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1.
Tao Liu Tianle Yang Chunyan Li Rui Li Wei Wu Xiaochun Zhong Chengming Sun Wenshan Guo 《Plant methods》2018,14(1):101
Background
The number of cultivated wheat seedlings per unit area allows calculation of plant density. Wheat seedling density provides emergence data and this is useful for improving crop management. The number of wheat seedlings is typically determined by visual counts but this is time-consuming and laborious.Results
We obtained field digital images of 1st to 3rd leaf stage wheat seedlings. The seedlings were extracted using an image analysis technique that calculated the coverage degree of the seedlings and the number of angular points of overlapping leaves. The wheat seedling quantity estimation model was constructed using multivariate regression analysis. The model parameters included coverage degree, number of angular points, variety coefficient, and leaf age. Introduction of the number of angular points increased the accuracy of the single coverage degree model. The R2 value was consistently?>?0.95 when the model was applied to different varieties, indicating that the model was adaptable for different varieties. As the leaf stage or density increased, the accuracy of the model declined, but the minimum R2 remained?>?0.87, indicating good adaptability of the model to seedlings with different leaf ages and densities.Conclusions
This method is an effective means for counting wheat seedlings in the 1st to the 3rd leaf stages.2.
Pouria Sadeghi-Tehran Nicolas Virlet Kasra Sabermanesh Malcolm J. Hawkesford 《Plant methods》2017,13(1):103
Background
Accurately segmenting vegetation from the background within digital images is both a fundamental and a challenging task in phenotyping. The performance of traditional methods is satisfactory in homogeneous environments, however, performance decreases when applied to images acquired in dynamic field environments.Results
In this paper, a multi-feature learning method is proposed to quantify vegetation growth in outdoor field conditions. The introduced technique is compared with the state-of the-art and other learning methods on digital images. All methods are compared and evaluated with different environmental conditions and the following criteria: (1) comparison with ground-truth images, (2) variation along a day with changes in ambient illumination, (3) comparison with manual measurements and (4) an estimation of performance along the full life cycle of a wheat canopy.Conclusion
The method described is capable of coping with the environmental challenges faced in field conditions, with high levels of adaptiveness and without the need for adjusting a threshold for each digital image. The proposed method is also an ideal candidate to process a time series of phenotypic information throughout the crop growth acquired in the field. Moreover, the introduced method has an advantage that it is not limited to growth measurements only but can be applied on other applications such as identifying weeds, diseases, stress, etc.3.
Shengli Tao Qinghua Guo Fangfang Wu Le Li Shaopeng Wang Zhiyao Tang Baolin Xue Jin Liu Jingyun Fang 《Landscape Ecology》2016,31(8):1711-1723
Context
Spatial scale and pattern play important roles in forest aboveground biomass (AGB) estimation in remote sensing. Changes in the accuracy of satellite images-estimated forest AGBs against spatial scales and pixel distribution patterns has not been evaluated, because it requires ground-truth AGBs of fine resolution over a large extent, and such data are difficult to obtain using traditional ground surveying methods.Objectives
We intend to quantify the accuracy of AGB estimation from satellite images on changing spatial scales and varying pixel distribution patterns, in a typical mixed coniferous forest in Sierra Nevada mountains, California.Methods
A forest AGB map of a 143 km2 area was created using small-footprint light detection and ranging. Landsat Thematic Mapper images were chosen as typical examples of satellite images, and resampled to successively coarser resolutions. At each spatial scale, pixels forming random, uniform, and clustered spatial patterns were then sampled. The accuracies of the AGB estimation based on Landsat images associated with varying spatial scales and patterns were finally quantified.Results
The changes in the accuracy of AGB estimation from Landsat images are not monotonic, but increase up to 60–90 m in spatial scale, and then decrease. Random and uniform spatial patterns of pixel distributions yield better accuracy for AGB estimation than clustered spatial patterns. The corrected NDVI (NDVIc) was the best predictor of AGB estimation.Conclusions
A spatial scale of 60–90 m is recommended for forest AGB estimation at the Sierra Nevada mountains using Landsat images and those with similar spectral resolutions.4.
