Discriminating Crop, Weeds and Soil Surface with a Terrestrial LIDAR Sensor

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R 2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying

Using ICESAT\u27s geoscience laser altimeter system to assess large scale forest disturbance caused by Hurricane Katrina

We assessed the use of GLAS data as a tool to quantify large-scale forest damage. GLAS data for the year prior to and following Hurricane Katrina were compared to wind speed, forest cover, and MODIS NPV maps to analyze senor sampling, and changes in mean canopy height. We detected significant losses in mean canopy height post-Katrina that increased with wind intensity, from ∼.5m in forests hit by tropical storm winds to ∼4m in forests experiencing category two force winds. Season of data acquisition was shown to influence calculations of mean canopy height. There was insufficient sampling to adequately detect changes at one degree resolution and less. We observed a strong relationship between delta NPV and post storm mean canopy heights. Changes in structure were converted into loss of standing carbon estimates using a height structured ecosystem model, yielding above ground carbon storage losses of ∼30Tg over the domain

Estimation of the Conifer-Broadleaf Ratio in Mixed Forests Based on Time-Series Data

Most natural forests are mixed forests, a mixed broadleaf-conifer forest is essentially a heterogeneously mixed pixel in remote sensing images. Satellite missions rely on modeling to acquire regional or global vegetation parameter products. However, these retrieval models often assume homogeneous conditions at the pixel level, resulting in a decrease in the inversion accuracy, which is an issue for heterogeneous forests. Therefore, information on the canopy composition of a mixed forest is the basis for accurately retrieving vegetation parameters using remote sensing. Medium and high spatial resolution multispectral time-series data are important sources for canopy conifer-broadleaf ratio estimation because these data have a high frequency and wide coverage. This paper highlights a successful method for estimating the conifer-broadleaf ratio in a mixed forest with diverse tree species and complex canopy structures. Experiments were conducted in the Purple Mountain, Nanjing, Jiangsu Province of China, where we collected leaf area index (LAI) time-series and forest sample plot inventory data. Based on the Invertible Forest Reflectance Model (INFORM), we simulated the normalized difference vegetation index (NDVI) time-series of different conifer-broadleaf ratios. A time-series similarity analysis was performed to determine the typical separable conifer-broadleaf ratios. Fifteen Gaofen-1 (GF-1) satellite images of 2015 were acquired. The conifer-broadleaf ratio estimation was based on the GF-1 NDVI time-series and semi-supervised k-means cluster method, which yielded a high overall accuracy of 83.75%. This study demonstrates the feasibility of accurately estimating separable conifer-broadleaf ratios using field measurement data and GF-1 time series in mixed broadleaf-conifer forests

