Use of Coarse‐Resolution Models of Species’ Distributions to Guide Local Conservation Inferences

Abstract: Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter (Lutra lutra), in the Iberian Peninsula. The models, built from presence–absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time‐consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse‐resolution distribution data are available to define high‐quality areas at a scale that is practical for the application of concrete conservation measures.     

The importance of incorporating functional habitats into conservation planning for highly mobile species in dynamic systems

The distribution of mobile species in dynamic systems can vary greatly over time and space. Estimating their population size and geographic range can be problematic and affect the accuracy of conservation assessments. Scarce data on mobile species and the resources they need can also limit the type of analytical approaches available to derive such estimates. We quantified change in availability and use of key ecological resources required for breeding for a critically endangered nomadic habitat specialist, the Swift Parrot (Lathamus discolor). We compared estimates of occupied habitat derived from dynamic presence‐background (i.e., presence‐only data) climatic models with estimates derived from dynamic occupancy models that included a direct measure of food availability. We then compared estimates that incorporate fine‐resolution spatial data on the availability of key ecological resources (i.e., functional habitats) with more common approaches that focus on broader climatic suitability or vegetation cover (due to the absence of fine‐resolution data). The occupancy models produced significantly (P < 0.001) smaller (up to an order of magnitude) and more spatially discrete estimates of the total occupied area than climate‐based models. The spatial location and extent of the total area occupied with the occupancy models was highly variable between years (131 and 1498 km²). Estimates accounting for the area of functional habitats were significantly smaller (2–58% [SD 16]) than estimates based only on the total area occupied. An increase or decrease in the area of one functional habitat (foraging or nesting) did not necessarily correspond to an increase or decrease in the other. Thus, an increase in the extent of occupied area may not equate to improved habitat quality or function. We argue these patterns are typical for mobile resource specialists but often go unnoticed because of limited data over relevant spatial and temporal scales and lack of spatial data on the availability of key resources. Understanding changes in the relative availability of functional habitats is crucial to informing conservation planning and accurately assessing extinction risk for mobile resource specialists.     

Spatially stratified sampling using auxiliary information for geostatistical mapping

This paper presents a method of spatial sampling based on stratification by Local Moran’s I _i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.     

Spatial structure effects on the detection of patches boundaries using local operators

Landscapes exhibit various degrees of spatial heterogeneity according to the differential intensity and interactions among processes and disturbances that they are subjected to. The management of these spatially dynamical landscapes requires that we can accurately map them and monitor the evolution of their spatial arrangement through time. Such a mapping requires first the delineation of various spatial features present in the landscape such as patches and their boundaries. However, there are several environmental (spatial variability) as well as technical (spatial resolution) factors that impair our ability to accurately delineate patches and their boundaries as polygons. Here, we investigate how the spatial structure and spatial resolution of the data affect the accuracy of detecting patches and their boundaries over simulated landscapes and real data. Simulated landscapes consisted of two patches with parameterized spatial properties (patches’ level of spatial autocorrelation, mean value and variance) separated by a boundary of known location. Real data allowed the investigation of a more complex landscape where there is a known transition between two forest domains with unknown spatial properties. Boundary locations are defined using the lattice-wombling edge detector at various aggregation levels and the degree of patch homogeneity is determined using Getis-Ord’s G*. Results show that boundary detection using a local edge detector is greatly affected by the spatial conditions of the data, namely variance, abruptness of the spatial gradient between two patches and patches’ level of spatial autocorrelation. They also suggest that data aggregation is not a panacea for bringing out the ecological process creating the patches and that indicators derived from local measures of spatial association can be complementary tools for analysing spatial structures affecting boundary delineation.