Erick M. G. Cordeiro James F. Campbell Thomas W. Phillips Kimberly A. With 《Landscape Ecology》2018,33(11):1881-1894
Context
Although animal movement behaviors are influenced by spatial heterogeneity, such behaviors can also generate spatial heterogeneity via interactions with the emergent spatial structure and other individuals (i.e., the social landscape).Objective
Elucidate the behavioral and ecological mechanisms of pattern formation in a homogeneous resource landscape.Methods
We analyzed the movement pathways and space-use patterns of the lesser grain borer (Rhyzopertha dominica) within homogeneous resource landscapes (wheat kernels). Experimental trials consisted of individual beetles foraging alone or paired with a member of the same or different sex.Results
We identified two sources of pattern formation: (1) beetles were attracted to areas where they or another beetle had previously fed, leading to increased patchiness via positive reinforcement; and (2) the presence of conspecifics affected whether and at what scales patchiness occurred. Solitary males had lower rates of movement and less tortuous pathways than solitary females, but both sexes generated fine-scale patchiness in the resource distribution. Patchy resource landscapes were also generated by male–female pairs, but not by same-sex pairings. Paired females in particular exhibited significantly greater daily net displacements and more random space use than solitary females.Conclusions
Pattern formation is a complex process, even in a relatively simple, homogeneous resource landscape. In particular, patterns created by individuals when foraging alone versus in pairs underscores how social interactions can fundamentally alter the resultant pattern of heterogeneity that emerges in resource landscapes.5.
Context
Revealing the interaction between landscape pattern and urban land surface temperature (LST) can provide insight into mitigating thermal environmental risks. However, there is no consensus about the key landscape indicators influencing LST.Objectives
This study sought to identify the key landscape indicators influencing LST considering a large number of landscape pattern variables and multiple scales.Methods
This study applied ordinary least squares regression and partial least squares regression to explore a combination of landscape metrics and identify the key indicators influencing LST. A total of 49 Landsat images of the main city of Shenzhen, China were examined at 13 spatial scales.Results
The landscape composition indicators derived from biophysical proportion, a new metric developed in this study, more effectively determined LST variation than those derived from land cover proportion. Area-related landscape configuration indicators independently characterized LST variation, but did not give much more new information beyond that given by land cover proportion. Shape-related landscape configuration indicators were effective in combination with land cover proportion, but their importance was uncertain when temporal and spatial scales varied.Conclusions
The influence of landscape configuration on LST exists but should not be overestimated. Comparison of numerous variables at multiple spatiotemporal scales can help identify the influence of multiple landscape characteristics on LST variation.6.
Context
Despite decades of research, there is an intense debate about the consistency of the hump-shaped pattern describing the relationship between diversity and disturbance as predicted by the intermediate disturbance hypothesis (IDH). Previous meta-analyses have not explicitly considered interactive effects of disturbance frequency and intensity of disturbance on plant species diversity in terrestrial landscapes.Objective
We conducted meta-analyses to test the applicability of IDH by simultaneously examining the relationship between species richness, disturbance frequency (quantified as time since last disturbance as originally proposed) and intensity of disturbance in forest landscapes.Methods
The effects of disturbance frequency, intensity, and their interaction on species richness was evaluated using a mixed-effects model.Results
We found that species richness peaks at intermediate frequency after both high and intermediate disturbance intensities, but the richness-frequency relationship differed between intensity classes.Conclusions
Our study highlights the need to measure multiple disturbance components that could help reconcile conflicting empirical results on the effect of disturbance on plant species diversity.7.
8.
Jiangtao Xiao Yu Liang Hong S. He Jonathan R. Thompson Wen J. Wang Jacob S. Fraser Zhiwei Wu 《Landscape Ecology》2017,32(7):1347-1363
Context
Forest landscape models (FLMs) are important tools for simulating forest changes over broad spatial and temporal scales. The ability of FLMs to accurately predict forest changes may be significantly influenced by the formulations of site-scale processes including seedling establishment, tree growth, competition, and mortality.Objective
The objectives of this study were to investigate the effects of site-scale processes and interaction effects of site-scale processes and harvest on landscape-scale forest change predictions.Methods
We compared the differences in species’ distribution (quantified by species’ percent area), total aboveground biomass, and species’ biomass derived from two FLMs: (1) a model that explicitly incorporates stand density and size for each species age cohort (LANDIS PRO), and (2) a model that explicitly tracks biomass for each species age cohort (LANDIS-II with biomass succession extension), which are variants from the LANDIS FLM family with different formulations of site-scale processes.Results
For early successional species, the differences in simulated distribution and biomass were small (mostly less than 5 %). For mid- to late-successional species, the differences in simulated distribution and biomass were relatively large (10–30 %). The differences in species’ biomass predictions were generally larger than those for species’ distribution predictions. Harvest mediated the differences on landscape-scale predictions.Conclusions
The effects of site-scale processes on landscape-scale forest change predictions are dependent on species’ ecological traits such as shade tolerance, seed dispersal, and growth rates.9.