다중 규모 LiDAR 데이터를 활용한 도시생태계 구조 및 연결성 평가

학위논문(박사) -- 서울대학교대학원 : 환경대학원 협동과정 조경학, 2021.8. 송영근.Integrated multiscale light detection and ranging (LiDAR) datasets are required for managing urban ecosystems because 1) LiDAR datasets can represent various spatial structures across the urban landscape and 2) the multitemporal LiDAR approach can derive the changes of urban landscape structures. This dissertation aimed to find the various spatiotemporal availabilities (i.e., from the tree-level spatial scale to the city-level regional scale with the multitemporal approach) of LiDAR or laser scanning (LS) datasets for monitoring urban ecosystems in the following three chapters. Chapter 2: Collecting tree inventory data in urban areas is important for managing green areas. Surveying using airborne laser scanning (ALS) is effective for collecting urban tree structures but less efficient regarding the economic costs and its operation. Terrestrial laser scanning (TLS), and mobile laser scanning (MLS) datasets could have the potential in complementing those of ALS in the respect to efficiency. However, to the best of my knowledge, there were limited studies for seeking the similarities and variations among the canopy metrics derived from various LiDAR platforms. In Chapter 2, I compared structural canopy metrics among ALS, TLS, and MLS datasets in the urban parks. The purpose of Chapter 2 was to test whether the estimates of tree metrics differed depending on single or clustered trees and to test whether the errors in LiDAR-derived metrics were related to the tree structures. Small, urban parks were selected for surveying trees using the three LiDAR platforms. The ALS datasets were acquired on 14 May, 2017. The TLS and MLS datasets were acquired from 10–11 May, 2017, and 21–25 April, 2020, respectively. The tree point clouds were classified into single and clustered trees. The structural metrics were compared in each pair (i.e., ALS and TLS, ALS and MLS, and TLS and MLS pairs). The heights related metrics (e.g., percentile heights and the distribution of the heights values), the complexity metric (e.g., the Rumple index) and area were calculated for comparisons. The root mean square error (RMSE), bias, and the Pearson’s correlation coefficient (r) were calculated to evaluate the difference in each metric among the LiDAR platforms. The results showed that ZMAX, max and mean CHM, and area showed good consistencies (RMSE% 0.900). Especially, the biases of CHM-derived metrics did not present significant differences (p > 0.05) regardless of single or clustered trees. Moreover, the biases from the comparisons in each pair showed linear relations with the tree heights and vertical canopy complexity (i.e., Pearson’s correlation coefficient showed significant; r >0.29, p < 0.05). My results could be references when combining multiple LiDAR systems to estimate the canopy structures of urban park areas. Chapter 3: Understanding forest dynamics is important for assessing the health of urban forests, which experience various disturbances, both natural (e.g., treefall events) and artificial (e.g., making space for agricultural fields). Therefore, quantifying three-dimensional (3D) changes in canopies is a helpful way to manage and understand urban forests better. Multitemporal ALS datasets enable me to quantify the vertical and lateral growth of trees across a landscape scale. The goal of Chapter 3 is to assess the annual changes in the 3-D structures of canopies and forest gaps in an urban forest using annual airborne LiDAR datasets for 2012–2015. The canopies were classified as high canopies and low canopies by a 5 m height threshold. Then, I generated pixel- and plot-level canopy height models and conducted change detection annually. The vertical growth rates and leaf area index showed consistent values year by year in both canopies, while the spatial distributions of the canopy and leaf area profile (e.g., leaf area density) showed inconsistent changes each year in both canopies. In total, high canopies expanded their foliage from 12 m height, while forest gap edge canopies (including low canopies) expanded their canopies from 5 m height. Annual change detection with LiDAR datasets might inform about both steady growth rates and different characteristics in the changes of vertical canopy structures for both high and low canopies in urban forests. Chapter 4: Although many studies have considered urban structure when investigating urban ecological networks, few have considered the 3D structure of buildings as well