Hydrologic processes on tree islands in the Everglades (Florida, USA): tracking the effects of tree establishment and growth

The hydrodynamics of tree islands during the growth of newly planted trees has been found to be influenced by both vegetation biomass and geologic conditions. From July 2007 through June 2009, groundwater and surface-water levels were monitored on eight recently planted tree islands at the Loxahatchee Impoundment Landscape Assessment (LILA) facility in Boynton Beach, Florida, USA. Over the 2-year study, stand development coincided with the development of a water-table depression in the center of each of the islands that was bounded by a hydraulic divide along the edges. The water-table depression was greater in islands composed of limestone as compared to those composed of peat. The findings of this study suggest that groundwater evapotranspiration by trees on tree islands creates complex hydrologic interactions between the shallow groundwater in tree islands and the surrounding surface water and groundwater bodies.

The role of recharge and evapotranspiration as hydraulic drivers of ion concentrations in shallow groundwater on Everglades tree islands, Florida (USA)

Recently, evapotranspiration has been hypothesized to promote the secondary formation of calcium carbonate year-round on tree islands in the Everglades by influencing groundwater ions concentrations. However, the role of recharge and evapotranspiration as drivers of shallow groundwater ion accumulation has not been investigated. The goal of this study is to develop a hydrologic model that predicts the chloride concentrations of shallow tree island groundwater and to determine the influence of overlying biomass and underlying geologic material on these concentrations. Groundwater and surface water levels and chloride concentrations were monitored on eight constructed tree islands at the Loxahatchee Impoundment Landscape Assessment (LILA) from 2007 to 2010. The tree islands at LILA were constructed predominately of peat, or of peat and limestone, and were planted with saplings of native tree species in 2006 and 2007. The model predicted low shallow groundwater chloride concentrations when inputs of regional groundwater and evapotranspiration-to-recharge rates were elevated, while low evapotranspiration-to-recharge rates resulted in a substantial increase of the chloride concentrations of the shallow groundwater. Modeling results indicated that evapotranspiration typically exceeded recharge on the older tree islands and those with a limestone lithology, which resulted in greater inputs of regional groundwater. A sensitivity analysis indicated the shallow groundwater chloride concentrations were most sensitive to alterations in specific yield during the wet season and hydraulic conductivity in the dry season. In conclusion, the inputs of rainfall, underlying hydrologic properties of tree islands sediments and forest structure may explain the variation in ion concentration seen across Everglades tree islands.

Survival and growth responses of eight Everglades tree species along an experimental hydrological gradient on two tree island types

Questions: How are the early survival and growth of seedlings of Everglades tree species planted in an experimental setting on artificial tree islands affected by hydrology and substrate type? What are the implications of these responses for broader tree island restoration efforts? Location: Loxahatchee Impoundment Landscape Assessment (LILA), Boynton Beach, Florida, USA. Methods: An experiment was designed to test hydrological and substrate effects on seedling growth and survivorship. Two islands – a peat and a limestone-core island representing two major types found in the Everglades – were constructed in four macrocosms. A mixture of eight tree species was planted on each island in March of 2006 and 2007. Survival and height growth of seedlings planted in 2006 were assessed periodically during the next two and a half years. Results: Survival and growth improved with increasing elevation on both tree island substrate types. Seedlings' survival and growth responses along a moisture gradient matched species distributions along natural hydrological gradients in the Everglades. The effect of substrate on seedling performance showed higher survival of most species on the limestone tree islands, and faster growth on their peat-based counterparts. Conclusions: The present results could have profound implications for restoration of forests on existing landforms and artificial creation of tree islands. Knowledge of species tolerance to flooding and responses to different edaphic conditions present in wetlands is important in selecting suitable species to plant on restored tree islands

The Role of Recharge and Evapotranspiration as Hydraulic Drivers of Ion Concentrations in Shallow Groundwater on Everglades Tree Islands, Florida (USA)

