Estimating the Value of Non‐Use Benefits from Small Changes in the Provision of Ecosystem Services

Abstract: The unit of trade in ecosystem services is usually the use of a proportion of the parcels of land associated with a given service. Valuing small changes in the provision of an ecosystem service presents obstacles, particularly when the service provides non‐use benefits, as is the case with conservation of most plants and animals. Quantifying non‐use values requires stated‐preference valuations. Stated‐preference valuations can provide estimates of the public's willingness to pay for a broad conservation goal. Nevertheless, stated‐preference valuations can be expensive and do not produce consistent measures for varying levels of provision of a service. Additionally, the unit of trade, land use, is not always linearly related to the level of ecosystem services the land might provide. To overcome these obstacles, we developed a method to estimate the value of a marginal change in the provision of a non‐use ecosystem service—in this case conservation of plants or animals associated with a given land‐cover type. Our method serves as a tool for calculating transferable valuations of small changes in the provision of ecosystem services relative to the existing provision. Valuation is achieved through stated‐preference investigations, calculation of a unit value for a parcel of land, and the weighting of this parcel by its ability to provide the desired ecosystem service and its effect on the ability of the surrounding land parcels to provide the desired service. We used the water vole (Arvicola terrestris) as a case study to illustrate the method. The average present value of a meter of water vole habitat was estimated at UK£12, but the marginal value of a meter (based on our methods) could range between £0 and £40 or more.     

Using enhanced dasymetric mapping techniques to improve the spatial accuracy of sea level rise vulnerability assessments

This article reports on the application of dasymetric mapping techniques to interpolate and disaggregate block group population counts to smaller areal units (i.e., tax parcels) and derive surface population models with more realistic representations of population distributions in our residential study area in Miami-Dade, Florida. Three methods of dasymetric interpolation were tested: (i) binary, (ii) three-class, and (iii) limiting variable. Our enhanced limiting variable approach introduced an adjustment factor for parcel vacancy rates in the dasymetric calculations, and applied dasymetric mapping techniques to disaggregate future population projections to the tax lot level of analysis. The limiting variable interpolation generated the lowest coefficient of variation (0.188), followed by the three-class interpolation (0.645). We also found that population densities vary substantially within land use classes of single family, medium density and high density classes, and these variations also highlighted the importance of incorporating vacancy rates when interpolating population counts to categorical land use data. Overall, the enhanced dasymetric mapping technique is particularly useful for examining the impact of sea-level rise as its derivatives are compatible with high resolution LiDAR and orthoimagery data. Coastal counties can also benefit from such high resolution surface population models to enhance the accuracy of hazard-related vulnerability assessments and to guide the development of relevant shore zone conservation and adaptation strategies.     

Economics of Grassland Conversion to Cropland in the Prairie Pothole Region

Abstract: Much of the remaining grassland, particularly in North America, is privately owned, and its conversion to cultivated cropland is largely driven by economics. An understanding of why landowners convert grassland to cropland could facilitate more effective design of grassland‐conservation programs. We built an empirical model of land‐use change in the Prairie Pothole Region (north‐central United States) to estimate the probability of grassland conversion to alternative agricultural land uses, including cultivated crops. Conversion was largely driven by landscape characteristics and the economic returns of alternative uses. Our estimate of the probability of grassland conversion to cultivated crops (1.33% on average from 1979 to 1997) was higher than past estimates (0.4%). Our model also predicted that grassland‐conversion probabilities will increase if agricultural commodity prices continue to follow the trends observed from 2001 to 2006 (0.93% probability of grassland conversion to cultivated crops in 2006 to 1.5% in 2011). Thus, nearly 121 million ha (30 million acres) of grassland could be converted by 2011. Conversion probabilities, however, are spatially heterogeneous (range 0.2% to 3%), depending on characteristics of a parcel (e.g., soil quality and economic returns). Grassland parcels with relatively high‐quality land for agricultural production are more likely to be converted to cultivated crops than lower‐quality parcels and are more responsive to changes in the economic returns on alternative agricultural land uses (i.e., conversion probability increases by a larger magnitude for high‐quality parcels when economics returns to alternative uses increase). Our results suggest that grassland conservation programs could be proactively targeted toward high‐risk parcels by anticipating changes in economic returns, such as could occur if a new biofuel processing plant were to be built in an area.     

