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While the Chilean Society of Forest Sciences (SOCIFOR) was created by a group of forest-related institutions, its inactivity has wakened its progress. Here, we point out certain shortcomings of SOCIFOR, and propose actions to address them. We suggest increasing the number of members, restructuring its regulatory statutes - modeled on those used by other scientificsocieties-, taking an active role in the organization of the national forest science congress and editing the Chilean journal of forest science (i.e. Bosque). Strengthening SOCIFOR would help to improve the standing of forest sciences in the country. Our proposal is ambitious, though doable, if the keys come together to achieve a common goal: strengthening forest sciences in Chile.

Forest restoration is most efficient if it can take advantage of facilitative interactions between established vegetation and planted trees. However, positive and negative interactions have been identified in a number of plant communities. After centuries of anthropogenic fires, forest recovery has been extremely slow in southern bog forests previously dominated by the slow‐growing and vulnerable conifer Pilgerodendron uviferum on Chiloe Island, Chile. Today, the landscape is dominated by secondary shrublands with scattered patches of Sphagnum moss and limited natural tree regeneration. We hypothesized that the retention of secondary shrubs facilitates the early performance of P. uviferum restoration plantings by providing better microsite conditions. To test this hypothesis, we compared the response of seedlings planted on sites prepared at two levels of intervention: after shrubs had been removed or where shrubs were retained. Shrub retention showed a nurse‐plant effect on P. uviferum seedlings 4 years after planting, which resulted in reduced physiological stress (measured as Fv/Fm) for seedlings, as well as reduced browsing. Consequently, the seedlings growing in areas with shrub retention had larger height increment and higher vitality than those in areas where shrubs had been removed. Thus, the more open micro‐site conditions created by shrub removal resulted in generally poorer seedling performance, although seedling mortality—which was low overall (approximately 2–4%)—showed no significant difference between the two levels of intervention. These findings have direct implications for the restoration of slow‐growing conifers that can tolerate extreme wet conditions in highly degraded forests.

QUESTIONS: Fire is a key factor influencing Araucaria araucana forests, but the impact of fire severity on the understorey vegetation is not well understood. In this study we seek to answer the following questions: (a) how do initial plant diversity, composition and spatial distribution of the understorey vegetation change in response to different levels of fire severity; and (b) does the abundance of dominant tree species exhibit different patterns across a fire severity gradient shortly after fire? LOCATION: Old‐growth Araucaria araucana–Nothofagus pumilio forests in the Andes of south‐central Chile (38° S, 71° W) burned in 2015. METHODS: We evaluated the post‐fire plant regeneration across a fire severity gradient ranging from unburned forests to areas of high fire severity. One year after fire (in February 2016), we measured woody and herbaceous species richness, abundance, height, origin (native vs exotic species), life forms and the spatial pattern of plant recovery. RESULTS: Plant species richness and abundance were significantly higher within the unburned forest and low fire severity areas one year after fire, compared to areas of high and moderate fire severity. Overall, nearly 50% of the species present in the unburned forest were not found in areas of high severity, including the tree Nothofagus pumilio. Rapid vegetative resprouting of pioneer species such as Chusquea culeou resulted in an aggregated spatial distribution of plants after fire. CONCLUSIONS: Plant diversity and the abundance of Araucaria araucana and Nothofagus pumilio were reduced in areas of high fire severity one year after fire. Exotic species were more abundant within areas of low severity, being likely mediated by cattle browsing. Our research makes clear the potential changes in forest composition and structure if dominant tree species are not capable of recovering after fire. We recommend the exclusion of cattle within fire‐affected areas and planting Nothofagus pumilio in areas of high fire severity.

Background: South America has the largest area of temperate forests in the Southern Hemisphere, which grow in diverse site conditions. The aim of this paper is to review the practices of silviculture applied and recommended for these temperate forests, and to discuss prospects to develop new silvicultural proposals to improve sustainability, adaptation and in-situ conservation of forest ecosystems. Methods: We reviewed the silviculture knowledge in four major forest types: 1) The Nothofagus-dominated forests of south-central Chile; 2) the Angiosperm-dominated evergreen forests; 3) the Nothofagus and Austrocedrus chilensis (D.Don) Pic. Serm. & Bizzarri forests in the Argentinean Northern Patagonia; and 4) the Cool temperate Nothofagus forests and Magellanic rainforests. Results: In Chile, both Nothofagus-dominated and Angiosperm-dominated evergreen forests are diverse in tree species, and mixed-species silviculture with commercially valuable species of variable shade tolerance is most promising. Some secondary forests can reach growth rates as high as 20 m3ha-1yr-1. After thinnings, stands with 35–60% of residual densities have shown the best responses in growth. Even-aged silvicultural methods have shown a rapid reorganization and development of new cohorts, although, where Chusquea species are conspicuous, regeneration establishment requires controlling competing vegetation. Preliminary results also show interesting prospects for single-tree selection cuts in uneven-aged forests. East of the Andes, in Argentina, mixed Nothofagus forests and pure and mixed Nothofagus and A. chilensis forests occur. The shelterwood method has been the most practised and successful in the mixed Nothofagus forests, with abundant regeneration, and good growth rates. For A. chilensis forests, an adaptive management approach is proposed, conditioned by the cypress disease attack (e.g., Phytophthora austrocedri). Conversion of pure A. chilensis to mixed A. chilensis–N. dombeyi forests could increase growth considerably. Finally, in the cool temperate Nothofagus forests and Magellanic rainforests, shared by Chile and Argentina, the regular shelterwood cuts have been the most common silvicultural method, with massive regeneration a decade after the regeneration felling. Since the two major Nothofagus species in these forests regenerate well in gaps, uneven-aged silviculture seems also promising. Conclusions: There is abundant knowledge about the silviculture of these forest types. However, there are opportunities for several silvicultural systems to better contribute to sustainable forest management, reverse forest degradation, and cope with climate change challenges, primarily through developing mixed and single-species productive and carbon-rich forests, with greater adaptive capacity.

