Global evidence that deforestation amplifies flood risk and severity in the developing world

With the wide acceptance of forest‐protection policies in the developing world comes a requirement for clear demonstrations of how deforestation may erode human well‐being and economies. For centuries, it has been believed that forests provide protection against flooding. However, such claims have given rise to a heated polemic, and broad‐scale quantitative evidence of the possible role of forests in flood protection has not been forthcoming. Using data collected from 1990 to 2000 from 56 developing countries, we show using generalized linear and mixed‐effects models contrasted with information‐theoretic measures of parsimony that flood frequency is negatively correlated with the amount of remaining natural forest and positively correlated with natural forest area loss (after controlling for rainfall, slope and degraded landscape area). The most parsimonious models accounted for over 65% of the variation in flood frequency, of which nearly 14% was due to forest cover variables alone. During the decade investigated, nearly 100 000 people were killed and 320 million people were displaced by floods, with total reported economic damages exceeding US$1151 billion. Extracted measures of flood severity (flood duration, people killed and displaced, and total damage) showed some weaker, albeit detectable correlations to natural forest cover and loss. Based on an arbitrary decrease in natural forest area of 10%, the model‐averaged prediction of flood frequency increased between 4% and 28% among the countries modeled. Using the same hypothetical decline in natural forest area resulted in a 4–8% increase in total flood duration. These correlations suggest that global‐scale patterns in mean forest trends across countries are meaningful with respect to flood dynamics. Unabated loss of forests may increase or exacerbate the number of flood‐related disasters, negatively impact millions of poor people, and inflict trillions of dollars in damage in disadvantaged economies over the coming decades. This first global‐scale empirical demonstration that forests are correlated with flood risk and severity in developing countries reinforces the imperative for large‐scale forest protection to protect human welfare, and suggests that reforestation may help to reduce the frequency and severity of flood‐related catastrophes.     

北京城市土地利用/覆盖变化及其对雨洪调节服务的影响

深入认识城市土地利用/覆盖变化对雨洪调节服务的影响对于提升城市生态系统服务和雨洪管理具有重要意义。基于多期Landsat遥感影像,利用混合像元分解与人工目视解译集成的方法提取了北京市1991—2014年的土地利用/覆盖数据,模拟评估了不同降雨情景下的地表产流与雨洪调节服务,并分析了城市建成区的土地利用/覆盖变化对雨洪调节服务的影响。结果表明:1991—2014年,北京城市用地面积增长了1096.53 km²,建成区内不透水面比例上升了9.83%。城市建成区雨洪调节服务总体呈下降趋势,1a、10a、25a和100a一遇降雨情景下平均地表径流调节率分别下降了5.37%、2.40%、1.75%和1.04%,一定程度上加剧了城市的雨洪产流风险。同时,城市新扩张区的土地利用/覆盖变化对雨洪调节服务的影响较老城区更强,贡献度超过84%。建议未来城市新区发展应合理配置不透水地表和绿地空间以提升城市雨洪调节服务。     

Deforestation and Reforestation of Latin America and the Caribbean (2001–2010)

Forest cover change directly affects biodiversity, the global carbon budget, and ecosystem function. Within Latin American and the Caribbean region (LAC), many studies have documented extensive deforestation, but there are also many local studies reporting forest recovery. These contrasting dynamics have been largely attributed to demographic and socio‐economic change. For example, local population change due to migration can stimulate forest recovery, while the increasing global demand for food can drive agriculture expansion. However, as no analysis has simultaneously evaluated deforestation and reforestation from the municipal to continental scale, we lack a comprehensive assessment of the spatial distribution of these processes. We overcame this limitation by producing wall‐to‐wall, annual maps of change in woody vegetation and other land‐cover classes between 2001 and 2010 for each of the 16,050 municipalities in LAC, and we used nonparametric Random Forest regression analyses to determine which environmental or population variables best explained the variation in woody vegetation change. Woody vegetation change was dominated by deforestation (?541,835 km²), particularly in the moist forest, dry forest, and savannas/shrublands biomes in South America. Extensive areas also recovered woody vegetation (+362,430 km²), particularly in regions too dry or too steep for modern agriculture. Deforestation in moist forests tended to occur in lowland areas with low population density, but woody cover change was not related to municipality‐scale population change. These results emphasize the importance of quantitating deforestation and reforestation at multiple spatial scales and linking these changes with global drivers such as the global demand for food.     