as urban green spaces. In Chapter 4, I examined an urban ecological network using the 3D structure of both green spaces and buildings. Using breeding-season bird species observations and ALS data collected, I assessed the influence of 3D structural variables on species diversity. I used correlation analyses to determine if vertical distribution, volume, area, and height of both buildings and vegetation were related to bird species diversity. Then I conducted circuit theory-based current flow betweenness centrality (CFBC) analysis using the LiDAR-derived structural variables. I found that the volumes of buildings and 8–10 m vegetation heights were both highly correlated with species richness per unit area. There were significant differences between 2D and 3D connectivity analysis using LiDAR-derived variables among urban forest patches, boulevards, and apartment complexes. Within urban forest patches and parks, 3D CFBC represented canopy structural characteristics well, by showing high variance in spatial distributions. The 3D CFBC results indicated that adjacent high-rise buildings, dense apartment complexes, and densely urbanized areas were isolated, as characterized by low centrality values, but that vegetation planted in open spaces between buildings could improve connectivity by linking isolated areas to core areas. My research highlights the importance of considering 3D structure in planning and managing urban ecological connectivity. In this dissertation, the availability of integrated multiscale LiDAR datasets was found via three standalone studies. It was revealed that 3D information could enhance the quality of urban landscape monitoring and ecological connectivity analysis by elaborately explaining spatial structures. However, the spatiotemporal scales of each standalone study were limited to the city scale and to five years. The recently launched Global Ecosystem Dynamics Investigation (GEDI) would help to solve these limitations. Furthermore, the GEDI dataset could help researchers understand the relationship between ecosystem structures and their functions.본 학위논문은 다양한 시공간 스케일에서 도시생태계 모니터링을 위한 LiDAR 데이터의 활용과 생태적 의미 도출에 관한 내용을 다룬다. LiDAR란 Light Detection and Ranging의 약어로, LiDAR 센서에서 발사된 레이저가 대상에 도달한 뒤 반사되어 돌아오는 레이저의 세기와 시간을 계산하여 대상의 위치 정보를 3차원 점군 데이터로 변환해주는 능동형 원격탐사 도구이다. LiDAR 원격탐사 도구의 등장으로 자연과 도시의 3차원 공간정보의 취득이 기능해짐에 따라, 서식지의 3차원 공간정보와 생물 종 사이의 관계 도출, 시계열 LiDAR 데이터를 활용한 녹지 모니터링 연구 등이 이뤄지고 있다. 또한 항공 LiDAR(ALS), 지상 LiDAR(TLS), 이동형 LiDAR(MLS) 등 다양한 LiDAR 시스템의 개발로 연구 목적에 알맞은 시공간 해상도의 3차원 공간정보를 취득할 수 있게 되었다. 본 학위논문에서는 도시녹지를 대상으로 LiDAR 원격탐사 도구의 다양한 시공간 스케일 적용 측면에서, Chapter 2 항공, 지상, 이동형 LiDAR 시스템 사이 수목구조관련 변수들의 일치성 평가, Chapter 3 시계열 분석을 통한 도시녹지 동태 모니터링, Chapter 4 도시의 생태적 연결성 분석을 진행하였다. Chapter 2: 도시의 수목정보를 취득하는 것은 도시녹지 관리에 있어 필수적이다. LiDAR 기술의 발달로 도시수목의 3차원 정보를 취득할 수 있게 되었으며, 이를 통해 수목높이와 수목구조, 지상 바이오매스 등을 높은 정확도로 산출할 수 있게 되었다. 항공 LiDAR는 넓은 범위의 공간정보를 높은 정확도로 측정하는 특성을 지녀 산림 모니터링 분야에서 활발히 활용되고 있다. 하지만 항공 LiDAR 데이터의 취득은 항공기 운용비, 장비관련 막대한 비용이 발생하고 운용에 있어 전문성을 요구하며 대상의 점군밀도가 상대적으로 낮다는 단점을 지닌다. 반면 지상 LiDAR와 이동형 LiDAR는 운용하기 편리하고 높은 점군밀도를 출력한다는 점에서 항공 LiDAR의 단점을 극복할 수 있다. 이처럼 다양한 LiDAR 시스템의 등장과 이를 활용한 생태계 모니터링 연구 시도가 증가하면서 LiDAR 시스템간 효율적인 운용과 데이터의 보완 방법들이 요구되고 있다. 하지만 현재까지 ALS, TLS, MLS의 3개의 시스템을 통해 취득된 수목 정보를 서로 비교하고, 서로 대체가능한 수목정보를 도출한 연구는 많이 진행된 바 없다. 따라서 본 학위논문의 Chapter 2에서는 ALS, TLS, MLS 통해 취득된 도시의 수목정보를 서로 비교하여 일치성을 평가하고, 어떠한 수목구조관련 지표가 세 LiDAR 시스템 사이에서 대체가능한지 다루고 있다. 세부적으로 Chapter 2는 수목구조관련 지표가 단목차원과 군집차원, 수목구조에 따라 ALS, TLS, MLS 시스템에서 차이가 발생하는지에 대한 내용을 담고 있다. 천안시 도시공원 9개소에서 ALS 데이터는 2017년 5월 14일, TLS 데이터는 2017년 5월 10일과 11일, MLS 데이터는 2020년 4월 21에서 25일 취득되었다. 취득된 데이터셋은 수관의 겹침 여부에 따라 단목과 군집으로 분류되었으며, 3개의 페어(ALS-TLS, MLS-TLS, ALS-MLS)로 수관의 퍼센타일 높이, 수관복잡성, 면적 등의 수목구조관련 변수들을 1:1 비교하였다. 항공 LiDAR 데이터를 통해 도출된 수목구조관련 변수들을 참조로 하여 평균제곱근오차(RMSE), 편향(bias), 피어슨 상관계수(r) 등을 계산하고 세 LiDAR 시스템 사이의 일치성을 평가하였다. 평가 결과 ZMAX, CHM관련 수관높이 관련 변수들, 그리고 수관면적이 높은 일치성을 보였다(RMSE% 0.900). 특히 CHM을 통해 도출된 수관높이 관련 변수들은 단목과 군집에서 세개의 LiDAR 시스템간 통계적인 차이를 보이지 않았다(p > 0.05). 반면 퍼센타일 수관높이와 평균 수관높이 등은 매우 낮은 일치성을 나타냈으며, 세 페어에서 도출된 편향은 수고, 수관복잡성과 약한 선형관계를 나타냈다(r >, p < 0.05). Chapter 3: 수관동태는 숲의 건강성을 반영한다. 특히, 자연적·인위적인 교란에 의해 발생한 숲틈은 숲 내부에 빛의 투과율, 온도, 습도 등에 영향을 끼쳐 주변 환경의 변화를 야기한다. 따라서 숲틈을 탐지하고 모니터링하는 것은 숲의 동태를 이해하는데 있어 매우 중요하다. 항공 LiDAR 센서를 활용할 경우 위성영상이나 항공사진 등 2차원 데이터로 탐지하기 어려운 숲틈 또는 개방공간의 탐지와 수관의 3차원 형상의 취득이 가능하다. Chapter 3에서는 2012년도부터 2015년도 4개년의 항공 LiDAR를 활용하여 자연형 도시공원(봉서산)의 수관과 숲틈의 수평적 수직적 변화양상을 추정하였다. 수관은 높이 5m를 기준으로 상층부와 하층부 수관으로 분류되었으며, 수관높이모델(canopy height model, CHM)을 생성하여 연간변화를 탐지하였다. 