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Forests, Volume 7, Issue 3 (March 2016) – 25 articles

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1634 KiB  
Article
The Use of Decision Support Systems in Forest Management: Analysis of FORSYS Country Reports
by Silvana Nobre, Ljusk-Ola Eriksson and Renats Trubins
Forests 2016, 7(3), 72; https://doi.org/10.3390/f7030072 - 21 Mar 2016
Cited by 29 | Viewed by 7752
Abstract
From 2009 to 2013, a group of more than 100 researchers from 26 countries, under a COST-Action project named FORSYS, worked on a review of the use of forest management decision support systems (FMDSS). Guided by a template, local researchers conducted assessments of [...] Read more.
From 2009 to 2013, a group of more than 100 researchers from 26 countries, under a COST-Action project named FORSYS, worked on a review of the use of forest management decision support systems (FMDSS). Guided by a template, local researchers conducted assessments of FMDSS use in their countries; their results were documented in Country Reports. In this study, we have used the Country Reports to construct a summary of FMDSS use. For the purposes of our analysis, we conducted a two-round categorisation of the main themes to describe the most relevant aspects of FMDSS use. The material produced was used to generate quantitative summaries of (i) the types of problem where FMDSS are used, (ii) models and methods used to solve these problems, (iii) knowledge management techniques, and (iv) participatory planning techniques. Beyond this, a qualitative analysis identified and summarised the local researchers’ primary concerns, recorded in the conclusions to the Country Reports; we designated these “lessons learned”. Results from the quantitative analysis suggested that most of the participant countries were making use of latest generation FMDSS. A few did not have practical problems that justified the use of such technology or they were still at the beginning of the process of building models to solve their own forest problems. Full article
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<p>Country Reports Production Process.</p>
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<p>Methodology Description.</p>
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<p>The use of MCDA methods for strategic and tactical problems.</p>
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2859 KiB  
Article
The Urban Environment Can Modify Drought Stress of Small-Leaved Lime (Tilia cordata Mill.) and Black Locust (Robinia pseudoacacia L.)
by Astrid Moser, Thomas Rötzer, Stephan Pauleit and Hans Pretzsch
Forests 2016, 7(3), 71; https://doi.org/10.3390/f7030071 - 17 Mar 2016
Cited by 61 | Viewed by 8907
Abstract
The urban environment characterized by various stresses poses challenges to trees. In particular, water deficits and high temperatures can cause immense drought stress to urban trees, resulting in reduced growth and die-off. Drought-tolerant species are expected to be resilient to these conditions and [...] Read more.
The urban environment characterized by various stresses poses challenges to trees. In particular, water deficits and high temperatures can cause immense drought stress to urban trees, resulting in reduced growth and die-off. Drought-tolerant species are expected to be resilient to these conditions and are therefore advantageous over other, more susceptible species. However, the drought tolerance of urban trees in relation to the specific growth conditions in urban areas remains poorly researched. This study aimed to analyze the annual growth and drought tolerance of two common urban tree species, namely small-leaved lime (Tilia cordata Mill. (T. cordata)) and black locust (Robinia pseudoacacia L. (R. pseudoacacia)), in two cities in southern Germany in relation to their urban growing conditions. Marked growth reductions during drought periods and subsequent fast recovery were found for R. pseudoacacia, whereas T. cordata exhibited continued reduced growth after a drought event, although these results were highly specific to the analyzed city. We further show that individual tree characteristics and environmental conditions significantly influence the growth of urban trees. Canopy openness and other aspects of the surrounding environment (water supply and open surface area of the tree pit), tree size, and tree species significantly affect urban tree growth and can modify the ability of trees to tolerate the drought stress in urban areas. Sustainable tree planting of well adapted tree species to their urban environment ensures healthy trees providing ecosystem services for a high quality of life in cities. Full article
(This article belongs to the Special Issue Urban and Periurban Forest Diversity and Ecosystem Services)
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<p>Climate graphs of München (<b>a</b>) and Würzburg (<b>b</b>) from 1955 to 2014 (data source: DWD [<a href="#B40-forests-07-00071" class="html-bibr">40</a>]). Black dots and line represent the mean annual temperature in °C and the gray bars represent the annual precipitation in mm.</p>
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<p>Ring width index of <span class="html-italic">Robinia pseudoacacia</span> and <span class="html-italic">Tilia cordata</span> in München and Würzburg after double detrending (negative exponential function and 2/3 cubic smoothing spline).</p>
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<p>Boxplots showing the relationships of growth stability with city (<b>a</b>) and species (<b>b</b>). Significances are marked by asterisks.</p>
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<p>Regressions of stability with sensitivity (<b>a</b>) and stability with age (<b>b</b>). Highlighted are the regression lines of trees in München and Würzburg (a, ln(Stability) = 0.18 – 0.53 × ln(Sensitivity) – 0.08 × “City” + ε), and <span class="html-italic">Tilia cordata</span> as well as <span class="html-italic">Robinia pseudoacacia</span> (b, Sensitivity = 1.57 + 0.01 × age + 0.36 × “Species” + ε). For the regression of stability with sensitivity (b), both variables were log transformed.</p>
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<p>Calculated standard precipitation-evapotranspiration index (SPEI) for München (<b>a</b>) from 1955 to 2014 and Würzburg (<b>b</b>) from 1947 to 2014 with a time scale of four months. Blue-colored series represents positive SPEI values (&gt;0) of years with a positive climatic water balance, and red-colored series represents negative SPEI (&lt;0) values of a negative climatic water balance.</p>
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<p>Calculated standard precipitation-evapotranspiration index (SPEI) for München (<b>a</b>) from 1955 to 2014 and Würzburg (<b>b</b>) from 1947 to 2014 with a time scale of four months. Blue-colored series represents positive SPEI values (&gt;0) of years with a positive climatic water balance, and red-colored series represents negative SPEI (&lt;0) values of a negative climatic water balance.</p>
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<p>Drought year analysis (superposed epoch analysis) of the ring width index (RWI) during drought years (0), pre-drought (−5 to −1) and after drought (1−5) for <span class="html-italic">Robinia pseudoacacia</span> (black) and <span class="html-italic">Tilia cordata</span> (gray) in München. Input drought years are 2004, 2003, 1998, 1992, 1982, and 1976 for <span class="html-italic">R. pseudoacacia</span> and 2004, 2003, 1998, 1992, 1982, and 1976 for <span class="html-italic">T. cordata</span>. Marked columns (asterisk) represent a departure that is greater than would have occurred randomly as determined from 1000 bootstrap simulations at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Drought year analysis (superposed epoch analysis) of the ring width index (RWI) during drought years (0), pre-drought (−5 to −1) and after drought (1–5) for <span class="html-italic">Robinia pseudoacacia</span> (black) and <span class="html-italic">Tilia cordata</span> (gray) in Würzburg. Input drought years are 2012, 2003, 1993, 1976, and 1964 for <span class="html-italic">R. pseudoacacia</span> and 2012, 2003, 1976, and 1947 for <span class="html-italic">T. cordata</span>. Marked columns (asterisk) represent a departure that is greater than would have occurred randomly as determined from 1000 bootstrap simulations at <span class="html-italic">p</span> &lt; 0.05.</p>
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2617 KiB  
Article
Geospatial Estimation of above Ground Forest Biomass in the Sierra Madre Occidental in the State of Durango, Mexico
by Pablito M. López-Serrano, Carlos A. López Sánchez, Raúl Solís-Moreno and José J. Corral-Rivas
Forests 2016, 7(3), 70; https://doi.org/10.3390/f7030070 - 15 Mar 2016
Cited by 21 | Viewed by 6389
Abstract
Combined use of new geospatial techniques and non-parametric multivariate statistical methods enables monitoring and quantification of the biomass of large areas of forest ecosystems with acceptable reliability. The main objective of the present study was to estimate the aboveground forest biomass (AGB) in [...] Read more.
Combined use of new geospatial techniques and non-parametric multivariate statistical methods enables monitoring and quantification of the biomass of large areas of forest ecosystems with acceptable reliability. The main objective of the present study was to estimate the aboveground forest biomass (AGB) in the Sierra Madre Occidental (SMO) in the state of Durango, Mexico, using the M5 model tree (M5P) technique and the analysis of medium-resolution satellite-based multi-spectral data, and field data collected from a network of 201 permanent forest growth and soil research sites (SPIFyS). Research plots were installed by systematic sampling throughout the study area in 2011. The digital levels of the images were converted to apparent reflectance (ToA) and surface reflectance (SR). The M5P technique that constructs tree-based piecewise linear models was used. The fitted model with SR and tree abundance by species group as predictive variables (ASG) explained 73% of the observed AGB variance (the root mean squared error (RMSE) = 39.40 Mg·ha−1). The variables that best discriminated the AGB, in order of decreasing importance, were the normalized difference vegetation index (NDVI), tree abundance of other broadleaves species (OB), Band 4 of Landsat 5 TM (Thematic Mapper) satellite and tree abundance of pines (Pinus). The results demonstrate the potential usefulness of the M5P method for estimating AGB based in the surface reflectance values (SR). Full article
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<p>Location of the study area.</p>
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<p>Decision tree obtained using the M5P technique with ToA (upper), SR (middle) and SR with ASG variables (bottom). (Band 1 to 7): of Landsat 5 TM (Thematic Mapper) satellite, (NDVI): normalized difference vegetation index, (OB) tree abundance of other broadleaves species, and (Pinus) tree abundance of pines.</p>
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<p>Graphs showing the distribution of the residuals and of the observed AGB values with ToA (upper), SR (middle) and SR with ASG variables (bottom).</p>
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<p>Spatial distribution of the total AGB in the SMO, state of Durango, Mexico.</p>
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7845 KiB  
Article
Effect of Organic Layer Thickness on Black Spruce Aging Mistakes in Canadian Boreal Forests
by Ahmed Laamrani, Annie DesRochers and Line Blackburn
Forests 2016, 7(3), 69; https://doi.org/10.3390/f7030069 - 15 Mar 2016
Cited by 3 | Viewed by 5314
Abstract
Boreal black spruce (Picea mariana) forests are prone to developing thick organic layers (paludification). Black spruce is adapted to this environment by the continuous development of adventitious roots, masking the root collar and making it difficult to age trees. Ring counts [...] Read more.
