A nested-intensity design for surveying plant diversity

Managers of natural landscapes need cost-efficient, accurate, and precise systems to inventory plant diversity. We investigated a nested-intensity sampling design to assess local and landscape-scale heterogeneity of plant species richness in aspen stands in southern Colorado, USA. The nested-intensity design used three vegetation sampling techniques: the Modified-Whittaker, a 1000-m² multiple-scale plot (n = 8); a 100-m² multiple-scale Intensive plot (n = 15); and a 100-m² single-scale Extensive plot (n = 28). The large Modified-Whittaker plot (1000 m²) recorded greater species richness per plot than the other two sampling techniques (P < 0.001), estimated cover of a greater number of species in 1-m² subplots (P < 0.018), and captured 32 species missed by the smaller, more numerous 100-m² plots of the other designs. The Intensive plots extended the environmental gradient sampled, capturing 17 species missed by the other techniques, and improved species–area calculations. The greater number of Extensive plots further expanded the gradient sampled, and captured 18 additional species. The multi-scale Modified-Whittaker and Intensive designs allowed quantification of the slopes of species–area curves in the single-scale Extensive plots. Multiple linear regressions were able to predict the slope of species–area curves (adj R ² = 0.64, P < 0.001) at each Extensive plot, allowing comparison of species richness at each sample location. Comparison of species–accumulation curves generated with each technique suggested that small, single-scale plot techniques might be very misleading because they underestimate species richness by missing locally rare species at every site. A combination of large and small multi-scale and single-scale plots greatly improves our understanding of native and exotic plant diversity patterns.     

Multi-scale comparisons of cliff vegetation in Colorado

We developed a nested vegetation sampling protocol to sample the plant diversity on south-facing cliffs and cliff bases in Jefferson County, Colorado. The multi-scale plots included three nested spatial scales, 1 m², 20 m², and 40 m². We compared plant species richness and species diversity among large cliffs, medium cliffs, small cliffs, and non-cliff sites using Hill's diversity numbers (N ₀, N ₁, and N ₂) for the 1-m² quadrats. Species richness (N ₀) was calculated for the 20-m² and 40-m² plots. Our results indicate that plant species diversity on the cliff faces did not increase with increasing cliff area. This pattern was consistent at all three sampling scales. A model selection was run to determine if plant species diversity values on the cliff faces were associated with cliff variables. None of the cliff variables measured were good predictors of diversity at the 1-m² scale. However, at the 20-m² scale, canyon differences and a positive relationship with increasing cliff surface roughness explained 70% of the variability in species richness. Although most plant species sampled on the cliff faces were also found in the base plots, 13 species were sampled only on the cliff faces. Additionally, dry south facing cliffs support a mix of xeric and mesic plants indicating that cliffs may provide unique microenvironments for plant establishment. This revised version was published online in August 2006 with corrections to the Cover Date.     

Are Plant Censuses Carried Out on Small Quadrats More Reliable than on Larger Ones?

Plant censuses are known to be significantly affected by observers’ biases. In this study, we checked whether the magnitude of observer effects (defined as the % of total variance) varied with quadrat size: we expected the census repeatability (% of the total variance that is not due to measurement errors) to be higher for small quadrats than for larger ones. Variations according to quadrat size of the repeatability of species richness, Simpson equitability and reciprocal diversity indices, Ellenberg indicator values, plant cover and plant frequency were assessed using 359 censuses of vascular plants. These were carried out independently by four professional botanists during spring 2002 on the same 18 forest plots, each comprising one 400-m² quadrat, four 4-m² and four 2-m² quadrats. Time expenditure was controlled for. General Linear Models using random effects only were applied to the ecological indices to estimate variance components and magnitude of the following effects (if possible): plot, quadrat, observer, plant species and two-way interactions. High repeatability was obtained for species richness and Ellenberg indicator values. Species richness and Ellenberg indicator values were generally more accurate but also more biased in large quadrats. Simpson reciprocal diversity and equitability indices were poorly repeatable (especially equitability) probably because plant cover estimates varied widely among observers, irrespective of quadrat size. Grouping small quadrats usually increased the repeatability of the variable considered (e.g. species richness, Simpson diversity, plant cover) but the number of plant species found on those pooled 16 m² was much lower than if large plots were sampled. We therefore recommend to use large, single quadrats for forest vegetation monitoring.     

