Drivers of spatial structure in thinned forests

Background:As is widely known,an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems.However,previous research on forest management has often overlooked the importance of structure-based.Aims:Our objectives were to define the direction of structure-based forest management.Subsequently,we investigated the relationships between forest structure and the regeneration,growth,and mortality of trees under different thinning treatments.Ultimately,the drivers of forest structural change were explored.Methods:On the basis of 92 sites selected from northeastern China,with different recovery time (from 1 to 15years) and different thinning intensities (0–59.9%) since the last thinning.Principal component analysis (PCA)identified relationships among factors determining forest spatial structure.The structural equation model (SEM)was used to analyze the driving factors behind the changes in forest spatial structure after thinning.Results:Light thinning (0–20%trees removed) promoted forest regeneration,and heavy thinning (over 35% of trees removed) facilitated forest growth.However,only moderate thinning (20%–35%trees removed) created a reasonable spatial structure.While dead trees were clustered,and they were hardly affected by thinning intensity.Additionally,thinning intensity,recovery time,and altitude indirectly improve the spatial structure of the forest by influencing diameter at breast height (DBH) and canopy area.Conclusion:Creating larger DBH and canopy area through thinning will promote the formation of complex forest structures,which cultivates healthy and stable forests.

Population distribution and threats to sustainable management of selected non-timber forest products in tropical lowland rainforests of south western Nigeria

Uncontrolled harvesting of non-timber forest products （NTFPs） poses a serious risk of extermination to several of these species in Nigeria. Yet, there is a paucity of information on the distribution, population status and sustainable management of NTFPs in most of the tropical lowland rainforests. We, therefore, assessed the population, distribution and threats to sustainable management of NTFPs within the tropical lowland rainforests of Omo and Shasha Forest Reserves, south western Nigeria. Data were obtained through inventory surveys on five top priority species including： bush mango （Irvingia gabonensis （Aubry-Lecomte ex O’Rorke） Baill）, African walnut （Tetracarpidium conophorum （Mull. Arg.） Hutch. ＆ Dalziel syn. Plukenetia conophora）, chew-stick （Massularia acuminata （G. Don） Bullock）, fever bark （Annickia chlorantha Setten ＆ P.J.Maas syn. Enantia chloranta） and bush pepper （Piper guineense Schumach. ＆ Thonn.）. Purposive and stratified random sampling techniques were used for the inventory. Each forest reserve was stratified into three, viz： less disturbed natural forest （for areas that have been rested for at least ten years）, recently disturbed natural forest （for areas that have suffered one form of human perturbation or the other in the last five years）, and plantation forest （for areas carrying forest plantation）. Data were collected from eighteen 10 m × 500 m belt transects located in the above strata. The species were generally fewer in both plantation and recently disturbed natural forest than the less disturbed natural forest, suggesting that forest disturbances （habitat modification） for other uses may have an effect on the occurrence and densities of the NTFPs. Exceptions to this trend were found for P. guineense and T. conophorum, which were fairly common in both plantation and recently disturbed natural forest. Among three tree NTFP species （i.e. I. gabonensis, M. acuminata and A. chlorantha）, only I. gabonensis showed a significant difference in overall DBH size classes for both reserves （t=？2.404; df =21; p=0.026）. Three tree NTFP species in both reserves further showed differences from the regular patterns of distribution of trees. The fairly regular reverse J-shaped size class distribution observed for M. acuminata in the study sites, however, suggests a recuperating population. In general, destructive harvesting of species, logging operations, low population size, narrow distribution ranges and habitat degradation are the major threats to the population of NTFPs in the study area. The implications of our findings for sustainable management of NTFPs in the study area are discussed and recommendations are made for a feasible approach towards enhancing the status of the species.