Recently, evapotranspiration has been hypothesized to promote the secondary formation of calcium carbonate year-round on tree islands in the Everglades by influencing groundwater ions concentrations. However, the role of recharge and evapotranspiration as drivers of shallow groundwater ion accumulation has not been investigated. The goal of this study is to develop a hydrologic model that predicts the chloride concentrations of shallow tree island groundwater and to determine the influence of overlying biomass and underlying geologic material on these concentrations. Groundwater and surface water levels and chloride concentrations were monitored on eight constructed tree islands at the Loxahatchee Impoundment Landscape Assessment (LILA) from 2007 to 2010. The tree islands at LILA were constructed predominately of peat, or of peat and limestone, and were planted with saplings of native tree species in 2006 and 2007. The model predicted low shallow groundwater chloride concentrations when inputs of regional groundwater and evapotranspiration-to-recharge rates were elevated, while low evapotranspiration-to-recharge rates resulted in a substantial increase of the chloride concentrations of the shallow groundwater. Modeling results indicated that evapotranspiration typically exceeded recharge on the older tree islands and those with a limestone lithology, which resulted in greater inputs of regional groundwater. A sensitivity analysis indicated the shallow groundwater chloride concentrations were most sensitive to alterations in specific yield during the wet season and hydraulic conductivity in the dry season. In conclusion, the inputs of rainfall, underlying hydrologic properties of tree islands sediments and forest structure may explain the variation in ion concentration seen across Everglades tree islands.

Integrated Surface-Ground Water Modeling in Wetlands With Improved Methods to Simulate Vegetative Resistance to Flow

This dissertation focused on developing an integrated surface – subsurface hydrologic simulation numerical model by programming and testing the coupling of the USGS MODFLOW-2005 Groundwater Flow Process (GWF) package (USGS, 2005) with the 2D surface water routing model: FLO-2D (O’Brien et al., 1993). The coupling included the necessary procedures to numerically integrate and verify both models as a single computational software system that will heretofore be referred to as WHIMFLO-2D (Wetlands Hydrology Integrated Model). An improved physical formulation of flow resistance through vegetation in shallow waters based on the concept of drag force was also implemented for the simulations of floodplains, while the use of the classical methods (e.g., Manning, Chezy, Darcy-Weisbach) to calculate flow resistance has been maintained for the canals and deeper waters. A preliminary demonstration exercise WHIMFLO-2D in an existing field site was developed for the Loxahatchee Impoundment Landscape Assessment (LILA), an 80 acre area, located at the Arthur R. Marshall Loxahatchee National Wild Life Refuge in Boynton Beach, Florida. After applying a number of simplifying assumptions, results have illustrated the ability of the model to simulate the hydrology of a wetland. In this illustrative case, a comparison between measured and simulated stages level showed an average error of 0.31% with a maximum error of 2.8%. Comparison of measured and simulated groundwater head levels showed an average error of 0.18% with a maximum of 2.9%.

Assessment and management of the geomorphological heritage of Monte Pindo (NW Spain): a landscape as a symbol of identity

This study focuses on the granite mountain known as Monte Pindo (627 m above sea level) in the Autonomous Community of Galicia (NW Spain). This territory is included in the area classified as “Costa da Morte” in the “Politica de Ordenación Litoral” (POL) (Coastal Planning Policy) for the region of Galicia. This coastal unit, located between “Rías Baixas” and “Cape Fisterra” has great potential for demonstrating geological processes and its geomorphological heritage is characterized by a high degree of geodiversity of granite landforms. The main objective of our work is to assess the geomorphological heritage of the site, thus revealing its wide geodiversity. We shall analyze and highlight: its scientific value, developing an inventory of granite landforms; its educational valuel and its geotouristic potential. It must be ensured that the Administration understands that natural diversity is composed of both geodiversity and biodiversity. Only then will the sustainable management of Monte Pindo become possible by integrating natural and cultural heritage values. The goal is to ensure that Monte Pindo and its immediate surroundings become a geopark with the aim of promoting local development projects based on the conservation and valorization of its geological heritage.

