Integrated modelling for economic valuation of the role of forests and woodlands in drinking water provision to two African cities

Rapidly growing economies often have high population growth, resulting in agricultural expansion in rural areas and increased water demand in urban areas. Conversion of forests and woodlands to agriculture may threaten safe and reliable water supply in cities. This study assesses the regulating functions and economic values of forests and woodlands in meeting the water needs of two major cities in Tanzania and proposes an integrated modelling approach with a scenario-based analysis to estimate costs of water supply avoided by forest conservation. We use the process-based hydrological Soil and Water Assessment Tool (SWAT) to simulate the role of woody habitats in the regulation of hydrological flow and sediment control. We find that the forests and woodlands play a significant role in regulating sediment load in rivers and reducing peak flows, with implications for the water supply from the Ruvu River to Dar es Salaam and Morogoro. A cost-based value assessment under water treatment works conditions up to 2016 suggests that water supply failure due to deforestation would cost Dar es Salaam USD 4.6-17.6 million per year and Morogoro USD 308 thousand per year. Stronger enforcement of forest and woodland protection in Tanzania must balance water policy objectives and food security

Habitat availability explains variation in climate-driven range shifts across multiple taxonomic groups

Range shifting is vital for species persistence, but there is little consensus on why individual species vary so greatly in the rates at which their ranges have shifted in response to recent climate warming. Here, using 40 years of distribution data for 291 species from 13 invertebrate taxa in Britain, we show that interactions between habitat availability and exposure to climate change at the range margins explain up to half of the variation in rates of range shift. Habitat generalists expanded faster than more specialised species, but this intrinsic trait explains less of the variation in range shifts than habitat availability, which additionally depends on extrinsic factors that may be rare or widespread at the range margin. Similarly, while climate change likely underlies polewards expansions, we find that more of the between-species variation is explained by differences in habitat availability than by changes in climatic suitability. A model that includes both habitat and climate, and their statistical interaction, explains the most variation in range shifts. We conclude that climate-change vulnerability assessments should focus as much on future habitat availability as on climate sensitivity and exposure, with the expectation that habitat restoration and protection will substantially improve species' abilities to respond to uncertain future climates

Local costs of conservation exceed those borne by the global majority

Cost data are crucial in conservation planning to identify more efficient and equitable land use options. However, many studies focus on just one cost type and neglect others, particularly those borne locally. We develop, for a high priority conservation area, spatial models of two local costs that arise from protected areas: foregone agricultural opportunities and increased wildlife damage. We then map these across the study area and compare them to the direct costs of reserve management, finding that local costs exceed management costs. Whilst benefits of conservation accrue to the global community, significant costs are borne by those living closest. Where livelihoods depend upon opportunities forgone or diminished by conservation intervention, outcomes are limited. Activities can be displaced (leakage); rules can be broken (intervention does not work); or the intervention forces a shift in livelihood profiles (potentially to the detriment of local peoples’ welfare). These raise concerns for both conservation and development outcomes and timely consideration of local costs is vital in conservation planning tools and processes

Tree demographics and soil charcoal evidence of fire disturbances in an inaccessible forest atop the Mount Lico inselberg, Mozambique

