest fragments within plantation landscapes are resilient to drought. Here the authors analyse LiDAR and ground-based data from the 2015-16 El Nino event across a logging intensity gradient in Borneo. Although regenerating forests continued to grow, canopy height near oil palm plantations decreased, and a strong edge effect extended up to at least 300 m away.

Exploring New Multi-Instrument Approaches To Observing Terrestrial Ecosystems And The Carbon Cycle From Space

Abstract: Terrestrial ecosystem and carbon cycle feedbacks will significantly impact future climate, but their responses are highly uncertain. Models and tipping point analyses suggest the tropics and arctic/boreal zone carbon-climate feedbacks could be disproportionately large. In situ observations in those regions are sparse, resulting in high uncertainties in carbon fluxes and fluxes. Key parameters controlling ecosystem carbon responses, such as plant traits, are also sparsely observed in the tropics, with the most diverse biome on the planet treated as a single type in models. We analyzed the spatial distribution of in situ data for carbon fluxes, stocks and plant traits globally and also evaluated the potential of remote sensing to observe these quantities. New satellite data products go beyond indices of greenness and can address spatial sampling gaps for specific ecosystem properties and parameters. Because environmental conditions and access limit in situ observations in tropical and arctic/boreal environments, use of space-based techniques can reduce sampling bias and uncertainty about tipping point feedbacks to climate. To reliably detect change and develop the understanding of ecosystems needed for prediction, significantly, more data are required in critical regions. This need can best be met with a strategic combination of remote and in situ data, with satellite observations providing the dense sampling in space and time required to characterize the heterogeneity of ecosystem structure and function.

Revisiting the Holy Grail: Using plant functional traits to understand ecological processes

Abstract: One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding and predicting ecological processes from species' traits has been considered a ‘Holy Grail’ in ecology. Plant functional traits are increasingly being used to develop mechanistic models that can predict how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world; however, significant challenges remain. In this review, we highlight recent work and outstanding questions in three areas: - (i) selecting relevant traits; - (ii) describing intraspecific trait variation and incorporating this variation into models, and; - (iii) scaling trait data to community- and ecosystem-level processes. Over the past decade, there have been significant advances in the characterization of plant strategies based on traits and trait relationships, and the integration of traits into multivariate indices and models of community and ecosystem function. However, the utility of trait-based approaches in ecology will benefit from efforts that demonstrate how these traits and indices influence organismal, community, and ecosystem processes across vegetation types, which may be achieved through meta-analysis and enhancement of trait databases. Additionally, intraspecific trait variation and species interactions need to be incorporated into predictive models using tools such as Bayesian hierarchical modelling. Finally, existing models linking traits to community and ecosystem processes need to be empirically tested for their applicability to be realized.

Meta-analysis Reveals that Hydraulic Traits Explain Cross-Species Patterns of Drought-Induced Tree Mortality across the Globe

Abstract: Significance Predicting the impacts of climate extremes on plant communities is a central challenge in ecology. Physiological traits may improve prediction of drought impacts on forests globally. We perform a meta-analysis across 33 studies that span all forested biomes and find that, among the examined traits, hydraulic traits explain cross-species patterns in mortality from drought. Gymnosperm and angiosperm mortality was associated with different hydraulic traits, giving insight into the relative weights of different traits and mechanisms in mortality prediction. Our results provide a foundation for more mechanistic predictions of drought-induced tree mortality across Earth’s diverse forests. Drought-induced tree mortality has been observed globally and is expected to increase under climate change scenarios, with large potential consequences for the terrestrial carbon sink. Predicting mortality across species is crucial for assessing the effects of climate extremes on forest community biodiversity, composition, and carbon sequestration. However, the physiological traits associated with elevated risk of mortality in diverse ecosystems remain unknown, although these traits could greatly improve understanding and prediction of tree mortality in forests. We performed a meta-analysis on species’ mortality rates across 475 species from 33 studies around the globe to assess which traits determine a species’ mortality risk. We found that species-specific mortality anomalies from community mortality rate in a given drought were associated with plant hydraulic traits. Across all species, mortality was best predicted by a low hydraulic safety margin—the difference between typical minimum xylem water potential and that causing xylem dysfunction—and xylem vulnerability to embolism. Angiosperms and gymnosperms experienced roughly equal mortality risks. Our results provide broad support for the hypothesis that hydraulic traits capture key mechanisms determining tree death and highlight that physiological traits can improve vegetation model prediction of tree mortality during climate extremes.