Assembling spatially explicit landscape models of pollen and spore dispersal by wind for risk assessment

Models of windblown pollen or spore movement are required to predict gene flow from genetically modified (GM) crops and the spread of fungal diseases. We suggest a simple form for a function describing the distance moved by a pollen grain or fungal spore, for use in generic models of dispersal. The function has power-law behaviour over sub-continental distances. We show that air-borne dispersal of rapeseed pollen in two experiments was inconsistent with an exponential model, but was fitted by power-law models, implying a large contribution from distant fields to the catches observed. After allowance for this 'background' by applying Fourier transforms to deconvolve the mixture of distant and local sources, the data were best fit by power-laws with exponents between 1.5 and 2. We also demonstrate that for a simple model of area sources, the median dispersal distance is a function of field radius and that measurement from the source edge can be misleading. Using an inverse-square dispersal distribution deduced from the experimental data and the distribution of rapeseed fields deduced by remote sensing, we successfully predict observed rapeseed pollen density in the city centres of Derby and Leicester (UK).

Risk assessment of UK skylark populations using life-history and individual-based landscape models

Abstract: Following a workshop exercise, two models, an individual-based landscape model (IBLM) and a non-spatial life-history model were used to assess the impact of a fictitious insecticide on populations of skylarks in the UK. The chosen population endpoints were abundance, population growth rate, and the chances of population persistence. Both models used the same life-history descriptors and toxicity profiles as the basis for their parameter inputs. The models differed in that exposure was a pre-determined parameter in the life-history model, but an emergent property of the IBLM, and the IBLM required a landscape structure as an input. The model outputs were qualitatively similar between the two models. Under conditions dominated by winter wheat, both models predicted a population decline that was worsened by the use of the insecticide. Under broader habitat conditions, population declines were only predicted for the scenarios where the insecticide was added. Inputs to the models are very different, with the IBLM requiring a large volume of data in order to achieve the flexibility of being able to integrate a range of environmental and behavioural factors. The life-history model has very few explicit data inputs, but some of these relied on extensive prior modelling needing additional data as described in Roelofs et al.(2005, this volume). Both models have strengths and weaknesses; hence the ideal approach is that of combining the use of both simple and comprehensive modeling tools.

Experimental assessment of Heliconia acuminata growth in a fragmented Amazonian landscape

1 Fragmentation severely alters physical conditions in forest understories, but few studies have connected these changes to demographic impacts on forest species using detailed experimental examination at the individual and population levels.2 Using a 32-month, reciprocal-transplant experiment, we show that individuals of the Amazonian understory herb Heliconia acuminata transplanted into forest fragments lost over 20% of their vegetative shoots, while those transplanted to continuous forest showed a slight gain. The leaf area of plants in fragments also increased at half the rate it did in continuous forest sites.3 It appears that the normal dry season stresses to which forest understorey plants are exposed are greatly exacerbated in fragments, causing plants to shed shoots and leaves.4 the observed shifts in size could help explain why populations in fragments are more skewed towards smaller demographic stage classes than those in continuous forest. These shifts in size structure could also result in reduced abundances of flowering plants, as reproduction in H. acuminata is positively correlated with shoot number.5 Fragmentation-related changes in growth rates resulting from abiotic stress may have significant demographic consequences.

An experimental assessment of landscape configuration effects on frog and toad abundance and diversity in tropical agro-savannah landscapes of southeastern Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Landscape and forest structure at moose mortality sites on Isle Royale National Park. A LiDAR based assessment