Weather and landscape factors associated with adult mosquito abundance in southwestern Georgia, U.S.A

Mosquito community composition and population dynamics were compared to weather variables and land use/cover data during 2008 to determine which variables affected population dynamics at the J.W. Jones Ecological Research Center in southwestern Georgia. Models relating adult mosquito distributions to weather variables and time of year were compared using Akaike's Information Criterion (AIC) model selection. Precipitation, temperature, humidity, and Keetch-Byram Drought Index were important factors correlated with mosquito abundance or presence/absence for the species considered. A cluster analysis, which grouped eight sites based on the percentages of land use/cover and hydric soils located in a 1-km radius surrounding collection sites, and an indicator species analysis were used to investigate the associations among 11 mosquito species and sites with similar land use/cover. Aedes albopictus (Skuse), Culex coronator Dyar & Knab, Culex quinquefasciatus Say, and Culex salinarius Coquillett were associated with sites that had the most anthropogenic influence, while Coquillettidia perturbans (Walker) and Psorophora ferox (von Humboldt) were associated with natural land cover such as wetlands and forested land. This study demonstrates that regional climate and land use/cover data can be predictive of the population dynamics of certain mosquito populations and is the first to examine how the distribution of Cx. coronator adults relate to land use/cover in the southeastern United States.     

Anticipated climate and land‐cover changes reveal refuge areas for Borneo's orang‐utans

Habitat loss and climate change pose a double jeopardy for many threatened taxa, making the identification of optimal habitat for the future a conservation priority. Using a case study of the endangered Bornean orang‐utan, we identify environmental refuges by integrating bioclimatic models with projected deforestation and oil‐palm agriculture suitability from the 1950s to 2080s. We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s. We then projected to the 2020s, 2050s and 2080s in models incorporating only land‐cover change, climate change or both processes combined. For future climate, we incorporated projections from four model and emission scenario combinations. For future land cover, we developed spatial deforestation predictions from 10 years of satellite data. Refuges were delineated as suitable forested habitats identified by all models that were also unsuitable for oil palm – a major threat to tropical biodiversity. Our analyses indicate that in 2010 up to 260 000 km² of Borneo was suitable habitat within the core orang‐utan range; an 18–24% reduction since the 1950s. Land‐cover models predicted further decline of 15–30% by the 2080s. Although habitat extent under future climate conditions varied among projections, there was majority consensus, particularly in north‐eastern and western regions. Across projections habitat loss due to climate change alone averaged 63% by 2080, but 74% when also considering land‐cover change. Refuge areas amounted to 2000–42 000 km² depending on thresholds used, with 900–17 000 km² outside the current species range. We demonstrate that efforts to halt deforestation could mediate some orang‐utan habitat loss, but further decline of the most suitable areas is to be expected given projected changes to climate. Protected refuge areas could therefore become increasingly important for ongoing translocation efforts. We present an approach to help identify such areas for highly threatened species given environmental changes expected this century.     

Simulating the response of land-cover changes to road paving and governance along a major Amazon highway: the Santarém–Cuiabá corridor

