Homeward bound:canopy cover and species identity influence non-breeding season homing success and speed in forest birds

Background:Efficient and safe movement is fundamental for wild birds to thrive in their environments.For arboreal forest animals,especially birds,canopy cover has a large impact on birds’daily movements and is a crucial component of conservation strategies seeking to retain avian population in disturbed or urban habitats.Methods:We translocated woodland bird species utilizing different forest strata during two non-breeding seasons in Gainesville,FL,USA.We used linear model and generalized linear model to examine the effects of canopy cover and species identity on homing success and speed.Results:Among our study species of Tufted Titmouse(Baeolophus bicolor),Carolina Chickadee(Poecile carolinensis),and Northern Cardinal(Cardinalis cardinalis),we found that Carolina Chickadees and Tufted Titmice were more likely to return than Northern Cardinals.Among birds that successfully returned,homing speed is significantly affected by forest canopy cover and species identity(titmice had higher homing speed than cardinals).Birds return much faster in landscape with higher canopy cover.Conclusions:This study presented evidence of species identity’s effect on homing success and speed in common feeder bird species in Southeast US and provided further evidence that bird movements in the suburban land cover are constrained by low canopy cover.

Quality Assessment of River Offin along a Canopy Cover Gradient

The potential effect of canopy cover on the quality of River Offin which serves as drinking water for communities including Hwediem, Mprim and Boanim in the Mampong Municipality of the Ashanti region of Ghana was studied. These communities exemplify Ghanaian farming communities. Often, rural farmers do not have access to clean water. Using the part of the river serving these communities as a test case, we assessed the quality of water along a gradient of three different levels of canopy cover (closed, semi-closed and open canopy) where residents frequently access water. Physico-chemical tests showed that, the level of most of the physical and chemical properties of the water under all three different canopy covers was within the acceptable limits set by the World Health Organization. There was low turbidity where the canopy was closed resulting in relatively lower faecal coliforms. Total dissolved solids were also less where canopy cover was closed. Therefore, the general water quality could be potentially improved by planting trees along the river to form canopy.

Improving the estimation of canopy cover from UAV-LiDAR data using a pit-free CHM-based method

Accurate and rapid estimation of canopy cover(CC)is crucial for many ecological and environmental models and for forest management.Unmanned aerial vehicle-light detecting and ranging(UAV-LiDAR)systems represent a promising tool for CC estimation due to their high mobility,low cost,and high point density.However,the CC values from UAV-LiDAR point clouds may be underestimated due to the presence of large quantities of within-crown gaps.To alleviate the negative effects of within-crown gaps,we proposed a pit-free CHM-based method for estimating CC,in which a cloth simulation method was used to fill the within-crown gaps.To evaluate the effect of CC values and withincrown gap proportions on the proposed method,the performance of the proposed method was tested on 18 samples with different CC values(40−70%)and 6 samples with different within-crown gap proportions(10−60%).The results showed that the CC accuracy of the proposed method was higher than that of the method without filling within-crown gaps(R^(2)=0.99 vs 0.98;RMSE=1.49%vs 2.2%).The proposed method was insensitive to within-crown gap proportions,although the CC accuracy decreased slightly with the increase in withincrown gap proportions.

Effects of environmental factors on species richness patterns of herb layer in Eastern Zhongtiao Mountain

The species richness of herb layer was investigated among 43 plots of forest vegetation in the eastern Zhongtiao Mountain, in southern Shanxi Province, China. The forest vegetation was divided into two major vegetation types such as the deciduous forest and the coniferous forest by the two-way indicator species analysis （TWINSPAN）. The species richness of herb layer was fitted in the topographic and soil feature factors, as well as the topographic relative moisture index （TRMI） by the generalized linear models （GLM）. The results showed that canopy cover and altitude were the most significant environmental factors. Soil pH value and soil nutrients index such as total N, organic matter content had no significant influence. The effect of environment factors on species richness of herb layer had significant difference in vegetation types. For the broad-leaved forest, litter depth and TRMI were the important environment factors. For the coniferous forest, soil clay content was another important environment factor. The range of environmental gradient such as altitude may contribute to the difference.

Seed germination and seedling establishment of Neotropical dry forest species in response to temperature and light conditions

A study was conducted to examine the germination requirements of Cedrela odorata, Guaiacum sanctum and Calycophyllum candidissimum seeds, and the effect of light intensity on survival and growth of C. odorata and G. sanctum seedlings planted on open, partially-open and beneath the canopy of a dry forest in Nicaragua. The results show that germination of C. candidissimum seeds was signifi- cantly higher in light than darkness at constant temperatures ranging from 20-35℃. Both C. odorata and G. sanctum seeds germinated in light and darkness to a varying extent, and the optimal germination temperature was around 20-25℃. Alternating temperature regimes did not improve germination. Survival of G. sanctum seedlings was 70% beneath the canopy and 80% in the open, and its relative growth rate in collar diameter was 1.88 mm/month in the open and 1.42 mm/month in the understory. Survival was generally poor for C. odorata, particularly in the understory. We concluded that light is an absolute requirement for the germination of C. candidissimum seeds while germination of C. odorata and G. sanctum seeds are more sensitive to temperature. Owing to its high survival rate on open site, G. sanctum could serve as a candidate species for reforestation of degraded sites.

