Changes in heron and egret populations on the Laurentian Great Lakes and connecting channels, 1977-2009

Canadian and U.S. federal wildlife agencies completed four decadal surveys, spanning the years 1977 to 2009, to census colonial waterbirds breeding on the Great Lakes and adjoining bodies of water. In this paper, we reports abundance, distribution, and general population trends of three species: Black-crowned Night-Heron (Nycticorax nycticorax), Great Egret (Ardea alba), and Great Blue Heron (Ardea herodias). Estimates of nest numbers ranged from approximately 4000-6100 for the Black-crowned Night-Heron, 250-1900 for the Great Egret, and 3800-6400 for the Great Blue Heron. Average annual rates of change in nest numbers between the first (1977) and fourth (2008) census were −1% for the Black-crowned Night-Heron, +23% for the Great Egret, and −0.27% for the Great Blue Heron. Across the 30-year census, Black-crowned Night-Heron estimates decreased in U.S. (−57%) but increased (+18%) in Canadian waters, Great Egret nests increased 1381% in Canadian waters with a smaller, but still substantial increase in the number of nests at U.S. colonies (+613%), and Great Blue Heron numbers increased 148% in Canadian waters and 713% in U.S. waters. Although a single factor cannot be clearly linked to changes observed in each species’ distribution, hydrological variation, habitat succession, nest competition with Double-crested Cormorants (Phalacrocorax auritus), and land use changes likely all contributed. Management activities should support both breeding and foraging conditions including restoration of early successional habitats and anticipate continued northward expansions in the distributions of these waterbirds.

Inbreeding and loss of genetic variation in a reintroduced population of Mauritius Kestrel

Many populations have recovered from severe bottlenecks either naturally or through intensive conservation management. In the past, however, few conservation programs have monitored the genetic health of recovering populations. We conducted a conservation genetic assessment of a small, reintroduced population of Mauritius Kestrel (Falco punctatus) to determine whether genetic deterioration has occurred since its reintroduction. We used pedigree analysis that partially accounted for individuals of unknown origin to document that (1) inbreeding occurred frequently (2.6% increase per generation; N-el = 18.9), (2) 25% of breeding pairs were composed of either closely or moderately related individuals, (3) genetic diversity has been lost from the population (1,6% loss per generation; N-ev = 32.1) less rapidly than the corresponding increase in inbreeding, and (4) ignoring the contribution of unknown individuals to a pedigree will bias the metrics derived from that pedigree, ultimately obscuring the prevailing genetic dynamics. The rates of inbreeding and loss of genetic variation in the subpopulation of Mauritius Kestrel we examined were extreme and among the highest yet documented in a wild vertebrate population. Thus, genetic deterioration may affect this population's long-term viability. Remedial conservation strategies are needed to reduce the impact of inbreeding and loss of genetic variation in this species, We suggest that schemes to monitor genetic variation after reintroduction should be an integral component of endangered species recovery programs

Managing threatened species – the ecological toolbox, evolutionary theory and the declining-population paradigm

1. The management of threatened species is an important practical way in which conservationists can intervene in the extinction process and reduce the loss of biodiversity. Understanding the causes of population declines (past, present and future) is pivotal to designing effective practical management. This is the declining-population paradigm identified by Caughley. 2. There are three broad classes of ecological tool used by conservationists to guide management decisions for threatened species: statistical models of habitat use, demographic models and behaviour-based models. Each of these is described here, illustrated with a case study and evaluated critically in terms of its practical application. 3. These tools are fundamentally different. Statistical models of habitat use and demographic models both use descriptions of patterns in abundance and demography, in relation to a range of factors, to inform management decisions. In contrast, behaviourbased models describe the evolutionary processes underlying these patterns, and derive such patterns from the strategies employed by individuals when competing for resources under a specific set of environmental conditions. 4. Statistical models of habitat use and demographic models have been used successfully to make management recommendations for declining populations. To do this, assumptions are made about population growth or vital rates that will apply when environmental conditions are restored, based on either past data collected under favourable environmental conditions or estimates of these parameters when the agent of decline is removed. As a result, they can only be used to make reliable quantitative predictions about future environments when a comparable environment has been experienced by the population of interest in the past. 5. Many future changes in the environment driven by management will not have been experienced by a population in the past. Under these circumstances, vital rates and their relationship with population density will change in the future in a way that is not predictable from past patterns. Reliable quantitative predictions about population-level responses then need to be based on an explicit consideration of the evolutionary processes operating at the individual level. 6. Synthesis and applications. It is argued that evolutionary theory underpins Caughley’s declining-population paradigm, and that it needs to become much more widely used within mainstream conservation biology. This will help conservationists examine critically the reliability of the tools they have traditionally used to aid management decision-making. It will also give them access to alternative tools, particularly when predictions are required for changes in the environment that have not been experienced by a population in the past.