Importance of deepening integration of crime and conservation sciences

Conservation crime is a globally distributed societal problem. Conservation crime science, an emerging interdisciplinary field, has the potential to help address this problem. However, its utility depends on serious reflection on the transposition of crime science approaches to conservation contexts, which may differ in meaningful ways from traditional crime contexts. We considered the breadth of crime science approaches being used in conservation as well as the depth of crime science integration in conservation. We used the case of sea cucumber (Holothuria floridana, Isostichopus badionotus) trafficking in Mexico as an example of why the interdisciplinarity of crime and conservation sciences should be deepened and how integration can help ideate new solutions. We first conducted a review of literature to capture the range of interdisciplinarity applications. We identified 6 crime science approaches being applied to the conservation contexts of illegal, unreported, and unregulated fishing; wildlife and plant crime; and illegal logging. We then compared this knowledge base to the case of illegal sea cucumber fishing in Mexico. We identified 5 challenges in the application of these approaches to conservation contexts: the relative diffusion of harms and victims in conservation crimes; scalar mismatches in crime, authority, and the conservation issue itself; interactions between legal and illegal networks; communities and their authority to define and control crime; and the role of natural science in the rule of law. Considering these 5 factors may enhance the depth of interdisciplinarity between crime and conservation sciences. Nurturing interdisciplinary crime and conservation science will expand innovation and help accelerate successful risk management programs and other policy agendas.     

Combined Effects of Levels of Protection and Environmental Variables at Different Spatial Resolutions on Fish Assemblages in a Marine Protected Area

Abstract: The links between species–environment relations and species’ responses to protection are unclear, but the objectives of marine protected areas (MPAs) are most likely to be achieved when those relations are known and inform MPA design. The components of a species’ habitat vary with the spatial resolution of the area considered. We characterized areas at two resolutions: 250 m² (transect) and approximately 30,000 m² (seascape). We considered three categories of environmental variables: substrate type, bottom complexity, and depth. We sought to determine at which resolution habitat characteristics were a better predictor of abundance and species composition of fishes and whether the relations with environmental variables at either resolution affected species’ responses to protection. Habitat features accounted for a larger proportion of spatial variation in species composition and abundances than differences in protection status. This spatial variation was explained best by habitat characteristics at the seascape level than at the transect level. Species’ responses to protected areas were specific to particular seascape characteristics, primarily depth, and bottom complexity. Our method may be useful for prioritizing marine areas for protection, designing MPAs, and monitoring their effectiveness. It identified areas that provided natural shelter, areas acting as buffer zones, and areas where fish species were most responsive to protection. The identification of such areas is necessary for cost‐effective establishment and monitoring of MPAs.     

Estimating digestion time in gelatinous predators: a methodological comparison with the scyphomedusa Aurelia aurita

In order to quantify the trophic impact of gelatinous predators, digestion time estimates are commonly applied to counts of prey in the guts. Three primary approaches are used, the Manual-feeding, Natural-feeding and Steady-state methods; these differ in methodology and their underlying assumptions. The criteria used to define the end-point of digestion, and the resolution at which digestion progress is observed, also vary across studies. To understand the impact of such differences, we estimate digestion times of the scyphomedusa Aurelia aurita fed adult females of the copepod Acartia tonsa using these various approaches. We find ~fourfold differences which can be attributed to bias towards the slowest rates of digestion by some end-point criteria, and overestimation from low observation resolution. Artificial manipulation and the degree to which swimming and feeding behaviour are natural may also influence estimates. We provide recommendations for those quantifying digestion times of Aurelia aurita medusae and gelatinous predators.     

Evaluation of variance approximation techniques for non-linear photosynthesis—irradiance models

Parameters derived from photosynthesis-irradiance (P-I) models, although often empirical in nature, are useful indicators of the photoadaptive state of phytoplankton in culture and in situ. However objective criteria for determining significant changes in P-I curves are rarely provided, because confidence intervals for parameters of non-linear models are not estimated easily. Examination of least-squares residuals in parameter space and Monte Carlo approaches have been used to estimate confidence regions around parameter values, but the computationally intensive nature of these methods has prevented their routine application. We present an alternative method of estimating confidence intervals for parameters of P-I curves that runs quickly on a microcomputer and is easily combined with common parameter-estimation routines. This algorithm was tested using a 3-parameter P-I model and curves describing a wide range of photoadaptive states, with different numbers of observations and different amounts of inherent variability. The method produced results comparable to the Monte Carlo technique. This analysis makes it possible to specify the sample size required to define parameters with acceptable confidence as a function of data variance and photoadaptive state. In most reasonable situations, 25 observations are sufficient.     