Boreal black spruce (Picea mariana) forests are prone to developing thick organic layers (paludification). Black spruce is adapted to this environment by the continuous development of adventitious roots, masking the root collar and making it difficult to age trees. Ring counts above the root collar underestimate age of trees, but the magnitude of age underestimation of trees in relation to organic layer thickness (OLT) is unknown. This age underestimation is required to produce appropriate age-correction tools to be used in land resource management. The goal of this study was to assess aging errors that are done with standard ring counts of trees growing in sites with different degrees of paludification (OLT; 0–25 cm, 26–65 cm, >65 cm). Age of 81 trees sampled at three geographical locations was determined by ring counts at ground level and at 1 m height, and real age of trees was determined by cross-dating growth rings down to the root collar (root/shoot interface). Ring counts at 1 m height underestimated age of trees by a mean of 22 years (range 13–49) and 52 years (range 14–112) in null to low vs. moderately to highly paludified stands, respectively. The percentage of aging-error explained by our linear model was relatively high (R2adj = 0.71) and showed that OLT class and age at 0-m could be used to predict total aging-error while neither DBH nor geographic location could. The resulting model has important implications for forest management to accurately estimate productivity of these forests. Full article
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<p>(<b>A</b>) study area in the Clay Belt region; (<b>B</b>) sampling plots sites along three locations Matagami (<b>green dots</b>), Lebel-sur-Quévillon (<b>yellow dots</b>), and Villebois (<b>red dots</b>) on a black and white Landsat satellite image that covers the investigated area.</p>
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<p>Photographs of the study area and sample processing. At each sampled plot, dominant and co-dominant trees were selected; (<b>A</b>) the main lateral roots that provide most of the structural support were cut off (<b>B</b>,<b>C</b>), pushing down on them, so that the stump gets lifted out of the ground by the weight of the falling stem (<b>D</b>); and cross-sections of the stumps were made at each 2 cm with a Wood-Mizer ™ portable sawmill for cross-dating and retracing the root collar (interface root/stem) (<b>E</b>,<b>F</b>).</p>
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<p>Mean true age (<b>upper graph</b>) and total aging error (<b>lower graph</b>) for the three organic layer thickness classes ((A) ≤ 25 cm; (B) = 26–65 cm; (C) &gt;65 cm). Error bars indicate the standard error of the mean; different letters designate statistically significant (<span class="html-italic">p</span> &lt; 0.05) differences using Tukey tests.</p>
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<p>Relationship between total aging error and organic layer thickness. Blue, red and green dots represent OLT classes A, B, and C, respectively.</p>
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<p>Relationship between true age (root collar age) and ages obtained at 0 m (<b>A</b>) and at 1 m (<b>B</b>) tree height. R-squared values and equations are displayed on each graph.</p>
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<p>Relationship between total aging error and age at 0 m with (<b>a</b>) all sampled trees (<span class="html-italic">n</span> = 81) and (<b>b</b>) only trees with root collar present (<span class="html-italic">n</span> = 51). Blue circle, red square, and black triangle symbols represent data belonging to OLT classes A, B, and C (representing the three paludification classes), respectively.</p>
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1204 KiB  
Communication
Forest Management Challenges for Sustaining Water Resources in the Anthropocene
by Ge Sun and James M. Vose
Forests 2016, 7(3), 68; https://doi.org/10.3390/f7030068 - 15 Mar 2016
Cited by 43 | Viewed by 8134
Abstract
The Earth has entered the Anthropocene epoch that is dominated by humans who demand unprecedented quantities of goods and services from forests. The science of forest hydrology and watershed management generated during the past century provides a basic understanding of relationships among forests [...] Read more.
The Earth has entered the Anthropocene epoch that is dominated by humans who demand unprecedented quantities of goods and services from forests. The science of forest hydrology and watershed management generated during the past century provides a basic understanding of relationships among forests and water and offers management principles that maximize the benefits of forests for people while sustaining watershed ecosystems. However, the rapid pace of changes in climate, disturbance regimes, invasive species, human population growth, and land use expected in the 21st century is likely to create substantial challenges for watershed management that may require new approaches, models, and best management practices. These challenges are likely to be complex and large scale, involving a combination of direct and indirect biophysical watershed responses, as well as socioeconomic impacts and feedbacks. We discuss the complex relationships between forests and water in a rapidly changing environment, examine the trade-offs and conflicts between water and other resources, and propose new management approaches for sustaining water resources in the Anthropocene. Full article
(This article belongs to the Special Issue Forest Management and Water Resources in the Anthropocene)
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<p>Complex interactions among forests, water resources, climate change, and humans in the Anthropocene. The solid lines represent impacts of stressors while the dotted lines represent feedbacks.</p>
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2406 KiB  
Article
Short-Term vs. Long-Term Effects of Understory Removal on Nitrogen and Mobile Carbohydrates in Overstory Trees
by Zhong Du, Xiaohu Cai, Weikai Bao, Huai Chen, Hongli Pan, Xue Wang, Qingxia Zhao, Wanze Zhu, Xingliang Liu, Yong Jiang and Mai-He Li
Forests 2016, 7(3), 67; https://doi.org/10.3390/f7030067 - 14 Mar 2016
Cited by 8 | Viewed by 10175
Abstract
Understory management in forest ecosystems has been applied to improve the wood production for hundreds of years worldwide. The carbon-physiological mechanisms underlying these positive effects of understory management on the growth of overstory trees have received less attention. We studied the non-structural carbohydrate [...] Read more.
Understory management in forest ecosystems has been applied to improve the wood production for hundreds of years worldwide. The carbon-physiological mechanisms underlying these positive effects of understory management on the growth of overstory trees have received less attention. We studied the non-structural carbohydrate (NSC) and total nitrogen (N) concentrations in tissues (needles, stem sapwood, and fine roots) of three tree species (two evergreen and one deciduous species) grown in the presence or absence (understory cut) of understory shrubs in plantations in southwestern China, to test whether understories affect the carbon and nitrogen status in the overstory trees. The concentrations of N, NSC (= soluble sugars + starch) in overstory trees varied significantly with understory treatments during the dry season rather than the wet season. Trees grown without understory shrubs had higher levels of N and NSC compared to trees grown with understories. The present study provides insight to explain the functional mechanisms for understory effects on growth of overstory trees, and indicates that the nitrogen and carbon status in overstory trees may be more strongly negatively affected by understory in stressful conditions rather than in optimal growth conditions. Moreover, the present study provides ecophysiology-based knowledge for dealing with understory vegetation management in forest ecosystems. Full article
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<p>Concentration (% d.m., mean values ± 1 SD, <span class="html-italic">n</span> = 3) of total nitrogen (N), non-structural carbohydrate (NSC) and its components (soluble sugars, starch) in (<b>a</b>) current-year needles, (<b>b</b>) stem sapwood, and (<b>c</b>) fine roots of <span class="html-italic">Cryptomeria fortunei</span> trees grown in the absence (LUR = long-term understory removal, SUR = short-term understory removal) and presence of understory shrubs (CUR = understory intact control) on a gentle W-facing slope, Chongzhou, SW China. Statistical differences were tested using one-way ANOVAs, and followed, if significant, by Tukey’s HSD test. Different letters indicate significant differences at <span class="html-italic">p</span> &lt; 0.05; ns indicates non-significant difference; SW indicates southwest.</p>
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<p>Concentration (% d.m., mean values ± 1 SD, <span class="html-italic">n</span> = 3) of total nitrogen, non-structural carbohydrate (NSC) and its components (soluble sugars, starch) in (<b>a</b>) current-year needles, (<b>b</b>) stem sapwood, and (<b>c</b>) fine roots of <span class="html-italic">Taiwania flousiana</span> trees grown in the absence (LUR = long-term understory removal, SUR = short-term understory removal) and presence of understory shrubs (CUR = understory intact control) on a gentle W-facing slope, Chongzhou, SW China. Statistical differences were tested using one-way ANOVAs, and followed, if significant, by Tukey’s HSD test. Different letters indicate significant differences at <span class="html-italic">p</span> &lt; 0.05; ns indicates non-significant difference; SW indicates southwest.</p>
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<p>Concentration (% d.m., mean values ± 1 SD, <span class="html-italic">n</span> = 3) of total nitrogen, non-structural carbohydrate (NSC) and its components (soluble sugars, starch) in (a) current-year needles, (b) stem sapwood, and (c) fine roots of <span class="html-italic">Metasequoia glyptostroboides</span> trees grown in the absence (LUR = long-term understory removal, SUR = short-term understory removal) and presence of understory shrubs (CUR = understory intact control) on a gentle NW-facing slope, Chongzhou, SW China. Statistical differences were tested using one-way ANOVAs, and followed, if significant, by Tukey’s HSD test. Different letters indicate significant differences at <span class="html-italic">p</span> &lt; 0.05; ns indicates non-significant difference; SW indicates southwest.</p>
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6762 KiB  
Article
Decreasing Deforestation in the Southern Brazilian Amazon—The Role of Administrative Sanctions in Mato Grosso State
by Paulo Queiroz Sousa
Forests 2016, 7(3), 66; https://doi.org/10.3390/f7030066 - 12 Mar 2016
Cited by 13 | Viewed by 10722
Abstract
Forest conservation efforts through regulatory enforcement routinely failed to prevent large scale deforestation in the Brazilian Amazon. However, a turning point occurred in 2005, when a combination of unfavorable economic conditions and an unprecedented coordinated effort between governmental institutions resulted in a gradual [...] Read more.
Forest conservation efforts through regulatory enforcement routinely failed to prevent large scale deforestation in the Brazilian Amazon. However, a turning point occurred in 2005, when a combination of unfavorable economic conditions and an unprecedented coordinated effort between governmental institutions resulted in a gradual slowdown in deforestation. The continuation of this deforestation slowdown in an environment of economic recovery and expansion after 2009 suggests that regulatory enforcement achieved a measure of success not experienced before. In this study, the impact of fines, embargoes on rural private properties, and confiscation of means of production and produce on deforestation in the Southern Amazon state of Mato Grosso was considered through regression and GIS-based analyses. It was found that while all three sanctions were negatively correlated with deforestation, there were important differences in their level of enforcement. Embargoes were effectively implemented and showed high deforestation deterrence effectiveness, but the actual collection of the values of fines issued was extremely low, which casts doubts on their actual effectiveness as a deforestation deterrence mechanism. The results suggest that while sanctions for illegal deforestation have played an important role in the slowdown in deforestation, measures to increase the collection of fines issued are urgently needed. Full article
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<p>Deforestation, cattle and soy beans variation in Mato Grosso (2003–2012). Source: author, based on [<a href="#B11-forests-07-00066" class="html-bibr">11</a>,<a href="#B12-forests-07-00066" class="html-bibr">12</a>,<a href="#B13-forests-07-00066" class="html-bibr">13</a>,<a href="#B14-forests-07-00066" class="html-bibr">14</a>].</p>
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<p>Steps for fine collection in IBAMA. Source: adapted from [<a href="#B32-forests-07-00066" class="html-bibr">32</a>].</p>
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<p>Study area municipalities (See <a href="#app1-forests-07-00066" class="html-app">Appendix 1</a> for the names of municipalities represented by numbers in this and subsequent maps) in Mato Grosso.</p>
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<p>Fines in study area in Mato Grosso.</p>
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<p>Collection of fines issued in the period 2004–2012.</p>
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<p>Hot spot map of embargoed properties with remaining forest.</p>
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<p>Hot spot map of effective embargoes.</p>
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<p>Hot spot map of ineffective embargoes.</p>
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<p>Hot spot analysis of confiscations.</p>
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2520 KiB  
Article
Tree Mortality Undercuts Ability of Tree-Planting Programs to Provide Benefits: Results of a Three-City Study
by Sarah Widney, Burnell C. Fischer and Jess Vogt
Forests 2016, 7(3), 65; https://doi.org/10.3390/f7030065 - 11 Mar 2016
Cited by 43 | Viewed by 10493
Abstract
Trees provide numerous benefits for urban residents, including reduced energy usage, improved air quality, stormwater management, carbon sequestration, and increased property values. Quantifying these benefits can help justify the costs of planting trees. In this paper, we use i-Tree Streets to quantify the [...] Read more.