A novel parallel approach to the likelihood-based estimation of admixture in population genetics

Inferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic approaches are computationally demanding. Effectively exploiting the computational power of modern multiprocessor systems can thus have a positive impact to Monte Carlo-based simulation of admixture modeling. A novel parallel approach is briefly described and promising results on its message passing interface (MPI)-based C implementation are reported.

The use of image analysis to estimate population growth rate in Daphnia magna

1. Population growth rate (PGR) is central to the theory of population ecology and is crucial for projecting population trends in conservation biology, pest management and wildlife harvesting. Furthermore, PGR is increasingly used to assess the effects of stressors. Image analysis that can automatically count and measure photographed individuals offers a potential methodology for estimating PGR. 2. This study evaluated two ways in which the PGR of Daphnia magna, exposed to different stressors, can be estimated using an image analysis system. The first method estimated PGR as the ratio of counts of individuals obtained at two different times, while the second method estimated PGR as the ratio of population sizes at two different times, where size is measured by the sum of the individuals' surface areas, i.e. total population surface area. This method is attractive if surface area is correlated with reproductive value (RV), as it is for D. magna, because of the theoretical result that PGR is the rate at which the population RV increases. 3. The image analysis system proved reliable and reproducible in counting populations of up to 440 individuals in 5 L of water. Image counts correlated well with manual counts but with a systematic underestimate of about 30%. This does not affect accuracy when estimating PGR as the ratio of two counts. Area estimates of PGR correlated well with count estimates, but were systematically higher, possibly reflecting their greater accuracy in the study situation. 4. Analysis of relevant scenarios suggested the correlation between RV and body size will generally be good for organisms in which fecundity correlates with body size. In these circumstances, area estimation of PGR is theoretically better than count estimation. 5. Synthesis and applications. There are both theoretical and practical advantages to area estimation of population growth rate when individuals' reproductive values are consistently well correlated with their surface areas. Because stressors may affect both the number and quality of individuals, area estimation of population growth rate should improve the accuracy of predicting stress impacts at the population level.

Managing threatened species: the ecological toolbox, evolutionary theory and declining-population paradigm

1. The management of threatened species is an important practical way in which conservationists can intervene in the extinction process and reduce the loss of biodiversity. Understanding the causes of population declines (past, present and future) is pivotal to designing effective practical management. This is the declining-population paradigm identified by Caughley. 2. There are three broad classes of ecological tool used by conservationists to guide management decisions for threatened species: statistical models of habitat use, demographic models and behaviour-based models. Each of these is described here, illustrated with a case study and evaluated critically in terms of its practical application. 3. These tools are fundamentally different. Statistical models of habitat use and demographic models both use descriptions of patterns in abundance and demography, in relation to a range of factors, to inform management decisions. In contrast, behaviour-based models describe the evolutionary processes underlying these patterns, and derive such patterns from the strategies employed by individuals when competing for resources under a specific set of environmental conditions. 4. Statistical models of habitat use and demographic models have been used successfully to make management recommendations for declining populations. To do this, assumptions are made about population growth or vital rates that will apply when environmental conditions are restored, based on either past data collected under favourable environmental conditions or estimates of these parameters when the agent of decline is removed. As a result, they can only be used to make reliable quantitative predictions about future environments when a comparable environment has been experienced by the population of interest in the past. 5. Many future changes in the environment driven by management will not have been experienced by a population in the past. Under these circumstances, vital rates and their relationship with population density will change in the future in a way that is not predictable from past patterns. Reliable quantitative predictions about population-level responses then need to be based on an explicit consideration of the evolutionary processes operating at the individual level. 6. Synthesis and applications. It is argued that evolutionary theory underpins Caughley's declining-population paradigm, and that it needs to become much more widely used within mainstream conservation biology. This will help conservationists examine critically the reliability of the tools they have traditionally used to aid management decision-making. It will also give them access to alternative tools, particularly when predictions are required for changes in the environment that have not been experienced by a population in the past.