10.
Context
Human and natural systems interact at multiple scales which are context specific in relation to ecosystem service supply. Scenic beauty is recognised as a cultural ecosystem service whose aesthetic value is perceived at a holistic landscape level.Objectives
In this study we provide methodological advancements for assessing the relationship between landscape visual character and scenic beauty based on crowdsourced geographic information. The final aim is to demonstrate, through a case study application, an empirical method for mapping the scenic beauty of complex mountain landscapes from the perspective of observers which are realistically exposed to the environment being evaluated.Methods
We propose a viewshed based approach which relies on visual indicators and the location of visitors retrieved by public image storage analysis. A cluster analysis was used to integrate visual characters of the landscape and visiting users’ preferences.Results
Four different typologies of landscapes were finally characterized by distinct values of visual indicators. The spatial distribution of the landscape typologies presented a clustered pattern, allowing a regionalization of the landscape characters. The analysis of the visiting users’ provenance revealed that visual scale, naturalness and ephemera attract mainly foreign users, while imageability, complexity and historicity attract mostly domestic and local users.Conclusions
The combination of crowdsourced images with visual indicators allows a systematic analysis of landscape scenic beauty properties. In all, by understanding how specific landscape characters contributes to aesthetic service provision we provide a tool for facilitating the visualization and interpretation of complex landscape characters.11.
Context
Forest cover change analyses have revealed net forest gain in many tropical regions. While most analyses have focused solely on forest cover, trees outside forests are vital components of landscape integrity. Quantifying regional-scale patterns of tree cover change, including non-forest trees, could benefit forest and landscape restoration (FLR) efforts.Objectives
We analyzed tree cover change in Southwestern Panama to quantify: (1) patterns of change from 1998 to 2014, (2) differences in rates of change between forest and non-forest classes, and (3) the relative importance of social-ecological predictors of tree cover change between classes.Methods
We digitized tree cover classes, including dispersed trees, live fences, riparian forest, and forest, in very high resolution images from 1998 to 2014. We then applied hurdle models to relate social-ecological predictors to the probability and amount of tree cover gain.Results
All tree cover classes increased in extent, but gains were highly variable between classes. Non-forest tree cover accounted for 21% of tree cover gains, while riparian trees constituted 31% of forest cover gains. Drivers of tree cover change varied widely between classes, with opposite impacts of some social-ecological predictors on non-forest and forest cover.Conclusions
We demonstrate that key drivers of forest cover change, including topography, road distance and historical forest cover, do not explain rates of non-forest tree cover change. Consequently, predictions from medium-resolution forest cover change analyses may not apply to finer-scale patterns of tree cover. We highlight the opportunity for FLR projects to target tree cover classes adapted to local social and ecological conditions.12.
Werner Jud J. Barbro Winkler Bishu Niederbacher Simon Niederbacher Jörg-Peter Schnitzler 《Plant methods》2018,14(1):109
Background
Climate change represents a grand challenge for agricultural productivity. Understanding complex plant traits such as stress tolerance, disease resistance or crop yield is thus essential for breeding and the development of sustainable agriculture strategies. When screening for the most robust plant phenotypes, fast, high-throughput phenotyping represents the means of choice.Results
We have developed a plant phenotyping platform to measure the emission of volatile organic compounds (VOCs), photosynthetic gas exchange and transpiration under ambient, or abiotic and biotic stress conditions. These parameters are highly suitable markers to non-invasively and dynamically study plant growth and plant stress status, making them perfect test variables for long-term, online plant monitoring. Here we introduce the new phenotyping platform, termed VOC-SCREEN, and present results of a first case study with three barley cultivars, demonstrating that the plant’s volatilome can be successfully applied to discriminate different barley varieties.Conclusion
Volatilomics is a promising technique to non-invasively screen for plant phenotypic traits.13.