Trees provide numerous benefits for urban residents, including reduced energy usage, improved air quality, stormwater management, carbon sequestration, and increased property values. Quantifying these benefits can help justify the costs of planting trees. In this paper, we use i-Tree Streets to quantify the benefits of street trees planted by nonprofits in three U.S. cities (Detroit, Michigan; Indianapolis, Indiana, and Philadelphia, Pennsylvania) from 2009 to 2011. We also use both measured and modeled survival and growth rates to “grow” the tree populations 5 and 10 years into the future to project the future benefits of the trees under different survival and growth scenarios. The 4059 re-inventoried trees (2864 of which are living) currently provide almost $40,000 (USD) in estimated annual benefits ($9–$20/tree depending on the city), the majority (75%) of which are increased property values. The trees can be expected to provide increasing annual benefits during the 10 years after planting if the annual survival rate is higher than the 93% annual survival measured during the establishment period. However, our projections show that with continued 93% or lower annual survival, the increase in annual benefits from tree growth will not be able to make up for the loss of benefits as trees die. This means that estimated total annual benefits from a cohort of planted trees will decrease between the 5-year projection and the 10-year projection. The results of this study indicate that without early intervention to ensure survival of planted street trees, tree mortality may be significantly undercutting the ability of tree-planting programs to provide benefits to neighborhood residents. Full article
(This article belongs to the Special Issue Urban and Periurban Forest Diversity and Ecosystem Services)
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<p>Hypothetical benefits and costs over a tree’s lifetime [<a href="#B10-forests-07-00065" class="html-bibr">10</a>]. Used with the permission of the International Society of Arboriculture.</p>
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<p>Estimated total annual benefits, by type, for each city based on 2014 re-inventory data.</p>
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<p>Cumulative survival rates of re-inventoried trees in 5 and 10 years with the three different survival scenarios in the three study cities.</p>
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<p>Average diameter at breast height (DBH) at re-inventory and projected 5 and 10 years into the future with average growth and 40% faster growth for each study city. Error bars represent 95% confidence intervals based on the standard error of the growth rate in each city.</p>
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<p>Estimated total annual benefits of re-inventoried trees in Indianapolis at the time of re-inventory and projected 5 and 10 years into the future.</p>
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<p>Estimated total cumulative benefits of re-inventoried trees in Indianapolis at the time of re-inventory and projected 5 and 10 years into the future.</p>
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<p>Estimated annual benefits per tree in Indianapolis at the time of re-inventory and projected 5 and 10 years into the future with average growth and 40% faster growth.</p>
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<p>Annual benefits per tree by size for a hypothetical sugar maple (<span class="html-italic">Acer saccharum</span>) in the Northeast and Lower Midwest climate zones.</p>
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1976 KiB  
Article
Edge Influence on Diversity of Orchids in Andean Cloud Forests
by Edicson Parra Sánchez, Dolors Armenteras and Javier Retana
Forests 2016, 7(3), 63; https://doi.org/10.3390/f7030063 - 11 Mar 2016
Cited by 22 | Viewed by 6214
Abstract
Cloud forests harbor high levels of orchid diversity. However, due to the high fragmentation of these forests in the Andes, combined with the pressure for new agricultural land, orchid diversity is highly threatened. Despite this worrying scenario, few studies have assessed the effects [...] Read more.
Cloud forests harbor high levels of orchid diversity. However, due to the high fragmentation of these forests in the Andes, combined with the pressure for new agricultural land, orchid diversity is highly threatened. Despite this worrying scenario, few studies have assessed the effects of habitat loss specifically on orchid assemblages in the Andes. The aim of this study was to analyze the edge effect on orchids in cloud forest fragments of varying size. We measured forest structure, neighboring land cover and edge effect on orchid abundance, species richness and beta-diversity, by sampling assemblages along edge-to-interior transects in six different sized Andean (southwest Colombia) forest remnants. We recorded 11,127 stem-individuals of orchids in 141 species. Within the forest, edges sustained equal or more species than interior plots. Our results revealed neither patch metrics nor forest structure showed any significant association to orchid diversity at any scale. Nonetheless, from our observations in composition, the type of neighboring cover, particularly pastures, negatively influences interior species (richness and composition) in larger reserves. This might be due to the fact that some species found in interior plots tend to be confined, with sporadic appearances in regeneration forest and are very scarce or absent in pastures. Species richness differed significantly between matrix types. Our results suggest that (1) orchid diversity shows spatial variability in response to disturbances, but the response is independent from forest structure, patch size and patch geometry; (2) orchid communities are negatively affected by covers, and this pattern is reflected in reduced richness and high species turnover; (3) orchid richness edge effect across a pasture-interior gradient. Two forest management implications can be discerned from our results: (1) management strategies aiming to reduce edge effects may focus on improvement regeneration conditions around pasture lands; and (2) local scale management and conservation activities of natural forests in cloud forests will favor small reserves that harbor high levels of richness. Full article
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<p>Study area in Valle del Cauca state, red dots represent the studied reserves.</p>
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<p>Scheme of the location of the sampling units in the patch, orchid and forest structure sampled method. Upper graph: representation of the distribution of the sampling units in each site. Lower graph: design of orchid inventory (<b>above</b>), and forest structure (<b>below</b>) within a sampling unit.</p>
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<p>Orchid richness, abundance and beta diversity (βSOR) within three sampling units. Whiskers show the standard deviation from the mean.</p>
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<p>The edge effect in richness of Andean orchids varies according to the type of cover of the neighboring matrix. The effect of distance (in meters) from the edge to the interior on richness (<b>above</b>), and abundance (<b>below</b>), with distance from edge plotted out in a linear scale. Black horizontal line represents means, and grey shades illustrate the calculation of edge penetration distance, confidence values of 95%.</p>
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7887 KiB  
Article
Application of Wildfire Risk Assessment Results to Wildfire Response Planning in the Southern Sierra Nevada, California, USA
by Matthew P. Thompson, Phil Bowden, April Brough, Joe H. Scott, Julie Gilbertson-Day, Alan Taylor, Jennifer Anderson and Jessica R. Haas
Forests 2016, 7(3), 64; https://doi.org/10.3390/f7030064 - 10 Mar 2016
Cited by 82 | Viewed by 10157
Abstract
How wildfires are managed is a key determinant of long-term socioecological resiliency and the ability to live with fire. Safe and effective response to fire requires effective pre-fire planning, which is the main focus of this paper. We review general principles of effective [...] Read more.
How wildfires are managed is a key determinant of long-term socioecological resiliency and the ability to live with fire. Safe and effective response to fire requires effective pre-fire planning, which is the main focus of this paper. We review general principles of effective federal fire management planning in the U.S., and introduce a framework for incident response planning consistent with these principles. We contextualize this framework in relation to a wildland fire management continuum based on federal fire management policy in the U.S. The framework leverages recent advancements in spatial wildfire risk assessment—notably the joint concepts of in situ risk and source risk—and integrates assessment results with additional geospatial information to develop and map strategic response zones. We operationalize this framework in a geographic information system (GIS) environment based on landscape attributes relevant to fire operations, and define Potential wildland fire Operational Delineations (PODs) as the spatial unit of analysis for strategic response. Using results from a recent risk assessment performed on several National Forests in the Southern Sierra Nevada area of California, USA, we illustrate how POD-level summaries of risk metrics can reduce uncertainty surrounding potential losses and benefits given large fire occurrence, and lend themselves naturally to design of fire and fuel management strategies. To conclude we identify gaps, limitations, and uncertainties, and prioritize future work to support safe and effective incident response. Full article
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<p>Conceptual Wildland Fire Management Continuum.</p>
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<p>Map of the Southern Sierra Risk Assessment analysis area, including the fire modeling extent and Environmental Impact Statement (EIS) extent.</p>
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<p>Eight fire occurrence areas (FOAs) used in the Southern Sierra Risk Assessment for summarizing historical fire occurrence.</p>
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<p>Map of Remote Automated Weather Station (RAWS) locations used in the Southern Sierra Risk Assessment.</p>
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<p>ERC-G by Julian day for each of the four RAWS locations used in fire modeling.</p>
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<p>Burn probability results for the Southern Sierra Risk Assessment landscape.</p>
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<p>Conditional flame length probabilities (<span class="html-italic">FLPs</span>) for each of the six flame length classes for the Southern Sierra Risk Assessment landscape.</p>
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<p>Geospatial distribution of conditional net value change (cNVC) for all HVRAs in the Southern Sierra Risk Assessment.</p>
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<p>Large-fires simulated as a source of risk as measured by large-fire net value change (<span class="html-italic">NVC<sub>fire</sub></span>).</p>
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<p>POD-level strategic response category assignments.</p>
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16837 KiB  
Article
Estimation of Tree Stem Attributes Using Terrestrial Photogrammetry with a Camera Rig
by Mona Forsman, Niclas Börlin and Johan Holmgren
Forests 2016, 7(3), 61; https://doi.org/10.3390/f7030061 - 8 Mar 2016
Cited by 73 | Viewed by 11699
Abstract
We propose a novel photogrammetric method for field plot inventory, designed for simplicity and time efficiency on-site. A prototype multi-camera rig was used to acquire images from field plot centers in multiple directions. The acquisition time on-site was less than two minutes. From [...] Read more.