Comparative evaluation of a new effective population size estimator based on approximate Bayesian computation

We describe and evaluate a new estimator of the effective population size (N-e), a critical parameter in evolutionary and conservation biology. This new "SummStat" N-e. estimator is based upon the use of summary statistics in an approximate Bayesian computation framework to infer N-e. Simulations of a Wright-Fisher population with known N-e show that the SummStat estimator is useful across a realistic range of individuals and loci sampled, generations between samples, and N-e values. We also address the paucity of information about the relative performance of N-e estimators by comparing the SUMMStat estimator to two recently developed likelihood-based estimators and a traditional moment-based estimator. The SummStat estimator is the least biased of the four estimators compared. In 32 of 36 parameter combinations investigated rising initial allele frequencies drawn from a Dirichlet distribution, it has the lowest bias. The relative mean square error (RMSE) of the SummStat estimator was generally intermediate to the others. All of the estimators had RMSE > 1 when small samples (n = 20, five loci) were collected a generation apart. In contrast, when samples were separated by three or more generations and Ne less than or equal to 50, the SummStat and likelihood-based estimators all had greatly reduced RMSE. Under the conditions simulated, SummStat confidence intervals were more conservative than the likelihood-based estimators and more likely to include true N-e. The greatest strength of the SummStat estimator is its flexible structure. This flexibility allows it to incorporate any, potentially informative summary statistic from Population genetic data.

Detecting insect pollinator declines on regional and global scales.

Recently there has been considerable concern about declines in bee communities in agricultural and natural habitats. The value of pollination to agriculture, provided primarily by bees, is >$200 billion/year worldwide, and in natural ecosystems it is thought to be even greater. However, no monitoring program exists to accurately detect declines in abundance of insect pollinators; thus, it is difficult to quantify the status of bee communities or estimate the extent of declines. We used data from 11 multiyear studies of bee communities to devise a program to monitor pollinators at regional, national, or international scales. In these studies, 7 different methods for sampling bees were used and bees were sampled on 3 different continents. We estimated that a monitoring program with 200–250 sampling locations each sampled twice over 5 years would provide sufficient power to detect small (2–5%) annual declines in the number of species and in total abundance and would cost U.S.$2,000,000. To detect declines as small as 1% annually over the same period would require >300 sampling locations. Given the role of pollinators in food security and ecosystem function, we recommend establishment of integrated regional and international monitoring programs to detect changes in pollinator communities.

Improving assessment and modelling of climate change impacts on global terrestrial biodiversity.

Understanding how species and ecosystems respond to climate change has become a major focus of ecology and conservation biology. Modelling approaches provide important tools for making future projections, but current models of the climate-biosphere interface remain overly simplistic, undermining the credibility of projections. We identify five ways in which substantial advances could be made in the next few years: (i) improving the accessibility and efficiency of biodiversity monitoring data, (ii) quantifying the main determinants of the sensitivity of species to climate change, (iii) incorporating community dynamics into projections of biodiversity responses, (iv) accounting for the influence of evolutionary processes on the response of species to climate change, and (v) improving the biophysical rule sets that define functional groupings of species in global models.

Effects of detectability on estimates of geographic range size in bignonieae

Extinction risk has not been evaluated for 96% of all described plant species. Given that the Global Strategy for Plant Conservation proposes preliminary conservation assessments of all described plant species by 2010, herbarium specimens (i.e., primary occurrence data) are increasingly being used to infer threat components from estimates of geographic range size. Nevertheless, estimates of range size based on herbarium data may be inaccurate due to collection bias associated with interspecific variation in detectability. We used data on 377 species of Bignonieae to test the hypothesis that there is a positive relationship between detectability and estimates of geographic range size derived from herbarium specimens. This relationship is expected if the proportion of the true geographic range size of a species that is documented by herbarium specimens is given by the product of the true geographic range size and the detectability of the species, assuming no relationship between true geographic range size and detectability. We developed 4 measures of detectability that can be estimated from herbarium data and examined the relationship between detectability and 2 types of estimates of geographic range size: area of occupancy and extent of occurrence. Our results from regressing estimates of extent of occurrence and area of occupancy on detectability across genera provided no support for this hypothesis. The same was true for regressions of estimated extent of occurrence on detectability across species within genera. Nevertheless, regressions of estimated area of occupancy on detectability across species within genera provided partial support for our hypothesis. We considered 3 possible explanations for this mixed outcome: violation of the assumption of no relationship between true geographic range size and detectability; the relationships between estimated geographic range size and detectability may be an artifact of a negative relationship between estimated area of occupancy and the sampling variance of detectability; detectability may have had 2 opposite effects on estimated species range sizes: one determines the proportion of the true range of a species documented by herbarium specimens and the other determines the distribution of true range size for the species actually observed with herbarium data. Our findings should help improve understanding of the potential biases incurred with the use of herbarium data.