The spatial distribution of human activities in forest frontier regions is strongly influenced by transportation infrastructure. With the planned paving of 6000 km of highway in the Amazon Basin, agricultural frontier expansion will follow, triggering potentially large changes in the location and rate of deforestation. We developed a land‐cover change simulation model that is responsive to road paving and policy intervention scenarios for the BR‐163 highway in central Amazonia. This corridor links the cities of Cuiabá, in central Brazil, and Santarém, on the southern margin of the Amazon River. It connects important soybean production regions and burgeoning population centers in Mato Grosso State with the international port of Santarém, but 1000 km of this road are still not paved. It is within this context that the Brazilian government has prioritized the paving of this road to turn it into a major soybean exportation facility. The model assesses the impacts of this road paving within four scenarios: two population scenarios (high and moderate growth) and two policy intervention scenarios. In the ‘business‐as‐usual’ policy scenario, the responses of deforestation and land abandonment to road paving are estimated based on historical rates of Amazon regions that had a major road paved. In the ‘governance’ scenario, several plausible improvements in the enforcement of environmental regulations, support for sustainable land‐use systems, and local institutional capacity are invoked to modify the historical rates. Model inputs include data collected during expeditions and through participatory mapping exercises conducted with agents from four major frontier types along the road. The model has two components. A scenario‐generating submodel is coupled to a landscape dynamics simulator, ‘DINAMICA’, which spatially allocates the land‐cover transitions using a GIS database. The model was run for 30 years, divided into annual time steps. It predicted more than twice as much deforestation along the corridor in business‐as‐usual vs. governance scenarios. The model demonstrates how field data gathered along a 1000 km corridor can be used to develop plausible scenarios of future land‐cover change trajectories that are relevant to both global change science and the decision‐making process of governments and civil society in an important rainforest region.     

Land cover change 2002–2005 in Borneo and the role of fire derived from MODIS imagery

Borneo has experienced heavy deforestation and forest degradation during the past two decades. In this study the Moderate Resolution Imaging Spectroradiometer was used to monitor land cover change in Borneo between 2002 and 2005 in order to assess the current extent of the forest cover, the deforestation rate and the role of fire. Using Landsat and ground observation for validation it was possible to discriminate 11 land cover classes. In 2002 57% of the land surface of Borneo was covered with forest of which 74% was dipterocarp and more than 23% peat swamp forest. The average deforestation rate between 2002 and 2005 was 1.7% yr^{− 1}. The carbon-rich ecosystem of peat swamp forests showed a deforestation rate of 2.2%. Almost 98% of all deforestation occurred within a range of 5 km to the forest edge. Fire is highly correlated with land cover changes. Most fires were detected in degraded forests. Ninety-eight per cent of all forest fires were detected in the 5 km buffer zone, underlining that fire is the major driver for forest degradation and deforestation.     

Changing Landscapes for Forest Commons: Linking Land Tenure with Forest Cover Change Following Mexico’s 1992 Agrarian Counter-Reforms

Mexico’s 1992 agrarian counter-reforms opened up the country’s vast network of common property regimes, known as ejidos, to the possibility of privatization. This study investigates the relationship between dynamic common property regimes and deforestation in the wake of policy reform among eight ejidos in southeastern Mexico. Using institutional analyses, land use/land cover change (LULCC) analyses and a Forest Dependency Index, we examine how land tenure arrangements relate to land use and forest cover change patterns. We demonstrate that informally privatized ejidos had larger individual landholdings, more land in use, and higher rates of deforestation. Commonly-held ejidos exhibited lower deforestation rates and, in some cases, forests provided economic benefits via community forest management. However, forest dependency did not correlate with low deforestation rates, suggesting alternative pathways for conservation.     

A large‐area,spatially continuous assessment of land cover map error and its impact on downstream analyses

Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high‐resolution map of South African cropland to assess (1) the magnitude of error in several current generation land cover maps, and (2) how these errors propagate in downstream studies. We first quantified pixel‐wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, and then calculated errors in several representative “downstream” (map‐based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps’ spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g., at 1 km resolution, up to ～45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National‐scale maps derived from higher‐resolution imagery were most accurate, followed by multi‐map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland‐adjacent covers (e.g., with forest as adjacent cover, carbon map error was 200%–500% greater than in input cropland maps, but ～40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land cover map users.     

