Species distribution modelling—Effect of design and sample size of pseudo-absence observations

We explored the effect of varying pseudo-absence data in species distribution modelling using empirical data for four real species and simulated data for two imaginary species. In all analyses we used a fixed study area, a fixed set of environmental predictors and a fixed set of presence observations. Next, we added pseudo-absence data generated by different sampling designs and in different numbers to assess their relative importance for the output from the species distribution model. The sampling design strongly influenced the predictive performance of the models while the number of pseudo-absences had minimal effect on the predictive performance. We attribute much of these results to the relationship between the environmental range of the pseudo-absences (i.e. the extent of the environmental space being considered) and the environmental range of the presence observations (i.e. under which environmental conditions the species occurs). The number of generated pseudo-absences had a direct effect on the predicted probability, which translated to different distribution areas. Pseudo-absence observations that fell within grid cells with presence observations were purposely included in our analyses. We discourage the practice of excluding certain pseudo-absence data because it involves arbitrary assumptions about what are (un)suitable environments for the species being modelled.     

An inventory of tree species in Europe—An essential data input for air pollution modelling

We present a detailed tree species inventory covering Europe, parts of Africa and parts of Asia. The inventory contains 39 groups of species that are important for biogenic VOCs or pollen emission calculations. For example: oak (Quercus), poplar (Populus), pines (Pinus), spruce (Picea), birch (Betula) and alder (Alnus). The inventory is based on national forest inventories and national statistics and gives tree species distribution in percentage within broadleaved as well as conifer forests. The inventory includes data from 799 regions and is redistributed into the 50 km × 50 km EMEP grid. The inventory is therefore prepared for easy implementation into atmospheric transport models by providing an extension to already applied land use data such as the Corine Land Cover (CLC2000) or Global Land Cover (GLC2000). The gridded version of the data set will be available on the webpage http://www.dmu.dk/International/Air/Models/Background/Trees/.     

Trees and rural households’ adaptation to local environmental change in the central highlands of Ethiopia

This study assesses the role of trees in adaptation strategies of rural households to local environmental change in the central highlands of Ethiopia. Change in tree cover was assessed by producing Land Use and Land Cover (LULC) maps using satellite remote sensing images, and household survey was conducted to generate socioeconomic data. The results show that tree cover has increased over the last 30 years, mostly in the form of eucalyptus woodlots around homesteads. Eucalyptus reportedly helps households pass through livelihood shocks and provide protection against negative effects of climate change and variability. Despite some concerns on the part of local agricultural experts that planting eucalyptus may affect future food production, farmers are converting their croplands into eucalyptus woodlots. We conclude that land use planning and proper allocation of land resource is important to improve local livelihoods while also supporting adaptation of communities to local environmental change in general and climate change in particular.     

Spatially explicit modeling of overstory manipulations in young forests: Effects on stand structure and light

Young forests can be manipulated in diverse ways to enhance their ecological values. We used stem maps from two dense, second-growth stands in western Washington and a spatially explicit light model (tRAYci) to simulate effects of five silvicultural manipulations on diameter distribution, species composition, spatial patterning, and light availability. Each treatment removed 30% of the basal area, but differed in how trees were selected for removal. Three primary treatments were thin from below (removing the smallest trees), random thin (removing trees randomly), and gap creation (removing all trees in circles ∼1 tree height in diameter). Two additional treatments combined elements of these approaches: random ecological thin (a mixture of thin from below and random thin) and structured ecological thin (a mixture of thin from below and gap creation).     

Dances with Horses: Lessons from the Environmental Fringe

When environmental activists disregard or show contempt for facts and the rules of evidence, their intrusion into environmental issues may be perversely counterproductive. Using field and telephone interview data and unpublished and published documents, including court briefs, I show that certain activists misrepresented the Nevada Bureau of Land Management in its custodial role for the nation's wild horses. The core of the misrepresentation was an independent census of Nevada's wild horses conducted by the Public Lands Resource Council, an ad hoc association. These census data differ dramatically from those produced by the Bureau of Land Management. The latter data were confirmed, in part, by Bureau of Land Management roundups in northcentral Nevada. The Animal Rights Law Clinic at the Rutger's School of Law joined forces with the Public Lands Resource Council and used the council's questionable census results in an attack on the Bureau of Land Management's horse program. A careful probing of environmentalist agendas and data is at least as important as careful scientific design, execution, and display of results. Saving species and ecosystems is, then, as much an exercise in human psychology and the politics and sociology of advocacy groups as it is in conservation biology.     