Identification of calanoid copepod prey species via molecular detection of carbon fixation genes

Zooplankton and their phytoplankton prey form the basis of the marine food web, yet historically it has been difficult to discern species-specific trophic interactions. Molecular techniques provide opportunities to obtain taxonomic data where the traditional methodologies for gut content analysis lack resolution. The large subunit gene of RubisC/O, rbcL, was utilized as a molecular marker for the identification of prey species in calanoid copepods. Clone libraries were generated from DNA extracted from seawater and whole copepods during a transect cruise on the northern Gulf of Mexico shelf. Sequence data analysis provided evidence of diatoms, nanoplankton-sized chlorophytes, and cyanobacteria in DNA extracted from whole copepods. These data demonstrate that rbcL can be a useful marker for the identification of copepod phytoplankton prey. Combining the described approach with quantitative techniques such as quantitative PCR will provide opportunities for the assessment of species-specific predator–prey interactions.     

Biochemical composition and trophic strategies of the amphipod Eurythenes gryllus at hadal depths (Atacama Trench,South Pacific)

Amphipods Eurythenes gryllus were collected at 7800?m depth in the Atacama Trench (South Pacific) for studying their biochemical composition (in terms of proteins, lipids and carbohydrates and fatty acid content) and to gather information on bioenergetic strategies and trophic habits of organisms living in this extreme environment. The effect of long-term formalin storage on the biochemical determinations was also determined. Proteins were the dominant biochemical class of organic compounds (39–53%D.W.), whereas carbohydrates accounted for a very small fraction (1–2%D.W.). Lipid concentrations of E. gryllus accounted for 7–18%D.W. and were much lower than those reported for other deep-sea amphipods. These differences are likely to be more dependent upon food availability in the Atacama Trench rather than upon temperature. Lipid composition of E. gryllus revealed the dominance of monounsaturated fatty acids with polyunsaturated fatty acids accounting for a very small fraction, suggesting that hadal amphipods are higher dependent upon lipid reserves than amphipods inhabiting at shallow depths. The ratio of C18:1Δ⁹ to C18:1Δ¹¹ was >11 confirming the necrophagous trophic habits of this hadal amphipod.     

The problem of specifying otolith-mass growth parameters in the radiometric estimation of fish age using whole otoliths

A problem in the radiometric estimation of age using whole otoliths is the necessity to specify otolith-mass growth. Unless it can be assumed that otolith-mass growth is linear, parameters describing this growth will occur in the radiometric equation used to estimate age. Previous authors have assumed that the values of these parameters must be known before age can be estimated. This leads to circular reasoning: to estimate the age of a fish (and thus infer its growth) prior knowledge about the growth of the otolith is needed. A reanalysis of published radiometric data for Hoplostethus atlanticus is presented to illustrate two new approaches that avoid this assumption and thus the problem of circular reasoning. The first calculates the age that is most probable for each sample given the radiometric and otolith-mass data; the second estimates a lower bound for the maximum age. These analyses depend on correcting a misinterpretation of the otolith-mass term in a common radiometric equation. The effect of between-individual variability in otolith growth rates on the radiometric method is discussed.     

An integrated sustainability decision-support framework Part II: Problem analysis