Relationship between plant species richness and biomass in a coastal Maine Quercus-Pinus forest

Abstract. Several researchers have hypothesized that plant species richness has a unimodal relationship with biomass, while others have argued for a linear relationship. Data from various types of herbaceous communities show some support for the unimodal hypothesis, but this has not been tested extensively for forests and questions remain concerning its generality. We used linear and quadratic regression models to examine the relationship between overstory biomass and richness in a coastal Maine Quercus-Pinus forest across and within cover types using data from two plot sizes (2500-m² quadrats and 625-m² sub-quadrats). Understory data from 1-m² plots were also analysed. Richness was quadratically related to biomass at both plot sizes for all cover types combined, but the amount of variation explained by the models was very low (R²s < 0.09). Richness and biomass were not significantly related at either plot size for the mixed mesic cover type, the most common type in the forest. The best fit (R²= 0.43) was obtained with a quadratic model for the conifer cover type at the sub-quadrat level, with the quadratic model for the 1-m² data having the second highest R² (0.24). Across all six data sets, the quadratic model was the only one with a significant fit in two cases, and had considerably higher R²s (1.3–1.9 ×) in two others. The remaining two data sets could not be fit with a significant model of either type. For this forest, these results suggest little support for a linear relationship between plant species richness and biomass and variable, often weak, support for a unimodal relationship. Density, a potentially confounding variable in this type of analysis, was only weakly correlated with richness and was not found to alter the relationship between biomass and richness.     

The Historic Square Foot Dataset – Outstanding small-scale richness in Swiss grasslands around the year 1900

Grasslands host a significant share of Europe's species diversity but are among the most threatened vegetation types of the continent. Resurvey studies can help to understand patterns and drivers of changes in grassland diversity and species composition. However, most resurveys are based on local or regional data, and hardly reach back more than eight decades. Here, we publish and describe the Historic Square Foot Dataset, comprising 580 0.09-m² and 43 1-m² vegetation plots carefully sampled between 1884 and 1931, covering a wide range of grassland types across Switzerland. We provide the plots as an open-access data set with coordinates, relocation accuracy and fractional aboveground biomass per vascular plant species. We assigned EUNIS habitat types to most plots. Mean vascular plant species richness in 0.09 m² was 19.7, with a maximum of 47. This is considerably more than the present-day world record of 43 species for this plot size. Historically, species richness did not vary with elevation, differing from the unimodal relationship found today. The data set provides unique insight into how grasslands in Central Europe looked more than 100 years ago, thus offering manifold options for studies on the development of grassland biodiversity and productivity.     

Clustered animal burrows yield higher spatial heterogeneity

An understanding of the relationships between spatial heterogeneity and disturbance regime is important for establishing the mechanisms necessary to maintain biodiversity. Our objective was to examine how the configuration of disturbance by burrowing rodents (Siberian marmot) affected the spatial heterogeneity of vegetation and soil nutrient properties. We established three 2500-m² (50 m × 50 m) isolated-burrows plots and three 2500-m² clustered-burrows plots in a Mongolian grassland. Each plot was subdivided into 4-m² quadrats, and the plant species richness, percent coverage, and soil nutrient properties in the quadrats were surveyed. Spatial heterogeneity was calculated for vegetation using the mean dissimilarity of species composition among sample quadrats, and geostatistical analysis was used to calculate soil properties. Heterogeneous patches of plants such as Achnatherum splendens and higher nutrient concentrations were found only near the clustered burrows. As a result, spatial heterogeneities of vegetation and soil nutrient properties were higher in the clustered colony than those in the isolated colony. The configuration of disturbance patches affected the spatial heterogeneity at the landscape level through the spatial pattern of disturbance frequency.     

Using plant functional types to compare vegetation structure of alien-invaded and uninvaded Acacia nilotica savannas

Four plant functional types (PFTs) were used to compare the vegetation structure of an alien-invaded Acacia nilotica savanna with one of negligible invasions. Heights, canopy covers and species richness of three native PFTs (woody plants, grasses and herbs) and one alien PFT (woody plants) were measured in 14, 1-m² quadrats sampled in a stratified-random pattern in a 400-m² plot demarcated in each savanna. In the uninvaded plot, mean heights of native PFTs were stratified. In the invaded plot, the mean height of aliens extended into the native woody stratum with the lower range of native woody PFT heights reduced to the grass stratum. Discriminant analysis of canopy covers and species richness of the four PFTs revealed significant differences in composition between plots with the alien PFT being the most important variable correlated with these differences. Univariate analysis confirmed the dominance of alien woody plants in the invaded plot but also showed significant reductions in the canopy covers and species richness of native herbs and grasses compared to those in the uninvaded plot. These results suggest that PFTs can rapidly measure small-scale, spatial differences in the physiognomy, composition and species richness of A. nilotica savannas when invaded by alien woody plants.     

