Using satellite data to assess spatial drivers of bird diversity.

Birds are useful indicators of overall biodiversity, which continues to decline globally, despite targets to reduce its loss. The aim of this paper is to understand the importance of different spatial drivers for modelling bird distributions. Specifically, it assesses the importance of satellite-derived measures of habitat productivity, heterogeneity and landscape structure for modelling bird diversity across Great Britain. Random forest (RF) regression is used to assess the extent to which a combination of satellite-derived covariates explain woodland and farmland bird diversity and richness. Feature contribution analysis is then applied to assess the relationships between the response variable and the covariates in the final RF models. We show that much of the variation in farmland and woodland bird distributions is explained (R 2 0.64-0.77) using monthly habitat-specific productivity values and landscape structure (FRAGSTATS) metrics. The analysis highlights important spatial drivers of bird species richness and diversity, including high productivity grassland during spring for farmland birds and woodland patch edge length for woodland birds. The feature contribution provides insight into the form of the relationship between the spatial drivers and bird richness and diversity, including when a particular spatial driver affects bird richness positively or negatively. For example, for woodland bird diversity, the May 80th percentile Normalized Difference Vegetation Index (NDVI) for broadleaved woodland has a strong positive effect on bird richness when NDVI is >0.7 and a strong negative effect below. If relationships such as these are stable over time, they offer a useful analytical tool for understanding and comparing the influence of different spatial drivers.

An extended PROSPECT: Advance in the leaf optical properties model separating total chlorophylls into chlorophyll a and b.

The PROSPECT leaf optical model has, to date, well-separated the effects of total chlorophyll and carotenoids on leaf reflectance and transmittance in the 400-800 nm. Considering variations in chlorophyll a:b ratio with leaf age and physiological stress, a further separation of total plant-based chlorophylls into chlorophyll a and chlorophyll b is necessary for advanced monitoring of plant growth. In this study, we present an extended version of PROSPECT model (hereafter referred to as PROSPECT-MP) that can combine the effects of chlorophyll a, chlorophyll b and carotenoids on leaf directional hemispherical reflectance and transmittance (DHR and DHT) in the 400-800 nm. The LOPEX93 dataset was used to evaluate the capabilities of PROSPECT-MP for spectra modelling and pigment retrieval. The results show that PROSPECT-MP can both simultaneously retrieve leaf chlorophyll a and b, and also performs better than PROSPECT-5 in retrieving carotenoids concentrations. As for the simulation of DHR and DHT, the performances of PROSPECT-MP are similar to that of PROSPECT-5. This study demonstrates the potential of PROSPECT-MP for improving capabilities of remote sensing of leaf photosynthetic pigments (chlorophyll a, chlorophyll b and carotenoids) and for providing a framework for future refinements in the modelling of leaf optical properties.

Variability in the Effectiveness of Two Ornithological Survey Methods between Tropical Forest Ecosystems.

Birds are a frequently chosen group for biodiversity monitoring as they are comparatively straightforward and inexpensive to sample and often perform well as ecological indicators. Two commonly used techniques for monitoring tropical forest bird communities are point counts and mist nets. General strengths and weaknesses of these techniques have been well-defined; however little research has examined how their effectiveness is mediated by the ecology of bird communities and their habitats. We examine how the overall performance of these methodologies differs between two widely separated tropical forests-Cusuco National Park (CNP), a Honduran cloud forest, and the lowland forests of Buton Forest Reserves (BFR) located on Buton Island, Indonesia. Consistent survey protocols were employed at both sites, with 77 point count stations and 22 mist netting stations being surveyed in each location. We found the effectiveness of both methods varied considerably between ecosystems. Point counts performed better in BFR than in CNP, detecting a greater percentage of known community richness (60% versus 41%) and generating more accurate species richness estimates. Conversely, mist netting performed better in CNP than in BFR, detecting a much higher percentage of known community richness (31% versus 7%). Indeed, mist netting proved overall to be highly ineffective within BFR. Best Akaike's Information Criterion models indicate differences in the effectiveness of methodologies between study sites relate to bird community composition, which in turn relates to ecological and biogeographical influences unique to each forest ecosystem. Results therefore suggest that, while generalized strengths and weaknesses of both methodologies can be defined, their overall effectiveness is also influenced by local characteristics specific to individual study sites. While this study focusses on ornithological surveys, the concept of local factors influencing effectiveness of field methodologies may also hold true for techniques targeting a wide range of taxonomic groups; this requires further research.

Does the Establishment of Sustainable Use Reserves Affect Fire Management in the Humid Tropics?