One of the main goals in decision-making for sustainable development is to identify and choose the most sustainable option among different alternatives. This process usually involves a large number of stakeholders with multiple, often conflicting objectives. Facilitating and resolving such difficult decision situations can be complex, so that a more formal and systematic approach to decision-making may be necessary. This paper proposes an integrated multiple criteria decision-support framework specifically developed to provide a systematic, step-by-step guidance to decision-makers. The framework, which is suitable for both corporate and public policy-making in the context of sustainable development, comprises three steps: problem structuring, problem analysis and problem resolution. This paper concentrates on problem analysis and resolution, where decision-makers articulate their preferences for different decision criteria. A suitable Multiple Criteria Decision Analysis (MCDA) technique, such as multi-objective optimisation, goal programming, value-based and outranking approaches, is then used to model the preferences. These techniques are discussed here in some detail, to provide guidance on the choice of the most appropriate MCDA method. Based on the outcome of preference modelling, which estimates the overall 'value' of each alternative being considered, decision-makers can then choose the 'best' or most sustainable option. Such an integrated decision-support framework is useful for providing structure to the debate, ensuring dialogue among decision-makers and showing trade-offs between conflicting objectives. In this way, it may be possible to create shared understanding about the issues, generate a sense of common purpose and, often, resolve 'difficult' decision problems.     

The effectiveness of incentives in protected area management: An empirical analysis

Incentive approaches are believed to be indispensable for effective conservation and successful management in protected areas. However, the actual effectiveness of these approaches is still debatable. We carried out a case study in Wolong Biosphere Reserve (WBR), the largest reserve for the giant panda (Ailuropoda melanoleuca), to evaluate the effectiveness of incentives. We obtained data from government documents and statistics, interviews and surveys on the employment status of public sector and industries. Results indicated that government-paid community-based conservation projects provided the most widespread and direct economic incentives. The conservation sector and several industries including hotels, hydropower and tourism have directly raised the employment level of local communities. The hotel industry, driven by the development of tourism, has been the most effective means of increasing local employment. However, the problem of immigrants attracted by the improved economic situation in WBR should be considered in the management plans. Suggestions for WBR management include development of quality ecotourism, vocational education for local young adults and new policies encouraging employment of local labour, both in the reserve and outside. Lessons learned from this research are constructive for the management of other protected areas.     

An integrated sustainability decision-support framework Part I: Problem structuring

One of the main goals in decision-making for sustainable development is to identify and choose the most sustainable option from among different alternatives. This process usually involves a large number of stakeholders with multiple, often conflicting, objectives. Facilitating and resolving such difficult decision situations can be complex, so that a more formal and systematic approach to decision-making may be necessary. This two-part paper proposes an integrated multiple criteria decision-support framework specifically developed to provide systematic, step-by-step guidance to decision-makers. The framework, which is suitable for both corporate and public policy-making in the context of sustainable development, comprises three steps: problem structuring, problem analysis and problem resolution. In this paper, the focus is on problem structuring while Part II concentrates on problem analysis and resolution. Problem structuring includes identification of stakeholders, sustainability issues and indicators relevant for a particular decision problem. Sustainability indicators are used as decision criteria for identifying and choosing the most sustainable option. In the problem analysis step, decision makers articulate their preferences for different decision criteria. A suitable Multiple Criteria Decision Analysis (MCDA) technique, such as multi-objective optimisation, goal programming, value-based and outranking approaches, is then used to model the preferences. These techniques are discussed in Part II, which also gives guidance on the choice of the most appropriate MCDA method. Based on the outcome of preference modelling, which estimates the overall 'value' of each alternative being considered, decision-makers can then choose the 'best' or most sustainable option. Such an integrated decision-support framework is useful for providing structure to the debate, ensuring dialogue among decision-makers and showing trade-offs between conflicting objectives. In this way, it may be possible to create shared understanding about the issues, generate a sense of common purpose, and often, resolve 'difficult' decision problems.     

Body morphologies shape territorial dominance in the satyrine butterfly <Emphasis Type="Italic">Lethe diana</Emphasis>