Consequences of the Armed Conflict, Forced Human Displacement, and Land Abandonment on Forest Cover Change in Colombia: A Multi-scaled Analysis

Most studies of land change have focused on patterns, rates, and drivers of deforestation, but much less is known about the dynamics associated with agricultural abandonment and ecosystem recovery. Furthermore, most studies are conducted at a single spatial scale, and few have included variables related with internal socio-political conflicts. Here we evaluated the effect of environmental, demographic, and socio-economic variables on woody cover change in Colombia between 2001 and 2010 at the country, biome, and ecoregion scales. We also incorporated factors that reflect the unique history of Colombia such as the presence of illegal-armed groups and forced human displacement. Environmental variables explained the patterns of deforestation and forest regrowth at all scales because they can restrict or encourage different land uses across multiple spatial scales. Demographic variables were important at the biome and ecoregion scales and appear to be a consequence of the armed conflict, particularly through forced human displacement (for example, rural–urban migration), which in some areas has resulted in forest regrowth. In other areas, the impact of illegal armed groups has reduced forest cover, particularly in areas rich in gold and lands appropriate for cattle grazing. This multi-scale and multivariate approach provides a new insight into the complex relationship between woody cover change and land abandonment triggered mainly by armed conflict.     

Stream macroinvertebrate response to catchment urbanisation (Georgia, U.S.A.)

SUMMARY 1. The effects of catchment urbanisation on water quality were examined for 30 streams (stratified into 15, 50 and 100 km² ± 25% catchments) in the Etowah River basin, Georgia, U.S.A. We examined relationships between land cover (implying cover and use) in these catchments (e.g. urban, forest and agriculture) and macroinvertebrate assemblage attributes using several previously published indices to summarise macroinvertebrate response. Based on a priori predictions as to mechanisms of biotic impairment under changing land cover, additional measurements were made to assess geomorphology, hydrology and chemistry in each stream. 2. We found strong relationships between catchment land cover and stream biota. Taxon richness and other biotic indices that reflected good water quality were negatively related to urban land cover and positively related to forest land cover. Urban land cover alone explained 29–38% of the variation in some macroinvertebrate indices. Reduced water quality was detectable at c. >15% urban land cover. 3. Urban land cover correlated with a number of geomorphic variables such as stream bed sediment size (–) and total suspended solids (+) as well as a number of water chemistry variables including nitrogen and phosphorus concentrations (+), specific conductance (+) and turbidity (+). Biotic indices were better predicted by these reach scale variables than single, catchment scale land cover variables. Multiple regression models explained 69% of variation in total taxon richness and 78% of the variation in the Invertebrate Community Index (ICI) using phi variability, specific conductance and depth, and riffle phi, specific conductance and phi variability, respectively. 4. Indirect ordination analysis was used to describe assemblage and functional group changes among sites and corroborate which environmental variables were most important in driving differences in macroinvertebrate assemblages. The first axis in a non‐metric multidimensional scaling ordination was highly related to environmental variables (slope, specific conductance, phi variability; adj. R²=0.83) that were also important in our multiple regression models. 5. Catchment urbanisation resulted in less diverse and more tolerant stream macroinvertebrate assemblages via increased sediment transport, reduced stream bed sediment size and increased solutes. The biotic indices that were most sensitive to environmental variation were taxon richness, EPT richness and the ICI. Our results were largely consistent over the range in basin size we tested.     

Analysis of regional species distribution models based on radio-telemetry datasets from multiple small-scale studies

The identification of core habitat areas and resulting prediction maps are vital tools for land managers. Often, agencies have large datasets from multiple studies over time that could be combined for a more informed and complete picture of a species. Colorado Parks and Wildlife has a large database for greater sage-grouse (Centrocercus urophasianus) including 11 radio-telemetry studies completed over 12 years (1997–2008) across northwestern Colorado. We divided the 49,470-km² study area into 1-km² grids with the number of sage-grouse locations in each grid cell that contained at least 1 location counted as the response variable. We used a generalized linear mixed model (GLMM) using land cover variables as fixed effects and individual birds and populations as random effects to predict greater sage-grouse location counts during breeding, summer, and winter seasons. The mixed effects model enabled us to model correlations that may exist in grouped data (e.g., correlations among individuals and populations). We found only individual groupings accounted for variation in the summer and breeding seasons, but not the winter season. The breeding and summer seasonal models predicted sage-grouse presence in the currently delineated populations for Colorado, but we found little evidence supporting a winter season model. According to our models, about 50% of the study area in Colorado is considered highly or moderately suitable habitat in both the breeding and summer seasons. As oil and gas development and other landscape changes occur in this portion of Colorado, knowledge of where management actions can be accomplished or possible restoration can occur becomes more critical. These seasonal models provide data-driven, distribution maps that managers and biologists can use for identification and exploration when investigating greater sage-grouse issues across the Colorado range. Using historic data for future decisions on species management while accounting for issues found from combining datasets allows land managers the flexibility to use all information available. © 2013 The Wildlife Society.     