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness., Proceedings of the National Academy of Sciences of the United States of America, 119 (6), ISSN:0027-8424, ISSN:1091-6490

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers. The team collaboration and manuscript development are supported by the web-based team science platform: science-i.org, with the project number 202205GFB2. We thank the following initiatives, agencies, teams and individuals for data collection and other technical support: the Global Forest Biodiversity Initiative (GFBI) for establishing the data standards and collaborative framework; United States Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program; University of Alaska Fairbanks; the SODEFOR, Ivory Coast; University Félix Houphouët-Boigny (UFHB, Ivory Coast); the Queensland Herbarium and past Queensland Government Forestry and Natural Resource Management departments and staff for data collection for over seven decades; and the National Forestry Commission of Mexico (CONAFOR). We thank M. Baker (Carbon Tanzania), together with a team of field assistants (Valentine and Lawrence); all persons who made the Third Spanish Forest Inventory possible, especially the main coordinator, J. A. Villanueva (IFN3); the French National Forest Inventory (NFI campaigns (raw data 2005 and following annual surveys, were downloaded by GFBI at https://inventaire-forestier.ign.fr/spip.php?rubrique159; site accessed on 1 January 2015)); the Italian Forest Inventory (NFI campaigns raw data 2005 and following surveys were downloaded by GFBI at https://inventarioforestale.org/; site accessed on 27 April 2019); Swiss National Forest Inventory, Swiss Federal Institute for Forest, Snow and Landscape Research WSL and Federal Office for the Environment FOEN, Switzerland; the Swedish NFI, Department of Forest Resource Management, Swedish University of Agricultural Sciences SLU; the National Research Foundation (NRF) of South Africa (89967 and 109244) and the South African Research Chair Initiative; the Danish National Forestry, Department of Geosciences and Natural Resource Management, UCPH; Coordination for the Improvement of Higher Education Personnel of Brazil (CAPES, grant number 88881.064976/2014-01); R. Ávila and S. van Tuylen, Instituto Nacional de Bosques (INAB), Guatemala, for facilitating Guatemalan data; the National Focal Center for Forest condition monitoring of Serbia (NFC), Institute of Forestry, Belgrade, Serbia; the Thünen Institute of Forest Ecosystems (Germany) for providing National Forest Inventory data; the FAO and the United Nations High Commissioner for Refugees (UNHCR) for undertaking the SAFE (Safe Access to Fuel and Energy) and CBIT-Forest projects; and the Amazon Forest Inventory Network (RAINFOR), the African Tropical Rainforest Observation Network (AfriTRON) and the ForestPlots.net initiative for their contributions from Amazonian and African forests. The Natural Forest plot data collected between January 2009 and March 2014 by the LUCAS programme for the New Zealand Ministry for the Environment are provided by the New Zealand National Vegetation Survey Databank https://nvs.landcareresearch.co.nz/. We thank the International Boreal Forest Research Association (IBFRA); the Forestry Corporation of New South Wales, Australia; the National Forest Directory of the Ministry of Environment and Sustainable Development of the Argentine Republic (MAyDS) for the plot data of the Second National Forest Inventory (INBN2); the National Forestry Authority and Ministry of Water and Environment of Uganda for their National Biomass Survey (NBS) dataset; and the Sabah Biodiversity Council and the staff from Sabah Forest Research Centre. All TEAM data are provided by the Tropical Ecology Assessment and Monitoring (TEAM) Network, a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partially funded by these institutions, the Gordon and Betty Moore Foundation and other donors, with thanks to all current and previous TEAM site manager and other collaborators that helped collect data. We thank the people of the Redidoti, Pierrekondre and Cassipora village who were instrumental in assisting with the collection of data and sharing local knowledge of their forest and the dedicated members of the field crew of Kabo 2012 census. We are also thankful to FAPESC, SFB, FAO and IMA/SC for supporting the IFFSC. This research was supported in part through computational resources provided by Information Technology at Purdue, West Lafayette, Indiana.This work is supported in part by the NASA grant number 12000401 ‘Multi-sensor biodiversity framework developed from bioacoustic and space based sensor platforms’ (J. Liang, B.P.); the USDA National Institute of Food and Agriculture McIntire Stennis projects 1017711 (J. Liang) and 1016676 (M.Z.); the US National Science Foundation Biological Integration Institutes grant NSF‐DBI‐2021898 (P.B.R.); the funding by H2020 VERIFY (contract 776810) and H2020 Resonate (contract 101000574) (G.-J.N.); the TEAM project in Uganda supported by the Moore foundation and Buffett Foundation through Conservation International (CI) and Wildlife Conservation Society (WCS); the Danish Council for Independent Research | Natural Sciences (TREECHANGE, grant 6108- 00078B) and VILLUM FONDEN grant number 16549 (J.-C.S.); the Natural Environment Research Council of the UK (NERC) project NE/T011084/1 awarded to J.A.-G. and NE/S011811/1; ERC Advanced Grant 291585 (‘T-FORCES’) and a Royal Society-Wolfson Research Merit Award (O.L.P.); RAINFOR plots supported by the Gordon and Betty Moore Foundation and the UK Natural Environment Research Council, notably NERC Consortium Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘BIO-RED’ (NE/N012542/1); CIFOR’s Global Comparative Study on REDD+ funded by the Norwegian Agency for Development Cooperation, the Australian Department of Foreign Affairs and Trade, the European Union, the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety and the CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA) and donors to the CGIAR Fund; AfriTRON network plots funded by the local communities and NERC, ERC, European Union, Royal Society and Leverhume Trust; a grant from the Royal Society and the Natural Environment Research Council, UK (S.L.L.); National Science Foundation CIF21 DIBBs: EI: number 1724728 (A.C.C.); National Natural Science Foundation of China (31800374) and Shandong Provincial Natural Science Foundation (ZR2019BC083) (H.L.). UK NERC Independent Research Fellowship (grant code: NE/S01537X/1) (T.J.); a Serra-Húnter Fellowship provided by the Government of Catalonia (Spain) (S.d.-M.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.A.S.); a grant from the Franklinia Foundation (D.A.C.); Russian Science Foundation project number 19-77-300-12 (R.V.); the Takenaka Scholarship Foundation (A.O.A.); the German Research Foundation (DFG), grant number Am 149/16-4 (C.A.); the Romania National Council for Higher Education Funding, CNFIS, project number CNFIS-FDI-2022-0259 (O.B.); Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-05109 and STPGP506284) and the Canadian Foundation for Innovation (36014) (H.Y.H.C.); the project SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797) (E.C.); Consejo de Ciencia y Tecnología del estado de Durango (2019-01-155) (J.J.C.