Random prism: an alternative to random forests

Ensemble learning techniques generate multiple classifiers, so called base classifiers, whose combined classification results are used in order to increase the overall classification accuracy. In most ensemble classifiers the base classifiers are based on the Top Down Induction of Decision Trees (TDIDT) approach. However, an alternative approach for the induction of rule based classifiers is the Prism family of algorithms. Prism algorithms produce modular classification rules that do not necessarily fit into a decision tree structure. Prism classification rulesets achieve a comparable and sometimes higher classification accuracy compared with decision tree classifiers, if the data is noisy and large. Yet Prism still suffers from overfitting on noisy and large datasets. In practice ensemble techniques tend to reduce the overfitting, however there exists no ensemble learner for modular classification rule inducers such as the Prism family of algorithms. This article describes the first development of an ensemble learner based on the Prism family of algorithms in order to enhance Prism’s classification accuracy by reducing overfitting.

REDD+ and community-controlled forests in low-income countries: any hope for a linkage?

Deforestation and forest degradation are estimated to account for between 12% and 20% of annual greenhouse gas emissions and in the 1990s (largely in the developing world) released about 5.8 Gt per year, which was bigger than all forms of transport combined. The idea behind REDD + is that payments for sequestering carbon can tip the economic balance away from loss of forests and in the process yield climate benefits. Recent analysis has suggested that developing country carbon sequestration can effectively compete with other climate investments as part of a cost effective climate policy. This paper focuses on opportunities and complications associated with bringing community-controlled forests into REDD +. About 25% of developing country forests are community controlled and therefore it is difficult to envision a successful REDD + without coming to terms with community controlled forests. It is widely agreed that REDD + offers opportunities to bring value to developing country forests, but there are also concerns driven by worries related to insecure and poorly defined community forest tenure, informed by often long histories of government unwillingness to meaningfully devolve to communities. Further, communities are complicated systems and it is therefore also of concern that REDD + could destabilize existing well-functioning community forestry systems.

Persistent reduced ecosystem respiration after insect disturbance in high elevation forests

Amid a worldwide increase in tree mortality, mountain pine beetles (Dendroctonus ponderosae Hopkins) have led to the death of billions of trees from Mexico to Alaska since 2000. This is predicted to have important carbon, water and energy balance feedbacks on the Earth system. Counter to current projections, we show that on a decadal scale, tree mortality causes no increase in ecosystem respiration from scales of several square metres up to an 84 km2 valley. Rather, we found comparable declines in both gross primary productivity and respiration suggesting little change in net flux, with a transitory recovery of respiration 6–7 years after mortality associated with increased incorporation of leaf litter C into soil organic matter, followed by further decline in years 8–10. The mechanism of the impact of tree mortality caused by these biotic disturbances is consistent with reduced input rather than increased output of carbon.

Random Prism: a noise-tolerant alternative to Random Forests

Ensemble learning can be used to increase the overall classification accuracy of a classifier by generating multiple base classifiers and combining their classification results. A frequently used family of base classifiers for ensemble learning are decision trees. However, alternative approaches can potentially be used, such as the Prism family of algorithms that also induces classification rules. Compared with decision trees, Prism algorithms generate modular classification rules that cannot necessarily be represented in the form of a decision tree. Prism algorithms produce a similar classification accuracy compared with decision trees. However, in some cases, for example, if there is noise in the training and test data, Prism algorithms can outperform decision trees by achieving a higher classification accuracy. However, Prism still tends to overfit on noisy data; hence, ensemble learners have been adopted in this work to reduce the overfitting. This paper describes the development of an ensemble learner using a member of the Prism family as the base classifier to reduce the overfitting of Prism algorithms on noisy datasets. The developed ensemble classifier is compared with a stand-alone Prism classifier in terms of classification accuracy and resistance to noise.

Impact of a drier Early-Mid-Holocene climate upon Amazonian forests

This paper uses a palaeoecological approach to examine the impact of drier climatic conditions of the Early-Mid-Holocene (ca 8000-4000 years ago) upon Amazonia's forests and their fire regimes. Palaeovegetation (pollen data) and palaeofire (charcoal) records are synthesized from 20 sites within the present tropical forest biome, and the underlying causes of any emergent patterns or changes are explored by reference to independent palaeoclimate data and present-day patterns of precipitation, forest cover and fire activity across Amazonia. During the Early-Mid-Holocene, Andean cloud forest taxa were replaced by lowland tree taxa as the cloud base rose while lowland ecotonal areas, which are presently covered by evergreen rainforest, were instead dominated by savannahs and/or semi-deciduous dry forests. Elsewhere in the Amazon Basin there is considerable spatial and temporal variation in patterns of vegetation disturbance and fire, which probably reflects the complex heterogeneous patterns in precipitation and seasonality across the basin, and the interactions between climate change, drought- and fire susceptibility of the forests, and Palaeo-Indian land use. Our analysis shows that the forest biome in most parts of Amazonia appears to have been remarkably resilient to climatic conditions significantly drier than those of today, despite widespread evidence of forest burning. Only in ecotonal areas is there evidence of biome replacement in the Holocene. From this palaeoecological perspective, we argue against the Amazon forest 'dieback' scenario simulated for the future.