Use of models in large-area forest surveys： comparing model-assisted, model-based and hybrid estimation

This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the development of models predicting the variables of interest in forest surveys. We present, review and compare three different estimation frameworks where models play a core role： model-assisted, model-based, and hybrid estimation. The first two are well known, whereas the third has only recently been introduced in forest surveys. Hybrid inference mixes design- based and model-based inference, since it relies on a probability sample of auxiliary data and a model predicting the target variable from the auxiliary data.We review studies on large-area forest surveys based on model-assisted, model- based, and hybrid estimation, and discuss advantages and disadvantages of the approaches. We conclude that no general recommendations can be made about whether model-assisted, model-based, or hybrid estimation should be preferred. The choice depends on the objective of the survey and the possibilities to acquire appropriate field and remotely sensed data. We also conclude that modelling approaches can only be successfully applied for estimating target variables such as growing stock volume or biomass, which are adequately related to commonly available remotely sensed data, and thus purely field based surveys remain important for several important forest parameters.

Comparison of estimators of variance for forest inventories with systematic sampling-results from artificial populations

Background:Large area forest inventories often use regular grids(with a single random start)of sample locations to ensure a uniform sampling intensity across the space of the surveyed populations.A design-unbiased estimator of variance does not exist for this design.Oftentimes,a quasi-default estimator applicable to simple random sampling(SRS)is used,even if it carries with it the likely risk of overestimating the variance by a practically important margin.To better exploit the precision of systematic sampling we assess the performance of five estimators of variance,including the quasi default.In this study,simulated systematic sampling was applied to artificial populations with contrasting covariance structures and with or without linear trends.We compared the results obtained with the SRS,Matern’s,successive difference replication,Ripley’s,and D’Orazio’s variance estimators.Results:The variances obtained with the four alternatives to the SRS estimator of variance were strongly correlated,and in all study settings consistently closer to the target design variance than the estimator for SRS.The latter always produced the greatest overestimation.In populations with a near zero spatial autocorrelation,all estimators,performed equally,and delivered estimates close to the actual design variance.Conclusion:Without a linear trend,the SDR and DOR estimators were best with variance estimates more narrowly distributed around the benchmark;yet in terms of the least average absolute deviation,Matern’s estimator held a narrow lead.With a strong or moderate linear trend,Matern’s estimator is choice.In large populations,and a low sampling intensity,the performance of the investigated estimators becomes more similar.

Delineation of homogeneous forest patches using combination of field measurements and LiDAR point clouds as a reliable reference for evaluation of low resolution global satellite data

Backgrounds： There are many satellite systems acquiring environmental data on the world. Acquired global remote sensing datasets require ground reference data in order to calibrate them and assess their quality. Regarding calibration and validation of these datasets with broad geographical extents, it is essential to register zones which might be considered as Homogeneous Patches （HPs）. Such patches enable an optimal calibration of satellite data/sensors, and what is more important is an analysis of components which significantly influence electro-magnetic signals registered by satellite sensors. Methods： We proposed two structurally different methods to identify HPs： predefined thresholding-based one （static one）, and statistical thresholding-based technique （dynamic one）. In the first method, 3 different thresholds were used： 5%, 10%, and 20%. Next, it was aimed to assess how delineated HPs were spatially matched to satellite data with coarse spatial resolution. Selected cell sizes were 25, 50, 100, 250, and 500 m. The number of particular grid cells which almost entirely fell into registered HPs was counted （leaving 2% cell area tolerance level）. This procedure was executed separately for each variant and selected structural variables, as well as for their intersection parts. Results： The results of this investigation revealed that ALS data might have the potential in the identification of HPs of forest stands. We showed that different ALS based variables and thresholds of HPs definition influenced areas which can be treated as similar and homogeneous. We proved that integration of more than one structural variable limits size of the HPs, in contrast, visual interpretation revealed that inside such patches vegetation structure is more constant. Conclusions： We concluded that ALS data can be used as a potential source of data to ＂enlarge＂ small ground sample plots and to be used for evaluation and calibration of remotely sensed datasets provided by global systems with coarse spatial resolutions.