연구결과 상층부 및 하층부 수관의 수직생장량과 엽면적지수는 일정한 연간 변화양상을 보인 반면, 수평적 변화와 엽면적밀도는 불규칙적인 연간 변화양상을 보였다. 전반적으로 상층부 수관은 높이 12m에서 측방향 생장을 하는 것으로 나타났으며, 하층부 수관 중 숲틈에서는 높이 5m에서 측방향 생장이 활발하게 나타났다. LiDAR 데이터의 연간 변화 탐지를 통해 자연적으로 형성된 숲틈의 경우 생장과 교란 측면에서 매우 활발한 동태가 발생하고 있으며, 인위적으로 형성된 개방공간의 경우 수관의 동태가 다소 침체됨을 도출하였다. Chapter 4는 도시 내 건물과 녹지의 3차원 구조를 입력자료로 활용하여 도시의 생태적 연결성을 평가하는 연구를 다룬다. 도시 내 생태적 연결성 도출과 관련한 연구는 도시와 녹지의 형태 등을 주요 변수로 하여 진행이 되고 있다. 그러나 3차원적인 특성인 도시 건물의 부피, 수목의 수직적인 구조 등을 고려한 연결성 분석은 많이 진행된 바 없다. 연구 대상지는 천안시 시청을 중심으로한 4 km × 4 km 지역으로, 2015년에 취득된 항공 LiDAR와 같은 해 취득된 조류 종 조사 데이터를 활용하여 1)도시 내 건물과 녹지의 3차원 구조와 조류 종 다양성 사이 관계를 살피고, 2)조류 종 다양성과 상관관계를 가지는 3차원 구조변수를 활용하여 전류흐름기반 매개중심성 연결성 분석(CFBC)을 진행하였다. 연구결과 건축물의 부피와 수목높이 8-10m의 녹지 부피비가 면적당 조류 종 풍부도와 스피어만 순위상관관계에서 높은 상관관계(ρ> 0.6)를 나타냈다. 연결성 분석의 결과는 입력변수의 공간차원(2D 및 3D)에 따라 다르게 나타났다. 특히 도시숲, 대로변, 아파트단지내 녹지 등에서 2D 기반 CFBC와 3D기반 CFBC는 통계적으로 유의미한 차이를 보였다. 또한 도시녹지의 3D 기반 CFBC의 경우 같은 녹지 면적임에도 수관의 구조적인 특성에 따라 높은 차이가 나타남을 확인하였다. 3D CFBC 분석결과를 통해 고층 건물 주변부, 고밀도 아파트단지, 고밀 시가화지역 등이 낮은 중심성을 보여 고립지역으로 나타났으며, 건물 사이 공지 내 식생은 연결성이 고립된 지역과 핵심지역을 연결하는 기능을 나타냈다. 이 학위논문은 서로 다른 LiDAR 시스템을 활용하여 단목, 경관 지역단위 등 다양한 공간 스케일에서의 도시경관구조 분석, 도시녹지구조와 토지이용 등에 따른 시간적 변화양상, 도시경관구조가 가지는 생태적 의미 등과 관련된 내용을 다루고 있다. 향후 Global Ecosystem Dynamics Investigation(GEDI) 미션의 데이터를 활용하여 본 학위논문에서 다루는 지역규모의 연구를 국가단위, 대륙단위 등으로 확장할 수 있을 것이며 이를 통해 도시생태계 구조와 그 기능 사의 관계를 이해하는데 도움을 줄 수 있을 것이다.Chapter 1. Introduction 1 1. Background 1 1.1. Urbanization and the importance of urban green spaces 1 1.2. Urban landscape and Light detection and ranging application 1 2. Purpose 6 Chapter 2. Comparing tree structures derived among multiple LiDAR systems in urban parks 10 1. Introduction 10 2. Methods and materials 12 2.1. Study site and tree classification 12 2.2. LiDAR survey and processing 14 2.3. Deriving the structural variables of the parks 17 2.4. Assessing the accuracy of the LiDAR-derived indices 18 3. Results 19 3.1. Comparing height metrics among the three LiDAR systems 19 3.2. Comparing CHM-derived canopy height metrics from each LiDAR systems 22 3.3. Comparing the area and the Rumple index determined using the LiDAR systems 23 4. Discussion 25 4.1. LiDAR configurations and data acquisition time intervals 25 4.2. Uncertainty of the structural indices derived from the three LiDAR systems 28 Chapter 3. Urban forest growth and gap dynamics detected by yearly repeated airborne LiDAR 31 1. Introduction 31 2. Methods and Materials 33 2.1. Field survey 33 2.2. Canopy opening detection 34 2.3. Airborne LiDAR dataset acquisition and registration 35 2.4. Generation of height models and change detection 36 2.5. Gap detection and classification 38 2.6. Estimating changes of vertical canopy distribution and canopy complexity 38 3. Results 39 3.1. Pixel and hexagon height model-based change detection 39 3.2. Continuous one-year vertical growth area 41 3.3. Open canopy change detection 42 3.4. Changes in vertical canopy structures in High Canopy and Open Canopy 43 4. Discussion 45 4.1. What are the differences between the canopy structural changes derived from annual change detections and three-year interval change detection? 45 4.2. What are the characteristics of the structural changes according to the different canopy classes (e.g., high canopies and low canopies) in the urban forest? 46 Chapter 4. LiDAR-derived three-dimensional ecological connectivity mapping 49 1. Introduction 49 2. Materials and Methods 51 2.1. Study area and avian species observation 52 2.2. Airborne LiDAR acquisition, preprocessing and classification and deriving structural variables 53 2.3. Correlation analysis and selection of structural variables 55 2.4. 2D and 3D ecological networks 55 3. Results 56 3.1. Avian species survey 56 3.2. Correlation analyses and variable selection 56 3.3. Connectivity analysis results 58 3.4. Correlation between connectivity results with bird species diversity 59 3.5. Differences between 2D- and 3D-based CFBCs 60 4. Discussion 61 4.1. Vegetation and building structures and bird species diversity 61 4.2. 3D-based connectivity results 62 4.3. Differences between 2D and 3D network analyses 64 4.3.1. Forest and artificial green area 65 4.3.2. Roads and residential areas 66 Appendix 67 Chapter 5. Conclusion 70 1. Combination with multiple LiDAR data for surveying structures of urban green spaces 70 2. Multi-temporal urban forest gap monitoring 71 3. Ecological connectivity analysis using LiDAR 71 4. LiDAR application to Urban ecosystem monitoring 72 5. Expanding spatiotemporal scale and further works 73 Acknowledgments 75 Reference 76 Abstract in Korean 85박