Assessment of a large watershed in Brazil using Emergy Evaluation and Geographical Information System

Humanity's future depends on the preservation of natural ecosystems that supply resources and absorb pollutants. Rural and urban productions are currently based on chemical products made from petroleum, which are responsible for high negative impacts on the Biosphere. In order to prevent those impacts, efficient public policies seeking for sustainable development are necessary. Aiming to assess the load on the environment (considering the gratuitous contributions of natural systems—a donor's perspective) due to human-dominated process, a scientific tool called Emergy Evaluation has been applied in different production systems, including crops and farms. However, there is still a lack of emergy studies in the context of watersheds, probably due to the difficulty of collecting raw data. The present work aims to carry out an assessment of Mogi-Guaçu and Pardo watershed, through the combined use of Emergy Evaluation and Geographical Information System. The agricultural and natural land uses were considered, while urban areas were excluded. Emergy flows (expressed in seJ ha⁻¹ yr⁻¹) obtained for all agricultural and natural land uses were expanded for the whole watershed and the emergy indices were calculated. The results show that the watershed has: low renewability (%R = 32%); low capture of natural resources through high external economic investment (EYR = 1.86); low dependence on natural resources (EIR = 1.16); and moderate load on the environment (ELR = 2.08). Considering a scenario where sugar-cane crops, orchards and pasture areas are converted from conventional to organic management, watershed's emergy performance improved, reaching a new renewability of 38%, but it is still not enough to be considered sustainable.     

Carbon sequestration in soils of SW-Germany as affected by agricultural management—Calibration of the EPIC model for regional simulations

Global emissions trading allows for agricultural measures to be accounted for the carbon sequestration in soils. The Environmental Policy Integrated Climate (EPIC) model was tested for central European site conditions by means of agricultural extensification scenarios. Results of soil and management analyses of different management systems (cultivation with mouldboard plough, reduced tillage, and grassland/fallow establishment) on 13 representative sites in the German State Baden-Württemberg were used to calibrate the EPIC model. Calibration results were compared to those of the Intergovernmental Panel on Climate Change (IPCC) prognosis tool. The first calibration step included adjustments in (a) N depositions, (b) N₂-fixation by bacteria during fallow, and (c) nutrient content of organic fertilisers according to regional values. The mixing efficiency of implements used for reduced tillage and four crop parameters were adapted to site conditions as a second step of the iterative calibration process, which should optimise the agreement between measured and simulated humus changes. Thus, general rules were obtained for the calibration of EPIC for different criteria and regions. EPIC simulated an average increase of +0.341 Mg humus-C ha⁻¹ a⁻¹ for on average 11.3 years of reduced tillage compared to land cultivated with mouldboard plough during the same time scale. Field measurements revealed an average increase of +0.343 Mg C ha⁻¹ a⁻¹ and the IPCC prognosis tool +0.345 Mg C ha⁻¹ a⁻¹. EPIC simulated an average increase of +1.253 Mg C ha⁻¹ a⁻¹ for on average 10.6 years of grassland/fallow establishment compared to an average increase of +1.342 Mg humus-C ha⁻¹ a⁻¹ measured by field measurements and +1.254 Mg C ha⁻¹ a⁻¹ according to the IPCC prognosis tool. The comparison of simulated and measured humus C stocks was r² ≥ 0.825 for all treatments. However, on some sites deviations between simulated and measured results were considerable. The result for the simulation of yields was similar. In 49% of the cases the simulated yields differed from the surveyed ones by more than 20%. Some explanations could be found by qualitative cause analyses. Yet, for quantitative analyses the available information from farmers was not sufficient. Altogether EPIC is able to represent the expected changes by reduced tillage or grassland/fallow establishment acceptably under central European site conditions of south-western Germany.     