(1) Research aims and rationaleThe sheer rock cliffs of the Mount Lico inselberg, northern Mozambique, is relatively inaccessible to people. A 0.57 km2 forest covers the top of the isolated mountain and the tree demographics and soil offer an opportunity to investigate the long term fire ecology of the forests of the western, leeside of the mountain and potential for changing regional hydroclimate of the Late Holocene. (2) MethodsOn the western side of the mountaintop, a 20x20 m plot was surveyed for tree taxa , heights, and bole diameters. A 220 cm deep pit was dug into the forest soil and analysed to describe the soil texture and carbon content. C harcoal was quantified on sieved subsamples and classified into charcoal morphologies that were then grouped by how readily entrainable on an index score. Three radiocarbon dates were collected from pieces charcoal. (3) ResultsThe forest is a combination of montane and woodland tree taxa that differed from the older, more mesic eastern side and reflected differential disturbance patterns. The reddish loam soils dated to the Middle Holocene. Charcoal was present in all soil subsamples and varied little until increasing consistently during the past millennium. The charcoal morphologies suggested a combination of locally-derived charcoal and charcoal derived from the surrounding lowlands with the latter increasing in the past centuries. (4) Main conclusionsFew Holocene paleoenvironmental records have been developed from tropical soils in Africa and are useful in locations that do not host lakes and wetlands. Both tree demographics and soil charcoal suggest that changing forest disturbance regimes began during the past millennium. An understanding of history informs future conservation and appropriate management of these special places.<br/

Implications of zero-deforestation commitments: forest quality and hunting pressure limit mammal persistence in fragmented tropical landscapes

Zero-deforestation commitments seek to decouple agricultural production and forest loss to improve prospects for biodiversity. However, the effectiveness of methods designed to meet these commitments is poorly understood. In a highly-fragmented tropical landscape dominated by oil palm, we tested the capacity for the High Carbon Stock (HCS) Approach to prioritise forest remnants that sustain mammal diversity. Patches afforded High Priority by HCS protocols (100 ha core area) provided important refuges for IUCN-threatened species and megafauna. However, patch-scale HCS area recommendations conserved only 35% of the mammal community. At least 3,000 ha would be required to retain intact mammal assemblages, with nearly ten times this area needed if hunting pressure was high. While current HCS protocols will safeguard patches capable of sustaining biodiversity, highly-fragmented tropical landscapes typical of zero-deforestation pledges will require thinking beyond the patch, towards strategically configured forest remnants at the landscape-level and enforcing strict controls on hunting

Validating and Linking the GIMMS Leaf Area Index (LAI3g) with Environmental Controls in Tropical Africa

The recent Global Inventory Modeling and Mapping Studies (GIMMS) LAI3g product provides a 30-year global times-series of remotely sensed leaf area index (LAI), an essential variable in models of ecosystem process and productivity. In this study, we use a new dataset of field-based LAITrue to indirectly validate the GIMMS LAI3g product, LAIavhrr, in East Africa, comparing the distribution properties of LAIavhrr across biomes and environmental gradients with those properties derived for LAITrue. We show that the increase in LAI with vegetation height in natural biomes is captured by both LAIavhrr and LAITrue, but that LAIavhrr overestimates LAI for all biomes except shrubland and cropland. Non-linear responses of LAI to precipitation and moisture indices, whereby leaf area peaks at intermediate values and declines thereafter, are apparent in both LAITrue and LAIavhrr, although LAITrue reaches its maximum at lower values of the respective environmental driver. Socio-economic variables such as governance (protected areas) and population affect both LAI responses, although cause and effect are not always obvious: a positive relationship with human population pressure was detected, but shown to be an artefact of both LAI and human settlement covarying with precipitation. Despite these complexities, targeted field measurements, stratified according to both environmental and socio-economic gradients, could provide crucial data for improving satellite-derived LAI estimates, especially in the human-modified landscapes of tropical Africa.Peer reviewe

Climate change, climatic variation and extreme biological responses

Extreme climatic events could be major drivers of biodiversity change, but it is unclear whether extreme biological changes are (i) individualistic (species- or group-specific), (ii) commonly associated with unusual climatic events and/or (iii) important determinants of long-term population trends. Using population time series for 238 widespread species (207 Lepidoptera and 31 birds) in England since 1968, we found that population 'crashes' (outliers in terms of species' year-to-year population changes) were 46% more frequent than population 'explosions'. (i) Every year, at least three species experienced extreme changes in population size, and in 41 of the 44 years considered, some species experienced population crashes while others simultaneously experienced population explosions. This suggests that, even within the same broad taxonomic groups, species are exhibiting individualistic dynamics, most probably driven by their responses to different, short-term events associated with climatic variability. (ii) Six out of 44 years showed a significant excess of species experiencing extreme population changes (5 years for Lepidoptera, 1 for birds). These 'consensus years' were associated with climatically extreme years, consistent with a link between extreme population responses and climatic variability, although not all climatically extreme years generated excess numbers of extreme population responses. (iii) Links between extreme population changes and long-term population trends were absent in Lepidoptera and modest (but significant) in birds. We conclude that extreme biological responses are individualistic, in the sense that the extreme population changes of most species are taking place in different years, and that long-term trends of widespread species have not, to date, been dominated by these extreme changes.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'