Context
Annual grass invasions often increase the frequency and extent of wildfire. Climate variability and fire history may have modifying effects on invasion success and its link to changing fire regimes.Objective
Characterize the role of climate variability and fire history in vegetation shifts of an invaded desert landscape.Method
Pre- and post-fire landscape vegetation greenness were assessed on multiple, independent wildfires in Mojave Desert shrublands using a 34 year record of normalized difference vegetation index (NDVI) derived from 1685 Landsat images and matched with a record of precipitation using linear regression.Results
Annual maximum NDVI, and its annual variance of monthly maximum values, were significantly higher on post-fire than pre-fire landscapes. Additionally, post-fire landscapes showed greater sensitivity to antecedent precipitation received the previous 4 months than pre-fire and unburned landscapes. Ground surveys of vegetation indicate that post-fire landscapes show little indication of recovery of native shrub cover and density but instead are dominated by the exotic grass red brome (Bromus rubens L.). Increased NDVI sensitivity to precipitation is likely related to the growth of red brome, which dominates burned landscapes. Record precipitation in the fall of 2004 contributed to the record NDVI values in 2005 likely driven by high density of red brome.Conclusions
The heightened response of post-fire vegetation to extreme and more variable precipitation events appears to be contributing to the emergence of an invasive grass-fire cycle that constrains the re-establishment of fire sensitive native shrubs while reinforcing the dominance of exotic grasses.14.
Amy E. Frazier 《Landscape Ecology》2016,31(2):351-363
Context
Considerable research has examined scale effects for patch-based metrics with the ultimate goal of predicting values at finer resolutions (i.e., downscaling), but results have been inconsistent. Surface metrics have been suggested as an alternative to patch-based metrics, although far less is known about their scaling relationships and downscaling potential. If successful, downscaling would enable integration of disparate datasets and comparison of landscapes using different resolution datasets.Objectives
(1) Determine how surface metrics scale as resolution changes and how consistent those scaling relationships are across landscapes. (2) Test whether these scaling relationships can be accurately downscaled to predict metric values for finer resolutions.Methods
Various scaling functions were fit to 16 surface metrics computed for multiple resolutions for a set of landscapes. Best-fitting functions were then extrapolated to test downscaling behavior (i.e., predict metric value for a finer resolution) for an independent set of validation landscapes. Relative error was assessed between the predicted and true values to determine downscaling robustness.Results
Seven surface metrics (Sa, Sq, S10z, Sdq, Sds, Sdr, Srwi) fit consistently well (R2 > 0.99) with a 3rd order polynomial or power law. Of those, the scaling functions for Sa, Sq, and S10z were able to predict metric values at a finer resolution within 5 %. Three metrics, (Ssk, Sku, Sfd) were also notable in terms of fit and downscaling.Conclusions
Many metrics exhibit consistent scaling relations across resolution, and several are able to accurately predict values at finer resolutions. However, prediction accuracy is likely related to the amount of information lost during aggregation.15.
Context
In response to predominantly local and private approaches to landscape change, landscape ecologists should critically assess the multiscalar influences on landscape design.Objectives
This study develops a governance framework for Nassauer and Opdam’s “Design-in-Science” model. Its objective is to create an approach for examining hierarchical constraints on landscape design in order to investigate linkages among urban greening initiatives, patterns of landscape change, and the broader societal values driving those changes. It aims to provide an integrative and actionable approach for landscape sustainability science.Methods
This framework is examined through an ethnographic study of public policy processes surrounding the urban tree initiatives in Boston, MA; Philadelphia, PA; and Baltimore, MD.Results
These initiatives demonstrate the impact of political and economic decentralization on urban landscape patterns. Their collaborative governance approach incorporates diverse resources to implement programming at a fine-scale. The predominant tree giveaway program fragments the urban and regional forest.Conclusion
Spatial and temporal fragmentation undermines the long-term security of urban greening programs, and it suggests reconsideration of the role of state regimes in driving broad scale spatial planning.16.
Background
The phenological development of the maize crop from emergence through flowering to maturity, usually expressed as a rate (i.e. 1/duration), is largely controlled by temperature in the tropics. Maize plant phenological responses vary between varieties and quantifying these responses can help in predicting the timing and duration of critical periods for crop growth that affect the quality and quantity of seed. We used routine multi-environment trials data of diverse tropical maize varieties to: (1) fit 82 temperature dependent phenology models and select the best model for an individual variety, (2) develop a spatial framework that uses the phenology model to predict at landscape level the length of the vegetative and reproductive phases of diverse varieties of maize in different agro-ecologies. Multi-environment trial data of 22 maize varieties from 16 trials in Kenya, Ethiopia, and Sudan was analyzed and the Levenberg–Marquardt algorithm combined with statistical criteria was applied to determine the best temperature-dependent model.Results
The Briere model, which is not often used in plant phenology, provided the best fit, with observed and predicted days to flowering showing good agreement. Linking the model with temperature and scaling out through mapping gave the duration from emergence to maturity of different maize varieties in areas where maize could potentially be grown.Conclusion
The methodology and framework used in the study provides an opportunity to develop tools that enhance farmers’ ability to predict stages of maize development for efficient crop management decisions and assessment of climate change impacts. This methodology could contribute to increase maize production if used to identify varieties with desired maturity for a specific agro-ecology in in the targeted regions.17.