Development of TRIPLEX-Management model for simulating the response of forest growth to pre-commercial thinning

In order to simulate forest growth response to pre-commercial thinning (PCT), TRIPLEX1.0 - a process-based model designed to predict forest growth as well as carbon (C) and nitrogen (N) dynamics - was modified and improved to also simulate managed forest ecosystem thinning practices. A three-parameter Weibull distribution model was integrated to simulate thinning treatments within the newly developed TRIPLEX-Management model. The thinning intensity component within the model allows users to simulate thinning treatments by applying basal area, stand density and volume to quantify thinning intensity. Natural mortality decreased following thinning due to an increase in growing space for residual stems. Predicted litterfall pools also increased after thinning events took place. The TRIPLEX-Management model was tested against published observational data for Jack Pine (Pinus banksiana Lamb.) stands subjected to PCT in Northwestern Ontario, Canada. The coefficients of determination (R²) between the predicted and observed variables including stand density, mean DBH (diameter at breast height), the quadratic mean DBH, total volume and merchantable volume as well as belowground, aboveground, and total biomass ranged from 0.50 to 0.88 (n = 20, P < 0.001) with the exception of mean tree height (R² = 0.25, n = 20, P < 0.05). Overall, the Willmott index of agreement between predicted and observed variables ranged from 0.97 to 1.00. Results show that the TRIPLEX-Management model is generally capable of simulating growth response to PCT for Jack Pine stands.     

Wildlife corridors as a connected subgraph problem

Wildlife corridors connect areas of biological significance to mitigate the negative ecological impacts of habitat fragmentation. In this article we formalize the optimal corridor design as a connected subgraph problem, which maximizes the amount of suitable habitat in a fully connected parcel network linking core habitat areas, subject to a constraint on the funds available for land acquisition. To solve this challenging computational problem, we propose a hybrid approach that combines graph algorithms with Mixed Integer Programming-based optimization. We apply this technique to the design of corridors for grizzly bears in the U.S. Northern Rockies, illustrating the underlying computational complexities by varying the granularity of the parcels available for acquisition. The approach that is introduced is general and can be applied to other species or other similar problems, such as those occurring in social networks.     

Integrating farming techniques in an ecological matrix model: Implementation on the primrose (Primula vulgaris)

Several studies have proven the importance of field margins in sustaining biodiversity and other work has been done on the effect of field management on field margin flora. However few models have been built to predict the effects of field management on the flora. Our project addresses this need for a model capable of predicting the effect of cropping techniques and their timing on the flora of field margins. Primula vulgaris is a biodiversity indicator, characteristic of undisturbed flora and found in field margins and woodlands: its population has been declining for several years. We created a temporal matrix model of P. vulgaris populations on field margins, taking into account the effects of field, field margin and roadside management based on literature and expert knowledge. We then analysed its sensitivity to demographic parameters by comparing lambda (growth rate) sensitivity and elasticity. We compared the management parameter effect using the relative growth rate of the population after 6 years of simulation. Sensitivity analysis to biological parameters showed the importance of adult survival and seed production and germination. Results show that P. vulgaris is particularly sensitive to broad-spectrum herbicides and that other management techniques like early mowing, scything and scrub-killer (diluted broad-spectrum herbicide or specific herbicide) are less aggressive. Our simulations show that management of cash crops in Brittany is too aggressive for P. vulgaris populations and that 4-5 years of grassland in the adjacent field are necessary to maintain populations.     