Long-term dynamics of aboveground fungal communities in a subalpine Norway spruce forest under elevated nitrogen input

As anthropogenic N deposition has been suspected to be the main reason for the decline of macromycetous sporocarp production in forest ecosystems, various N-fertilization experiments were started in the mid 1990s. The dynamics of ectomycorrhizal (root-inhabiting) and terricolous saprobic (litter-inhabiting) fungal communities were studied by exhaustive sporocarp inventories in a substitution Norway spruce (Picea abies) forest in two 256-m² plots sampled for periods of 1 week at 1-m² resolution between 1994 and 2007. N was added to the soil twice per year in one plot from the fourth year onwards. The effects of N input and time on aboveground fungal communities were assessed using redundancy analysis, principal response curves and non-parametric multivariate ANOVA. Results of this long-term experiment revealed that both ectomycorrhizal and saprobic fungal communities responded to an increase in soil N input. The ectomycorrhizal community reacted by a fast decrease in sporocarp production and in species richness, whereas the saprobic community was less affected. The response was highly species specific, especially for the saprobic community. The difference in species composition between control and fertilized plots was significant after 1 year of N addition for ectomycorrhizal fungi and only after 3 years for saprobic fungi. An aging effect affected sporocarp production in the whole area. For both communities, this unidirectional drift in species composition was as important as the treatment effect. This result highlights the importance of considering the respective role of treatment and year effects in long-term field experiments on fungal communities.     

PROBLEMS WITH SAMPLING DESERT TORTOISES: A SIMULATION ANALYSIS BASED ON FIELD DATA

Abstract: The desert tortoise (Gopherus agassizii) was listed as a U.S. threatened species in 1990 based largely on population declines inferred from mark-recapture surveys of 2.59-km² (1-mi²) plots. Since then, several census methods have been proposed and tested, but all methods still pose logistical or statistical difficulties. We conducted computer simulations using actual tortoise location data from 2 1-mi² plot surveys in southern California, USA, to identify strengths and weaknesses of current sampling strategies. We considered tortoise population estimates based on these plots as “truth” and then tested various sampling methods based on sampling smaller plots or transect lines passing through the mile squares. Data were analyzed using Schnabel's mark-recapture estimate and program CAPTURE. Experimental subsampling with replacement of the 1-mi² data using 1-km² and 0.25-km² plot boundaries produced data sets of smaller plot sizes, which we compared to estimates from the 1-mi² plots. We also tested distance sampling by saturating a 1-mi² site with computer simulated transect lines, once again evaluating bias in density estimates. Subsampling estimates from 1-km² plots did not differ significantly from the estimates derived at 1-mi². The 0.25-km² subsamples significantly overestimated population sizes, chiefly because too few recaptures were made. Distance sampling simulations were biased 80% of the time and had high coefficient of variation to density ratios. Furthermore, a prospective power analysis suggested limited ability to detect population declines as high as 50%. We concluded that poor performance and bias of both sampling procedures was driven by insufficient sample size, suggesting that all efforts must be directed to increasing numbers found in order to produce reliable results. Our results suggest that present methods may not be capable of accurately estimating desert tortoise populations.     