Bridging information domains to improve ecological understanding of biological invasions in a marine ecosystem

We devised a practical method for integrating information on 2 marine invasive species using 3 different approaches: standardized ecological monitoring, online-reporting databases, and surveys of anglers and crabbers. Focusing on 2 recently introduced species with different characteristics, the Asian shore crab (Hemigrapsus sanguineus) and Chinese mitten crab (Eriocheir sinensis), in the Hudson-Raritan watershed of New York and New Jersey, we used sensitivity analyses to explore the relative contribution of each information source to knowledge of species abundance and distribution. All 3 information sources contributed something unique to understanding abundance and distribution of the introduced crabs. Online and survey data on Asian shore crabs significantly affected predictions of abundance, whereas monitoring data did not. When survey data were omitted, abundance estimates were unchanged over time, but when they were included, the model predicted an increased abundance in 2012. All 3 data sets for the Asian shore crab significantly affected estimates of species coverage; surveys had the biggest influence, increasing range size by 4097.25 km². For the catadromous Chinese mitten crab, ecological monitoring data collected in freshwater shortly after the original sighting significantly shaped model estimates for abundance and documented the establishment phase of the mitten crab in an area outside the spatial scope of the surveyed resource users. However, the survey data significantly enlarged mitten crab range-size estimates by 6498.01 km². By demonstrating that data integration produced an image of the invasion process that would not have emerged had we used any 1 method individually, model results provide evidence for the advantages of an interdisciplinary approach.     

SEIB–DGVM: A new Dynamic Global Vegetation Model using a spatially explicit individual-based approach

We report the development of a new spatially explicit individual-based Dynamic Global Vegetation Model (SEIB–DGVM), the first DGVM that can simulate the local interactions among individual trees within a spatially explicit virtual forest. In the model, a sample plot is placed at each grid box, and then the growth, competition, and decay of each individual tree within each plot is calculated by considering the environmental conditions for that tree as it relates to the trees that surround it. Based on these parameters only, the model simulated time lags between climate change and vegetation change. This time lags elongated when original biome was forest, because existing trees prevent newly establish trees from receiving enough sunlight and space to quickly replace the original vegetation. This time lags also elongated when horizontal heterogeneity of sunlight distribution was ignored, indicating the potential importance of horizontal heterogeneity for predicting transitional behavior of vegetation under changing climate. On a local scale, the model reproduced climate zone-specific patterns of succession, carbon dynamics, and water flux, although on a global scale, simulations were not always in agreement with observations. Because the SEIB–DGVM was formulated to the scale at which field biologists work, the measurements of relevant parameters and data comparisons are relatively straightforward, and the model should enable more robust modeling of terrestrial ecosystems.     

Defining Historical Baselines for Conservation: Ecological Changes Since European Settlement on Vancouver Island,Canada

Abstract: Conservation and restoration goals are often defined by historical baseline conditions that occurred prior to a particular period of human disturbance, such as European settlement in North America. Nevertheless, if ecosystems were heavily influenced by native peoples prior to European settlement, conservation efforts may require active management rather than simple removal of or reductions in recent forms of disturbance. We used pre‐European settlement land survey records (1859–1874) and contemporary vegetation surveys to assess changes over the past 150 years in tree species and habitat composition, forest density, and tree size structure on southern Vancouver Island and Saltspring Island, British Columbia, Canada. Several lines of evidence support the hypothesis that frequent historical burning by native peoples, and subsequent fire suppression, have played dominant roles in shaping this landscape. First, the relative frequency of fire‐sensitive species (e.g., cedar [Thuja plicata]) has increased, whereas fire‐tolerant species (e.g., Douglas‐fir [Pseudotsuga menziesii]) have decreased. Tree density has increased 2‐fold, and the proportion of the landscape in forest has greatly increased at the expense of open habitats (plains, savannas), which today contain most of the region's threatened species. Finally, the frequency distribution of tree size has shifted from unimodal to monotonically decreasing, which suggests removal of an important barrier to tree recruitment. In addition, although most of the open habitats are associated with Garry oak (Quercus garryana) at present, most of the open habitats prior to European settlement were associated with Douglas‐fir, which suggests that the current focus on Garry oak as a flagship for the many rare species in savannas may be misguided. Overall, our results indicate that the maintenance and restoration of open habitats will require active management and that historical records can provide critical guidance to such efforts.     