We propose a novel photogrammetric method for field plot inventory, designed for simplicity and time efficiency on-site. A prototype multi-camera rig was used to acquire images from field plot centers in multiple directions. The acquisition time on-site was less than two minutes. From each view, a point cloud was generated using a novel, rig-based matching of detected SIFT keypoints. Stems were detected in the merged point cloud, and their positions and diameters were estimated. The method was evaluated on 25 hemi-boreal forest plots of a 10-m radius. Due to difficult lighting conditions and faulty hardware, imagery from only six field plots was processed. The method performed best on three plots with clearly visible stems with a 76% detection rate and 0% commission. Diameters could be estimated for 40% of the stems with an RMSE of 2.8–9.5 cm. The results are comparable to other camera-based methods evaluated in a similar manner. The results are inferior to TLS-based methods. However, our method is easily extended to multiple station image schemas, something that could significantly improve the results while retaining low commission errors and time on-site. Furthermore, with smaller hardware, we believe this could be a useful technique for measuring stem attributes in the forest. Full article
(This article belongs to the Special Issue Forest Ground Observations through Terrestrial Point Clouds)
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Graphical abstract
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<p>The camera rig used in the campaign. Outer height, 49 cm; width, 124 cm. Optical baseline, 113 cm; optical offset, 35 cm. Cameras 1, 3, 5 were Canon 7D with Sigma fixed lenses. Cameras 2, 4 were Canon 40D with Canon zoom lenses, only partially used in the study (the image shows a slightly different configuration).</p>
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<p>The five-camera rig in the field with rain covers, carried with EasyRig 2.5.</p>
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<p>The calibration target used for camera and rig calibration.</p>
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<p>Calibration and image acquisition workflow. The cameras were individually calibrated at the beginning and the end of the campaign. The assembled camera rig was calibrated before and after each forest excursion. The rig calibration serves the dual purpose of not requiring exact camera mounting and guards against disturbance during transportation between and to/from the plots.</p>
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<p>An example view from Cameras 1, 3 and 5; epipolar lines in Camera 3 and 5 for the marked (<b>red</b>) feature point in Camera 1.</p>
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<p>Overview of the data processing pipeline.</p>
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<p>Green points are segmented as ground points, red points as stem points, and black points are neither. The point cloud is cropped at 12 m from the center and contains approximately 30,000 points.</p>
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<p>Seven connected stem segments.</p>
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<p>Upper row: An example of a stem segment before (<b>left</b>) and after (<b>center</b>) verticalization. Verticalized points at a height interval of 1.3 m (<b>breast height</b>) <math display="inline"> <mrow> <mo>±</mo> <mn>0</mn> <mo>.</mo> <mn>4</mn> </mrow> </math> m were cut out and projected to 2D (<b>right</b>). Lower row: A circle was initially fitted to all points by the method of Gander (<b>left</b>) followed by iterative Gauss–Newton (<b>center</b>). If necessary, outliers were removed, and the Gauss–Newton procedure was repeated. The rightmost subfigure shows the result after final outlier removal and with outliers as black points. In this example, the differences between the circle estimates are too small to be seen.</p>
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<p>Relative error in diameter estimation <span class="html-italic">vs</span>. the number of points in the disc used for circle estimation. Red points indicate errors of at least 20% of the tree diameter, and cyan points mark errors less than 20%. For discs with less than 50 points (left of the red vertical line), the occurrence of gross errors is significant.</p>
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<p>Center camera images from field Plot 165 with clearly visible stems. The individual images were acquired from the center of the field plot in a counter-clockwise panorama-style acquisition protocol in steps of approximately 30 degrees.</p>
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<p>Center camera images from field Plot 203. In contrast to field Plot 165, the images contain a lot of twigs and shrubs on the ground, posing a challenge for the photogrammetric collection of stem attributes.</p>
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<p>Results for field Plot 165. The green circles and ID numbers correspond to ground truth data. The circles are plotted to scale. Only trees within 10 m (large black circle) are indicated. Blue stars indicate correctly estimated trees (diameter within 20% of the ground truth). Red crosses indicate incorrectly estimated trees (diameter not within 20% of the ground truth). Black squares indicate detected, but not estimated trees (too few points). The camera rig position is near the center of the plot. Most trees have been detected. About half of the detected trees were also correctly estimated. The invisible trees are all obscured by trees closer to the plot center. Most position errors are below 0.5 m. A systematic shift to the southeast for the detected trees is visible, indicating a slightly off-center rig position.</p>
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<p>Results for field Plot 343. Labeling as in <a href="#forests-07-00061-f013" class="html-fig">Figure 13</a>.</p>
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<p>Error <span class="html-italic">vs.</span> distance to tree for Plots 165, 167 and 343. The errors increase slightly with distance.</p>
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<p>Estimated diameter <span class="html-italic">vs</span>. ground truth on Plots 165, 167 and 343. The red line is the regression line. The black line indicates 1:1.</p>
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4623 KiB  
Review
Managing Forests for Water in the Anthropocene—The Best Kept Secret Services of Forest Ecosystems
by Irena F. Creed, Marian Weber, Francesco Accatino and David P. Kreutzweiser
Forests 2016, 7(3), 60; https://doi.org/10.3390/f7030060 - 8 Mar 2016
Cited by 24 | Viewed by 9306
Abstract
Water and forests are inextricably linked. Pressures on forests from population growth and climate change are increasing risks to forests and their aquatic ecosystem services (AES). There is a need to incorporate AES in forest management but there is considerable uncertainty about how [...] Read more.
Water and forests are inextricably linked. Pressures on forests from population growth and climate change are increasing risks to forests and their aquatic ecosystem services (AES). There is a need to incorporate AES in forest management but there is considerable uncertainty about how to do so. Approaches that manage forest ecosystem services such as fiber, water and carbon sequestration independently ignore the inherent complexities of ecosystem services and their responses to management actions, with the potential for unintended consequences that are difficult to predict. The ISO 31000 Risk Management Standard is a standardized framework to assess risks to forest AES and to prioritize management strategies to manage risks within tolerable ranges. The framework consists of five steps: establishing the management context, identifying, analyzing, evaluating and treating the risks. Challenges to implementing the framework include the need for novel models and indicators to assess forest change and resilience, quantification of linkages between forest practice and AES, and the need for an integrated systems approach to assess cumulative effects and stressors on forest ecosystems and AES. In the face of recent international agreements to protect forests, there are emerging opportunities for international leadership to address these challenges in order to protect both forests and AES. Full article
(This article belongs to the Special Issue Forest Management and Water Resources in the Anthropocene)
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<p>(<b>a</b>) Global forest loss; and (<b>b</b>) biome specific rates of forest loss (modified from [<a href="#B3-forests-07-00060" class="html-bibr">3</a>]). Data for both (<b>a</b>) and (<b>b</b>) from [<a href="#B4-forests-07-00060" class="html-bibr">4</a>].</p>
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<p>International Organization for Standardization (ISO) 31000 Risk Management Framework for the management of forest-ecosystem risk. Modified from [<a href="#B39-forests-07-00060" class="html-bibr">39</a>,<a href="#B40-forests-07-00060" class="html-bibr">40</a>].</p>
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<p>Forest aquatic ecosystem services are part of a socio-ecological system. Modified from [<a href="#B41-forests-07-00060" class="html-bibr">41</a>].</p>
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<p>Forest aquatic ecosystem services affect people long after and far from where forest management decisions are made. The vertical axis shows the time lag in terms of multi-decadal recovery, and scale of impacts ranging from local to national and global. Modified from [<a href="#B44-forests-07-00060" class="html-bibr">44</a>].</p>
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<p>Concepts of thresholds, tipping points and regimes shifts into forest management strategies.</p>
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<p>Quantitative (deductive) <span class="html-italic">versus</span> qualitative (inductive) scenario analyses.</p>
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<p>ISO 31010 Bowtie Analysis Tool to analyze the performance of the management system. <span class="html-italic">Prevention controls</span> act to reduce the effect. <span class="html-italic">Mitigation controls</span> act to decrease the severity of the impacts as a result of the effect. <span class="html-italic">Escalation factors</span> are outside influences (e.g., climate change) that undermine the performance of prevention or mitigation controls. Modified from [<a href="#B77-forests-07-00060" class="html-bibr">77</a>].</p>
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<p>Risk tolerance curve is based on acceptable risks (there is no need to act), tolerable risks (risks can be managed by adaptation), and intolerable risks (risks that cannot be managed with adaptation). Modified from [<a href="#B94-forests-07-00060" class="html-bibr">94</a>] based on [<a href="#B95-forests-07-00060" class="html-bibr">95</a>].</p>
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<p>(<b>A</b>) Risk criteria and (<b>B</b>) risk tolerance matrices to evaluate if a management system should be changed (effects (<b>E</b>) are managed through mitigating (<b>M</b>) or preventative (<b>P</b>) measures). Coloration within the matrices denotes the necessary course of management action (<b>Green</b>: No management measures required; <b>Yellow</b>: Existing management measures adequate; <b>Orange</b>: Existing management measures need enhancement, and <b>Red</b>: Additional management measures needed). Modified from [<a href="#B40-forests-07-00060" class="html-bibr">40</a>,<a href="#B77-forests-07-00060" class="html-bibr">77</a>].</p>
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Article
Assessment of Forest Structure Using Two UAV Techniques: A Comparison of Airborne Laser Scanning and Structure from Motion (SfM) Point Clouds
by Luke Wallace, Arko Lucieer, Zbyněk Malenovský, Darren Turner and Petr Vopěnka
Forests 2016, 7(3), 62; https://doi.org/10.3390/f7030062 - 7 Mar 2016
Cited by 518 | Viewed by 29348
Abstract
This study investigates the potential of unmanned aerial vehicles (UAVs) to measure and monitor structural properties of forests. Two remote sensing techniques, airborne laser scanning (ALS) and structure from motion (SfM) were tested to capture three-dimensional structural information from a small multi-rotor UAV [...] Read more.
This study investigates the potential of unmanned aerial vehicles (UAVs) to measure and monitor structural properties of forests. Two remote sensing techniques, airborne laser scanning (ALS) and structure from motion (SfM) were tested to capture three-dimensional structural information from a small multi-rotor UAV platform. A case study is presented through the analysis of data collected from a 30 × 50 m plot in a dry sclerophyll eucalypt forest with a spatially varying canopy cover. The study provides an insight into the capabilities of both technologies for assessing absolute terrain height, the horizontal and vertical distribution of forest canopy elements, and information related to individual trees. Results indicate that both techniques are capable of providing information that can be used to describe the terrain surface and canopy properties in areas of relatively low canopy closure. However, the SfM photogrammetric technique underperformed ALS in capturing the terrain surface under increasingly denser canopy cover, resulting in point density of less than 1 ground point per m2 and mean difference from ALS terrain surface of 0.12 m. This shortcoming caused errors that were propagated into the estimation of canopy properties, including the individual tree height (root mean square error of 0.92 m for ALS and 1.30 m for SfM). Differences were also seen in the estimates of canopy cover derived from the SfM (50%) and ALS (63%) pointclouds. Although ALS is capable of providing more accurate estimates of the vertical structure of forests across the larger range of canopy densities found in this study, SfM was still found to be an adequate low-cost alternative for surveying of forest stands. Full article
(This article belongs to the Special Issue Forest Ground Observations through Terrestrial Point Clouds)
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<p>The small-UAV platform used to collect both airborne RGB photography and laser scanning data.</p>
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<p>Field-measured crown projections within the study plot (<b>left</b>) and a photo looking into the plot from the South-East corner (<b>right</b>).</p>
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<p>(<b>a</b>) Side-view of a transect through the study plot generated from the point cloud of the ALS system and (<b>b</b>) the same produced using RGB photography and the SfM algorithm.</p>
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<p>(<b>a</b>) Spatial distribution, (<b>b</b>) and (<b>c</b>) transects (indicated in a) extracted across DTM<sub>SfM</sub> and DTM<sub>ALS</sub>, and (<b>d</b>) histogram of the height difference between DTM<sub>SfM</sub> and DTM<sub>ALS</sub>. The black polygons in (<b>a</b>) represent the silhouettes of field-measured horizontal crown projections, and the shaded areas in (<b>b</b>) and (<b>c</b>) represent generated canopy cover.</p>
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<p>The alpha shape canopy cover maps produced from the (<b>a</b>) ALS (orange shaded area) and (<b>b</b>) SfM (blue shaded area) point clouds. The black lines represent the silhouettes of field-measured horizontal crown projections; Direct comparisons of the ALS and SfM techniques in (<b>c</b>) and (<b>d</b>) showing two detailed subsets outlined by red squares in a and b, respectively.</p>
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<p>Above ground height distribution of points (&gt;1.5 m above the ground) in the ALS all returns, ALS first returns only, and SfM point clouds captured within the entire plot boundary.</p>
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<p>Spatial difference in the (<b>a</b>) mean AGH, (<b>b</b>) 60th above ground height percentiles (<b>c</b>) 90th above ground height percentiles as derived from ALS and SfM datasets. The black lines represent the silhouettes of field-measured horizontal crown projections. The white (no data) cells have minimal or no information above a height of 1.3 m.</p>
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<p>(<b>a</b>) ALS determined tree height compared to field-measured tree height; (<b>b</b>) SfM determined tree height compared to field-measured tree height; and (<b>c</b>) ALS height against SfM height. The dashed line represents the 1:1 line and the solid line represents the fitted linear function.</p>
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Article
Variation of Drying Strains between Tangential and Radial Directions in Asian White Birch
by Zongying Fu, Jingyao Zhao, Yeli Yang and Yingchun Cai
Forests 2016, 7(3), 59; https://doi.org/10.3390/f7030059 - 7 Mar 2016
Cited by 14 | Viewed by 5183
Abstract
In this study, wood disks of 30 mm in thickness cut from white birch (Betula platyphylla Suk) logs were dried at a constant temperature (40 °C). The drying strains including practical shrinkage strain, elastic strain, viscoelastic creep strain and mechano-sorptive creep were [...] Read more.