-R.); Science and Engineering Research Board (SERB), New Delhi, Government of India (file number PDF/2015/000447)— ‘Assessing the carbon sequestration potential of different forest types in Central India in response to climate change’ (J.A.D.); Investissement d’avenir grant of the ANR (CEBA: ANR-10-LABEX-0025) (G.D.); National Foundation for Science & Technology Development of Vietnam, 106-NN.06-2013.01 (T.V.D.); Queensland government, Department of Environment and Science (T.J.E.); a Czech Science Foundation Standard grant (19-14620S) (T.M.F.); European Union Seventh Framework Program (FP7/2007– 2013) under grant agreement number 265171 (L. Finer, M. Pollastrini, F. Selvi); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (J.F.); CNPq productivity grant number 311303/2020-0 (A.L.d.G.); DFG grant HE 2719/11-1,2,3; HE 2719/14-1 (A. Hemp); European Union’s Horizon Europe research project OpenEarthMonitor grant number 101059548, CGIAR Fund INIT-32-MItigation and Transformation Initiative for GHG reductions of Agrifood systems RelaTed Emissions (MITIGATE+) (M.H.); General Directorate of the State Forests, Poland (1/07; OR-2717/3/11; OR.271.3.3.2017) and the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (A.M.J.); Czech Science Foundation 18-10781 S (S.J.); Danish of Ministry of Environment, the Danish Environmental Protection Agency, Integrated Forest Monitoring Program—NFI (V.K.J.); State of São Paulo Research Foundation/FAPESP as part of the BIOTA/FAPESP Program Project Functional Gradient-PELD/BIOTA-ECOFOR 2003/12595-7 & 2012/51872-5 (C.A.J.); Danish Council for Independent Research—social sciences—grant DFF 6109– 00296 (G.A.K.); Russian Science Foundation project 21-46-07002 for the plot data collected in the Krasnoyarsk region (V.K.); BOLFOR (D.K.K.); Department of Biotechnology, New Delhi, Government of India (grant number BT/PR7928/ NDB/52/9/2006, dated 29 September 2006) (M.L.K.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (J.N.K.); Korea Forest Service (2018113A00-1820-BB01, 2013069A00-1819-AA03, and 2020185D10- 2022-AA02) and Seoul National University Big Data Institute through the Data Science Research Project 2016 (H.S.K.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.K.); CSIR, New Delhi, government of India (grant number 38(1318)12/EMR-II, dated: 3 April 2012) (S.K.); Department of Biotechnology, New Delhi, government of India (grant number BT/ PR12899/ NDB/39/506/2015 dated 20 June 2017) (A.K.); Coordination for the Improvement of Higher Education Personnel (CAPES) #88887.463733/2019-00 (R.V.L.); National Natural Science Foundation of China (31800374) (H.L.); project of CEPF RAS ‘Methodological approaches to assessing the structural organization and functioning of forest ecosystems’ (AAAA-A18-118052590019-7) funded by the Ministry of Science and Higher Education of Russia (N.V.L.); Leverhulme Trust grant to Andrew Balmford, Simon Lewis and Jon Lovett (A.R.M.); Russian Science Foundation, project 19-77-30015 for European Russia data processing (O.M.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (M.T.E.M.); the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (S.M.); the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund (A. Morera); Queensland government, Department of Environment and Science (V.J.N.); Pinnacle Group Cameroon PLC (L.N.N.); Queensland government, Department of Environment and Science (M.R.N.); the Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-05201) (A.P.); the Russian Foundation for Basic Research, project number 20-05-00540 (E.I.P.); European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 778322 (H.P.); Science and Engineering Research Board, New Delhi, government of India (grant number YSS/2015/000479, dated 12 January 2016) (P.S.); the Chilean Government research grants Fondecyt number 1191816 and FONDEF number ID19 10421 (C.S.-E.); the Deutsche Forschungsgemeinschaft (DFG) Priority Program 1374 Biodiversity Exploratories (P.S.); European Space Agency projects IFBN (4000114425/15/NL/FF/gp) and CCI Biomass (4000123662/18/I-NB) (D. Schepaschenko); FunDivEUROPE, European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement number 265171 (M.S.-L.); APVV 20-0168 from the Slovak Research and Development Agency (V.S.); Manchester Metropolitan University’s Environmental Science Research Centre (G.S.); the project ‘LIFE+ ForBioSensing PL Comprehensive monitoring of stand dynamics in Białowieża Forest supported with remote sensing techniques’ which is co-funded by the EU Life Plus programme (contract number LIFE13 ENV/PL/000048) and the National Fund for Environmental Protection and Water Management in Poland (contract number 485/2014/WN10/OP-NM-LF/D) (K.J.S.); Global Challenges Research Fund (QR allocation, MMU) (M.J.P.S.); Czech Science Foundation project 21-27454S (M.S.); the Russian Foundation for Basic Research, project number 20-05-00540 (N. Tchebakova); Botanical Research Fund, Coalbourn Trust, Bentham Moxon Trust, Emily Holmes scholarship (L.A.T.); the programmes of the current scientific research of the Botanical Garden of the Ural Branch of Russian Academy of Sciences (V.A.U.); FCT—Portuguese Foundation for Science and Technology—Project UIDB/04033/2020. Inventário Florestal Nacional—ICNF (H. Viana); Grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (C.W.); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (B.W.); ATTO project (grant number MCTI-FINEP 1759/10 and BMBF 01LB1001A, 01LK1602F) (F.W.); ReVaTene/ PReSeD-CI 2 is funded by the Education and Research Ministry of Côte d’Ivoire, as part of the Debt Reduction-Development Contracts (C2Ds) managed by IRD (I.C.Z.-B.); the National Research Foundation of South Africa (NRF, grant 89967) (C.H.). The Tropical Plant Exploration Group 70 1 ha plots in Continental Cameroon Mountains are supported by Rufford Small Grant Foundation, UK and 4 ha in Sierra Leone are supported by the Global Challenge Research Fund through Manchester Metropolitan University, UK; the National Geographic Explorer Grant, NGS-53344R-18 (A.C.-S.); University of KwaZulu-Natal Research Office grant (M.J.L.); Universidad Nacional Autónoma de México, Dirección General de Asuntos de Personal Académico, Grant PAPIIT IN-217620 (J.A.M.). Czech Science Foundation project 21-24186M (R.T., S. Delabye). Czech Science Foundation project 20-05840Y, the Czech Ministry of Education, Youth and Sports (LTAUSA19137) and the long-term research development project of the Czech Academy of Sciences no. RVO 67985939 (J.A.). The American Society of Primatologists, the Duke University Graduate School, the L.S.B. Leakey Foundation, the National Science Foundation (grant number 0452995) and the Wenner-Gren Foundation for Anthropological Research (grant number 7330) (M.B.). Research grants from Conselho Nacional de Desenvolvimento Científico e Tecnologico (CNPq, Brazil) (309764/2019; 311303/2020) (A.C.V., A.L.G.). The Project of Sanya Yazhou Bay Science and Technology City (grant number CKJ-JYRC-2022-83) (H.-F.W.). The Ugandan NBS was supported with funds from the Forest Carbon Partnership Facility (FCPF), the Austrian Development Agency (ADC) and FAO. FAO’s UN-REDD Program, together with the project on ‘Native Forests and Community’ Loan BIRF number 8493-AR UNDP ARG/15/004 and the National Program for the Protection of Native Forests under UNDP funded Argentina’s INBN2.