Impacts of COVID-19 on tourism and management response from Banff National Park,Canada

The COVID-19 pandemic posed challenges to the tourism sector globally.We investigated changes in visitor demographics,satisfaction level,and its determinants pre-and peri-COVID-19.Data were collected using questionnaire surveys in 2019 and 2021 within Banff National Park(BNP).The data analyses were based on a sample size of 1183 respondents by conducting factor analysis,correlation analysis and stepwise regression analysis.Results highlight that there were fewer international visitors and more local and domestic visitors during the pandemic.Park attributes were evaluated at a higher satisfaction level peri-COVID-19.The quality of the Park facilities and services were the most important satisfaction determinants pre-and peri-COVID-19,and all the Park COVID-19 measures and actions received positive experience from visitors.This research fills this knowledge gap by developing a better understanding in the change of visitor demographics and satisfaction level in BNP under the context of the pandemic.It also provides implication for both scholars and practitioners to understand the impacts of the pandemic on Park visitation.The study can provide insights for utilizing the pandemic as a transformative strength and for mitigating its negative impact on tourism industry.

Evaluation of Some Weibull Parameter Estimation Methods for Characterizing Stem Diameter Distribution in a Tropical Mixed Forest of Southern Nigeria

Stem diameter distribution information is useful in forest management planning. Weibull function is flexible, and has been used in characterising diameter distributions, especially in single-species planted stands, the world over. We evaluated some Weibull parameter estimation methods for stem diameter characterisation in （Oban） multi-species Forest in southern Nigeria. Four study sites （Aking, Ekang, Erokut and Ekuri） were selected. Four 2 km-long transects situated at 600 m apart were laid in each location. Five 50m x 50m plots were alternately laid along each transect at 400 m apart （20 plots/location） using systematic sampling technique. Tree growth variables： diameter at breast height （Dbh）, diameters at the base, middle and merchantable limit, total height, merchantable height, stem straightness, crown length and crown diameter were measured on all trees 〉 10 cm to compute model response variables such as mean diameters, basal area and stem volume. Weibull parameters estimation methods used were： moment-based, percentile-based, hybrid and maximum-likelihood （ML）. Data were analysed using descriptive statistics, regression models and ANOVA at α0.05. Percentile-based method was the best for Weibull [location （a）, scale （b） and shape （c）] parameters estimations with mLogL = 116.66±21.89, while hybrid method was least-suitable （mLogL = 690.14±128.81） for Weibull parameters estimations. Quadratic mean diameter （Dq） was the only suitable predictor of Weibull parameters in Oban Forest.

Assessment of Conflicts between Forestry and Agricultural Land Uses in Nigeria and Ghana

The study was conducted in four states of the Southwest geo-political zone in Nigeria and four regions in Ghana.. The results showed that the existing forest, agricultural and land use decree/policies in Nigeria and Ghana indicated lack of integration between Forestry and Agricultural land uses. The main conflicting areas were obsolete land use decree in Nigeria and lack of national land use policy in Ghana. The causes and effects of the conflicts had policy enunciation, stakeholders, and institutional and managerial dimensions. Some of the causes of the conflicts were lack of national land use policies for coherent and integrated forest and agricultural sectors; high population growth, de-reservation of forest reserves, unsustainable agricultural practices and technologies, land hunger, encroachment of forest reserves with cash crops and stakeholders＇ litany of demands and other diverse interests. Consequences of conflicts in the study locations included disharmony between forestry officials and farmers, antagonism between timber concenssionnaires and communities, wanton destruction of economic trees and seedlings, extinction of tree species, expansion of illegal farm lands and an attendant poverty. The logistic regression model for conflicts between forestry and agricultural land uses in Nigeria and Ghana indicated significant fit to the data judging from chi square value （df, 9） = 3174.1 that is significant at P 〈 0.05. The final loss of the model indicated a value of 92.47.

Functional composition of tall-statured trees underpins aboveground biomass in tropical forests

The influences of trait diversity(i.e.,the niche complementarity effect)and functional composition(i.e.,the mass ratio effect)on aboveground biomass(AGB)is a highly debated topic in forest ecology.Therefore,further studies are needed to explore these mechanisms in unstudied forest ecosystems to enhance our understanding,and to provide guidelines for specific forest management.Here,we hypothesized that functional composition would drive AGB better than trait diversity and stem size inequality in the(sub-)tropical forests of Nepal.Using data from 101 forest plots,we tested 25 structural equation models(SEMs)to link elevation,stem DBH inequality,trait diversity(i.e.,trait richness,evenness,dispersion and divergence),functional composition[i.e.,community-weighted of maximum height mean(CWM of Hmax),specific leaf area(CWM of SLA),leaf dry matter content(CWM of LDMC),and wood density(CWM of WD)]and AGB.The best-fitted SEMs indicated that CWM of Hmax promoted AGB while overruling the impacts of trait diversity indices on AGB.However,low trait diversity indices were linked with higher AGB while overruling the effects of CWM of SLA,LDMC and WD on AGB.In addition,AGB decreased with increasing elevation,whereas stem size inequality did not influence AGB.Our results suggest that divergent species’functional strategies could shape AGB along an altitudinal gradient in tropical forests.We argue that forest management practices should include plant functional traits in the management plan for the co-benefits of biodiversity conservation and carbon sequestration that underpins human wellbeing.