Forests of the tropical eastern Andean flank during the middle pleistocene

Inter-bedded volcanic and organic sediments from Erazo (Ecuador) indicate the presence of four different forest assemblages on the eastern Andean flank during the middle Pleistocene. Radiometric dates (40Ar–39Ar) obtained fromthe volcanic ash indicate that deposition occurred between 620,000 and 192,000 years ago. Examination of the organic sediment composition and the fossil pollen, wood and charcoal it contains provides insight into depositional environment, vegetation assemblage and fire history. The high organic content and abundance of macro fossils found throughout the sediment suggest that during the period of deposition the local environment was either a swamp or a shallow water body. The correlation of fire activity (peaks in charcoal abundance) with volcanic ash deposits through most of the record suggests that volcanoes were the main source of ignition. The low abundance of grass (typically b10%) throughout the sedimentary sequence along with the low abundance of other taxa indicative of open vegetation suggests the persistence of forest at Erazo. Four types of forest assemblage were identified (with the first taxa as the most dominant): i) Alnus-Arecaceae, ii) Miconia- Melastomataceae/Combretaceae-Moraceae/Urticaceae, iii) Arecaceae-Alnus, and iv) Podocarpus with Oreopanax sp. and Melastomataceae/Combretaceae. Changes in the forest floristic composition indicate high vegetation turnover and reassortment of taxa between upper and lower montane forests during the middle Pleistocene as well as the persistence of forest cover.

MODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests

Context: Variation in photosynthetic activity of trees induced by climatic stress can be effectively evaluated using remote sensing data. Although adverse effects of climate on temperate forests have been subjected to increased scrutiny, the suitability of remote sensing imagery for identification of drought stress in such forests has not been explored fully. Aim: To evaluate the sensitivity of MODIS-based vegetation index to heat and drought stress in temperate forests, and explore the differences in stress response of oaks and beech. Methods: We identified 8 oak and 13 beech pure and mature stands, each covering between 4 and 13 MODIS pixels. For each pixel, we extracted a time series of MODIS NDVI from 2000 to 2010. We identified all sequences of continuous unseasonal NDVI decline to be used as the response variable indicative of environmental stress. Neural Networks-based regression modelling was then applied to identify the climatic variables that best explain observed NDVI declines. Results: Tested variables explained 84–97% of the variation in NDVI, whilst air temperature-related climate extremes were found to be the most influential. Beech showed a linear response to the most influential climatic predictors, while oak responded in a unimodal pattern suggesting a better coping mechanism. Conclusions: MODIS NDVI has proved sufficiently sensitive as a stand-level indicator of climatic stress acting upon temperate broadleaf forests, leading to its potential use in predicting drought stress from meteorological observations and improving parameterisation of forest stress indices.

Multi‐method global sensitivity analysis (MMGSA) for modelling floodplain hydrological processes

When studying hydrological processes with a numerical model, global sensitivity analysis (GSA) is essential if one is to understand the impact of model parameters and model formulation on results. However, different definitions of sensitivity can lead to a difference in the ranking of importance of the different model factors. Here we combine a fuzzy performance function with different methods of calculating global sensitivity to perform a multi-method global sensitivity analysis (MMGSA). We use an application of a finite element subsurface flow model (ESTEL-2D) on a flood inundation event on a floodplain of the River Severn to illustrate this new methodology. We demonstrate the utility of the method for model understanding and show how the prediction of state variables, such as Darcian velocity vectors, can be affected by such a MMGSA. This paper is a first attempt to use GSA with a numerically intensive hydrological model.

Multi-method global sensitivity analysis (MMGSA) for modelling floodplain hydrological processes

When studying hydrological processes with a numerical model, global sensitivity analysis (GSA) is essential if one is to understand the impact of model parameters and model formulation on results. However, different definitions of sensitivity can lead to a difference in the ranking of importance of the different model factors. Here we combine a fuzzy performance function with different methods of calculating global sensitivity to perform a multi-method global sensitivity analysis (MMGSA). We use an application of a finite element subsurface flow model (ESTEL-2D) on a flood inundation event on a floodplain of the River Severn to illustrate this new methodology. We demonstrate the utility of the method for model understanding and show how the prediction of state variables, such as Darcian velocity vectors, can be affected by such a MMGSA. This paper is a first attempt to use GSA with a numerically intensive hydrological model