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Rubus ulmifolius is a highly invasive species that negatively affects biodiversity, especially on Robinson Crusoe Island (RCI), one of the two global mini-hotspots of vascular plants. The rust Phragmidium violaceum has been used as a biological control agent for some Rubus species in mainland Chile, New Zealand and Australia. We aim to quantify P. violaceum pathogenicity over R. ulmifolius on RCI, under both field and laboratory conditions, to determine its potential as a biological control. In addition, in order to broaden our knowledge about the pathogenicity of P. violaceum from RCI, it was also tested on a highly susceptible Rubus species: R. cf. constrictus. We sampled four forest sites on RCI, measuring abiotic, micro-site, and vegetation variables that could be related with infection. In the laboratory, we inoculated P. violaceum into R. ulmifolius seedlings from RCI and R. cf. constrictus seedlings from mainland Chile. We found a low infection incidence in the field, where only 62 of 182 plots presented infected individuals. Applying a fitted generalized linear model, we predicted ten times more infection of P. violaceum on R. ulmifolius when located in southern aspect slopes and shallow soils (< 30 cm). In the laboratory we determined that rust from RCI infected R. ulmifolius individuals from the island in low density, and did not infect R. cf. constrictus; this low infection rate reinforces our field results. The low infection on R. cf. constrictus may mean that P. violaceum from RCI could originate from very impoverished genetic material. We recommend testing different rust genetic origins, mainly from the Old World, to increase their genetic diversity.