An Investigation of the Factors That Motivated Illegal Settlements in the Mau Forest, Kenya

The Mau Forest has in the recent past elicited serious political and environmental debates regarding its conservation status, as the forest is fast dwindling and the repercussions felt widely across the country. The forest, regarded as the largest indigenous montane forest in east Africa, has been hard hit by land-use changes mainly extensive and ill-planned human settlements. To save the forest, the government has resorted to forced evictions of the settlers. We sought to understand the drivers and causes for the observed illegal settlements in the Mau Forest. To collect data, we conducted focus group discussions and administered household questionnaires on evictees in the South-West and Eastern Mau. Data were analyzed using descriptive and inferential statistics. The results of the binary logistic regression model indicate that Poverty (p = 0.000), Agricultural production (p = 0.000) and Land Given by Government (p = 0.018) contributed significantly to the prediction of people’s motivation of settling in the Mau Forest. In conclusion, population pressure, laxity in forest law enforcement and insecure land tenure and politics were identified as some of the factors that motivated the observed rise in illegal settlements in Mau Forest. Such information on the factors that led to the illegal settlements in Mau Forest would be useful for forest conservation policy makers and managers. It will be a basis upon which interventions can be undertaken to enhance sustainable forest management in Kenya and beyond.

Analysis of the inflection points of height-diameter models

The inflection point is an important feature of sigmoidal height-diameter(H-D)models.It is often cited as one of the properties favoring sigmoidal model forms.However,there are very few studies analyzing the inflection points of H-D models.The goals of this study were to theoretically and empirically examine the behaviors of inflection points of six common H-D models with a regional dataset.The six models were the Wykoff(WYK),Schumacher(SCH),Curtis(CUR),HossfeldⅣ(HOS),von Bertalanffy-Richards(VBR),and Gompertz(GPZ)models.The models were first fitted in their base forms with tree species as random effects and were then expanded to include functional traits and spatial distribution.The distributions of the estimated inflection points were similar between the two-parameter models WYK,SCH,and CUR,but were different between the threeparameter models HOS,VBR,and GPZ.GPZ produced some of the largest inflection points.HOS and VBR produced concave H-D curves without inflection points for 12.7%and 39.7%of the tree species.Evergreen species or decreasing shade tolerance resulted in larger inflection points.The trends in the estimated inflection points of HOS and VBR were entirely opposite across the landscape.Furthermore,HOS could produce concave H-D curves for portions of the landscape.Based on the studied behaviors,the choice between two-parameter models may not matter.We recommend comparing seve ral three-parameter model forms for consistency in estimated inflection points before deciding on one.Believing sigmoidal models to have inflection points does not necessarily mean that they will produce fitted curves with one.Our study highlights the need to integrate analysis of inflection points into modeling H-D relationships.

Using satellite-derived land surface temperatures to clarify the spatiotemporal warming trends of the Alborz Mountains in northern Iran

The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects the ecosystem of this area.This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500-4000 m above sea level.MODIS data were extracted for the period of 2000-2021,and the Mann-Kendall nonparametric test was applied to evaluating the changes in the LST.The results indicated a significant increasing trend for the monthly average LST in May-August along the southern aspect.Both the northern and southern aspects showed decreasing trends for the monthly average LST in October,November,and March and an increasing trend in other months.At all elevations,the average decadal change in the monthly average LST was more severe along the southern aspect(0.60°C)than along the northern aspect(0.37°C).The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months.At the same elevation,the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months.With increasing elevation,the lapse rate between the northern and southern aspects disappeared.Climate change was concluded to greatly decrease the difference in LST at different elevations for April-July.