Height to Crown Base Modelling for the Main Tree Species in an Even-Aged Pedunculate Oak Forest: A Case Study from Central Croatia

The height to crown base (hcb) is a critical measure used in many investigations as an input variable to investigate the vigour of the stands, the social position of the trees, and to evaluate the behaviour of forest fires, among other uses. Though measuring height-related variables in the field is always time-consuming, the foremost benefits offered by modelling hcb are that it permits to generalize and average a very uneven attribute and, furthermore, provides insights about which tree and stand variables have a significant impact on hcb. However, there are many species in which models of the crown base height have not been developed in Croatia. The objective of this research was to develop a height to base crown model for each of the main species present in the two-layered mixed stands of this study. According to previous investigations, logistic models provide the highest precision and require the lowest inventory cost owing to less frequent measurements. Tree- and plot-level variables with distance-independent competition indexes were studied in the fitting model. In this research, we obtained models for the main stand species: Acer campestre (root mean squared error (RMSE) = 2.28 m, R2 = 82.80%); Alnus glutinosa (RMSE = 1.78 m, R2 = 85.36%); Carpinus betulus (RMSE = 2.47 m, R2 = 67.55%); Fraxinus angustifolia (RMSE = 2.46 m, R2 = 82.45%); Quercus robur (RMSE = 2.60 m, R2 = 80.57%); Tilia sp. (RMSE = 2.01 m, R2 = 89.07%); and Ulmus laevis (RMSE = 1.71 m, R2 = 92.42%). The combination of the total height, tree, and plot-level variables with distance-independent competition indexes contributed to the prediction accuracy of proposed model significantly