The development of soil organic matter in restored biodiverse Jarrah forests of South-Western Australia as determined by ASE and GCMS

Background, aim and scope Soil organic matter (SOM) is known to increase with time as landscapes recover after a major disturbance; however, little is known about the evolution of the chemistry of SOM in reconstructed ecosystems. In this study, we assessed the development of SOM chemistry in a chronosequence (space for time substitution) of restored Jarrah forest sites in Western Australia. Materials and methods Replicated samples were taken at the surface of the mineral soil as well as deeper in the profile at sites of 1, 3, 6, 9, 12, and 17 years of age. A molecular approach was developed to distinguish and quantify numerous individual compounds in SOM. This used accelerated solvent extraction in conjunction with gas chromatography mass spectrometry. A novel multivariate statistical approach was used to assess changes in accelerated solvent extraction (ASE)-gas chromatography-mass spectrometry (GCMS) spectra. This enabled us to track SOM developmental trajectories with restoration time. Results Results showed total carbon concentrations approached that of native forests soils by 17 years of restoration. Using the relate protocol in PRIMER, we demonstrated an overall linear relationship with site age at both depths, indicating that changes in SOM chemistry were occurring. Conclusions The surface soils were seen to approach native molecular compositions while the deeper soil retained a more stable chemical signature, suggesting litter from the developing diverse plant community has altered SOM near the surface. Our new approach for assessing SOM development, combining ASE-GCMS with illuminating multivariate statistical analysis, holds great promise to more fully develop ASE for the characterisation of SOM.

Mining in Ghana’s forests: cross-sectoral linkages and the prospects for REDD

Strategies to Reduce Emissions from Deforestation and Degradation (REDD) are being pursued in numerous developing countries. Proponents contest that REDD mechanisms could deliver sustainable development by contributing to both environmental protection and economic development, particularly in poor forest communities. However, among the challenges to REDD, and natural resource management more generally, is the need to develop a comprehensive understanding of cross-sectoral linkages and addressing how they impact the pursuit of sustainable development. Drawing on an exploratory case-study of Ghana, this paper aims to outline the linkages between the forestry and minerals sectors. It is argued that contemporary debates give incommensurate attention to the reclamation of large-scale mine sites located in forest reserves, and neglect to consider more nuanced links which characterise the forestry-mining nexus in Ghana. A review of key stakeholders further elucidates the complex networks which characterise these linkages and highlights the important role of traditional authorities in governing across sectors. If the multiple roles of local resource users and traditional authorities continue to be neglected in policy mechanisms, schemes such as REDD will continue to fall short of achieving sustainable development.

Trees for development? Articulating the ambiguities of power, authority and legitimacy in governing Ghana’s mineral rich forests

The growth of mining activities in Africa in the last decade has coincided with increased attention on the fate of the continent’s forests, specifically in the contexts of livelihoods and climate change. Although mining has serious environmental impacts, scant attention has been paid to the processes which shape decision-making in contexts where minerals and forests overlap. Focussing on the illustrative case of Ghana, this paper articulates the dynamics of power, authority and legitimacy of private companies, traditional authorities and key state institutions in governing mining activities in forests. The analysis highlights how mining companies and donors promote a neoliberal model of resource management which entrenches their ability to benefit from mineral exploitation and marginalises the role of state institutions and traditional authorities in decision-making. This subsequently erodes state authority and legitimacy and compounds the contested nature of traditional authorities’ legitimacy. A more nuanced examination of foundational governance questions concerning the relative role of the state, traditional authorities and private interests is needed.

Differentiation of neotropical ecosystems by modern soil phytolith assemblages and its implications for palaeoenvironmental and archaeological reconstructions II: Southwestern Amazonian forests

Accurate archaeological and palaeoenvironmental reconstructions using phytoliths relies on the study of modern reference material. In eastern Acre, Brazil, we examined whether the five most common forest types present today were able to be differentiated by their soil phytolith assemblages, and thus provide analogues with which to compare palaeoecological assemblages from pre-Columbian earthwork sites in the region. Surface soils and vegetation from dense humid evergreen forest, dense humid evergreen forest with high palm abundance, palm forest, bamboo forest and fluvial forest were sampled and their phytoliths analysed. Relative phytolith frequencies were statistically compared using Principal Components Analyses (PCAs). We found the major differences in species composition to be well-represented by the phytolith assemblages as all forest types, apart from the two sub-types of dense humid evergreen forest, could be differentiated. Larger phytoliths from the sand fraction were found to be more ecologically diagnostic than those from the silt fraction. The surface soil phytolith assemblages we analysed can therefore be used as analogues to improve the accuracy of archaeological and palaeoecological reconstructions in the region.