Modeling the effect of stand and site characteristics on the probability of mistletoe infestation in Scots pine stands using remote sensing data

Over the past decade,the presence of mistletoe(Viscum album ssp.austriacum)in Scots pine stands has increased in many European countries.Understanding the factors that influence the occurrence of mistletoe in stands is key to making appropriate forest management decisions to limit damage and prevent the spread of mistletoe in the future.Therefore,the main objective of this study was to determine the probability of mistletoe occurrence in Scots pine stands in relation to stand-related endogenous factors such as age,top height,and stand density,as well as topographic and edaphic factors.We used unmanned aerial vehicle(UAV)imagery from 2,247 stands to detect mistletoe in Scots pine stands,while majority stand and site characteristics were calculated from airborne laser scanning(ALS)data.Information on stand age and site type from the State Forest database were also used.We found that mistletoe infestation in Scots pine stands is influenced by stand and site characteristics.We documented that the densest,tallest,and oldest stands were more susceptible to mistletoe infestation.Site type and specific microsite conditions associated with topography were also important factors driving mistletoe occurrence.In addition,climatic water balance was a significant factor in increasing the probability of mistletoe occurrence,which is important in the context of predicted temperature increases associated with climate change.Our results are important for better understanding patterns of mistletoe infestation and ecosystem functioning under climate change.In an era of climate change and technological development,the use of remote sensing methods to determine the risk of mistletoe infestation can be a very useful tool for managing forest ecosystems to maintain forest sustainability and prevent forest disturbance.

Advancing climate resilience through a geo-design framework: strengthening urban and community forestry for sustainable environmental design

Urban and community forestry is a specialized discipline focused on the meticulous management of trees and forests within urban,suburban,and town environments.This field often entails extensive civic involvement and collaborative partnerships with institutions.Its overarching objectives span a spectrum from preserving water quality,habitat,and biodiversity to mitigating the Urban Heat Island(UHI)effect.The UHI phenomenon,characterized by notably higher temperatures in urban areas compared to rural counterparts due to heat absorption by urban infrastructure and limited urban forest coverage,serves as a focal point in this study.The study focuses on developing a methodological framework that integrates Geographically Weighted Regression(GWR),Random Forest(RF),and Suitability Analysis to assess the Urban Heat Island(UHI)effect across different urban zones,aiming to identify areas with varying levels of UHI impact.The framework is designed to assist urban planners and designers in understanding the spatial distribution of UHI and identifying areas where urban forestry initiatives can be strategically implemented to mitigate its effect.Conducted in various London areas,the research provides a comprehensive analysis of the intricate relationship between urban and community forestry and UHI.By mapping the spatial variability of UHI,the framework offers a novel approach to enhancing urban environmental design and advancing urban forestry studies.The study’s findings are expected to provide valuable insights for urban planners and policymakers,aiding in creating healthier and more livable urban environments through informed decision-making in urban forestry management.

Evaluation and scenario simulation for forest ecological security in China

Continuously growing populations and rapid economic development have led to the excessive use of forest resources,and the forest ecosystem is threatened.In response,forest ecological security(FES)has attracted attention.In this study,an integrated dynamic simulation model was constructed using the system dynamic method,and it was used to evaluate the FES in China from 1999 to 2014.A scenario analysis was then used to evaluate the changes in the FES under five forestry policy scenarios for the 2015–2050 period,including the baseline,afforestation policy,harvesting policies,management policy,investment policy,and a policy mix.The results showed that the evaluation values of the FES increased during the period from 1999 to 2002,the period from 2004 to 2010 and the year 2014,and they decreased in 2003 and during the period from 2011 to 2013.During the 2015–2050 simulation period,the FES improved continuously.In particular,China would enter a new stage when the economic systems,social systems and ecosystems were in harmony after 2040.To improve the FES and the current status of the FES,a scenario analysis showed the most suitable scenario to be Scenario 5 from 2015 to 2020 and Scenario 2 from 2021 to 2050.To relieve pressure,the most suitable scenario would be Scenario 5 from 2015 to 2040 and from 2046 to 2050,and the most suitable scenario would be Scenario 4 for 2041–2045.A policy mix(Scenario 5)would be most efficient under current conditions,while the effects of all the benefits of the forestry policies would weaken over the long term.The integrated method can be regarded as a decision support tool to help policy makers understand FES and promulgate a reasonable forestry policy.