Soil carbon stocks,deforestation and land‐cover changes in the Western Ghats biodiversity hotspot (India)

Habitat loss and soil organic carbon (SOC) stock variations linked to land‐cover change were estimated over two decades in the most densely populated biodiversity hotspot in the world, in order to assess the possible influence of conservation practices on the protection of SOC. For a study area of 88 484 km², 70% of which lie inside the Western Ghats Biodiversity Hotspot (WGBH), land‐cover maps for two dates (1977, 1999) were built from various data sources including remote sensing images and ecological forest maps. SOC stocks were calculated from climatic parameters, altitude, physiography, rock type, soil type and land‐cover, with a modelling approach used in predictive learning and based on Multiple Additive Regression Tree. The model was trained on 361 soil profiles data, and applied to estimate SOC stocks from predictor variables using a Geographical Information System (GIS). Comparison of 1977 and 1999 land‐cover maps showed 628 km² of dense forests habitat loss (6%), corresponding to an annual deforestation rate of 0.44%. This was found consistent with other studies carried out in other parts of the WGBH, but not with FAO figures showing an increase in forest area. This could be explained by the different forest definitions used, based on ecological classification in the former, and on percentage tree cover in the latter. Unexpectedly, our results showed that despite ongoing deforestation, overall SOC stock was maintained (～0.43 Pg). But a closer examination of spatial differences showed that soil carbon losses in deforested areas were compensated by sequestration elsewhere, mainly in recent plantations and newly irrigated croplands. This suggests that more carbon sequestration in soils could be achieved in the future through appropriate wasteland management. It is also expected that increasing concerns about biodiversity loss will favour more conservation and reinforce the already prevailing protective measures, thus further maintaining C stocks.     

Patterns of beta diversity in Europe: the role of climate,land cover and distance across scales

Aim We test the prediction that beta diversity (species turnover) and the decay of community similarity with distance depend on spatial resolution (grain). We also study whether patterns of beta diversity are related to variability in climate, land cover or geographic distance and how the independent effects of these variables depend on the spatial grain of the data. Location Europe, Great Britain, Finland and Catalonia. Methods We used data on European birds, plants, butterflies, amphibians and reptiles, and data on British plants, Catalonian birds and Finnish butterflies. We fitted two or three nested grids of varying resolutions to each of these datasets. For each grid we calculated differences in climate, differences in land‐cover composition (CORINE) and beta diversity (β_sim, β_Jaccard) between all pairs of grid cells. In a separate analysis we looked specifically at pairs of adjacent grid cells (the first distance class). We then used variation partitioning to identify the magnitude of independent statistical associations (i.e. independent effects in the statistical sense) of climate, land cover and geographic distance with spatial patterns of beta diversity. Results Beta diversity between grid cells at any given distance decreased with increasing grain. Geographic distance was always the most important predictor of beta diversity for all pairwise comparisons at the extent of Europe. Climate and land cover had weaker but distinct and grain‐dependent effects. Climate was more important at relatively coarse grains, whereas land‐cover effects were stronger at finer grains. In the country‐wide analyses, climate and land cover were more important than geographic distance. Climatic and land‐cover models performed poorly and showed no systematic grain dependence for beta diversity between adjacent grid cells. Main conclusions We found that relationships between geographic distance and beta diversity, as well as the environmental correlates of beta diversity, are systematically grain dependent. The strong independent effect of distance indicates that, contrary to the current belief, a substantial fraction of species are missing from areas with a suitable environment. Moreover, the effects of geographic distance (at continental extents) and land cover (at fine grains) indicate that any species distribution modelling should take both environment and dispersal limitation into account.     