Forest fragmentation and human population varies logarithmically along elevation gradient in Hindu Kush Himalaya-utility of geospatial tools and free data set

Hindu Kush Himalaya(HKH) is the largest and the most diverse mountain region in the world that provides ecosystem services to one fifth of the total world population. The forests are fragmented to different degrees due to expansion and intensification of human land use. However, the quantitative relationship between fragmentation and demography has not been established before for HKH vis-à-vis along elevation gradient. We used the globally available tree canopy cover data derived from Landsat-TM satellite to find out the decadal forest cover change over 2000 to 2010 and their corresponding fragmentation levels. Using SRTMderived DEM, we observed high forest cover loss up to2400 m that highly corroborated with the population distribution pattern as derived from satellite observation. In general, forest cover loss was found to be higher in south-eastern part of HKH. Forest fragmentation obtained using ‘area-weighted mean radius of gyration' as indicator, was found to be very high up to 2400 m that also corroborated with high human population for the year 2000 and 2010. We observed logarithmic decrease in fragmentation change(area-weighted mean radius of gyration value),forest cover loss and population growth during 2000-2010 along the elevation gradient with very high R^2 values(i.e., 0.889, 0.895, 0.944 respectively). Our finding on the pattern of forest fragmentation and human population across the elevation gradient in HKH region will have policy level implication for different nations and would help in characterizing hotspots of change. Availability of free satellite derived data products on forest cover and DEM, griddata on demography, and utility of geospatial tools helped in quick evaluation of the forest fragmentation vis-a-vis human impact pattern along the elevation gradient in HKH.

Seed germination and seedling establishment of Neotropical dry forest species in response to temperature and light conditions

A study was conducted to examine the germination requirements of Cedrela odorata, Guaiacum sanctum and Calycophyllum candidissimum seeds, and the effect of light intensity on survival and growth of C.odorata and G.sanctum seedlings planted on open, partially-open and beneath the canopy of a dry forest in Nicaragua.The results show that germination of C.candidissimum seeds was significantly higher in light than darkness at constant temperatures ranging from 20-35oC.Both C.odorata and G.sanctum seeds germinated in light and darkness to a varying extent, and the optimal germination temperature was around 20-25oC.Alternating temperature regimes did not improve germination.Survival of G.sanctum seedlings was 70% beneath the canopy and 80% in the open, and its relative growth rate in collar diameter was 1.88 mm/month in the open and 1.42 mm/month in the understory.Survival was generally poor for C.odorata, particularly in the understory.We concluded that light is an absolute requirement for the germination of C.candidissimum seeds while germination of C.odorata and G.sanctum seeds are more sensitive to temperature.Owing to its high survival rate on open site, G.sanctum could serve as a candidate species for reforestation of degraded sites.

Estimating oak forest parameters in the western mountains of Iran using satellite-based vegetation indices

Remote sensing is an important tool for studying and modeling forest stands.Vegetation indices obtained from Landsat-8 remotely sensed data were used to estimate the forest parameters in the western mountains of Iran.Thirtyfour sample points were selected on the map of Bayangan County,Kermanshah province,Iran.At each point,a cluster of five rectangular plots of 8100 m2 and 200 m apart was established.Some clusters were primarily sampled to determine the variance of the forest parameters.The coefficient of variation was used as a criterion for sample allocation.Stand density,canopy cover and basal area per hectare were calculated for each plot.Vegetation indices were extracted fromthe Landsat-8 images for each plot.Simple linear and nonlinear regressions were conducted to develop the models.The models were validated using an independent data set.Stability of model parameters was statistically evaluated.The results showed that Normalized difference vegetation index(NDVI)and Transformed normalized difference vegetation index(TNDVI)followed by Simple ratio vegetation index(SRVI)were the best predictors,explaining up to 91%of the variations with high precision.For NDVI,Soil adjusted vegetation index 2(SAVI2)and SRVI,the cubic model was more appropriate than the linear model for predicting the forest parameters.For this model,the R-square value increased while NRMSE decreased significantly.For Infrared percentage vegetation index(IPVI),the quadratic model was better,but,for other vegetation indices,nonlinear models were not superior to linear ones.Finally,it can be concluded that Landsat-8 imagery is suitable for predicting forest parameters in the oak forests of western Iran.Of course,large plots must be selected,and pre-classification is necessary to gain accurate and precise estimations.