Structural changes in lake functioning induced from nutrient loading and climate variability

Climate variability is increasingly recognized as an important regulatory factor, capable of influencing the structural properties of aquatic ecosystems. Lakes appear to be particularly sensitive to the ecological impacts of climate variability, and several long time series have shown a close coupling between climate, lake thermal properties and individual organism physiology, population abundance, community structure, and food web dynamics. Thus, understanding the complex interplay among meteorological forcing, hydrological variability, and ecosystem functioning is essential for improving the credibility of model-based water resources/fisheries management. Our objective herein is to examine the relative importance of the ecological mechanisms underlying plankton seasonal variability in Lake Washington, Washington State (USA), over a 35-year period (1964–1998). Our analysis is founded upon an intermediate complexity plankton model that is used to reproduce the limiting nutrient (phosphate)–phytoplankton–zooplankton–detritus (particulate phosphorus) dynamics in the lake. Model parameterization is based on a Bayesian calibration scheme that offers insights into the degree of information the data contain about model inputs and allows obtaining predictions along with uncertainty bounds for modeled output variables. The model accurately reproduces the key seasonal planktonic patterns in Lake Washington and provides realistic estimates of predictive uncertainty for water quality variables of environmental management interest. A principal component analysis of the annual estimates of the underlying ecological processes highlighted the significant role of the phosphorus recycling stemming from the zooplankton excretion on the planktonic food web variability. We also identified a moderately significant signature of the local climatic conditions (air temperature) on phytoplankton growth (r = 0.41), herbivorous grazing (r = 0.38), and detritus mineralization (r = 0.39). Our study seeks linkages with the conceptual food web model proposed by Hampton et al. [Hampton, S.E., Scheuerell, M.D., Schindler, D.E., 2006b. Coalescence in the Lake Washington story: interaction strengths in a planktonic food web. Limnol. Oceanogr. 51, 2042–2051.] to emphasize the “bottom-up” control of the Lake Washington plankton phenology. The posterior predictive distributions of the plankton model are also used to assess the exceedance frequency and confidence of compliance with total phosphorus (15 μg L⁻¹) and chlorophyll a (4 μg L⁻¹) threshold levels during the summer-stratified period in Lake Washington. Finally, we conclude by underscoring the importance of explicitly acknowledging the uncertainty in ecological forecasts to the management of freshwater ecosystems under a changing global environment.     

Modelling forest management within a global vegetation model—Part 1: Model structure and general behaviour

This article describes a new forest management module (FMM) that explicitly simulates forest stand growth and management within a process-based global vegetation model (GVM) called ORCHIDEE. The net primary productivity simulated by ORCHIDEE is used as an input to the FMM. The FMM then calculates stand and management characteristics such as stand density, tree size distribution, tree growth, the timing and intensity of thinnings and clear-cuts, wood extraction and litter generated after thinning. Some of these variables are then fed back to ORCHIDEE. These computations are made possible with a distribution-based modelling of individual tree size. The model derives natural mortality from the relative density index (rdi), a competition index based on tree size and stand density. Based on the common forestry management principle of avoiding natural mortality, a set of rules is defined to calculate the recurrent intensity and frequency of forestry operations during the stand lifetime. The new-coupled model is called ORCHIDEE-FM (forest management).The general behaviour of ORCHIDEE-FM is analysed for a broadleaf forest in north-eastern France. Flux simulation throughout a forest rotation compare well with the literature values, both in absolute values and dynamics.Results from ORCHIDEE-FM highlight the impact of forest management on ecosystem C-cycling, both in terms of carbon fluxes and stocks. In particular, the average net ecosystem productivity (NEP) of 225 gC m⁻² year⁻¹ is close to the biome average of 311 gC m⁻² year⁻¹. The NEP of the “unmanaged” case is 40% lower, leading us to conclude that management explains 40% of the cumulated carbon sink over 150 years. A sensitivity analysis reveals 4 major avenues for improvement: a better determination of initial conditions, an improved allocation scheme to explain age-related decline in productivity, and an increased specificity of both the self-thinning curve and the biomass-diameter allometry.     