Influence of soil microorganisms and physicochemical properties on plant diversity in an arid desert of Western China

Soil microorganisms and physicochemical properties are considered the two most influencing factors for maintaining plant diversity.However,the operational mechanisms and which factor is the most influential manipulator remain poorly understood.In this study,we examine the collaborative influences of soil physicochemical properties(i.e.,soil water,soil organic matter(SOM),salinity,total phosphorus and nitrogen,pH,soil bulk density and fine root biomass)and soil microorganisms(fungi and bacteria)on plant diversity across two types of tree patches dominated by big and small trees(big trees:height≥7 m and DBH≥60 cm;small trees:height≤4.5 m and DBH≤20 cm)in an arid desert region.Tree patch is consists of a single tree or group of trees and their accompanying shrubs and herbs.It was hypothesized that soil physicochemical properties and microorganisms affect plant diversity but their influence differ.The results show that plant and soil microbial diversity increased with increasing distances from big trees.SOM,salinity,fine root biomass,soil water,total phosphorus and total nitrogen contents decreased with increasing distance from big trees,while pH and soil bulk density did not change.Plant and soil microbial diversity were higher in areas close to big trees compared with small trees,whereas soil physicochemical properties were opposite.The average contribution of soil physicochemical properties(12.2%-13.5%)to plant diversity was higher than microbial diversity(4.8%-6.7%).Salinity had the largest negative affect on plant diversity(24.7%-27.4%).This study suggests that soil fungi constrain plant diversity while bacteria improve it in tree patches.Soil physicochemical properties are the most important factor modulating plant diversity in arid desert tree patches.

Climate change impacts and forest adaptation in the Asia–Pacific region: from regional experts' perspectives

Expert opinions have been used in a variety of fields to identify relevant issues and courses of action. This study surveys experts in forestry and climate change from the Asia–Pacific region to gauge their perspectives on the impacts of climate change and on the challenges faced by forest adaptation in the region, and explores recommendations and initiatives for adapting forests to climate change. There was consensus regarding the impacts of climate change on forest ecosystems and on economic sectors such as agriculture and forestry. Respondents also indicated a lack of public awareness and policy and legislation as challenges to addressing climate change. However, the results indicate differences in opinion between regions on the negative impacts of climate change and in satisfaction with actions taken to address climate change,highlighting the need for locally specific policies and research. The study presents specific recommendations to address issues of most concern, based on subregion and professional affiliation throughout the Asia–Pacific region.The results can be used to improve policy and forest management throughout the region. This research will also provide valuable suggestions on how to apply research findings and management recommendations outside of the AP region. The conclusions should be communicated relative to the level of the research and the target audience,ensuring that scientific findings and management recommendations are effectively communicated to ensure successful implementation of forest adaptation strategies.

Methods of modeling relative growth rate

Background： Analysing and modelling plant growth is an important interdisciplinary field of plant science. The use of relative growth rates, involving the analysis of plant growth relative to plant size, has more or less independently emerged in different research groups and at different times and has provided powerful tools for assessing the growth performance and growth efficiency of plants and plant populations. In this paper, we explore how these isolated methods can be combined to form a consistent methodology for modelling relative growth rates. Methods： We review and combine existing methods of analysing and modelling relative growth rates and apply a combination of methods to Sitka spruce （Piceo sitchensis （Bong.） Carr.） stem-analysis data from North Wales （UK） and British Douglas fir （Pseudotsugd menziesii （Mirb.） Franco） yield table data. Results： The results indicate that, by combining the approaches of different plant-growth analysis laboratories and using them simultaneously, we can advance and standardise the concept of relative plant growth. Particularly the growth multiplier plays an important role in modelling relative growth rates. Another useful technique has been the recent introduction of size-standardised relative growth rates. Conclusions： Modelling relative growth rates mainly serves two purposes, 1） an improved analysis of growth performance and efficiency and 2） the prediction of future or past growth rates. This makes the concept of relative growth ideally suited to growth reconstruction as required in dendrochronology, climate change and forest decline research and for interdisciplinary research projects beyond the realm of plant science.