Male butterflies compete over mating territories via aerial interactions. It has often been suggested that flight performance, and thus flight-related traits, would play an important role in butterflies’ contest resolution; however, most studies have not demonstrated a clear relationship between these traits and territory ownership in butterflies. Males of the satyrine butterfly Lethe diana compete over territories via linear chases, a behavior that is uncommon among butterflies: rather, contests of most butterfly species consist of circling flights. In the present study, some morphological and physiological traits of L. diana were compared between territory owners and intruders to search for traits correlated with resource holding power (RHP). Territory owners had higher flight-muscle ratio (FMR) and were heavier than intruders, indicating that flight performance plays a key role in their contest resolution. Contest duration was not affected by the owners’ FMR or body mass, and thus I obtained no evidence supporting the hypothesis that contestants assess their relative RHP before making a decision to retreat. I speculate that the fact that these traits had an effect on territorial status in L. diana was a result of the characteristics of the contest behavior of this butterfly. During their contests, males L. diana fly faster in their linear flights than males of most other butterflies, which engage in slower circling flights. Therefore, males of L. diana probably need higher flight performance capabilities in order to win their contests.     

PIXGRO: A model for simulating the ecosystem CO2 exchange and growth of spring barley

A model, PIXGRO, developed by coupling a canopy flux sub-model (PROXEL_NEE; PROcess-based piXEL Net Ecosystem CO₂ Exchange) to a vegetation structure submodel (CGRO), for simulating both net ecosystem CO₂ exchange (NEE) and growth of spring barley is described. PIXGRO is an extension of the stand-level CO₂ and H₂O-flux model PROXEL_NEE, that simulates the NEE on a process basis, but goes further to include the dry matter production, partitioning, and crop development for spring barley. Dry matter partitioned to the leaf was converted to leaf area index (LAI) using relationships for the specific leaf area (SLA). The canopy flux component, PROXEL_NEE was calibrated using information from the literature on C3 plants and was tested using CO₂ flux data from an eddy-covariance (EC) method in Finland with long-term observations. The growth component (CGRO) was calibrated using data from the literature on spring barley as well as data from the Finland site. It was then validated against field data from two sites in Germany and partly via the use of MODIS remotely sensed LAI from the Finland site.Both the diurnal and the seasonal patterns of gross CO₂ uptake were very well simulated (R² = 0.92). A slight seasonal bias may be attributed to leaf ageing. Crop growth was also well simulated; simulated dry matter agreed with field observed data from Germany (R² = 0.90). For LAI, the agreement between the simulated and observed was good (R² = 0.80), giving an indication that functions describing the conversion of fixed CO₂ to dry matter and the subsequent partitioning leaf dry matter and LAI simulation were robust and provided reliable estimates.The MODIS LAI at a resolution of 1000 m agreed poorly (R² = 0.45) with the PIXGRO simulated LAI and the observed LAI at the Finland site in 2001. We attributed this to the coarse resolution of the image and/or the small size of the barley field (about 17 ha or 0.25 km²) at the Finland site. By deriving a regression relation between the observed LAI and NDVI from a higher resolution MODIS (500 m resolution), the MODIS-recalculated LAI agreed better with the PIXGRO-simulated LAI (R² = 0.86).PIXGRO provides a prototype model bridging the disciplines of plant physiology, crop modeling and remote sensing, for use in a spatial context in evaluating carbon balances and plant growth at stand level, landscape, regional, and with some care, continental scales. Since almost 50% of the European land surface is covered by crops, such a model is needed for the dynamic estimation of LAI and NEE of croplands.     

Evaluating the Quality of Citizen‐Scientist Data on Pollinator Communities

Abstract: Concerns about pollinator declines have grown in recent years, yet the ability to detect changes in abundance, taxonomic richness, and composition of pollinator communities is hampered severely by the lack of data over space and time. Citizen scientists may be able to extend the spatial and temporal extent of pollinator monitoring programs. We developed a citizen‐science monitoring protocol in which we trained 13 citizen scientists to observe and classify floral visitors at the resolution of orders or super families (e.g., bee, wasp, fly) and at finer resolution within bees (superfamily Apoidea) only. We evaluated the protocol by comparing data collected simultaneously at 17 sites by citizen scientists (observational data set) and by professionals (specimen‐based data set). The sites differed with respect to the presence and age of hedgerows planted to improve habitat quality for pollinators. We found significant, positive correlations among the two data sets for higher level taxonomic composition, honey bee (Apis mellifera) abundance, non‐Apis bee abundance, bee richness, and bee community similarity. Results for both data sets also showed similar trends (or lack thereof) in these metrics among sites differing in the presence and age of hedgerows. Nevertheless, citizen scientists did not observe approximately half of the bee groups collected by professional scientists at the same sites. Thus, the utility of citizen‐science observational data may be restricted to detection of community‐level changes in abundance, richness, or similarity over space and time, and citizen‐science observations may not reliably reflect the abundance or frequency of occurrence of specific pollinator species or groups.     