Simulating soil organic matter with CQESTR (v. 2.0): Model description and validation against long-term experiments across North America

Soil carbon (C) models are important tools for examining complex interactions between climate, crop and soil management practices, and to evaluate the long-term effects of management practices on C-storage potential in soils. CQESTR is a process-based carbon balance model that relates crop residue additions and crop and soil management to soil organic matter (SOM) accretion or loss. This model was developed for national use in U.S and calibrated initially in the Pacific Northwest. Our objectives were: (i) to revise the model, making it more applicable for wider geographic areas including potential international application, by modifying the thermal effect and incorporating soil texture and drainage effects, and (ii) to recalibrate and validate it for an extended range of soil properties and climate conditions. The current version of CQESTR (v. 2.0) is presented with the algorithms necessary to simulate SOM at field scale. Input data for SOM calculation include crop rotation, aboveground and belowground biomass additions, tillage, weather, and the nitrogen content of crop residues and any organic amendments. The model was validated with long-term data from across North America. Regression analysis of 306 pairs of predicted and measured SOM data under diverse climate, soil texture and drainage classes, and agronomic practices at 13 agricultural sites having a range of SOM (7.3–57.9 g SOM kg⁻¹), resulted in a linear relationship with an r² of 0.95 (P < 0.0001) and a 95% confidence interval of 4.3 g SOM kg⁻¹. Using the same data the version 1.0 of CQESTR had an r² of 0.71 with a 95% confidence interval of 5.5 g SOM kg⁻¹. The model can be used as a tool to predict and evaluate SOM changes from various management practices and offers the potential to estimate C accretion required for C credits.     

Mass balanced and dynamic simulations of trophic models of kelp ecosystems near the Mejillones Peninsula of northern Chile (SE Pacific): Comparative network structure and assessment of harvest strategies

Mass balanced trophic models for kelp ecosystems which include subsystems dominated by Macrocystis integrifolia, Lessonia trabeculata and areas of barren ground (BG) were constructed for subtidal areas near the Mejillones Peninsula (SE Pacific), Chile. Information on biomass, P/B ratios, catches, food spectrum, consumption and dynamics of commercial and non-commercial populations was obtained and examined using Ecopath with Ecosim software analyses. The biomass of blades of L. trabeculata and M. integrifolia represented the compartments most relevant to the subsystems studied. Within the herbivores, the sea urchin Tetrapigus niger was dominant, followed by the snails Turritella sp. and Tegula sp. The fishes Pinguipes chilensis and Cheilodactylus variegatus were the dominant predators, followed by the asteroids Heliaster helianthus and Meyenaster gelatinosus. The highest system throughput (72,512 g wet weight m⁻² year⁻¹) was calculated for the subsystem dominated by M. integrifolia. The mean trophic level of the catch ranged from 1.1 (subsystem dominated by L. trabeculata) to 1.3 (subsystem dominated by M. integrifolia) to 3.2 (barren ground subsystem), showing that harvesting in each system was concentrated either on primary producers (blades of kelp species) or top predator fishes. Although the values for the Relative Ascendency (A/C) fluctuated from 36.5 to 45%, suggesting that all the systems were immature, the subsystem dominated by M. integrifolia emerged as the least resistant to external disturbances (e.g. fisheries). This result agreed with the high value of the system recovery time (SRT) for the M. integrifolia subsystem as a response to combined fisheries scenarios. The results obtained using mixed trophic impact (MTI) and Ecosim [increasing the fishing mortality F_i by 4×] showed that in most of the cases the predictions had the same qualitative tendencies. One of the most important results obtained in this study was that exploitation of kelp blades as an alternative strategy to harvesting the whole plants appeared to be ecologically sustainable, since harvesting the blades propagated only small effects on the entire subsystem. The fish P. chilensis may be considered as a top predator species with a strong top-down control since an increase in its fishing mortality in the subsystem dominated by M. integrifolia produced a high SRT value, and the F_MSY was less than the originally entered F_i in Ecopath. Based on the results obtained, it was concluded that the trophic mass balanced models and simulated management scenarios offered good possibilities for the planning of interventions and manipulations or the planning of more sustainable management strategies in highly disturbed natural systems.     