Tropical forests are experiencing a growing fire problem driven by climatic change, agricultural expansion and forest degradation. Protected areas are an important feature of forest protection strategies, and sustainable use reserves (SURs) may be reducing fire prevalence since they promote sustainable livelihoods and resource management. However, the use of fire in swidden agriculture, and other forms of land management, may be undermining the effectiveness of SURs in meeting their conservation and sustainable development goals. We analyse MODIS derived hot pixels, TRMM rainfall data, Terra-Class land cover data, socio-ecological data from the Brazilian agro-census and the spatial extent of rivers and roads to evaluate whether the designation of SURs reduces fire occurrence in the Brazilian Amazon. Specifically, we ask (1) a. Is SUR location (i.e., de facto) or (1) b. designation (i.e. de jure) the driving factor affecting performance in terms of the spatial density of fires?, and (2), Does SUR creation affect fire management (i.e., the timing of fires in relation to previous rainfall)? We demonstrate that pre-protection baselines are crucial for understanding reserve performance. We show that reserve creation had no discernible impact on fire density, and that fires were less prevalent in SURs due to their characteristics of sparser human settlement and remoteness, rather than their status de jure. In addition, the timing of fires in relation to rainfall, indicative of local fire management and adherence to environmental law, did not improve following SUR creation. These results challenge the notion that SURs promote environmentally sensitive fire-management, and suggest that SURs in Amazonia will require special attention if they are to curtail future accidental wildfires, particularly as plans to expand the road infrastructure throughout the region are realised. Greater investment to support improved fire management by farmers living in reserves, in addition to other fire users, will be necessary to help ameliorate these threats.

Meta-Analysis of the Detection of Plant Pigment Concentrations Using Hyperspectral Remotely Sensed Data.

Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550-560nm) and red edge (680-750nm) regions; chlorophyll b on the red, (630-660nm), red edge (670-710nm) and the near-infrared (800-810nm); carotenoids on the 500-580nm region; and anthocyanins on the green (550-560nm), red edge (700-710nm) and near-infrared (780-790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a.

The effects of gap size on some microclimate variables during late summer and autumn in a temperate broadleaved deciduous forest.

The creation of gaps can strongly influence forest regeneration and habitat diversity within forest ecosystems. However, the precise characteristics of such effects depend, to a large extent, upon the way in which gaps modify microclimate and soil water content. Hence, the aim of this study was to understand the effects of gap creation and variations in gap size on forest microclimate and soil water content. The study site, in North West England, was a mixed temperate broadleaved deciduous forest dominated by mature sessile oak (Quercus petraea), beech (Fagus sylvatica) and ash (Fraxinus excelsior) with some representatives of sycamore (Acer pseudoplatanus). Solar radiation (I), air temperature (T(A)), soil temperature (T(S)), relative humidity (h), wind speed (v) and soil water content (Psi) were measured at four natural treefall gaps created after a severe storm in 2006 and adjacent sub-canopy sites. I, T(A), T(S), and Psi increased significantly with gap size; h was consistently lower in gaps than the sub-canopy but did not vary with gap size, while the variability of v could not be explained by the presence or size of gaps. There were systematic diurnal patterns in all microclimate variables in response to gaps, but no such patterns existed for Psi. These results further our understanding of the abiotic and consequent biotic responses to gaps in broadleaved deciduous forests created by natural treefalls, and provide a useful basis for evaluating the implications of forest management practices.

Monitoring conservation effectiveness in a global biodiversity hotspot: the contribution of land cover change assessment.

Tropical forests, which play critical roles in global biogeochemical cycles, radiation budgets and biodiversity, have undergone rapid changes in land cover in the last few decades. This study examines the complex process of land cover change in the biodiversity hotspot of Western Ghats, India, specifically investigating the effects of conservation measures within the Indira Gandhi Wildlife Sanctuary. Current vegetation patterns were mapped using an IRS P6 LISS III image and this was used together with Landsat MSS data from 1973 to map land cover transitions. Two major and divergent trends were observed. A dominant degradational trend can be attributed to agricultural expansion and infrastructure development while a successional trend, resulting from protection of the area, showed the resilience of the system after prolonged disturbances. The sanctuary appears susceptible to continuing disturbances under the current management regime but at lower rates than in surrounding unprotected areas. The study demonstrates that remotely sensed land cover assessments can have important contributions to monitoring land management strategies, understanding processes underpinning land use changes and helping to inform future conservation strategies.

Hyperspectral remote sensing of plant pigments.

The dynamics of pigment concentrations are diagnostic of a range of plant physiological properties and processes. This paper appraises the developing technologies and analytical methods for quantifying pigments non-destructively and repeatedly across a range of spatial scales using hyperspectral remote sensing. Progress in deriving predictive relationships between various characteristics and transforms of hyperspectral reflectance data are evaluated and the roles of leaf and canopy radiative transfer models are reviewed. Requirements are identified for more extensive intercomparisons of different approaches and for further work on the strategies for interpreting canopy scale data. The paper examines the prospects for extending research to the wider range of pigments in addition to chlorophyll, testing emerging methods of hyperspectral analysis and exploring the fusion of hyperspectral and LIDAR remote sensing. In spite of these opportunities for further development and the refinement of techniques, current evidence of an expanding range of applications in the ecophysiological, environmental, agricultural, and forestry sciences highlights the growing value of hyperspectral remote sensing of plant pigments.