In this study, wood disks of 30 mm in thickness cut from white birch (Betula platyphylla Suk) logs were dried at a constant temperature (40 °C). The drying strains including practical shrinkage strain, elastic strain, viscoelastic creep strain and mechano-sorptive creep were measured both tangentially and radially. The effects of moisture content and radial position on each strain were also discussed qualitatively. Overall, the difference of the practical shrinkage strain between the tangential and radial directions was proportional to the distance from the pith. The tangential elastic strain and viscoelastic creep strain were higher than these strains in a radial direction, and they all decreased with the decrease of moisture content. Additionally, there were opposite mechano-sorptive creep between tangential and radial directions. Full article
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<p>Cutting diagram of moisture content and strain slices. T indicates a tangential measurement; R, radial; L, longitudinal.</p>
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<p>Illustration of the change in moisture content over time in wood disks.</p>
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<p>Variation of the shrinkage ratio in heartwood and sapwood of <span class="html-italic">Betula platyphylla</span> between the tangential and radial directions. T-hw indicates tangential heartwood; R-hw, radial heartwood; T-sw, tangential sapwood; R-sw, radial sapwood.</p>
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<p>Effect of radial position and moisture content on drying strains for tangential and radial directions. (<b>a</b>) Practical shrinkage strain; (<b>b</b>) Elastic strain; (<b>c</b>) Viscoelastic creep strain; (<b>d</b>) Mechano-sorptive creep. T indicates Tangential; R indicates Radial.</p>
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1917 KiB  
Article
Fuel Classes in Conifer Forests of Southwest Sichuan, China, and Their Implications for Fire Susceptibility
by San Wang and Shukui Niu
Forests 2016, 7(3), 52; https://doi.org/10.3390/f7030052 - 7 Mar 2016
Cited by 8 | Viewed by 5252
Abstract
The fuel characteristics that influence the initiation and spread of wildfires were measured in Keteleeria fortune forest (FT1), Pinus yunnanensis forest (FT2), P. yunnanensis and Platycladus orientalis (L.) Franco mixed forest (FT3), P. yunnanensis Franch and K. fortunei (Murr.) Carr mixed forest (FT4), [...] Read more.
The fuel characteristics that influence the initiation and spread of wildfires were measured in Keteleeria fortune forest (FT1), Pinus yunnanensis forest (FT2), P. yunnanensis and Platycladus orientalis (L.) Franco mixed forest (FT3), P. yunnanensis Franch and K. fortunei (Murr.) Carr mixed forest (FT4), Tsuga chinensis forest (FT5), and P. orientalis forest (FT6) in southwest Sichuan Province, China. We compared vertical distributions of four fuel classes (active fuel, fine fuel, medium fuel and thick fuel) in the same vertical strata and in different spatial layers, and analyzed the fire potential (surface fire, passive and active crown fires) of the six forest types (FT). We then classified the six forest types into different groups depending on their wildfire potential. By using the pattern of forest wildfire types that burnt the most number of forests, we identified four fire susceptibility groups. The first two groups had the lowest susceptibility of active crown fires but they differed in the proportion of surface and passive crown fires. The third group was positioned in the middle between types with low and extremely high fire susceptibility; while the fourth group had the highest susceptibility of active crown fires. The results of this study will not only contribute to the prediction of fire behavior, but also will be invaluable for use in forestry management. Full article
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<p>Study area in Sichuan Province, China.</p>
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<p>Observed (bar) and fitted (curve) distributions of surface fuel loading by six forest types.</p>
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<p>A vertical profile of the aboveground canopy bulk density of four fuel classes in six forest types.</p>
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<p>Representation of (A) plots of the six forest types and (B) environmental factor variables on the first two axes of the canonical component analysis. <span class="html-italic">n</span> = 253 plots.</p>
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Article
Calorific Value and Chemical Composition of Five Semi-Arid Mexican Tree Species
by Maginot Ngangyo-Heya, Rahim Foroughbahchk-Pournavab, Artemio Carrillo-Parra, José Guadalupe Rutiaga-Quiñones, Volker Zelinski and Luis Fernando Pintor-Ibarra
Forests 2016, 7(3), 58; https://doi.org/10.3390/f7030058 - 4 Mar 2016
Cited by 27 | Viewed by 7664
Abstract
The current global energy crisis has generated growing interest in looking for alternatives to traditional fossil fuels, presenting lignocellulosic materials as a promising resource for sustainable energy production. In this paper, the calorific values and chemical composition of the trunks, branches, twigs and [...] Read more.
The current global energy crisis has generated growing interest in looking for alternatives to traditional fossil fuels, presenting lignocellulosic materials as a promising resource for sustainable energy production. In this paper, the calorific values and chemical composition of the trunks, branches, twigs and leaves of five timber species of the semi-arid land of Mexico (Helietta parvifolia (Gray) Benth., Ebenopsis ebano (Berl.) Barneby, Acacia berlandieri (Benth.), Havardia pallens (Benth.) Britton & Rose and Acacia wrightii (Benth.)) were determined according to international standards. The results highlighted the calorific value ranges of 17.56 to 18.61 MJ kg−1 in trunks, 17.15 to 18.45 MJ kg−1 in branches, 17.29 to 17.92 MJ kg−1 in twigs, and 17.35to 19.36 MJ kg−1 in leaves. The pH presented an acidic trend (3.95–5.64). The content of mineral elements varied in trunks (1.09%–2.29%), branches (0.86%–2.75%), twigs (4.26%–6.76%) and leaves (5.77%–11.79%), showing the higher proportion in Ca (57.03%–95.53%), followed by K (0.95%–19.21%) and Mg (0.88%–13.47%). The highest amount of extractives was obtained in the methanolic solvent (3.96%–17.03%). The lignin recorded values of 28.78%–35.84% for trunks, 17.14%–31.39% for branches and 20.61%–29.92% for twigs. Lignin showed a moderately strong correlation (r = 0.66) with calorific value, but the best mathematical model was registered with the calorific value depending on the pH and lignin (R2 = 58.86%). Full article
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<p>Calorific value of five planted timber species of the semi-arid land of Mexico, in different biomass components.</p>
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<p>Mineral elements content (%) of five planted timber species of the Mexican semi-arid land in different biomass components (trunks, branches, twigs and leaves).</p>
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<p>Amounts of extractives from five timber species of the semi-arid land of Mexico, in different biomass components (T = trunk, B = branches and M = twigs) with different solvents.</p>
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<p>Linear regressions and error bounds at 95% confidence interval of the calorific value in function of chemical constituents (<b>A</b>: pH, <b>B</b>: Inorganics, <b>C</b>: extractives and <b>D</b>: lignin) of five timber species of the Mexican semi-arid land.</p>
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4445 KiB  
Article
Spatial Variation in Tree Density and Estimated Aboveground Carbon Stocks in Southern Africa
by Lulseged Tamene, Powell Mponela, Gudeta W. Sileshi, Jiehua Chen and Jérôme E. Tondoh
Forests 2016, 7(3), 57; https://doi.org/10.3390/f7030057 - 4 Mar 2016
Cited by 4 | Viewed by 5922
Abstract
Variability in woody plant species, vegetation assemblages and anthropogenic activities derails the efforts to have common approaches for estimating biomass and carbon stocks in Africa. In order to suggest management options, it is important to understand the vegetation dynamics and the major drivers [...] Read more.