Stephen R. Shifley Hong S. He Heike Lischke Wen J. Wang Wenchi Jin Eric J. Gustafson Jonathan R. Thompson Frank R. ThompsonIII William D. Dijak Jian Yang 《Landscape Ecology》2017,32(7):1307-1325
Context
Quantitative models of forest dynamics have followed a progression toward methods with increased detail, complexity, and spatial extent.Objectives
We highlight milestones in the development of forest dynamics models and identify future research and application opportunities.Methods
We reviewed milestones in the evolution of forest dynamics models from the 1930s to the present with emphasis on forest growth and yield models and forest landscape models We combined past trends with emerging issues to identify future needs.Results
Historically, capacity to model forest dynamics at tree, stand, and landscape scales was constrained by available data for model calibration and validation; computing capacity; model applicability to real-world problems; and ability to integrate biological, social, and economic drivers of change. As computing and data resources improved, a new class of spatially explicit forest landscape models emerged.Conclusions
We are at a point of great opportunity in development and application of forest dynamics models. Past limitations in computing capacity and in data suitable for model calibration or evaluation are becoming less restrictive. Forest landscape models, in particular, are ready to transition to a central role supporting forest management, planning, and policy decisions.Recommendations
Transitioning forest landscape models to a central role in applied decision making will require greater attention to evaluating performance; building application support staffs; expanding the included drivers of change, and incorporating metrics for social and economic inputs and outputs.18.
Context
Regime shifts are well known for driving penetrating ecological change, yet we do not recognise the consequences of these shifts much beyond species diversity and productivity. Sound represents a multidimensional space that carries decision-making information needed for some dispersing species to locate resources and evaluate their quantity and quality.Objectives
Here we assessed the effect of regime shifts on marine soundscapes, which we propose has the potential function of strengthening the positive or negative feedbacks that mediate ecosystem shifts.Methods
We tested whether biologically relevant cues are altered by regime shifts in kelp forests and seagrass systems and how specific such shifted soundscapes are to the type of driver; i.e. local pollution (eutrophication) vs. global change (ocean acidification).Results
Here, we not only provide the first evidence for regime-shifted soundscapes, but also reveal that the modified cues of shifted ecosystems are similar regardless of spatial scale and type of environmental driver. Importantly, biological sounds can act as functional cues for orientation by dispersing larvae, and observed shifts in soundscape loudness may alter this function.Conclusions
These results open the question as to whether shifted soundscapes provide a functional role in mediating the positive or negative feedbacks that govern the arrival of species associated with driving change or stasis in ecosystem state.19.
Rita Bastos António T. Monteiro Diogo Carvalho Carla Gomes Paulo Travassos João P. Honrado Mário Santos João Alexandre Cabral 《Landscape Ecology》2016,31(4):701-710
Context
Land-use/land-cover (LU/LC) dynamics is one of the main drivers of global environmental change. In the last years, aerial and satellite imagery have been increasingly used to monitor the spatial extent of changes in LU/LC, deriving relevant biophysical parameters (i.e. primary productivity, climate and habitat structure) that have clear implications in determining spatial and temporal patterns of biodiversity, landscape composition and ecosystem services.Objectives
An innovative hierarchical modelling framework was developed in order to address the influence of nested attributes of LU/LC on community-based ecological indicators.Methods
Founded in the principles of the spatially explicit stochastic dynamic methodology (StDM), the proposed methodological advances are supported by the added value of integrating bottom-up interactions between multi-scaled drivers.Results
The dynamics of biophysical multi-attributes of fine-scale subsystem properties are incorporated to inform dynamic patterns at upper hierarchical levels. Since the most relevant trends associated with LU/LC changes are explicitly modelled within the StDM framework, the ecological indicators’ response can be predicted under different social-economic scenarios and site-specific management actions. A demonstrative application is described to illustrate the framework methodological steps, supporting the theoretic principles previously presented.Conclusions
We outline the proposed multi-model framework as a promising tool to integrate relevant biophysical information to support ecosystem management and decision-making.20.
John B. Graham Joan I. Nassauer William S. Currie Herbert Ssegane M. Cristina Negri 《Landscape Ecology》2017,32(5):1023-1037