The cover of living and dead corals from airborne remote sensing

Trends in coral cover are widely used to indicate the health of coral reefs but are costly to obtain from field survey over large areas. In situ studies of reflected spectra at the coral surface show that living and recently dead colonies can be distinguished. Here, we investigate whether such spectral differences can be detected using an airborne remote sensing instrument. The Compact Airborne Spectrographic Imager (Itres Research Ltd, Canada) was flown in two configurations: 10 spectral bands with 1-m² pixels and 6 spectral bands with 0.25-m² pixels. First, we show that an instrument with 10 spectral bands possesses adequate spectral resolution to distinguish living Porites, living Pocillopora spp., partially dead Porites, recently dead Porites (total colony mortality within 6 months), old dead (>6 months) Porites, Halimeda spp., and coralline red algae when there is no water column to confuse spectra. All substrata were distinguished using fourth-order spectral derivatives around 538 nm and 562 nm. Then, at a shallow site (Tivaru) at Rangiroa Atoll, Tuamotu Archipelago (French Polynesia), we show that live and dead coral can be distinguished from the air to a depth of at least 4 m using first- and fourth-order spectral derivatives between 562–580 nm. However, partially dead and recently dead Porites colonies could not be distinguished from an airborne platform. Spectral differences among substrata are then exploited to predict the cover of reef substrata in ten 25-m² plots at nearby Motu Nuhi (max depth 8 m). The actual cover in these plots was determined in situ using quadrats with a 0.01-m² grid. Considerable disparity occurred between field and image-based measures of substrate cover within individual 25-m² quadrats. At this small scale, disparity, measured as the absolute difference in cover between field and remote-sensing methods, reached 25% in some substrata but was always less than 10% for living coral (99% of which consisted of Porites spp.). At the scale of the reef (all ten 25-m² quadrats), however, disparities in percent cover between imagery and field data were less than 10% for all substrata and extremely low for some classes (e.g. <3% for living Porites, recently dead Porites and Halimeda). The least accurately estimated substrata were sand and coralline red algae, which were overestimated by absolute values 7.9% and 6.6%, respectively. The precision of sampling was similar for field and remote-sensing methods: field methods required 19 plots to detect a 10% difference in coral cover among three reefs with a statistical power of 95%. Remote-sensing methods required 21 plots. However, it took 1 h to acquire imagery over 92,500 m² of reef, which represents 3,700 plots of 25 m² each, compared with 3 days to survey 10 such plots underwater. There were no significant differences in accuracy between 1-m² and 0.25-m² image resolutions, suggesting that the advantage of using smaller pixels is offset by reduced spectral information and an increase in noise (noise was observed to be 1.6–1.8 times greater in 0.25-m² pixels). We show that airborne remote sensing can be used to monitor coral and algal cover over large areas, providing that water is shallow and clear, and that brown fleshy macroalgae are scarce, that depth is known independently (e.g. from sonar survey).     

尺度变化对关帝山庞泉沟云杉次生林空间分布格局的影响

林分空间格局研究对认识和理解森林群落结构的生态学过程具有重要作用。适宜的样地尺度不仅可以有效降低工作和时间成本,也可以提高林分属性的精确估计。同时,抽样尺度的适宜程度对科学评价林分空间结构调整也具有重要的现实意义。以关帝山庞泉沟4 hm²云杉次生林固定监测样地为研究对象,运用样地划分法和空间点格局的K2函数,评估了林分主要树种空间格局随样地面积变化的规律。结果表明:通过重要值排序,选取云杉(青杄+白杄)、华北落叶松、桦树(白桦+红桦)+其它阔叶树(花楸+辽东栎+山杨+山楂)作为主要树种(组)。随着样地尺度的减小(从4 hm²到0.25 hm²),空间分布格局主要表现为较小尺度(≤ 4 m)的聚集分布过度为随机分布与均匀分布,以及聚集和随机分布交替出现。所有树种的次级样地与参考样地的一致性指数差异显著,云杉和华北落叶松组合1 hm²样地一致性指数最高,而桦树和其它阔叶树完整1 hm²样地一致性指数最高;此外,云杉、华北落叶松和桦树0.25 hm²样地与组合1 hm²样地空间格局一致性指数组间差异显著。研究认为1 hm²样地尺度可以作为该地区云杉次生林空间分布格局的最小尺度。研究为探索云杉次生林空间格局的变化规律及样地抽样尺度的选取方面,提供了一定的理论基础和技术依据。     

Plot sizes used for phytosociological sampling of European vegetation

Abstract. In European phytosociology, variable plot sizes are traditionally used for sampling different vegetation types. This practice may generate problems in current vegetation or habitat survey projects based on large data sets, which include relevés made by many authors at different times. In order to determine the extent of variation in plot sizes used in European phytosociology, we collected a data set of 41 174 relevés with an indication of plot size, published in six major European journals focusing on phytosociology from 1970 to 2000. As an additional data set, we took 27 365 relevés from the Czech National Phytosociological Database. From each data set, we calculated basic statistical figures for plot sizes used to sample vegetation of various phytosociological classes. The results show that in Europe the traditionally used size of vegetation plots is roughly proportional to vegetation height; however, there is a large variation in plot size, both within and among vegetation classes. The effect of variable plot sizes on vegetation analysis and classification is not sufficiently known, but use of standardized plot sizes would be desirable in future projects of vegetation or habitat survey. Based on our analysis, we suggest four plot sizes as possible standards. They are 4 m² for sampling aquatic vegetation and low‐grown herbaceous vegetation, 16 m² for most grassland, heathland and other herbaceous or low‐scrub vegetation types, 50 m² for scrub, and 200 m² for woodlands. It has been pointed out that in some situations, sampling in either small or large plots may result in assignment of relevés to different phytosociological classes or habitat types. Therefore defining vegetation and habitat types as scale‐dependent concepts is needed.     