Landscape structure and heterogeneity play a potentially important, but little understood role in predator-prey interactions and behaviourally-mediated habitat selection. For example, habitat complexity may either reduce or enhance the efficiency of a predator's efforts to search, track, capture, kill and consume prey. For prey, structural heterogeneity may affect predator detection, avoidance and defense, escape tactics, and the ability to exploit refuges. This study, investigates whether and how vegetation and topographic structure influence the spatial patterns and distribution of moose (Alces alces) mortality due to predation and malnutrition at the local and landscape levels on Isle Royale National Park. 230 locations where wolves (Canis lupus) killed moose during the winters between 2002 and 2010, and 182 moose starvation death sites for the period 1996-2010, were selected from the extensive Isle Royale Wolf-Moose Project carcass database. A variety of LiDAR-derived metrics were generated and used in an algorithm model (Random Forest) to identify, characterize, and classify three-dimensional variables significant to each of the mortality classes. Furthermore, spatial models to predict and assess the likelihood at the landscape scale of moose mortality were developed. This research found that the patterns of moose mortality by predation and malnutrition across the landscape are non-random, have a high degree of spatial variability, and that both mechanisms operate in contexts of comparable physiographic and vegetation structure. Wolf winter hunting locations on Isle Royale are more likely to be a result of its prey habitat selection, although they seem to prioritize the overall areas with higher moose density in the winter. Furthermore, the findings suggest that the distribution of moose mortality by predation is habitat-specific to moose, and not to wolves. In addition, moose sex, age, and health condition also affect mortality site selection, as revealed by subtle differences between sites in vegetation heights, vegetation density, and topography. Vegetation density in particular appears to differentiate mortality locations for distinct classes of moose. The results also emphasize the significance of fine-scale landscape and habitat features when addressing predator-prey interactions. These finer scale findings would be easily missed if analyses were limited to the broader landscape scale alone.

Landscape mosaics maps as a basis for spatial assessment and negotiation of ecosystem services and their trade-offs at the meso-scale: Examples from Laos, Madagascar and China

Mapping ecosystem services (ES) and their trade-offs is a key requirement for informed decision making for land use planning and management of natural resources that aim to move towards increasing the sustainability of landscapes. The negotiations of the purposes of landscapes and the services they should provide are difficult as there is an increasing number of stakeholders active at different levels with a variety of interests present on one particular landscape.Traditionally, land cover data is at the basis for mapping and spatial monitoring of ecosystem services. In light of complex landscapes it is however questionable whether land cover per se and as a spatial base unit is suitable for monitoring and management at the meso-scale. Often the characteristics of a landscape are defined by prevalence, composition and specific spatial and temporal patterns of different land cover types. The spatial delineation of shifting cultivation agriculture represents a prominent example of a land use system with its different land use intensities that requires alternative methodologies that go beyond the common remote sensing approaches of pixel-based land cover analysis due to the spatial and temporal dynamics of rotating cultivated and fallow fields.Against this background we advocate that adopting a landscape perspective to spatial planning and decision making offers new space for negotiation and collaboration, taking into account the needs of local resource users, and of the global community. For this purpose we introduce landscape mosaicsdefined as new spatial unit describing generalized land use types. Landscape mosaics have allowed us to chart different land use systems and land use intensities and permitted us to delineate changes in these land use systems based on changes of external claims on these landscapes. The underlying idea behindthe landscape mosaics is to use land cover data typically derived from remote sensing data and to analyse and classify spatial patterns of this land cover data using a moving window approach. We developed the landscape mosaics approach in tropical, forest dominated landscapesparticularly shifting cultivation areas and present examples ofour work from northern Laos, eastern Madagascarand Yunnan Province in China.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

Heterogeneity of atmosfpheric ammonia at the landscape scale and consequences for environmental impact assessment.

We examined the consequences of the spatial heterogeneity of atmospheric ammonia (NH3) by measuring and modelling NH3 concentrations and deposition at 25 m grid resolution for a rural landscape containing intensive poultry farming, agricultural grassland, woodland and moorland. The emission pattern gave rise to a high spatial variability of modelled mean annual NH3 concentrations and dry deposition. Largest impacts were predicted for woodland patches located within the agricultural area, while larger moorland areas were at low risk, due to atmospheric dispersion, prevailing wind direction and low NH3 background. These high resolution spatial details are lost in national scale estimates at 1 km resolution due to less detailed emission input maps. The results demonstrate how the spatial arrangement of sources and sinks is critical to defining the NH3 risk to semi-natural ecosystems. These spatial relationships provide the foundation for local spatial planning approaches to reduce environmental impacts of atmospheric NH3.