Estimating California ecosystem carbon change using process model and land cover disturbance data: 1951-2000

Land use change, natural disturbance, and climate change directly alter ecosystem productivity and carbon stock level. The estimation of ecosystem carbon dynamics depends on the quality of land cover change data and the effectiveness of the ecosystem models that represent the vegetation growth processes and disturbance effects. We used the Integrated Biosphere Simulator (IBIS) and a set of 30- to 60-m resolution fire and land cover change data to examine the carbon changes of California's forests, shrublands, and grasslands. Simulation results indicate that during 1951-2000, the net primary productivity (NPP) increased by 7%, from 72.2 to 77.1 Tg C yr⁻¹ (1 teragram = 10¹² g), mainly due to CO₂ fertilization, since the climate hardly changed during this period. Similarly, heterotrophic respiration increased by 5%, from 69.4 to 73.1 Tg C yr⁻¹, mainly due to increased forest soil carbon and temperature. Net ecosystem production (NEP) was highly variable in the 50-year period but on average equalled 3.0 Tg C yr⁻¹ (total of 149 Tg C). As with NEP, the net biome production (NBP) was also highly variable but averaged −0.55 Tg C yr⁻¹ (total of -27.3 Tg C) because NBP in the 1980s was very low (-5.34 Tg C yr⁻¹). During the study period, a total of 126 Tg carbon were removed by logging and land use change, and 50 Tg carbon were directly removed by wildland fires. For carbon pools, the estimated total living upper canopy (tree) biomass decreased from 928 to 834 Tg C, and the understory (including shrub and grass) biomass increased from 59 to 63 Tg C. Soil carbon and dead biomass carbon increased from 1136 to 1197 Tg C.Our analyses suggest that both natural and human processes have significant influence on the carbon change in California. During 1951-2000, climate interannual variability was the key driving force for the large interannual changes of ecosystem carbon source and sink at the state level, while logging and fire were the dominant driving forces for carbon balances in several specific ecoregions. From a long-term perspective, CO₂ fertilization plays a key role in maintaining higher NPP. However, our study shows that the increase in C sequestration by CO₂ fertilization is largely offset by logging/land use change and wildland fires.     

Assessing the Ecological and Social Benefits of Private Land Conservation in Colorado

Abstract: Conservation of private land through conservation easements, development agreements, and clustered housing has increased greatly as have criticisms of the laws, public programs, and incentives that motivate landowners to use them. Rapid land‐use change at the urban–rural interface in Larimer County, Colorado, has given rise to programs that provide a variety of land‐conservation options for landowners. As of January 2005, roughly 60% of Larimer County was publicly owned, and 3% or 16,200 ha was privately owned with some form of protection. We used document analysis, a landowner survey, targeted interviews, and a landscape‐level spatial analysis to analyze the patterns, quantities, and qualities of private land conservation. We created a jurisdiction‐specific typology of desired benefits from local government‐planning documents to help evaluate conservation parcels. Most easements and other conservation documents used general terms and did not describe the site‐specific values of the land being conserved. Landowners were able to describe some benefits not included in parcel‐specific documents, and our spatial analysis revealed parcel‐specific and cumulative conservation benefits such as the amount of buffering, infill, connectivity, protected agricultural land, riparian protection, and other benefits not referenced by either documents or landowners. Conservation benefits provided by a parcel varied depending on its geographic location, the specific institution such as a land trust or open space program that a landowner worked with, and the conservation mechanism used, such as voluntary easement or residential clustering requirements. The methods we used provide a template for jurisdictions wishing to undertake a similar analysis. Our findings may assist other jurisdictions and institutions interested in improving how land‐conservation benefits are described; justify and inform future investments in private land conservation; assist local governments and other institutions with the assessment of program effectiveness; and be useful for conservation planners who wish to become more involved in on‐the‐ground implementation of conservation actions.     