Variability in woody plant species, vegetation assemblages and anthropogenic activities derails the efforts to have common approaches for estimating biomass and carbon stocks in Africa. In order to suggest management options, it is important to understand the vegetation dynamics and the major drivers governing the observed conditions. This study uses data from 29 sentinel landscapes (4640 plots) across the southern Africa. We used T-Square distance method to sample trees. Allometric models were used to estimate aboveground tree biomass from which aboveground biomass carbon stock (AGBCS) was derived for each site. Results show average tree density of 502 trees·ha−1 with semi-arid areas having the highest (682 trees·ha−1) and arid regions the lowest (393 trees·ha−1). The overall AGBCS was 56.4 Mg·ha−1. However, significant site to site variability existed across the region. Over 60 fold differences were noted between the lowest AGBCS (2.2 Mg·ha−1) in the Musungwa plains of Zambia and the highest (138.1 Mg·ha−1) in the scrublands of Kenilworth in Zimbabwe. Semi-arid and humid sites had higher carbon stocks than sites in sub-humid and arid regions. Anthropogenic activities also influenced the observed carbon stocks. Repeated measurements would reveal future trends in tree cover and carbon stocks across different systems. Full article
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<p>(<b>a</b>) Location of the sampling sites in Southern Africa and (<b>b</b>) description of areas with respect to miombo, pantoropical and ecozones.</p>
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<p>(<b>a</b>) Location of the sampling sites in Southern Africa and (<b>b</b>) description of areas with respect to miombo, pantoropical and ecozones.</p>
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<p>(<b>a</b>) Hierarchical sampling of plots (individual icons) in 16 clusters within the 10 by 10 km sentinel site (<b>b</b>) sampling subplots layout and (<b>c</b>) the T-square method employed to measure tree attributes for each subplot. NB: subplots c1 and c2 are non-vacant; c3 is vacant; and c1 could have tree 1 but no tree 2 within a 30 m radius (see <a href="#sec2dot3-forests-07-00057" class="html-sec">Section 2.3</a> for details).</p>
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<p>Variation in tree density (in ha<sup>−1</sup>) (<b>top panel</b>); total height (in m) and diameter at breast height (D in cm) (<b>bottom panel</b>) across eco-zones and sites. Vertical bars represent 95% confidence intervals.</p>
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<p>Tree and stand structure in varied land cover and use types (<b>a</b>) Miombo woodland at Massuque in Mozambique; (<b>b</b>) Terminalia woodland in arid zone at Gumare in Botswana; (<b>c</b>) trees on farm (scattered trees in intensively cropped areas at Linthipe in Malawi; (<b>d</b>) burnt and respouting trees with intensively grazed dry grass at Paje in Botswana; (<b>e</b>) intensively cultivated plains and forested hills at Luimbale in Angola; (<b>f</b>) intact mopane woodlands in semi-arid zone at Kenilworth in Zimbabwe; (<b>g</b>) mangroves with salt pans in depressions and trees on raised areas at Inhassunge in Mozambique; and (<b>h</b>) Dauwn palm on edge of Kafue river flood plain at Musungwa in Zambia.</p>
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<p>Tree and stand structure in varied land cover and use types (<b>a</b>) Miombo woodland at Massuque in Mozambique; (<b>b</b>) Terminalia woodland in arid zone at Gumare in Botswana; (<b>c</b>) trees on farm (scattered trees in intensively cropped areas at Linthipe in Malawi; (<b>d</b>) burnt and respouting trees with intensively grazed dry grass at Paje in Botswana; (<b>e</b>) intensively cultivated plains and forested hills at Luimbale in Angola; (<b>f</b>) intact mopane woodlands in semi-arid zone at Kenilworth in Zimbabwe; (<b>g</b>) mangroves with salt pans in depressions and trees on raised areas at Inhassunge in Mozambique; and (<b>h</b>) Dauwn palm on edge of Kafue river flood plain at Musungwa in Zambia.</p>
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1977 KiB  
Review
A Review of the Characteristics of Small-Leaved Lime (Tilia cordata Mill.) and Their Implications for Silviculture in a Changing Climate
by Tanguy De Jaegere, Sebastian Hein and Hugues Claessens
Forests 2016, 7(3), 56; https://doi.org/10.3390/f7030056 - 1 Mar 2016
Cited by 59 | Viewed by 12003
Abstract
Tilia cordata Mill. is a minor European broadleaved species with a wide but scattered distribution. Given its scarcity and low value in the wood market, it has received little attention from researchers and forest managers. This review summarizes the main aspects of T. [...] Read more.
Tilia cordata Mill. is a minor European broadleaved species with a wide but scattered distribution. Given its scarcity and low value in the wood market, it has received little attention from researchers and forest managers. This review summarizes the main aspects of T. cordata ecology and growth. Its main limiting factor is its need for warm summer temperatures to ensure successful seed production. It has a height growth pattern relatively similar to that of Acer pseudoplatanus L., with a slight delay in the early stages. Yield tables report great productivity, especially in eastern Europe. T. cordata used to be a major species in Europe, in contrast to its present distribution, but it is very likely to receive renewed interest in the future. Indeed, with the potential change of competition between species in some regions and the need for important diversification in others, T. cordata may play an important role in forest adaptation to climate change, especially owing to its wide ecological tolerance and its numerous ecosystem services. It is necessary to increase our knowledge about its regeneration and its responses to environmental and silvicultural factors, to establish clear management recommendations. Full article
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<p>(<b>a</b>) Comparison of height growth of <span class="html-italic">T. cordata</span> originating from generative (black, solid) <span class="html-italic">vs.</span> vegetative (blue, dotted) regeneration (Hungary [<a href="#B46-forests-07-00056" class="html-bibr">46</a>]); (<b>b</b>) <span class="html-italic">T. cordata</span> from Lithuania [<a href="#B55-forests-07-00056" class="html-bibr">55</a>]; (<b>c</b>) <span class="html-italic">T. cordata</span> from Poland (black, solid) [<a href="#B47-forests-07-00056" class="html-bibr">47</a>]; Ukraine/Moldavia (blue, solid) [<a href="#B49-forests-07-00056" class="html-bibr">49</a>]; and Russia (red, solid, values not displayed: 140–200 years) [<a href="#B48-forests-07-00056" class="html-bibr">48</a>]; (<b>d</b>) <span class="html-italic">T. cordata</span> (black, solid) [<a href="#B45-forests-07-00056" class="html-bibr">45</a>] <span class="html-italic">vs. F. sylvatica</span> (blue, dotted) [<a href="#B56-forests-07-00056" class="html-bibr">56</a>], both Germany.</p>
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<p>(<b>a</b>) Comparison of height growth of <span class="html-italic">T. cordata</span> originating from generative (black, solid) <span class="html-italic">vs.</span> vegetative (blue, dotted) regeneration (Hungary [<a href="#B46-forests-07-00056" class="html-bibr">46</a>]); (<b>b</b>) <span class="html-italic">T. cordata</span> from Lithuania [<a href="#B55-forests-07-00056" class="html-bibr">55</a>]; (<b>c</b>) <span class="html-italic">T. cordata</span> from Poland (black, solid) [<a href="#B47-forests-07-00056" class="html-bibr">47</a>]; Ukraine/Moldavia (blue, solid) [<a href="#B49-forests-07-00056" class="html-bibr">49</a>]; and Russia (red, solid, values not displayed: 140–200 years) [<a href="#B48-forests-07-00056" class="html-bibr">48</a>]; (<b>d</b>) <span class="html-italic">T. cordata</span> (black, solid) [<a href="#B45-forests-07-00056" class="html-bibr">45</a>] <span class="html-italic">vs. F. sylvatica</span> (blue, dotted) [<a href="#B56-forests-07-00056" class="html-bibr">56</a>], both Germany.</p>
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<p>European distribution of <span class="html-italic">T. cordata</span> [<a href="#B91-forests-07-00056" class="html-bibr">91</a>].</p>
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7410 KiB  
Article
Tropical Forest Gain and Interactions amongst Agents of Forest Change
by Sean Sloan
Forests 2016, 7(3), 55; https://doi.org/10.3390/f7030055 - 27 Feb 2016
Cited by 17 | Viewed by 7101
Abstract
The tropical deforestation literature advocates multi-agent enquiry in recognition that key dynamics arise from inter-agent interactions. Studies of tropical forest-cover gain have lagged in this respect. This article explores the roles and key aspects of interactions shaping natural forest regeneration and active reforestation [...] Read more.
The tropical deforestation literature advocates multi-agent enquiry in recognition that key dynamics arise from inter-agent interactions. Studies of tropical forest-cover gain have lagged in this respect. This article explores the roles and key aspects of interactions shaping natural forest regeneration and active reforestation in Eastern Panama since 1990. It employs household surveys of agricultural landholders, interviews with community forest-restoration organisations, archival analysis of plantation reforestation interests, satellite image analysis of forest-cover change, and the consideration of State reforestation policies. Forest-cover gain reflected a convergence of interests and land-use trends amongst agents. Low social and economic costs of sustained interaction and organisation enabled extensive forest-cover gain, but low transaction costs did not. Corporate plantation reforestation rose to the fore of regional forest-cover gain via opportunistic land sales by ranchers and economic subsidies indicative of a State preference for autonomous, self-organising forest-cover gain. This reforestation follows a recent history of neoliberal frontier development in which State-backed loggers and ranchers similarly displaced agriculturalists. Community institutions, long neglected by the State, struggled to coordinate landholders and so effected far less forest-cover gain. National and international commitments to tropical forest restoration risk being similarly characterised as ineffective by a predominance of industrial plantation reforestation without greater State support for community forest management. Full article
(This article belongs to the Special Issue Incentives and Constraints of Community and Smallholder Forestry)
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<p>The Bayano-Darién Region. Note: forest cover is for 2007.</p>
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<p>Cards Denoting Land Use/Covers (Red) and Number of Hectares (Yellow) Used to Reconstruct Household Land-Use Histories. Note: in this photo, the columns of cards indicate that there were 38 hectares in forest (bosque), two hectares in fallow (barbecho rastrojo), and a sum of 11 hectares in pasture (pasto) for the year in question. The notable accumulation of multiple small-denomination cards under the pasture card is indicative of the fact that, in any given year, only one or two hectares would typically have been taken from forest for subsistence agriculture (cultivos de corto plazo), which would subsequently be passed to fallow (as shown) and then ultimately to pasture, where it would remain.</p>
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<p>Key factors of forest-cover gain uniting sets of interacting agents. Arrows signify positive or negative effects of a factor on the facility and geographic centrality of forest-cover gain. Notes: the facility of forest-cover gain denotes the ease and efficiency by which interactions facilitate forest-cover gain, not the absolute area of forest-cover gain per se. Ellipses: these define key factors or traits of forest-cover gain uniting sets of interactions. Arrows pointing to the upper-right and lower-left, respectively, indicate a positive and negative effect of a factor on the facility and geographic centrality of forest-cover gain, e.g., greater external support and lower organisation costs both facilitate and centralise forest-cover gain. This schema is illustrative only, as clearly the effect of factors such as transaction costs will not maintain indefinitely at ever-higher values. Parentheses: labels indicate key, complementary traits of the primary (upper) and secondary (lower) agents of a given interaction promoting forest-cover gain.</p>
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<p>Land Cover in the Bayano-Darién Region, 1990.</p>
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<p>Land Cover in the Bayano-Darién Region, 2000. Source: Insert map after [<a href="#B67-forests-07-00055" class="html-bibr">67</a>].</p>
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<p>Land Cover in the Bayano-Darién Region, 2007.</p>
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<p>Land Cover in the Bayano-Darién Region, 2012.</p>
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<p>Annual area established in forest plantation, in hectares, for Greater Bayano Region and Panama, 1992–2007. Source: Data from Forest Registry of ANAM.</p>
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4426 KiB  
Review
Complex Challenges of Maintaining Whitebark Pine in Greater Yellowstone under Climate Change: A Call for Innovative Research, Management, and Policy Approaches
by Andrew Hansen, Kathryn Ireland, Kristin Legg, Robert Keane, Edward Barge, Martha Jenkins and Michiel Pillet
Forests 2016, 7(3), 54; https://doi.org/10.3390/f7030054 - 27 Feb 2016
Cited by 24 | Viewed by 8675
Abstract
Climate suitability is projected to decline for many subalpine species, raising questions about managing species under a deteriorating climate. Whitebark pine (WBP) (Pinus albicaulis) in the Greater Yellowstone Ecosystem (GYE) crystalizes the challenges that natural resource managers of many high mountain [...] Read more.