Environmental Research Letters, 15 (12), ISSN:1748-9326, ISSN:1748-9318

Unique combinations of geographic and environmental conditions make quantifying the importance of factors that influence forest productivity difficult. I aimed to model the height growth of dominant Nothofagus alpina trees in temperate forests of Chile, as a proxy for forest productivity, by building a dynamic model that accounts for topography, habitat type, and climate conditions. Using stem analysis data of 169 dominant trees sampled throughout south-central Chile (35°50' and 41°30' S), I estimated growth model parameters using a nonlinear mixed-effects framework that takes into account the hierarchical structure of the data. Based on the proposed model, I used a system dynamics approach to analyze growth-rates as a function of topographic, habitat type, and climatic variability. I found that the interaction between aspect, slope, and elevation, as well as the effect of habitat type, play an essential role in determining tree height growth-rates of N. alpina. Furthermore, the precipitation in the warmest quarter, precipitation seasonality, and annual mean temperature are critical climatic drivers of forest productivity. Given a forecasted climate condition for the region by 2100, where both precipitation seasonality and mean annual temperature increases by 10% and 1°C, respectively, and precipitation in the warmest quarter decreases by 10 mm, I predict a reduction of 1.4 m in height growth of 100-year-old dominant trees. This study shows that the sensitivity of N. alpina-dominated forests to precipitation and temperature patterns could lead to a reduction of tree height growth rates as a result of climate change, suggesting a decrease in carbon sequestration too. By implementing a system dynamics approach, I provide a new perspective on climate-productivity relationships, bettering the quantitative understanding of forest ecosystem dynamics under climate change. The results highlight that while temperature rising might favour forest growth, the decreasing in both amount and distribution within a year of precipitation can be even more critical to reduce forest productivity.

RESUMEN Prumnopitys andina (lleuque) es una especie de conífera con una distribución restringida en Chile y Argentina. A pesar de su importancia ecológica, los conocimientos sobre la estructura y dinámica de los bosques donde crece P. andina son limitados. El objetivo de este trabajo fue describir la estructura y regeneración de bosques con alta presencia de P. andina. Se muestrearon bosques cercanos a Lonquimay (38°1' S, 71º3' O - 38°3'S, 71°3' O) midiendo árboles, regeneración y flora vascular a través de 24 parcelas. Se encontró que P. andina ocurre predominantemente en el estrato superior (15-18 m) acompañado por Nothofagus obliqua y/o Austrocedrus chilensis, además de Lomatia hirsuta y Maytenus boaria en estratos intermedios (4-8 m). En base a la estructura, se identificaron tres tipos de bosques de P. andina: bosques abiertos, bosques secundarios adultos y bosques puros. Los bosques puros de P. andina o “lleuquerías” alcanzaron áreas basales entre las más grandes reportadas para bosques templados del sur de Sudamérica (230 m2/ha). La regeneración de P. andina osciló entre 1.550 individuos/ha en bosques abiertos y 25.000 individuos/ha en bosques puros. P. andina exhibió una estrategia de regeneración aparentemente continua, y en ausencia de disturbios antrópicos como pastoreo de ganado o tala selectiva, sus poblaciones serían autosuficientes.

In the lowlands of south-central Chile, old-growth forests are scarce, whereas secondary forests are more frequent. The ecosystem services provided by these secondary forests differ from those associated with old-growth forests, reflecting their differences in composition and forest structure. Trees over 200 years-old, basal areas higher than 80 m2, several shade-tolerant trees and large diameters, among other characteristics distinguish old-growth forests. Evaluation of the stage of development of a forest may be useful for classification purposes, and management reports. In this study, we applied an old-growth forest index based on Acker et al., to the lowland forests of south-central Chile. The index considered five variables: density, basal area, basal area of the trees > 80 cm in diameter, basal area of shade-tolerant species and Gini’s coefficient. We employed plots with areas ranging from 900 to 2,500 m2 from four secondary forests (two dominated by Nothofagaceae and two by other evergreen species) and from three old-growth forests (two with emergent Nothofagaceae and one without emergent Nothofagaceae). Results allowed us to suggest that index values larger tan 80 would represent old-growth forests, values between 60 and 80 would be forests in transition, and values lower than 60 forests with a scarce presence of old-growth attributes. According to the type of forest, the proposed index could differ in terms of the variables used in different regions of Chile.

Tree regeneration following even-aged silvicultural methods in the evergreen forest type (EFT) has been scarcely studied in Chile, although this is the largest forest type in a region of highly productive native forests. In 1981/1982 a total of nine 1.44-ha experimental units with old-growth forests of the EFT were subjected to block clearcutting (BCC), strip clearcutting (SCC) and reserve shelterwood cutting (RSC) methods (three replicates in each case) in the Andes range in south-central Chile (41°35′S–72°35′W). The resulting second-growth forest stands following these cuttings were evaluated in terms of composition, density, basal area, mean diameter and height after four and 26 years (432 4 m2 plots in 1986, and 78 100 m2 plots in 2008). Four years after cutting, there were >one million tree seedlings per hectare in more than 10 species. In all experimental units one shade-tolerant species (Amomyrtus luma), one midtolerant species (Eucryphia cordifolia) and two very shade-intolerant species (Embothrium coccineum and Weinmannia trichosperma) comprised between 69 and 74% of the total density. The SCC favored a greater relative dominance of all the more shade-tolerant species, and the BCC treatment was more favorable for pioneer species (in addition to E. coccineum and W. trichosperma also Drimys winteri, Caldcluvia paniculata and Nothofagus nitida). At age 26, the short-lived E. coccineum dominated in all treatments, and its major coexisting species in terms of tree density were the midtolerants D. winteri, Eucryphia cordifolia and N. nitida, and the shade-tolerants Laureliopsis philippiana and A. luma. However, the BCC significantly favored the development of N. nitida and D. winteri (three times more basal area than in the other treatments), which might be explained by increasing soil moisture that occurs in this region following this type of disturbances. While these treatments did not show significant differences in mean diameters and dominant height, the BCC and SCC treatments allowed denser, diverse and well-stocked second-growth forests compared to the RSC method, illustrating the differences between truly even-aged and two-aged silvicultural methods upon these variables. Overall, these forests show a high resilience, rapid reorganization and high productivity following the application of even-aged silvicultural methods.