Investigating within-canopy variation of functional traits and cellular structure of sugar maple (Acer saccharum) leaves

Patterns of increasing leaf mass per area (LMA), area-based leaf nitrogen (Narea), and carbon isotope composition (δ13C) with increasing height in the canopy have been attributed to light gradients or hydraulic limitation in tall trees. Theoretical optimal distributions of LMA and Narea that scale with light maximize canopy photosynthesis; however, sub-optimal distributions are often observed due to hydraulic constraints on leaf development. Using observational, experimental, and modeling approaches, we investigated the response of leaf functional traits (LMA, density, thickness, and leaf nitrogen), leaf carbon isotope composition (δ13C), and cellular structure to light availability, height, and leaf water potential (Ψl) in an Acer saccharum forest to tease apart the influence of light and hydraulic limitations. LMA, leaf and palisade layer thickness, and leaf density were greater at greater light availability but similar heights, highlighting the strong control of light on leaf morphology and cellular structure. Experimental shading decreased both LMA and area-based leaf nitrogen (Narea) and revealed that LMA and Narea were more strongly correlated with height earlier in the growing season and with light later in the growing season. The supply of CO2 to leaves at higher heights appeared to be constrained by stomatal sensitivity to vapor pressure deficit (VPD) or midday leaf water potential, as indicated by increasing δ13C and VPD and decreasing midday Ψl with height. Model simulations showed that daily canopy photosynthesis was biased during the early growing season when seasonality was not accounted for, and was biased throughout the growing season when vertical gradients in LMA and Narea were not accounted for. Overall, our results suggest that leaves acclimate to light soon after leaf expansion, through an accumulation of leaf carbon, thickening of palisade layers and increased LMA, and reduction in stomatal sensitivity to Ψl or VPD. This period of light acclimation in leaves appears to optimize leaf function over time, despite height-related constraints early in the growing season. Our results imply that vertical gradients in leaf functional traits and leaf acclimation to light should be incorporated in canopy function models in order to refine estimates of canopy photosynthesis

Changes in the Lepidoptera of Monks Wood NNR (1974-2003)

Introduction Monks Wood has been noted for the richness of its Lepidoptera, particularly butterflies, sinceat least the middle of the 19th century. In 1828 the black hairstreak was discovered for the first time in Britain in Monks Wood. A total of 48 butterfly species have been recorded in the Monks Wood area but today only 30 species (including two non-resident migrants) can be found there. Most of the losses had occurred by the time the Monks Wood book (Steele & Welch 1973) was published (Table 1). Less is known historically about the moth fauna. Steele & Welch (1973) listed some 129 microlepidoptera and 332 macrolepidoptera (hereafter referred to as macro-moths). These records came from variety of sources collated from the many collectors who had visited Monks Wood for well over a century. The list includes some species that have not been recorded in recent decades, some of which are almost certainly extinct in the wood (Table 2). The number of microlepidoptera recorded in the wood has greatly increased but no current list has been compiled. The current list of macro-moths stands at 460 species. Monks Wood has contributed to national recording schemes for both butterflies (Butterfly Monitoring Scheme – BMS) and moths (Rothamsted Insect Survey) for three decades and it is these standardised observations that allow an examination of change within Monks Wood and a comparison with national statistics. An earlier study by Pollard and others (1998), using these data, concluded that an increase in coarse grasses had benefited Lepidoptera feeding on them at the expense of those feeding on finer grasses. Several possible causes included ride management practices, the colonisation of the wood by muntjac, and an increase in atmospheric nitrogen deposition. In the current study we examine both the butterfly transect data and the Rothamsted Insect Survey (light trap) moth data for changes over the last 30 year