Loss of genetic diversity in the North American mayfly Ephemerella invaria associated with deforestation of headwater streams

1. Terrestrial dispersal by aquatic insects increases population connectivity in some stream species by allowing individuals to move outside the structure of the stream network. In addition, individual survival and reproductive success (as well as dispersal) are tightly linked to the quality of the terrestrial habitat. 2. In historically forested catchments, deforestation and altered land use have the potential to interfere with mayfly dispersal or mating behaviours by degrading the quality of the terrestrial matrix among headwater streams. We hypothesised that loss of tree cover in first‐order catchments would be associated with an increase in population substructure and a decrease in genetic diversity of mayfly populations. 3. To test this hypothesis, we investigated spatial patterns of genetic variation in the common mayfly Ephemerella invaria across a gradient of deforestation in the central piedmont region of eastern United States. Intraspecific genetic diversity and population substructure were estimated from data obtained using fluorescent amplified fragment length polymorphism (AFLP) markers. 4. We found that mayfly populations had low population substructure within headwater stream networks and that genetic diversity was strongly negatively correlated with mean deforestation of the first‐order catchments. The large‐scale pattern of population substructure followed a pattern of isolation by distance (IBD) in which genetic differentiation increases with geographical distance, but assignment tests placed a few individuals into populations 300 km away from the collection site. 5. Our results show that loss of genetic diversity in this widespread aquatic insect species is co‐occurring with deforestation of headwater streams. 6. Most arguments supporting protection of headwater streams in the United States have centred on the role of these streams as hydrological and biogeochemical conduits to downstream waters. Our work suggests that headwater stream land use, and specifically tree cover, may have a role in the maintenance of regional genetic diversity in some common aquatic insect species.     

Modelling climate response to historical land cover change

In order to estimate the effect of historical land cover change (deforestation) on climate, we perform a set of experiments with a climate system model of intermediate complexity – CLIMBER-2. We focus on the biophysical effect of the land cover change on climate and do not explicitly account for the biogeochemical effect. A dynamic scenario of deforestation during the last millennium is formulated based on the rates of land conversion to agriculture. The deforestation scenario causes a global cooling of 0.35 °C with a more notable cooling of the northern hemisphere (0.5 °C). The cooling is most pronounced in the northern middle and high latitudes, especially during the spring season. To compare the effect of deforestation on climate with other forcings, climate responses to the changing atmospheric CO₂ concentration and solar irradiance are also analysed. When all three factors are taken into account, dynamics of northern hemisphere temperature during the last 300 years within the model are generally in agreement with the observed (reconstructed) temperature trend. We conclude that the impact of historical land cover changes on climate is comparable with the impact of the other climate forcings and that land cover forcing is important for reproducing historical climate change.     

Carrot or Stick? Modelling How Landowner Behavioural Responses Can Cause Incentive-Based Forest Governance to Backfire

Mitigating the negative impacts of declining worldwide forest cover remains a significant socio-ecological challenge, due to the dominant role of human decision-making. Here we use a Markov chain model of land-use dynamics to examine the impact of governance on forest cover in a region. Each land parcel can be either forested or barren (deforested), and landowners decide whether to deforest their parcel according to perceived value (utility). We focus on three governance strategies: yearly incentive for conservation, one-time penalty for deforestation and one-time incentive for reforestation. The incentive and penalty are incorporated into the expected utility of forested land, which decreases the net gain of deforestation. By analyzing the equilibrium and stability of the landscape dynamics, we observe four possible outcomes: a stationary-forested landscape, a stationary-deforested landscape, an unstable landscape fluctuating near the equilibrium, and a cyclic-forested landscape induced by synchronized deforestation. We find that the two incentive-based strategies often result in highly fluctuating forest cover over decadal time scales or longer, and in a few cases, reforestation incentives actually decrease the average forest cover. In contrast, a penalty for deforestation results in the stable persistence of forest cover (generally >30%). The idea that larger conservation incentives will always yield higher and more stable forest cover is not supported in our findings. The decision to deforest is influenced by more than a simple, “rational” cost-benefit analysis: social learning and myopic, stochastic decision-making also have important effects. We conclude that design of incentive programs may need to account for potential counter-productive long-term effects due to behavioural feedbacks.     