Comparison of carbon-stock changes, eddycovariance carbon fluxes and model estimates in coastal Douglas-fir stands in British Columbia

Background： The global network of eddy-covariance （EC） flux-towers has improved the understanding of the terrestrial carbon （C） cycle, however, the network has a relatively limited spatial extent compared to forest inventory data and plots. Developing methods to use inventory-based and EC flux measurements together with modeling approaches is necessary evaluate forest C dynamics across broad spatial extents. Methods： Changes in C stock change （AC） were computed based on repeated measurements of forest inventory plots and compared with separate measurements of cumulative net ecosystem productivity （~NEP） over four years （2003 - 2006） for Douglas-fir （Pseudotsuga menzies# var menziesil} dominated regeneration （HDF00）, juvenile （HDF88 and HDF90） and near-rotation （DF49） aged stands （6, 18, 20, 57 years old in 2006, respectively） in coastal British Columbia. AC was determined from forest inventory plot data alone, and in a hybrid approach using inventory data along with litter fall data and published decay equations to determine the change in detrital pools. These AC-based estimates were then compared with Y_NEP measured at an eddy-covariance flux-tower （EC-flux） and modelled by the Carbon Budget Model - Canadian Forest Sector （CBM-CFS3） using historic forest inventory and forest disturbance data. Footprint analysis was used with remote sensing, soils and topography data to evaluate how well the inventory plots represented the range of stand conditions within the area of the flux-tower footprint and to spatially scale the plot data to the area of the EC-flux and model based estimates, Results： The closest convergence among methods was for the juvenile stands while the largest divergences were for the regenerating clearcut, followed by the near-rotation stand. At the regenerating clearcut, footprint weighting of CBM-CFS3 TNEP increased convergence with EC flux Z_NEP, but not for AC. While spatial scaling and footprint weighting did not increase convergence for AC, they did provide confidence that the sample plots represented site conditions as measured by the EC tower. Conclusions： Methods to use inventory and EC flux measurements together with modeling approaches are necessary to understand forest C dynamics across broad spatial extents. Each approach has advantages and limitations that need to be considered for investigations at varying spatial and temporal scales.

Cross-classes domain inference with network sampling for natural resource inventory

There are two distinct types of domains,design-and cross-classes domains,with the former extensively studied under the topic of small-area estimation.In natural resource inventory,however,most classes listed in the condition tables of national inventory programs are characterized as cross-classes domains,such as vegetation type,productivity class,and age class.To date,challenges remain active for inventorying cross-classes domains because these domains are usually of unknown sampling frame and spatial distribution with the result that inference relies on population-level as opposed to domain-level sampling.Multiple challenges are noteworthy:(1)efficient sampling strategies are difficult to develop because of little priori information about the target domain;(2)domain inference relies on a sample designed for the population,so within-domain sample sizes could be too small to support a precise estimation;and(3)increasing sample size for the population does not ensure an increase to the domain,so actual sample size for a target domain remains highly uncertain,particularly for small domains.In this paper,we introduce a design-based generalized systematic adaptive cluster sampling(GSACS)for inventorying cross-classes domains.Design-unbiased Hansen-Hurwitz and Horvitz-Thompson estimators are derived for domain totals and compared within GSACS and with systematic sampling(SYS).Comprehensive Monte Carlo simulations show that(1)GSACS Hansen-Hurwitz and Horvitz-Thompson estimators are unbiased and equally efficient,whereas thelatter outperforms the former for supporting a sample of size one;(2)SYS is a special case of GSACS while the latter outperforms the former in terms of increased efficiency and reduced intensity;(3)GSACS Horvitz-Thompson variance estimator is design-unbiased for a single SYS sample;and(4)rules-ofthumb summarized with respect to sampling design and spatial effect improve precision.Because inventorying a mini domain is analogous to inventorying a rare variable,alternative network sampling procedures are also readily available for inventorying cross-classes domains.