Digital surface model applied to unmanned aerial vehicle based photogrammetry to assess potential biotic or abiotic effects on grapevine canopies

Accurate data acquisition and analysis to obtain crop canopy information are critical steps to understand plant growth dynamics and to assess the potential impacts of biotic or abiotic stresses on plant development.A versatile and easy to use monitoring system will allow researchers and growers to improve the follow-up management strategies within farms once potential problems have been detected.This study reviewed existing remote sensing platforms and relevant information applied to crops and specifically grapevines to equip a simple Unmanned Aerial Vehicle(UAV)using a visible high definition RGB camera.The objective of the proposed Unmanned Aerial System(UAS)was to implement a Digital Surface Model(DSM)in order to obtain accurate information about the affected or missing grapevines that can be attributed to potential biotic or abiotic stress effects.The analysis process started with a three-dimensional(3D)reconstruction from the RGB images collected from grapevines using the UAS and the Structure from Motion(SfM)technique to obtain the DSM applied on a per-plant basis.Then,the DSM was expressed as greyscale images according to the halftone technique to finally extract the information of affected and missing grapevines using computer vision algorithms based on canopy cover measurement and classification.To validate the automated method proposed,each grapevine row was visually inspected within the study area.The inspection was then compared to the digital assessment using the proposed UAS in order to validate calculations of affected and missing grapevines for the whole studied vineyard.Results showed that the percentage of affected and missing grapevines was 9.5%and 7.3%,respectively from the area studied.Therefore,for this specific study,the abiotic stress that affected the experimental vineyard(frost)impacted a total of 16.8%of plants.This study provided a new method for automatically surveying affected or missing grapevines in the field and an evaluation tool for plant growth conditions,which can be implemented for other uses such as canopy management,irrigation scheduling and other precision agricultural applications.

High resolution aerial photogrammetry based 3D mapping of fruit crop canopies for precision inputs management

Rapid and accurate canopy attributes estimation is highly critical in fruit crops production management as this information can be used for canopy and crop load management as well as to develop nutrient/chemical prescription application maps.However,the existing ground based canopy sensing and attribute estimation methods are laborious and often involve complexity with field data collection and analysis.Manual methods can be subjec-tive as well.Therefore,this study explores aerial photogrammetry based method of tree–row–volume(TRV),leaf–wall–area(LWA),canopy volume(CV)and canopy cover(CC)esti-mation for grapevine and apple canopies.Remote sensing data was collected using a con-sumer–grade small unmanned aerial system(UAS)with an RGB imaging sensor flying at different flight altitudes i.e.,15 m(Ground sampling distance,GSD=0.45 cm pixel^(-1) at 65°sensor inclination),30 m(0.90 and 0.85 cm pixel^(-1) at 65°and 75°,respectively),45 m(1.35 and 1.27 cm pixel^(-1) at 65°and 75°,respectively)and 60 m(1.81 and 1.69 cm pixel^(-1) at 65°and 75°,respectively).Crop surface model(CSM)was derived from such data to esti-mate canopy height,width and foliage vigor,which are further used to estimate TRV,LWA,CV and CC.The ground measured and aerial imagery estimated TRV had a strong relation-ship with the data collected at the lowest GSD within grapevine canopies(R^(2)=0.77 at 0.45 cm pixel^(-1)as well as for apple canopies(R^(2)=0.82 at 0.90 cm pixel^(-1).Similar trends were observed for the LWA(R^(2)=0.77 and 0.86),CV(R^(2)=0.43 and 0.64)and CC(R^(2)=0.61 and 0.68)estimates for grapevine and apple canopies,respectively.Increasing GSD(≥0.45 cm pixel^(-1) in grapevine and≥0.90 cm pixel^(-1) in apple)resulted in a weak relationship between ground measurements and aerial imagery data-based estimates for grapevines(R^(2)=0.36)and apple canopies(R^(2)=0.39–0.78).Overall,the aerial flights with lower GSD and double grid missions with RGB imaging sensor in 65°orientation aided in the development of site–specific high–quality canopy vigor maps that can be used in precision crop inputs management related decision making.

A survey of high resolution image processing techniques for cereal crop growth monitoring

This paper presents a survey of image processing techniques proposed in the literature forextracting key cereal crop growth metrics from high spatial resolution, typically proximalimages. The descriptive crop growth metrics considered are: crop canopy cover, aboveground biomass, leaf area index (including green area index), chlorophyll content, andgrowth stage. The paper includes an overview of relevant fundamental image processingtechniques including camera types, colour spaces, colour indexes, and image segmentation. The descriptive crop growth metrics are defined. Reference methods for groundtruth measurement are described. Image processing methods for metric estimation aredescribed in detail. The performance of the methods is reviewed and compared. The surveyreveals limitations in image processing techniques for cereal crop monitoring such as lackof robustness to lighting conditions, camera position, and self-obstruction. Directions forfuture research to improve performance are identified.