The pattern of species turnover resulting from stochastic population dynamics: The model and field data

The model of random population dynamics in a sampling site returns geometric distribution of longevities of continuous presence (=persistence) and Poisson distribution of the presence–absence transitions. This discrete-time stochastic process describes the presence–absence pattern observed in the beetles surveyed 6 years on Mount Carmel, Israel. Homogeneous pools of species mostly on the Families rank, exhibit the predicted by the model patterns. Conformity to an ergodic hypothesis is the criterion of ecological homogeneity. This criterion assumes the equivalence of short-term behavior of entire pool and long-term behavior of any species from this pool. The pool of all 801 species of Order Coleoptera does not match the model. Thus a taxon of an arbitrary rank may not be considered a priory as a unit of ecological study. Determined from field data parameters of the model are biased and magnitude of the bias depends on longevity of the survey. Parameter of distribution depends also on species tolerance, which is the level adaptation of given species to given environment in given time interval. Random process of species turnover may be considered as a game of species to gain their presence against deteriorative fluctuations of environmental conditions.     

Combining a generic process-based productivity model and a statistical classification method to predict the presence and absence of tree species in the Pacific Northwest,U.S.A.

Although long-lived tree species experience considerable environmental variation over their life spans, their geographical distributions reflect sensitivity mainly to mean monthly climatic conditions. We introduce an approach that incorporates a physiologically based growth model to illustrate how a half-dozen tree species differ in their responses to monthly variation in four climatic-related variables: water availability, deviations from an optimum temperature, atmospheric humidity deficits, and the frequency of frost. Rather than use climatic data directly to correlate with a species’ distribution, we assess the relative constraints of each of the four variables as they affect predicted monthly photosynthesis for Douglas-fir, the most widely distributed species in the region. We apply an automated regression-tree analysis to create a suite of rules, which differentially rank the relative importance of the four climatic modifiers for each species, and provide a basis for predicting a species’ presence or absence on 3737 uniformly distributed U.S. Forest Services’ Forest Inventory and Analysis (FIA) field survey plots. Results of this generalized rule-based approach were encouraging, with weighted accuracy, which combines the correct prediction of both presence and absence on FIA survey plots, averaging 87%. A wider sampling of climatic conditions throughout the full range of a species’ distribution should improve the basis for creating rules and the possibility of predicting future shifts in the geographic distribution of species.     

Resampling methods for estimating dispersion indices in random and adaptive designs

In many surveys in environmental and natural phenomena the aim is to evaluate the heterogeneity, and the skewness of the distribution of the number point-objects in the study area opportunely partitioned in sub-regions. For this purpose, in this paper the estimation of dispersion indices is considered by using simple random sampling and adaptive sampling with initial simple random sampling selected with replacement or without replacement. The jackknife and the bootstrap procedures are proposed in both cases for reducing bias. Finally, both a simulation study and a case study on biological population referred to a Oidium tuckeri contamination in a growing vineyard is performed to assess the accuracy of the proposed estimators.     

Non-Timber forest products: Conservation status and management priorities in the community managed forests of Andhra Pradesh,South India