Methodology to Improve the Efficiency of Evaluation of the Severity of Angular Leaf Spot in Common Bean

Disease severity assessment by means of a scoring scale, especially for angular leaf spot (Pseudocercospora griseola) in common bean, is hindered in experiments for assessment of progenies and/or breeding lines due to lack of uniformity of occurrence of the pathogens and segregation within progenies. The purpose of this study was to estimate the efficiency of the use of one plant per plot in assessing the severity of angular leaf spot in experiments for assessment of progenies and/or breeding lines in the common bean crop. To that end, two experimental strategies were used – one of them using one plant per plot and another using a standard size plot (SPP) (2–4‐m length rows). The experiments were conducted in the period from November 2011 to May 2012 in the municipalities of Lavras and Lambari, state of Minas Gerais, Brazil. Forty‐one lines from the breeding programme of the Universidade Federal de Lavras (UFLA) and from other research institutions were assessed, which differed in regard to their degree of susceptibility to P. griseola. The lines were assessed in regard to the severity of said disease using a five‐degree diagrammatic scale. In all the one plant per plot experiments, severity scores of angular leaf spot from the beginning of its occurrence, and later in intervals ranging from 7 to 12 days, were obtained. In the experiment with the SPP, assessment was made a few days prior to grain harvest. Estimates of the correlations between severity scores and grain yield (GY) were mostly of small magnitude. There was good coincidence between the lines classified as more resistant or more susceptible to the pathogen under the two conditions.     

Effects of plot size on the ordination of vegetation samples

Questions: Do ordination patterns differ when based on vegetation samples recorded in plots of different size? If so, how large is the effect of plot size relative to the effects of data set heterogeneity and of using presence/absence or cover‐abundance data? Can we combine plots of different size in a single ordination? Methods: Two homogeneous and two heterogeneous data sets were sampled in Czech forests and grasslands. Cover‐abundances of plant species were recorded in series of five or six nested quadrats of increasing size (forest 49‐961 m2; grassland 1‐49 m²). Separate ordinations were computed for plots of each size for each data set, using either species presences/absences or cover‐abundances recorded on an ordinal scale. Ordination patterns were compared with Procrustean analysis. Also, ordinations of data sets jointly containing plots of different size were calculated; effects of plot size were evaluated using a Monte Carlo test in constrained ordination. Results: The results were consistent between forest and grassland data sets. In homogeneous data sets, the effect of presence/absence vs. cover‐abundance was similar to, or larger than, the effect of plot size; for presence/absence data the differences between ordinations of differently sized plots were smaller than for cover‐abundance data. In heterogeneous data sets, the effect of plot size was larger than the effect of presence‐absence vs. cover‐abundance. The plots of smaller size (= 100 m2 in forests, = 4 m² in grasslands) yielded the most deviating ordination patterns. Joint ordinations of differently sized plots mostly did not yield patterns that would be artifacts of different plot size, except for plots from the homogeneous data sets that differed in size by a factor of four or higher. Conclusions: Variation in plot size does influence ordination patterns. Smaller plots tend to produce less stable ordination patterns, especially in data sets with low ß‐diversity and species cover‐abundances. Data sets containing samples from plots of different sizes can be used for ordination if they represent vegetation with large ß‐diversity. However, if data sets are homogeneous, i.e. with low ß‐diversity, the differences in plot sizes should not be very large, in order to avoid the danger of plot size differences distorting the real vegetation differentiation in ordination patterns.     