Predicting tree distributions in an East African biodiversity hotspot : model selection, data bias and envelope uncertainty

The Eastern Arc Mountains (EAMs) of Tanzania and Kenya support some of the most ancient tropical rainforest on Earth. The forests are a global priority for biodiversity conservation and provide vital resources to the Tanzanian population. Here, we make a first attempt to predict the spatial distribution of 40 EAM tree species, using generalised additive models, plot data and environmental predictor maps at sub 1 km resolution. The results of three modelling experiments are presented, investigating predictions obtained by (1) two different procedures for the stepwise selection of predictors, (2) down-weighting absence data, and (3) incorporating an autocovariate term to describe fine-scale spatial aggregation. In response to recent concerns regarding the extrapolation of model predictions beyond the restricted environmental range of training data, we also demonstrate a novel graphical tool for quantifying envelope uncertainty in restricted range niche-based models (envelope uncertainty maps). We find that even for species with very few documented occurrences useful estimates of distribution can be achieved. Initiating selection with a null model is found to be useful for explanatory purposes, while beginning with a full predictor set can over-fit the data. We show that a simple multimodel average of these two best-model predictions yields a superior compromise between generality and precision (parsimony). Down-weighting absences shifts the balance of errors in favour of higher sensitivity, reducing the number of serious mistakes (i.e., falsely predicted absences); however, response functions are more complex, exacerbating uncertainty in larger models. Spatial autocovariates help describe fine-scale patterns of occurrence and significantly improve explained deviance, though if important environmental constraints are omitted then model stability and explanatory power can be compromised. We conclude that the best modelling practice is contingent both on the intentions of the analyst (explanation or prediction) and on the quality of distribution data; generalised additive models have potential to provide valuable information for conservation in the EAMs, but methods must be carefully considered, particularly if occurrence data are scarce. Full results and details of all species models are supplied in an online Appendix. (C) 2008 Elsevier B.V. All rights reserved

Conducting robust ecological analyses with climate data

Although the number of studies discerning the impact of climate change on ecological systems continues to increase, there has been relatively little sharing of the lessons learnt when accumulating this evidence. At a recent workshop entitled ‘Using climate data in ecological research’ held at the UK Met Office, ecologists and climate scientists came together to discuss the robust analysis of climate data in ecology. The discussions identified three common pitfalls encountered by ecologists: 1) selection of inappropriate spatial resolutions for analysis; 2) improper use of publically available data or code; and 3) insufficient representation of the uncertainties behind the adopted approach. Here, we discuss how these pitfalls can be avoided, before suggesting ways that both ecology and climate science can move forward. Our main recommendation is that ecologists and climate scientists collaborate more closely, on grant proposals and scientific publications, and informally through online media and workshops. More sharing of data and code (e.g. via online repositories), lessons and guidance would help to reconcile differing approaches to the robust handling of data. We call on ecologists to think critically about which aspects of the climate are relevant to their study system, and to acknowledge and actively explore uncertainty in all types of climate data. And we call on climate scientists to make simple estimates of uncertainty available to the wider research community. Through steps such as these, we will improve our ability to robustly attribute observed ecological changes to climate or other factors, while providing the sort of influential, comprehensive analyses that efforts to mitigate and adapt to climate change so urgently require