RESUMEN: Drimys winteri es una especie muy abundante en los bosques naturales de Chile, conformando bosques secundarios de alto rendimiento entre las latitudes 41° y 43° S. La relacion altura-diametro es clave para realizar estimaciones de volumen, biomasa, y para entender caracteristicas autoecologicas de las especies forestales. Sin embargo, esta relacion alometrica ha sido poco investigada para esta especie. El objetivo del presente estudio fue modelar la relacion altura-diametro de D. winteri mediante modelos no-lineales de efectos mixtos. Se empleo una amplia base muestral de arboles entre las provincias de Llanquihue y Chiloe en el sur de Chile. Se analizaron diferentes modelos, y posteriormente se evaluo a que parametro(s) agregar efectos aleatorios. Finalmente, se modelaron dichos efectos en funcion de variables agregadas de rodal (e.g., densidad, area basal). Se propone un modelo que: posee un comportamiento biologicamente consistente; sus parametros son estimados de forma eficiente al considerar la estructura jerarquica de los datos; e incluye el efecto de la competencia (representado por la densidad y diametro del arbol de area basal media) y la calidad del sitio (representado por el incremento medio anual en altura dominante) de los bosques donde estos arboles crecen. Esto implica que la alometria altura-diametro de D. winteri varia dependiendo de la competencia y productividad del sitio donde crece la especie, dos variables fundamentales de considerar en la toma de decisiones silvicolas.

Raul&iacute, (Nothofagus alpina (Poepp. &amp, Endl.)) and Ulmo (Eucryphia cordifolia Cav.) are mid-tolerant tree species in the Coihue-Raul&iacute, Tepa (ca. 0.55 mill ha) and Evergreen (ca. 4.1 mill ha) forest types in south-central Chile, respectively. These species have been selectively logged in old-growth forests especially during the 20th century, Raul&iacute, mostly for its highly valuable timber, and Ulmo for its highly demanded firewood and bark for the tannery industry. Natural regeneration of these species occurs mostly through canopy gaps, but it can be retarded, or even inhibited, when the cover of the understory vegetation becomes unusually dense, such as in high-graded forests. Although underplanting is possible for these species, the knowledge about their growth in forest understories is scarce, and necessary to inform restoration programs. Therefore, we evaluated short-term responses (two years) of underplanted containerized seedlings in root-collar diameter, height, stem volume, and in the slenderness index, as a function of canopy openness (%, continuous variable) and three restoration treatments (categorical variables, plus one control treatment) at two different sites with high-graded old-growth forests for each forest type. By using generalized linear mixed-effects models (GLMMs) we determined that Raul&iacute, was more sensitive to the influence of both canopy openness and restoration treatments, while Ulmo was mostly influenced by canopy openness. Specifically, Raul&iacute, was positively influenced by canopy openness and restoration treatments in all response variables except for the slenderness index. Conversely, Ulmo was influenced by canopy openness in all response variables except the slenderness index, which was influenced by both predictor variables (canopy openness and restoration treatments). Thus, prospects for restoration with these species are discussed, including possible ontogenetic changes in their responses to light that may demand continuous silvicultural operations to recover the productive and functional roles of these species in these forest ecosystems.

Self‐thinning and site maximum carrying capacity are key concepts for understanding and predicting ecosystem dynamics as they represent the outcome of several fundamental ecological processes (e.g., mortality and growth). Relationships are often derived using alternative modeling strategies, depending on the statistical approach, model formulation, and underlying data with unclear implications of these various assumptions. In this analysis, the influence of contrasting modeling strategies for estimating the self‐thinning relationship and maximum carrying capacity in long‐term, permanent plot data (n = 130) from the mixed Nothofagus forests in southern Chile was assessed and compared. Seven contrasting modeling strategies were used including ordinary least squares, quantile, and nonlinear regression that were formulated based on static (no remeasurements) or dynamic data (with remeasurements). Statistically distinct differences among these seven approaches were identified with mean maximum carrying capacity ranging from 1,050 to 1,912 stems/ha depending on the approach. The population‐level static approach based on quantile regression produced an estimate closest to the overall mean with site‐level carrying capacity depending on tree species diversity and climate. Synthesis and applications. Overall, the findings highlight strong variability within and between contrasting methods of determining self‐thinning and site maximum carry capacity, which may influence ecological inferences.