Climate suitability is projected to decline for many subalpine species, raising questions about managing species under a deteriorating climate. Whitebark pine (WBP) (Pinus albicaulis) in the Greater Yellowstone Ecosystem (GYE) crystalizes the challenges that natural resource managers of many high mountain ecosystems will likely face in the coming decades. We review the system of interactions among climate, competitors, fire, bark beetles, white pine blister rust (Cronartium ribicola), and seed dispersers that make WBP especially vulnerable to climate change. A well-formulated interagency management strategy has been developed for WBP, but it has only been implemented across <1% of the species GYE range. The challenges of complex climate effects and land allocation constraints on WBP management raises questions regarding the efficacy of restoration efforts for WBP in GYE. We evaluate six ecological mechanisms by which WBP may remain viable under climate change: climate microrefugia, climate tolerances, release from competition, favorable fire regimes, seed production prior to beetle-induced mortality, and blister-rust resistant trees. These mechanisms suggest that WBP viability may be higher than previously expected under climate change. Additional research is warranted on these mechanisms, which may provide a basis for increased management effectiveness. This review is used as a basis for deriving recommendations for other subalpine species threatened by climate change. Full article
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<p>(Inner box) Conceptual model of the projected direct and indirect effects of climate warming on WBP demography based on the current literature. Positive and negative signs denote the nature of the effect. Climate warming reduces whitebark pine (WBP) establishment, growth, and survival directly by exceeding WBP physiological tolerances and indirectly by favoring competing vegetation, severe fire, and mountain pine beetles. White pine blister rust negatively influences WBP growth, survival, and reproduction. However, the influence of climate change on white pine blister rust in the Greater Yellowstone Ecosystem (GYE) is not currently understood. (Outer Box) Ecological mechanisms that may allow WBP to remain viable in GYE in the face of projected climate warming and related threats (red text in call-out boxes). Picture and figure credits from left to right and top to bottom are: Tony Chang, Andrew Hansen, Yellowstone National Park Photo Archive, Colleen Kimmett, Grav Skeldon, Louisa Willcox, Karen Rentz.</p>
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<p>Average annual growth of WBP before and after thinning of competitors. Data from Keane <span class="html-italic">et al.</span> [<a href="#B79-forests-07-00054" class="html-bibr">79</a>].</p>
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<p>Frequency of occurrence of the major conifer species along the elevational gradient in the GYE as derived from Forest Inventory and Analysis data [<a href="#B20-forests-07-00054" class="html-bibr">20</a>,<a href="#B21-forests-07-00054" class="html-bibr">21</a>].</p>
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<p>Results for a sample of whitebark pine trees that were living in the 2004–2007 study initiation period and monitored through a 2012–2014 resample period. Rates of tree survival during the study period are shown by the gray bars and the left Y axis. Sample size in each diameter class is displayed above the gray bars. Potential reproduction as indicated by evidence of cone bearing (cones, conelets, or cone scars present) for trees alive at the end of the period is shown by the black bars and the right Y axis. Sample size in each diameter class is shown above the black bars. Data from the Greater Yellowstone Whitebark Pine Monitoring Working Group [<a href="#B106-forests-07-00054" class="html-bibr">106</a>].</p>
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<p>Distribution of projected deteriorating, core, and future habitat for WBP in the GYE under a moderate warming scenario for the period 2040–2070. These habitat projections are based on climate data from the CESM1-CAM5 global circulation model for the AR5 RCP 4.5 scenario [<a href="#B112-forests-07-00054" class="html-bibr">112</a>]. WBP climate suitability is from [<a href="#B26-forests-07-00054" class="html-bibr">26</a>]. Habitat types are defined in the text.</p>
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10233 KiB  
Article
Anthropogenic Decline of Ecosystem Services Threatens the Integrity of the Unique Hyrcanian (Caspian) Forests in Northern Iran
by Ardavan Zarandian, Himlal Baral, Ahmad R. Yavari, Hamid R. Jafari, Nigel E. Stork, Matthew A. Ling and Hamid Amirnejad
Forests 2016, 7(3), 51; https://doi.org/10.3390/f7030051 - 27 Feb 2016
Cited by 40 | Viewed by 7936
Abstract
The unique Hyrcanian (Caspian) forests of northern Iran provide vital ecosystem services for local and global communities. We assess the status and trends of key ecosystem services in this region where native forest conversion has accelerated to make way for housing and farm [...] Read more.
The unique Hyrcanian (Caspian) forests of northern Iran provide vital ecosystem services for local and global communities. We assess the status and trends of key ecosystem services in this region where native forest conversion has accelerated to make way for housing and farm development. This is a mountainous forested area that is valuable for both conservation and multiple human uses including recreation and farming. It contains globally significant natural habitats for in situ conservation of biological diversity. A rapid, qualitative, and participatory approach was used including interviews with local households and experts in combination with assessment of land use/cover remote sensing data to identify and map priority ecosystem services in the Geographic Information System (GIS). Based on the interests of the beneficiaries, eight priority services (food production, water supply, raw materials, soil conservation, water regulation, climate regulation, biodiversity, and recreation) were identified and mapped. The results indicate the current typical spatial distribution of the provided services based on structural characteristics of the study landscape and their changing trends through a comparison of past, present and future land use, and land cover. Although food production and recreation have greatly increased in recent decades, the other services, in particular timber production, biodiversity, and water purification and supply are being gradually lost. The results of this study and of others elsewhere should raise awareness of ecosystem service status and trends and the value of examining these since they provide much of the information to inform natural resources policy and decision making. The declines in supply of key ecosystem services both within and outside the protected area are creating conflicts within communities as well as impacting on the integrity of the area and careful planning and conservation is required to provide win-win opportunities. Full article
(This article belongs to the Special Issue Ecosystem Services from Forests)
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Graphical abstract

Graphical abstract
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<p>Geographic location of the Sarvelat and Javaherdasht district and the World Heritage Hyrcanian (Caspian) forests area.</p>
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<p>Practical approach of qualitative rapid assessment of Ecosystem Services (ES) in the study area.</p>
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<p>Past land use/land cover (LULC) (<b>a</b>); present, LULC (<b>b</b>); and plausible future LULC, if the current situation of LULC change continues (<b>c</b>) for the Sarvelat and Javaherdasht district.</p>
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<p>Classification of study villages based on their population, number of households, and geographical distribution across the study landscape.</p>
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<p>Maps of current, potential, and plausible future supply of ES based on individual service values associated with LULC types and land transformation. Services values are weighted between 0 and 5 based on expert judgment. Services include (<b>a</b>) food provision, (<b>b</b>) raw materials, (<b>c</b>) water supply, (<b>d</b>) climate regulation, (<b>e</b>) soil conservation, (<b>f</b>) recreation, (<b>g</b>) biodiversity, and (<b>h</b>) water regulation.</p>
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<p>Maps of current, potential, and plausible future supply of ES based on individual service values associated with LULC types and land transformation. Services values are weighted between 0 and 5 based on expert judgment. Services include (<b>a</b>) food provision, (<b>b</b>) raw materials, (<b>c</b>) water supply, (<b>d</b>) climate regulation, (<b>e</b>) soil conservation, (<b>f</b>) recreation, (<b>g</b>) biodiversity, and (<b>h</b>) water regulation.</p>
Full article ">Figure 5 Cont.
<p>Maps of current, potential, and plausible future supply of ES based on individual service values associated with LULC types and land transformation. Services values are weighted between 0 and 5 based on expert judgment. Services include (<b>a</b>) food provision, (<b>b</b>) raw materials, (<b>c</b>) water supply, (<b>d</b>) climate regulation, (<b>e</b>) soil conservation, (<b>f</b>) recreation, (<b>g</b>) biodiversity, and (<b>h</b>) water regulation.</p>
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<p>Maps of past, present, and plausible future supply of ES based on multiple service values associated with LULC types and land transformation. Services values are averaged based an integration of all eight individual key ES relative values.</p>
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<p>Percentage of the landscape with different relative capacities (low, moderate, and high) for multiple ES supply under each of past, present, and possible future conditions.</p>
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611 KiB  
Correction
Correction: DellaSala, D.A., et al. Building on Two Decades of Ecosystem Management and Biodiversity Conservation under the Northwest Forest Plan, USA. Forests, 2015, 6, 3326
by Dominick A. DellaSala, Rowan Baker, Doug Heiken, Chris A. Frissell, James R. Karr, S. Kim Nelson, Barry R. Noon, David Olson and James Strittholt
Forests 2016, 7(3), 53; https://doi.org/10.3390/f7030053 - 26 Feb 2016
Viewed by 4110
Abstract
We discovered two typos and a change in a sentence needed in our published manuscript.[...] Full article
(This article belongs to the Special Issue Biodiversity and Conservation in Forests)
2183 KiB  
Article
The Effects of Poplar Plantations on Vascular Plant Diversity in Riparian Landscapes
by Jorge Martín-García, Hervé Jactel, Juan Andrés Oria-de-Rueda and Julio Javier Diez
Forests 2016, 7(3), 50; https://doi.org/10.3390/f7030050 - 25 Feb 2016
Cited by 10 | Viewed by 6308
Abstract
Riparian vegetation, which performs many key ecological functions, has been modified or lost at an alarming rate during the past century as a result of human activity. The aims of this study are (a) to investigate the effects of poplar plantations on plant [...] Read more.