Habitat Split as a Cause of Local Population Declines of Amphibians with Aquatic Larvae

Most amphibian species have biphasic life histories and undergo an ontogenetic shift from aquatic to terrestrial habitats. In deforested landscapes, streams and forest fragments are frequently disjunct, jeopardizing the life cycle of forest-associated amphibians with aquatic larvae. We tested the impact of habitat split-defined as human-induced disconnection between habitats used by different life-history stages of a species-on four forest-associated amphibian species in a severely fragmented landscape of the Brazilian Atlantic Forest. We surveyed amphibians in forest fragments with and without streams (referred to as wet and dry fragments, respectively), including the adjacent grass-field matrix. Our comparison of capture rates in dry fragments and nearby streams in the matrix allowed us to evaluate the number of individuals that engaged in high-risk migrations through nonforested habitats. Adult amphibians moved from dry fragments to matrix streams at the beginning of the rainy season, reproduced, and returned at the end of the breeding period. Juveniles of the year moved to dry fragments along with adults. These risky reproductive migrations through nonforested habitats that expose individuals to dehydration, predation, and other hazards may cause population declines in dry fragments. Indeed, capture rates were significantly lower in dry fragments compared with wet fragments. Declining amphibians would strongly benefit from investments in the conservation and restoration of riparian vegetation and corridors linking breeding and nonbreeding areas.

Mitochondrial DNA Diversity of Orchid Bee Euglossa fimbriata (Hymenoptera: Apidae) Populations Assessed by PCR-RFLP

Euglossa fimbriata is a euglossine species widely distributed in Brazil and occurring primarily in Atlantic Forest remnants. In this study, the genetic mitochondrial structure of E. fimbriata from six Atlantic Forest fragments was studied by RFLP analysis of three PCR-amplified mtDNA gene segments (16S, COI-COII, and cyt b). Ten composite haplotypes were identified, six of which were exclusive and represented singleton mitotypes. Low haplotype diversity (0.085-0.289) and nucleotide diversity (0.000-0.002) were detected within samples. AMOVA partitioned 91.13% of the overall genetic variation within samples and 8.87% (I center dot(st) = 0.089; P < 0.05) among samples. Pairwise comparisons indicated high levels of differentiation among some pairs of samples (I center dot(st) = 0.161-0.218; P < 0.05). These high levels indicate that these populations of E. fimbriata, despite their highly fragmented landscape, apparently have not suffered loss of genetic variation, suggesting that this particular population is not currently endangered.

Taxon surrogates among Amazonian mammals: Can total species richness be predicted by single orders?

Limited financial sources and the difficulty in performing complete surveys, allied to the speed of habitat fragmentation and the urgent necessity in select conservation areas, create the necessity of using some methodologies which bypass these problems. One possibility is the use of surrogate taxa that might be used as indicator of others groups richness and even total richness of an area. We investigated if the use of surrogate taxon is useful among seven mammal orders in Amazon. We tested through Pearson`s correlation (Bonferroni`s adjusted) if (1) there was a correlation between richness of total species and some order; (2) there was a significant pair wise correlation between species richness of each order; and (3) the combination of two orders would give better results as a surrogate for the total richness. The correlations found, in general, were positive. It means that the increase in the richness of an order was followed by its increase in another order, as well as in the total species richness. Only Didelphimorphia was significantly correlated with the total species richness. In the pair wise analyses only one assembly, Primates and Artiodactyla, was significantly correlated with total richness. Since indicator species are more effective within taxonomic groups (life-history characteristics are likely to be more different among than within major taxonomic groups), we suggest that an indicator group might be chosen for each one. In this case, for mammals from Amazon, it would be Didelphimorphia. (C) 2008 Elsevier Ltd. All rights reserved.