Spatially distributed modeling of the long-term carbon balance of a boreal landscape

Spatially and temporally distributed information on the sizes of biomass carbon (C) pools (BCPs) and soil C pools (SCPs) is vital for improving our understanding of biosphere-atmosphere C fluxes. Because the sizes of C pools result from the integrated effects of primary production, age-effects, changes in climate, atmospheric CO₂ concentration, N deposition, and disturbances, a modeling scheme that interactively considers these processes is important. We used the InTEC model, driven by various spatio-temporal datasets to simulate the long-term C-balance in a boreal landscape in eastern Canada. Our results suggested that in this boreal landscape, mature coniferous stands had stabilized their productivity and fluctuated as a weak C-sink or C-source depending on the interannual variations in hydrometeorological factors. Disturbed deciduous stands were larger C-sinks (NEP₂₀₀₄ = 150 gC m⁻² yr⁻¹) than undisturbed coniferous stands (e.g. NEP₂₀₀₄ = 8 gC m⁻² yr⁻¹). Wetlands had lower NPP but showed temporally consistent C accumulation patterns. The simulated spatio-temporal patterns of BCPs and SCPs were unique and reflected the integrated effects of climate, plant growth and atmospheric chemistry besides the inherent properties of the C pool themselves. The simulated BCPs and SCPs generally compared well with the biometric estimates (BCPs: r = 0.86, SCPs: r = 0.84). The largest BCP biases were found in recently disturbed stands and the largest SCP biases were seen in locations where moss necro-masses were abundant. Reconstructing C pools and C fluxes in the ecosystem in such a spatio-temporal manner could help reduce the uncertainties in our understanding of terrestrial C-cycle.     

Impacts of residential development on vegetation cover for a remote coastal barrier in the Outer Banks of North Carolina, USA

Coastal barrier environments are heavily influenced by human activities yet there are few examples of landscape ecological work investigating human dimensions of settlement disturbance patterns and processes. We investigated the impacts of residential development on vegetation cover for a remote roadless coastal barrier in Carova, North Carolina that is subject to policies from the federal to local levels and addressed three research questions: How has the region’s the policy history influenced patterns of residential parcel development? What are the spatial and temporal patterns of parcel development? How has development impacted patterns of barrier vegetation cover? We traced the influences of the federal 1982 Coastal Barrier Resources Act (CBRA) designed to discourage development in risky coastal areas as well as state/local coastal policies and employed remote sensing change detection, NDVI analysis and spatial analysis and regression techniques. Results showed an acceleration of new housing structures since 1990, contrary to the intended effects of CBRA. An estimated vegetation cover loss of 437 m² was associated with each newly developed parcel. NDVI varied along spatial and temporal gradients with more recent development having lower NDVI than older development. Recently developed parcels were larger in area, closer to the beach, and contained houses with larger footprints compared to older developed parcels. Our approach represents a place-based analytical framework for coastal barrier landscapes. Beyond the Carova case study, adopting such an approach coupling natural and human systems for the entire eastern US barrier system requires defining a comprehensive set of coastal barrier spatial units to enable typological classification and subsequent systematic investigation to inform debates regarding coastal ecosystem services and sustainability.     

Identification of important factors for water vapor flux and CO2 exchange in a cropland

Water vapor flux and carbon dioxide (CO₂) exchange in croplands are crucial to water and carbon cycle research as well as to global warming evaluation. In this study, a standard three-layer feed-forward back propagation neural network technique associated with the Bayesian technique of automatic relevance determination (ARD) was employed to investigate water vapor and CO₂ exchange between the canopy of summer maize and atmosphere in responses to variations of environmental and physiological factors. These factors, namely the photosynthetically active radiation (PAR), air temperature (T), vapor pressure deficient (VPD), leaf-area index (LAI), soil water content in root zone (W), and friction velocity (U*), were used as inputs in neural network analysis. Results showed that PAR, VPD, T and LAI were the primary factors regulating both water vapor and CO₂ fluxes with VPD and W more critical to water vapor flux and PAR and T more crucial to CO₂ exchange. Furthermore, two time variables “day of the year (DOY)” and “time of the day (TOD)” could also improve the simulation results of neural network analysis. The important factors identified by the neural network technique used in this study were in the order of PAR > T > VPD > LAI > U* > TOD for water vapor flux and in the order of VPD > W > LAI > T > PAR > DOY for CO₂ exchange. This study suggests that neural network technique associated with ARD could be a useful tool for identifying important factors regulating water vapor and CO₂ fluxes in terrestrial ecosystem.     