Primary surveys were conducted in 20 villages and an equal number of community managed forests (CMFs) of two districts, Adilabad and Chittoor in the state of Andhra Pradesh in southern India. The interviews conducted with 216 respondents listed a total of 22 and 23 non-timber forest products (NTFP) from Adilabad and Chittoor districts, respectively, of which 15 species were common to both study districts. Eight of these NTFPs, including, Sterculia urens, Thysanolena maxima, Sapindus emerginatus, Dendrocalamus strictus, Pongamia pinnata, Schleichera oleosa, Azadirachta indica and Diospyros melenoxylon were collected for commercial purposes. The vegetation survey was conducted in a total of 240 sample plots in 20 CMFs, and found 15 NTFP species from Adilabad and 18 NTFP species from Chittoor. The density of NTFP trees in Adilabad was 52 trees/ha, as against an overall tree density of 278 trees/ha, while in Chittoor it was only 28 trees/ha as against an overall density of 110 trees/ha. The regeneration density of NTFP species was, however, higher in Chittoor. Some of the NTFP species, prioritized for conservation, included Sterculia urens, Tamarindus indica, Phyllanthus emblica, Strychnos nuxvomica, S. potatorum and Anogeissus latifolia.     

Gradient forests: calculating importance gradients on physical predictors

In ecological analyses of species and community distributions there is interest in the nature of their responses to environmental gradients and in identifying the most important environmental variables, which may be used for predicting patterns of biodiversity. Methods such as random forests already exist to assess predictor importance for individual species and to indicate where along gradients abundance changes. However, there is a need to extend these methods to whole assemblages, to establish where along the range of these gradients the important compositional changes occur, and to identify any important thresholds or change points. We develop such a method, called "gradient forest," which is an extension of the random forest approach. By synthesizing the cross-validated R2 and accuracy importance measures from univariate random forest analyses across multiple species, sampling devices, and surveys, gradient forest obtains a monotonic function of each predictor that represents the compositional turnover along the gradient of the predictor. When applied to a synthetic data set, the method correctly identified the important predictors and delineated where the compositional change points occurred along these gradients. Application of gradient forest to a real data set from part of the Great Barrier Reef identified mud fraction of the sediment as the most important predictor, with highest compositional turnover occurring at mud fraction values around 25%, and provided similar information for other predictors. Such refined information allows for more accurate capturing of biodiversity patterns for the purposes of bioregionalization, delineation of protected areas, or designing of biodiversity surveys.     

A spatial zero-inflated poisson regression model for oak regeneration

Ecological counts data are often characterized by an excess of zeros and spatial dependence. Excess zeros can occur in regions outside the range of the distribution of a given species. A zero-inflated Poisson regression model is developed, under which the species range is determined by a spatial probit model, including physical variables as covariates. Within that range, species counts are independently drawn from a Poisson distribution whose mean depends on biotic variables. Bayesian inference for this model is illustrated using data on oak seedling counts. Received: May 2004 / Revised: December 2004     

Effects of sample survey design on the accuracy of classification tree models in species distribution models

We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by resubstitution rates were similar for each lichen species irrespective of the underlying sample survey form. Cross-validation estimates of prediction accuracies were lower than resubstitution accuracies for all species and both design types, and in all cases were closer to the true prediction accuracies based on the EVALUATION data set. We argue that greater emphasis should be placed on calculating and reporting cross-validation accuracy rates rather than simple resubstitution accuracy rates. Evaluation of the DESIGN and PURPOSIVE tree models on the EVALUATION data set shows significantly lower prediction accuracy for the PURPOSIVE tree models relative to the DESIGN models, indicating that non-probabilistic sample surveys may generate models with limited predictive capability. These differences were consistent across all four lichen species, with 11 of the 12 possible species and sample survey type comparisons having significantly lower accuracy rates. Some differences in accuracy were as large as 50%. The classification tree structures also differed considerably both among and within the modelled species, depending on the sample survey form. Overlap in the predictor variables selected by the DESIGN and PURPOSIVE tree models ranged from only 20% to 38%, indicating the classification trees fit the two evaluated survey forms on different sets of predictor variables. The magnitude of these differences in predictor variables throws doubt on ecological interpretation derived from prediction models based on non-probabilistic sample surveys.     

Design-based estimation in environmental surveys with positional errors

The recent increased availability of information about the micro-geographic positions of population units in environmental surveys has led to important developments in spatial sampling methodologies and, as a result, has improved the estimation accuracy. In real data, however, information about the location of units is often affected by inaccuracy about their exact spatial positions, and these non-sampling errors can affect the estimation procedure. This paper aims to investigate the effects of positional errors on total estimation through a Monte-Carlo simulation study based on real populations of trees. Starting from perfect positioning, we examine two typical types of coarsening that frequently impact two different species of trees. The simulation results show that the exploitation of spatial information to estimate population totals continues to be relevant in the context of environmental surveys, even in the presence of inaccuracies.     