Soil contains a wide variety of microorganisms that are responsible for fundamental ecological processes. However, increased frequency and severity of fires reduce microbial diversity and alter soil nutrient availability, affecting vegetation recovery. By using a large-scale wildfire that burned endangered Araucaria araucana forests in south-central Chile (38°S), we assessed the short-term post-fire response of microorganisms, soil nutrients, and plant recovery. One year after fire, we sampled soils from burned and unburned areas, and measured the number of bacterial and fungal colony forming units, and the microbiological activity of the soil. We also measured soil nutrients (N, P, and K), organic matter content and species richness, abundance and plant diversity after fire. We found a significant increase in microbiological activity in burned soils (BS) compared to unburned soils (UBS), with bacteria and fungi being four and seven times greater in BS than in UBS, respectively. Concentrations of N, P and K were also greater in BS than in UBS. Plant species richness was two times higher in unburned than in burned areas, with a drastic reduction of the dominant tree species Araucaria araucana and Nothofagus pumilio after fire. The changes in soil properties after fire may be related to organic matter mineralization, the contribution of nutrients from ashes, or due to post-fire conditions (e.g., increased soil temperature after canopy removal by fire). Overall, our study shows a positive, short-term response in soil microorganisms abundance and nutrient content, but a rapid initial reduction of plant diversity of the main dominant tree species in these forest ecosystems after a severe fire. Further research is necessary as vegetation results are only preliminary and they can vary in the short-to-medium term. Our study provides insightful clues to delve into more applied research aimed at the post-fire restoration of the endemic, long-lived Araucaria araucana forests.

Background: Invasion by exotic plants worldwide can lead to the loss of native species, particularly on islands with a high proportion of endemic plants, such as Robinson Crusoe Island (RCI).Aims: ...

Binary variables have two possible outcomes: occurrence or non-occurrence of an event (usually with 1 and 0 values, respectively). Binary data are common in ecology, including studies of presence/absence, alive/dead, and change/no-change. Logistic regression analysis has been widely used to model binary response variables. Unbalanced data (i.e., an extremely larger proportion of zeros than ones) are often found across a variety of ecological datasets. Sometimes the data are balanced (i.e., same amount of zeros and ones) before fitting the model, however, the statistical implications of balancing (or not) the data remain unclear. We assessed the statistical effects of balancing data when fitting a logistic regression model by studying both its statistical properties of the estimated parameters and its predictive capabilities. We used a base forest-mortality model as reference, and by using stochastic simulations representing different configurations of 0/1 data in a sample (unbalanced data scenarios), we fitted the logistic regression model by maximum likelihood. For each scenario we computed the bias and variance of the estimated parameters and several prediction indexes. We found that the variability of the estimated parameters is affected, with the balanced-data scenario having the lowest variability, thus, affecting the statistical inference as well. Furthermore, the prediction capabilities of the model are altered by balancing the data, with the balanced-data scenario having the better sensitivity/specificity ratio. Balancing, or not, the data to be used for fitting a logistic regression models may affect the conclusion that can arise from the fitted model and its subsequent applications.

Tree mortality is a critical ecological phenomenon shaping forest ecosystem dynamics, structure, and composition, while its effects are of global relevance due to its relationship with forest conditions and environmental changes. There are several challenges associated with individual-based mortality data, particularly observations with uneven measurement intervals. Here, we develop and examine several common individual-based mortality modelling strategies that simultaneously account for unequal measurement lengths and the hierarchical structure of the data in long-term, permanent plot data from the mixed Nothofagus forests in south-central Chile. These strategies depend on: (a) the functional model form (logit and Gompit), (b) the period length adjustment method (annualized, covariate, and exposure), and (c) the data structure used (traditional or all multiple combinations of the time series). Our findings indicated that the Gompit functional form outperformed the commonly used logit link function. Furthermore, considering the period length as exposure in a generalized linear mixed-effects model offered better goodness-of-fit than the other examined period length adjustments. Using all the possible combinations of the dynamic data did not improve the prediction capabilities of the model variants, but important differences were found in the statistical inferences of the fitted models. Our results highlighted that understanding tree mortality strongly relies on using a suitable modelling strategy that is capable of both capturing and assigning the sources of variation to the corresponding variables, which was best accomplished using a multi-level, binary, and Gompit-exposure modelling framework in this analysis.

Understanding the height growth of trees is a fundamental component for scientific knowledge and management of forest ecosystems. The height of dominant trees at a reference-age, commonly known as the site-index, is the most widely used forest productivity indicator globally. Yet, it has been criticized for its restricted applicability to monospecific and even-aged forests, making it unreliable for natural forests or mixed-species where there is not a single meaningful age. Here, I develop a mathematical perspective for using height growth-rate at a reference-height as a new type of site index. I provide the mathematical basis for the proposed index and illustrate its application by fitting a nonlinear mixed-effects differential equation model to tree height growth data of three Nothofagus species in southern Chile. The proposed index allows us to foresee and analyze growth patterns, not only by representing growth-rates as a function of time but also of size. In doing so, the proposed index makes tree growth and productivity analyses accessible to a broader community of researchers.