Application of least-cost path model to identify a giant panda dispersal corridor network after the Wenchuan earthquake—Case study of Wolong Nature Reserve in China

With growing levels of human-activity and frequent natural disturbances throughout the world, it is increasingly important that both research and management efforts take into account the widespread landscape fragmentation and its consequences for biodiversity conservation. The magnitude 5.12 Wenchuan earthquake in China caused dramatic impacts on giant panda (Ailuropoda melanoleuca) habitat in the nature reserves within Minshan and Qionglai mountains. With the combined stresses of the natural disaster and the extensive human activities during postquake reconstruction, giant panda habitat in this region may become more fragmented in the future. In order to preserve the giant panda population after the earthquake and protect the species against habitat fragmentation, this article explores a method of identifying giant panda migration corridors involving habitat suitability assessments and a least-cost path model. Focusing on postquake Wolong Nature Reserve, our results demonstrate that it contains 430.3 km² of suitable habitat (21.1% of total area), 463.8 km² of marginally suitable habitat (22.8%) and 1141.9 km² of unsuitable habitat (50.1%). We further show that several giant panda dispersal corridors exist in the reserve, including four corridor groups that cross the provincial highway and five corridors that do not intersect areas of human activity. This study will contribute to management and conservation efforts in Wolong Nature Reserve and beyond after the Wenchuan earthquake.     

Modelling llama population development under environmental and market constraints in the Bolivian highlands

Changes in the size of animal populations over time are mainly determined by demographic and environmental factors. Livestock population dynamics are additionally influenced by harvesting decisions taken by herders. In Bolivia, not much is known about current llama husbandry and the main influencing factors determining population sizes. We collected data on demography, environmental factors and market values affecting the current and future llama population in three different regions in Bolivia. We generated a population model and assessed the future development of the llama population including environmental factors (rangeland carrying capacity, disturbance phenomena), herd structure and dynamics, and economic market demands. We calibrated and validated the llama model on the basis of 20-year data sets of the regions of Oruro, Potosi and La Paz, respectively. Model calibration by means of the Gauss-Marquardt-Levenberg algorithm yielded a model efficiency of 0.94. For model validation, however, the simulation slightly overestimated the observed llama population yielding model efficiencies of 0.91 and 0.87 for Potosi and La Paz, respectively. Model outcomes were most sensitive to death and birth rates of juveniles and death rate of females compared to environmental or other demographic factors. Population trajectories approached an overall carrying capacity for Oruro, Potosi and La Paz of 8.8 × 10⁵, 9.1 × 10⁵, and 9.0 × 10⁵ llama individuals after 100 years of simulation. Hence, detailed monitoring of demographic, environmental, and economic factors can improve predictions of llama population development over time. Further management should focus on improving birth rates and lowering female mortality through providing supplemental food and shelters against the harsh environmental conditions of the Andean highlands.     

On the use of growth rate parameters for projecting population sizes: Application to aphids

This paper extends the application of the cumulative size based mechanistic model, which has previously been shown to describe diverse aphid population size data well. The mechanistic model is reviewed with a focus on the explanatory role of the birth and death rate formulation. An analysis of two data sets, one on the mustard aphid and the other on the pecan aphid, indicates that multiple linear regression equations based on the estimated birth and death rate parameters alone account for nearly all (R² > 0.95) of the variability in two key population attributes, namely the peak count and the cumulative density. This indicates that population size variables may be projected directly from the growth rate parameters using linear equations. Such linear relationships based on the birth and death rate parameters are shown to hold also for certain generalized mechanistic models for which the analytical solution is not available. The birth and death rate coefficients, therefore, constitute a new succinct set of variables that could be included in the predictive modeling of aphid populations, as well as other insect and animal populations with local collapse which follow similar growth dynamics.