Riparian vegetation, which performs many key ecological functions, has been modified or lost at an alarming rate during the past century as a result of human activity. The aims of this study are (a) to investigate the effects of poplar plantations on plant diversity in riparian zones; and (b) to estimate the ecological implications of extending cover by poplar plantations. For this purpose, we assessed species richness, habitat indicator species and functional diversity based on Grime’s C-S-R strategies. We used non-metric multidimensional scaling to examine the role of environmental factors such as soil properties, forest structure and management. Disturbance, in particular the frequency of harrowing, led to a decline in species richness and modified the indicator species and functional diversity by favoring Ruderal (R) species at the expense Stress-Tolerant (S) and Competitor (C) species, which are better suited to riparian forest conditions. Poplar plantations should not be used as surrogates for riparian forests, and minimizing harrowing in poplar plantations promotes vascular plant diversity. Furthermore, reintroduction of herbs, ferns and geophytes with a high conservation value and low seed dispersal capacity is advisable from the sixth year after establishment, once harrowing for weed control has been completed. Full article
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<p>Geographical location of the study site.</p>
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<p>Sampling design adopted in the study.</p>
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<p>Ordination of vascular plants and stands. Type of forest: riparian forests are represented by circles, and poplar plantations (adult stands, not harrowed) by triangles. Vascular plant species: Apet <span class="html-italic">Alliaria petiolata</span> (M. Bieb.) Cavara &amp; Grande, Asto <span class="html-italic">Agrostis stolonifera</span> L., Bste <span class="html-italic">Bromus sterilis</span> L., Bsyl <span class="html-italic">Brachypodium sylvaticum</span> (Hudson) Beauv., Calb <span class="html-italic">Chenopodium album</span> L., Carv <span class="html-italic">Cirsium arvense</span> (L.) Scop., Ccup <span class="html-italic">Carex cuprina</span> (I. Sándor <span class="html-italic">ex</span> Heuff.) Nendtv. <span class="html-italic">ex</span> A. Kern., Cmon <span class="html-italic">Crataegus monogyna</span> Jacq., Dcar <span class="html-italic">Daucus carota</span> L., Dglo <span class="html-italic">Dactylis glomerata</span> L., Epar <span class="html-italic">Epilobium parviflorum</span> Schreb., Eamy <span class="html-italic">Euphorbia amygdaloides</span> L., Fulm <span class="html-italic">Filipendula ulmaria</span> (L.) Maxim., Gpal <span class="html-italic">Gallium palustre</span> L., Grob <span class="html-italic">Geranium robertianum</span> L., Gurb <span class="html-italic">Geum urbanum</span> L., Hlan <span class="html-italic">Holcus lanatus</span> L., Hlup <span class="html-italic">Humulus lupulus</span> L., Hmur <span class="html-italic">Hordeum murinum</span> L., Lser <span class="html-italic">Lactuca serriola</span> L., Lvul <span class="html-italic">Ligustrum vulgare</span> L., Lper <span class="html-italic">Loniera peryclimenum</span> L., Rrub <span class="html-italic">Ribes rubrum</span> L., Rcan <span class="html-italic">Rosa canina</span> L., Rcae <span class="html-italic">Rubus caesius</span> L., Rcris <span class="html-italic">Rumex crispus</span> L., Rulm <span class="html-italic">Rubus ulmifolius</span> Schott, Snig <span class="html-italic">Sambucus nigra</span> L., Ssyl <span class="html-italic">Stachys sylvatica</span> L., Tnod <span class="html-italic">Torilis nodosa</span> (L.) Gaertn., Toff <span class="html-italic">Taraxacum</span> <span class="html-italic">officinale</span> gr Weber, Trep <span class="html-italic">Trifolium repens</span> L. and Udio <span class="html-italic">Urtica dioica</span> L.</p>
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<p>Ordination of C-S-R signatures and stands. Type of forest: riparian forests are represented by circles, and poplar plantations (adult stands, not harrowed) by triangles. C-R-S signatures: C Competitor species, R Ruderal species and S Stress-Tolerant species.</p>
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<p>Habitat indicator species for the different levels of the hierarchical site typology (indicator value in brackets). Aarv <span class="html-italic">Anthemis arvensis</span>, Bcom <span class="html-italic">Bromus commutatus</span>, Bste <span class="html-italic">Bromus sterilis</span>, Carv <span class="html-italic">Convolvulus arvensis</span>, Cech <span class="html-italic">Cynosurus echinatus</span>, Cpyr <span class="html-italic">Cirsium pyrenaicum</span>, Cres <span class="html-italic">Crepis</span> sp., Cvul <span class="html-italic">Cirsium vulgare</span>, Dcar <span class="html-italic">Daucus carota</span>, Dglo <span class="html-italic">Dactylis glomerata</span>, Hmur <span class="html-italic">Hordeum murinum</span>, Hrad <span class="html-italic">Hypochoeris radicata</span>, Kspu <span class="html-italic">Kickxia spuria</span>, Lrig <span class="html-italic">Lolium rigidum,</span> Mlup <span class="html-italic">Medicago lupulina</span>, Pavi <span class="html-italic">Polygonum aviculare</span>, Plag <span class="html-italic">Plantago lagopus</span>, Prep <span class="html-italic">Potentilla reptans</span>, Pvul <span class="html-italic">Prunella vulgaris</span>, Smed <span class="html-italic">Stellaria media</span>, Tcap <span class="html-italic">Taeniatherum caput-medusae</span>, Toff <span class="html-italic">Taraxacum</span> <span class="html-italic">officinale</span> gr, Trep <span class="html-italic">Trifolium repens</span>, Vmyu <span class="html-italic">Vulpia myuros</span>.</p>
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<p>Ordination of vascular plants, stands and the environmental variables (represented by continuous arrows) retained by NMDS analysis. Type of forest: Adult-Poor-Harrowed are represented by black triangles, Adult-Poor-Not harrowed by black diamonds, Adult-Rich-Harrowed by black squares, Adult-Rich-Not harrowed by black circles, Young-Poor-Harrowed by white triangles, Young-Poor-Not harrowed by white diamonds, Young-Rich-Harrowed by white squares and Young-Rich-Not harrowed by white circles. C-R-S signatures: C Competitor, R Ruderal and S Stress-Tolerant species. Dotted arrows indicate the hypothetical axes (stress and disturbance) in terms of Grime’s theory.</p>
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2518 KiB  
Article
White Spruce Growth and Wood Properties over Multiple Time Periods in Relation to Current Tree and Stand Attributes
by Francesco Cortini, Dan A. MacIsaac and Philip G. Comeau
Forests 2016, 7(3), 49; https://doi.org/10.3390/f7030049 - 24 Feb 2016
Cited by 4 | Viewed by 4331
Abstract
The relationships between white spruce radial increment and wood properties were investigated in relation to tree and stand attributes using data from mature white spruce stands in the boreal forest of western Canada that experienced a range of shelterwood treatments. The model with [...] Read more.
The relationships between white spruce radial increment and wood properties were investigated in relation to tree and stand attributes using data from mature white spruce stands in the boreal forest of western Canada that experienced a range of shelterwood treatments. The model with the highest predictive ability was radial increment (adj-R2 = 67%) and included crown attributes, diameter at breast height (DBH), average height of competitors, and a climate index. Radial growth was positively related to live crown ratio, whereas wood density and modulus of elasticity were negatively correlated to the crown attribute. Tree slenderness had a significant negative effect on wood density and modulus of elasticity, as it reflects the mechanical stability requirement of the tree. The models consistently improved when using annual averages calculated over longer periods of time. However, when the annual averages were calculated using time periods of 5–10 and 10–20 years prior to sampling, the predictive ability of the models decreased, which indicated that the current tree and stand conditions were the best predictors of growth and wood properties up to five years prior to sampling. This study suggests that crown length equal to 2/3 of the tree height might represent an optimal balance between radial growth and wood quality. Full article
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<p>Location of the eight long-term studies.</p>
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<p>Plots representing the goodness-of-fit for Equation (1): (<b>a</b>) scatter plots of studentized residuals against predicted together with the fitted Lowess line and (<b>b</b>) normal Q-Q plot.</p>
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<p>Predicted values of average annual three-year radial area increment Equation (1) by treatment (thin lines) in relation to LCR of the subject tree. The thicker black line represents the fitted values at the study level (<span class="html-italic">i.e.</span>, fixed effects).</p>
Full article ">Figure 4
<p>Plots representing the goodness-of-fit for Equation (2): (<b>a</b>) scatter plots of studentized residuals against predicted together with the fitted Lowess line and (<b>b</b>) normal Q-Q plot.</p>
Full article ">Figure 5
<p>Predicted values of average annual three-year wood density Equation (2) by treatment (thin lines) in relation to LCR of the subject tree. The thicker black line represents the fitted values at the study level (<span class="html-italic">i.e.</span>, fixed effects).</p>
Full article ">Figure 6
<p>Plots representing the goodness-of-fit for Equation (3): (<b>a</b>) scatter plots of studentized residuals against predicted together with the fitted Lowess line and (<b>b</b>) normal Q-Q plot.</p>
Full article ">Figure 7
<p>Predicted values of average annual three-year MFA Equation (3) by treatment (thin lines) in relation to LCR of the subject tree. The thicker black line represents the fitted values at the study level (<span class="html-italic">i.e.</span>, fixed effects).</p>
Full article ">Figure 8
<p>Plots representing the goodness-of-fit for Equation (4) 1—scatter plots of studentized residuals against predicted together with the fitted Lowess line, and 2—Normal Q-Q plot.</p>
Full article ">Figure 9
<p>Predicted values of average annual three-year MOE Equation (4) by treatment (thin lines) in relation to LCR of the subject tree. The thicker black line represents the fitted values at the study level (<span class="html-italic">i.e.</span>, fixed effects).</p>
Full article ">
3094 KiB  
Article
National Assessment of the Fragmentation Levels and Fragmentation-Class Transitions of the Forests in Mexico for 2002, 2008 and 2013
by Elizabeth Clay, Rafael Moreno-Sanchez, Juan Manuel Torres-Rojo and Francisco Moreno-Sanchez
Forests 2016, 7(3), 48; https://doi.org/10.3390/f7030048 - 24 Feb 2016
Cited by 15 | Viewed by 5761
Abstract
Landscape modification and habitat fragmentation are key drivers of global species and biodiversity loss, as well as a major threat to the conservation of forest ecosystems. Mexico is one of the five biologically richest countries in the world. This study first generated a [...] Read more.
Landscape modification and habitat fragmentation are key drivers of global species and biodiversity loss, as well as a major threat to the conservation of forest ecosystems. Mexico is one of the five biologically richest countries in the world. This study first generated a national level assessment of the fragmentation of temperate and tropical forests in Mexico for 2002, 2008, and 2013. Then, using these results, it explores how transitions to non-forest or to other fragmentation classes have evolved within the previous date fragmentation classes for the 2002–2008 and 2008–2013 periods. The Morphological Spatial Pattern Analysis (MSPA) method was used to assess the forest fragmentation. The results show that high fragmentation classes are more likely to transition to no-forest land covers in tropical than in temperate forests and that these conversions were larger during 2002–2008 than during the 2008–2013 period in both forest types. When analyzing the transitions between fragmentation classes, a higher percent of the forest area remained the same fragmentation class between 2008 and 2013 than from 2002 to 2008. Transitions between forest fragmentation classes were relatively small compared to transitions to no-forest land covers, and transitions to higher fragmentation classes were slightly larger in tropical than in temperate forests. Full article
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Figure 1

Figure 1
<p>An illustration of the definition of the seven fragmentation classes resulting from the MSPA analysis for a hypothetical area and foreground (forest) patches. Cells in grey color represent the background (non-forest) areas [<a href="#B47-forests-07-00048" class="html-bibr">47</a>].</p>
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<p>Illustration of the fragmentation classes that are generated when setting the intext parameter to on (value of 1) or off (value of 0) for a hypothetical area and foreground (forest) patches. Cells in grey color represent the background (non-forest) areas. The numbers correspond to the values assigned to each fragmentation class as unique identifiers [<a href="#B47-forests-07-00048" class="html-bibr">47</a>].</p>
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<p>Sample of the map output of MSPA fragmentation classes generated with the intext parameter set to “Off” for an area of the tropical forests in 2002.</p>
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<p>Sample of the map output of MSPA fragmentation classes generated with the intext parameter set to “On” for an area of the tropical forests in 2002.</p>
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<p>Example of fragmentation classes in 2008 that fall within the 2002-Edge class for a sample area of tropical forests.</p>
Full article ">Figure 6
<p>Example of internal and external fragmentation classes in 2008 that fall within the 2002-External-Edge class for a sample area of tropical forests.</p>
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