Second-growth temperate forests usually have simpler composition and structure than comparable old-growth stands. We evaluated the application of variable density thinning (VDT) as a way to increase old-growth attributes, specifically tree species composition and density in two types of second-growth forests: a mixed evergreen-dominated forest (SE, stem exclusion phase) and a Nothofagus dombeyi-dominated forest (UR, understory reinitiation stage) in southern Chile (40°S Lat.). Six one-ha plots were established in each forest. We applied VDT in three plots in each forest, which included the following sub-treatments: a thinned matrix (M), large and small patches (LP and SP), and large and small reserves (LR and SR). We also established three one-ha plots in an old-growth forest (OG), which served as a reference for overall stand structural variables and the tree regeneration layer. OG had significantly more total regeneration and shade-tolerant regeneration, than the untreated SE and UR. After VDT, canopy openness was significantly greater in SE than in UR within the treated portions of the plots (M, LP and SP). The similarities in stand characteristics between untreated and pre-harvest treated plots in each second-growth forest suggest that harvesting was responsible for the lower densities observed in thinned plots. Regeneration patterns two growing seasons after harvests were reflective of the interaction between forest type and sub-treatments. While both second-growth forests showed increases in regeneration densities, none of these increases was significant, although proportionally and numerically they were greater in the SE forest. The sub-treatments showed differences only for shade-intolerant and shade-tolerant species in both forests. These differences in general illustrated a preference of shade-intolerant species for patches (only in the smaller height class in both forests), and of shade-tolerant species for the matrix or the reserves in all height classes from >50 cm through saplings (only in the SE forest). Overall, tree regeneration has been more responsive to VDT in the forest currently in an earlier successional stage, suggesting that second-growth forests in more advanced stages may need to be treated more intensively (larger patches, lower residual densities). Correspondingly, VDT protocols must be developed to account for the interaction between harvest disturbances, developmental stage, and silvics of the component species.

In this analysis, a method for construction of forest canopy three-dimensional (3D) models from terrestrial LiDAR was used for assessing the influence of structural changes on reflectance for an even-aged forest in Belgium. The necessary data were extracted by the developed method, as well as it was registered the adjacent point-clouds, and the canopy elements were classified. Based on a voxelized approach, leaf area index (LAI) and the vertical distribution of leaf area density (LAD) of the forest canopy were derived. Canopy–radiation interactions were simulated in a ray tracing environment, giving suitable illumination properties and optical attributes of the different canopy elements. Canopy structure was modified in terms of LAI and LAD for hyperspectral measurements. It was found that the effect of a 10% increase in LAI on NIR reflectance can be equal to change caused by translating 50% of leaf area from top to lower layers. As presented, changes in structure did affect vegetation indices associated with LAI and chlorophyll content. Overall, the work demonstrated the ability of terrestrial LiDAR for detailed canopy assessments and revealed the high complexity of the relationship between vertical LAD and reflectance. ispartof: SENSORS vol:18 issue:3357 pages:1-11 ispartof: location:Switzerland status: Published online

The landscape in the lowlands of south-central Chile is dominated by agricultural lands and forestry plantations of exotic species. Natural forests are restricted to successional forests, while old-growth forests are nearly absent. The lack of old-growth forests may deprive society from some ecosystem services. Both successional and old forests differ in their ecological functions and in the ecosystem services they can provide. To promote old-growth characteristics in successional forests, it becomes necessary to know which compositional and structural attributes differentiate forests along succession. We aim at identifying the differential attributes among successional and old-growth forests in the lowlands in the northern portion of the Valdivian Rainforests. We analyzed 19 variables in seven different forests and found statistically significant differences in 13 of them. A subset of these variables illustrated major patterns that differentiate successional stages, of which a few could be more easily controlled through management. The latter include lowering tree densities (from >3000 to 0.7 represents older forests). While successional forest show a rapid recovery, forest managers would need to focus in controlling these attributes to increase their old-growth characteristics.

Mediante un método no destructivo, basado en el empleo del relascopio de espejos, se cubicaron árboles individuales de las especies nativas del bosque relicto del predio Rucamanque (IX Región, Chile). A partir de esta cubicación, se ajustaron ecuaciones estimadoras del volumen. Se agruparon especies mediante un análisis de covarianza, producto del cual se obtuvieron los siguientes cuatro grupos: 1. Laurel (Laurelia sempervirens), Lingue (Persea lingue), Tepa (Laureliopsis philipiana); 2. Ulmo (Eucryphia cordifolia) con DAP £ 60 cm, Olivillo (Aextoxicon punctatum); 3. Roble (Nothofagus obliqua), y 4. Ulmo con DAP > 60 cm, Tineo (Weinmannia trichosperma). La obtención de la mejor ecuación de volumen total para cada uno de los grupos de especies se realizó en las siguientes cuatro etapas: Prueba de violación de supuestos estadísticos, Ranking de modelos de acuerdo a la bondad de ajuste, Ranking de modelos de acuerdo a sus capacidades predictivas, y análisis de las capacidades predictivas dentro de rangos de clases diamétricas. Las ecuaciones seleccionadas presentan errores cuadráticos medios (ECM) entre el 15-24%, lo cual está influenciado principalmente por la amplitud del rango de ajuste y la gran variabilidad natural del volumen en los mayores DAP. Using a non-destructive method based on the Bitterlich mirror relascope, we determined the total volume of individual trees in a relict native forest named Rucamanque, which is located in the IX region of Chile. Based on these estimations, equations relating volume were fitted. The seven species were grouped using a covariance analysis. After this analysis, four groups were chosen: 1. Laurel (Laurelia sempervirens), Lingue (Persea lingue), Tepa (Laureliopsis philipiana); 2. Ulmo (Eucryphia cordifolia) with DBH £ 60 cm, Olivillo (Aextoxicon punctatum); 3. Roble (Nothofagus obliqua), and 4. Ulmo with DBH > 60 cm, Tineo (Weinmannia trichosperma). To obtain the best volume equation for each species group, the following four steps were taken: fulfillment of statistical assumptions, models ranked according to goodness of fit, models ranked according to prediction capabilities and, finally, an analysis of the prediction capabilities of the models within diameter classes. The quadratic mean error (ECM) presented by the selected equations ranged from 15% to 24%, mainly influenced by the amplitude of fit range and the large natural variability of the volume in the larger diameter classes.