Phylogenetic characterisation of bacterial symbionts in the accessory nidamental glands of the sepioid Sepia officinalis (Cephalopoda: Decapoda)

 Female cuttlefish harbour a dense bacterial community in their accessory nidamental glands (ANG), as is also the case for the myopsid squids. Molecular approaches have been applied to explore this symbiotic association in the sepiid species Sepia officinalis. In situ localisation by Bacteria-specific probes in tissue sections of the ANG revealed the presence of a dense bacterial population in the lumina of the organ tubules. The phylogenetic identification of bacterial strains was realised by 16S rRNA gene sequencing analysis. None of the sequences obtained matched perfectly with known sequences in the database. However their similarity percentages allowed us to relate them to various bacterial groups including the taxa Agrobacterium, Roseobacter, Sporichthya, Rhodobium–Xanthobacter and Clostridium. Some bacterial species are common to both sepioids and myopsid teuthoids, others are different. Received: 28 May 1999 / Accepted: 2 November 1999     

Southern Ocean biogeography and taxonomic resolution: what’s in the name?

We examined the taxonomic resolution of zooplankton data required to identify ocean basin scale biogeographic zonation in the Southern Ocean. A 2,154 km transect was completed south of Australia. Sea surface temperature (SST) measured at 1 min intervals showed that seven physical zones were sampled. Zooplankton were collected at a spatial resolution of ~9.2 km with a continuous plankton recorder, identified to the highest possible taxonomic resolution and enumerated. Zooplankton assemblage similarity between samples was calculated using the Bray–Curtis index for the taxonomic levels of species, genus, family, order and class after first log₁₀(x + 1) (LA) and then presence/absence (PA) transformation of abundance data. Although within and between zone sample similarity increased with decreasing taxonomic resolution, for both data transformations, cluster analysis demonstrated that the biogeographic separation of zones remained at all taxonomic levels when using LA data. ANOSIM confirmed this, detecting significant differences in zooplankton assemblage structure between all seven a priori determined physical zones for all taxonomic levels when using the LA data. In the case of the PA data for the complete data set, and both LA and PA data for a crustacean only data set, no significant differences were detected between zooplankton assemblages in the Polar frontal zone (PFZ) and inter-PFZ at any taxonomic level. Loss of information at resolutions below the species level, particularly in the PA data, prevented the separation of some zones. However, the majority of physical zones were biogeographically distinct from species level to class using both LA and PA transformations. Significant relationships between SST and zooplankton community structure, summarised as NMDS scores, at all taxonomic levels, for both LA and PA transformations, and complete and crustacean only data sets, highlighted the biogeographic relevance of low resolution taxonomic data. The retention of biogeographic information in low taxonomic resolution data shows that data sets collected with different taxonomic resolutions may be meaningfully merged for the post hoc generation of Southern Ocean time series.     

AIC model selection and multimodel inference in behavioral ecology: some background,observations, and comparisons

We briefly outline the information-theoretic (I-T) approaches to valid inference including a review of some simple methods for making formal inference from all the hypotheses in the model set (multimodel inference). The I-T approaches can replace the usual t tests and ANOVA tables that are so inferentially limited, but still commonly used. The I-T methods are easy to compute and understand and provide formal measures of the strength of evidence for both the null and alternative hypotheses, given the data. We give an example to highlight the importance of deriving alternative hypotheses and representing these as probability models. Fifteen technical issues are addressed to clarify various points that have appeared incorrectly in the recent literature. We offer several remarks regarding the future of empirical science and data analysis under an I-T framework.