Submesoscale distribution of Antarctic krill and its avian and pinniped predators before and after a near gale

We conducted two ship-based surveys of the nearshore ecosystem north of Livingston Island, Antarctica during 2–10 February 2005. Between the two surveys, a low-pressure system (963 mbar) passed through the area providing the opportunity to measure ecosystem parameters before and after a near gale. A ship-based multiple-frequency acoustic-backscatter survey was used to assess the distribution and relative abundance of Antarctic krill (Euphausia superba). Net tows, hydrographic profiles, and meteorological data were collected to measure biological and physical processes that might affect the krill population. During the survey, the distribution and behavior of several krill predators [chinstrap penguins (Pygoscelis antarctica), cape petrels (Daption capense), and Antarctic fur seals (Arctocephalus gazella)] were measured from the vessel by visual observations. The survey encompassed an area of roughly 2,500 km², containing two submarine canyons with one to the west and one to the east of Cape Shirreff, which had different abundances of krill and predators. Several aspects of the nearshore ecosystem changed after the near gale including: hydrography of the upper 100 m of the water column, phytoplankton biomass, the abundance and distribution of krill, and the distribution of some krill predators. Differences in these parameters were also measured between the two canyons. These changes in the physical and biological environment during the survey period are quantified and show that the ecosystem exhibited significant changes over relatively short spatial (tens of kilometers) and time (tens of hours) scales.     

Settlement seasonality and temporal changes in hard substrate macrozoobenthic communities of Lesina Lagoon (Apulia, Southern Adriatic Sea)

The macrofauna settling on experimental substrates was studied at two sites of the Lesina Lagoon to test its possible role in monitoring ecological variations in a brackish-water ecosystem. The community settlement was seasonally investigated on 3-month-old wooden poles; the development was monitored from 2001 to 2005. Comparisons with benthic assemblages settled on 10-yr-old poles were also performed. The main hydrological parameters were periodically measured during the study. A total of 38 species were collected. The assemblage reached the highest development in the central lagoon, showing relevant carbonate structures which supported a rich vagile fauna. Close to the sea-water inlet species richness and abundance values were lower, with the disappearance of some brackish-water species. A remarkable salinity drop during 2004 produced some faunistic changes in the assemblages, which however maintained different structures between the study sites, thus confirming macrozoobenthos as an efficient bioindicator of different environmental conditions for transition biotopes and a useful investigation tool in monitoring programmes.     

Modeling the Effect of Climate Change on the Distribution of Oak and Pine Species of Mexico

Abstract:  We examined the vulnerability of 34 species of oaks ( Quercus ) and pines ( Pinus ) to the effects of global climate change in Mexico. We regionalized the HadCM2 model of climate change with local climatic data (mean annual temperature and rainfall) and downscaled the model with the inverse distance-weighted method. Databases of herbaria specimens, genetic algorithms (GARP), and digital covers of biophysical variables that affect oaks and pines were used to project geographic distributions of the species under a severe and conservative scenario of climate change for the year 2050. Starting with the current average temperature of 20.2 °C and average precipitation of 793 mm, under the severe warming scenario mean temperature and precipitation changed to 22.7 °C and 660 mm, respectively, in 2050. For the conservative warming scenario, these variables shifted to 21.8 °C and 721 mm. Responses to the different scenarios of climate change were predicted to be species-specific and related to each species climate affinity. The current geographic distribution of oaks and pines decreased 7–48% and 0.2–64%, respectively. The more vulnerable pines were Pinus rudis , P. chihuahuana , P. oocarpa , and P. culminicola , and the most vulnerable oaks were Quercus crispipilis , Q. peduncularis , Q. acutifolia , and Q. sideroxyla . In addition to habitat conservation, we think sensitive pine and oak species should be looked at more closely to define ex situ strategies (i.e., seed preservation in germplasm banks) for their long-term conservation. Modeling climatic-change scenarios is important to the development of conservation strategies.