Mapping ecosystem services: The supply and demand of flood regulation services in Europe

Ecosystem services (ES) feature highly distinctive spatial and temporal patterns of distribution, quantity, and flows. The flow of ecosystem goods and services to beneficiaries plays a decisive role in the valuation of ES and the successful implementation of the ES concept in environmental planning. This is particularly relevant to regulating services where demands emerge often spatially separated from supply. However, spatial patterns of both supply and demand are rarely incorporated in ES assessments on continental scales. In this paper, we present an ES modeling approach with low data demand, fit to be employed in scenario analysis and on multiple scales. We analyze flood regulation services at a European scale by explicitly addressing the spatial distribution of ES demand. A flood regulation supply indicator is developed based on scenario runs with a hydrological model in representative river catchments, incorporating detailed information on land, cover, land use and management. Land use sensitive flood damage estimates in the European Union (EU) are employed to develop a spatial indicator for flood regulation demand. Findings are transferred to the EU territory to create a map of the current supply of flood regulation and the potential supply under conditions of natural vegetation. Regions with a high capacity to provide flood regulation are mainly characterized by large patches of natural vegetation or extensive agriculture. The main factor limiting supply on a continental scale is a low water holding capacity of the soil. Flood regulation demand is highest in central Europe, at the foothills of the Alps and upstream of agglomerations. We were able to identify areas with a high potential capacity to provide flood regulation in conjunction with land use modifications. When combined with spatial patterns of current supply and demand, we could identify priority areas for investments in ES flood regulation supply through conservation and land use planning. We found that only in a fraction of the EU river catchments exhibiting a high demand, significant increases in flood regulation supply are achievable by means of land use modifications.     

Expanding temporal resolution in landscape transformations: Insights from a landsat-based case study in Southern Chile

Understanding temporal and spatial dimensions of land cover dynamics is a critical factor to link ecosystem transformation to land and environmental management. The trajectory of land cover change is not a simple difference between two conditions, but a continuous process. Therefore, there is a need to integrate multiple time periods to identify slow and rapid transformations over time. We mapped land cover composition and configuration changes using time series of Landsat TM/ETM+ images (1985–2011) in Southern Chile to understand the transformation process of a temperate rainforest relict and biodiversity hotspot. Our analysis builds on 28 Landsat scenes from 1985 to 2011 that have been classified using a random forests approach. Base on the high temporal data set we quantify land cover change and fragmentation indices to fully understand landscape transformation in this area. Our results show a high deforestation process for old growth forest strongest at the beginning of the study period (1985–1986–1998–1999) followed by a progressive slowdown until 2011. Within different study periods deforestation rates were much larger than the average rate over the complete study period (0.65%), with the highest annual deforestation rate of 1.2% in 1998–1999. The deforestation resulted in a low connectivity between native forest patches. Old-growth forest was less fragmented, but was concentrated mainly in two large regions (the Andes and Coastal mountain range) with almost no connection in between. Secondary forest located in more intensively used areas was highly fragmented. Exotic forest plantation areas, one of the most important economic activities in the area, increased sevenfold (from 12,836 to 103,540 ha), especially during the first periods at the expense of shrubland, secondary forest, grassland/arable land and old grown forest. Our analysis underlines the importance of expanding temporal resolution in land cover/use change studies to guide sustainable ecosystem management strategies as increase landscape connectivity and integrate landscape planning to economic activities. The study is highlighting the key role of remote sensing in the sustainable management of human influenced ecosystems.