Effects of Wild Pig Disturbance on Forest Vegetation and Soils

In North America, wild pigs (Sus scrofa; feral pigs, feral swine, wild boars) are a widespread exotic species capable of creating large-scale biotic and abiotic landscape perturbations. Quantification of wild pig environmental effects has been particularly problematic in northern climates, where they occur only recently as localized populations at low densities. Between 2016 and 2017, we assessed short-term (within ~2 yrs of disturbance) effects of a low-density wild pig population on forest features in the central Lower Peninsula of Michigan, USA. We identified 16 8-ha sites using global positioning system locations from 7 radio-collared wild pigs for sampling. Within each site, we conducted fine-scale assessments at 81 plots and quantified potential disturbance by wild pigs. We defined disturbance as exposure of overturned soil, often resulting from rooting behavior by wild pigs. We quantified ground cover of plants within paired 1-m² frames at each plot, determined effects to tree regeneration using point-centered quarter sampling, and collected soil cores from each plot. We observed less percent ground cover of native herbaceous plants and lower species diversity, particularly for plants with a coefficient of conservatism ≥5, in plots disturbed by wild pigs. We did not observe an increase in colonization of exotic plants following disturbance, though the observed prevalence of exotic plants was low. Wild pigs did not select for tree species when rooting, and we did not detect any differences in regeneration of light- and heavy-seeded tree species between disturbed or undisturbed plots. Magnesium and ammonium content in soils were lower in disturbed plots, suggesting soil disturbance accelerated leaching of macronutrients, potentially altering nitrogen transformation. Our study suggested that disturbances by wild pigs, even at low densities, alters short-term native herbaceous plant diversity and soil chemistry. Thus, small-scale exclusion of wild pigs from vulnerable and rare plant communities may be warranted. © 2020 The Wildlife Society.     

High-elevation rock outcrop vegetation of the Southern Appalachian Mountains

Abstract. Species composition patterns and vegetation-environment relationships were quantified for high-elevation rock outcrops of the Southern Appalachian Mountains, an infrequent and insular habitat in a forested landscape. Outcrops occur over a wide geographic range encompassing extensive variation in both geology and climate. Geographic-scale factors interact with site-scale factors to produce variation in vegetation among outcrops. Similarly, site-scale factors interact with micro-scale factors to produce variation in vegetation within outcrops. To provide a quantitatively-based classification of outcrop vegetation we used a TWINSPAN analysis of 154 100-m² plots. We recognized nine communities that primarily correspond to different combinations of elevation, bedrock type, geography, and moisture. Within outcrops of a single bedrock type, vegetation composition of 100-m² plots was consistently correlated with elevation and solar radiation, but relationships to soil nutrients varied with bedrock type. Both site-scale (100 m²) factors (e.g. elevation, slope, aspect, and bedrock type) and plot-scale (1-m²) microsite factors (e.g. soil depth, vegetation height, soil nutrients) were strongly correlated with species composition at the 1-m² level. Environment can be used to predict composition more effectively for 100-m² plots on a single bedrock type than either across bedrock types or at a 1-m² scale. Composition-environment relationships resemble those described for outcrop systems from other regions with pronounced topographic relief more than they do those described for the nearby but flatter and lower-elevation outcrops of the Southeastern Piedmont. There is strong spatial autocorrelation in this community, perhaps owing to dispersal limitation. Consequently, a comprehensive conservation strategy must include reservation of both a range of geologic types and a range of geographic locations.     

Estimates of gene frequencies in two heterotic maize populations

Summary The present study was undertaken to obtain information on average gene frequency in two heterotic populations of maize (Zea mays L.), Mezcla Amarillo Selection (MAS) and J607. Sixty-four male plants were taken in each of the populations and each of these were crossed to a different set of eight plants, four of which belonged to the same population and four to the other population. This resulted in two groups of intra-population (within MAS and within J607) and two groups of inter-population (MAS X J607 and J607 X MAS) progenies. Each group consisted of 256 full-sib progenies on the pattern of the North Carolina Design I mating system. The male plants were selfed to produce 64 S₁ prgenies in each population. The materials were evaluated at two diverse locations, Ludhiana and Gurdaspur, for grain yield, ear length, ear girth, number of kernel rows, plant height, ear height and days to silk. An incomplete block design with two replications were used. The plot consisted of a 5 m long row. Ratios of estimated genetic components of variance and covariance were compared with corresponding theoretical ratios computed for a single locus for various gene frequencies and levels of dominance, and approximate ranges of the gene frequencies and their relative magnitude were worked out in the two populations. The average frequency of favourable genes for plant height was estimated as 0.6 in MAS and 0.8 in J607. For grain yield the average gene frequency was 0.8 to 0.9 in MAS and 0.7 to 0.8 in J607 whereas for ear height it was 0.5 to 0.7 in MAS and 0.4 to 0.6 in J607. The gene frequency in the two populations seemed to be similar for days to silk, ear length, ear girth and kernel rows.     

Strategies in identifying individuals in a segregant population of common bean and implications of genotype x environment interaction in the success of selection

The objective of this study was to compare the BLUP selection method with different selection strategies in F(2:4) and assess the efficiency of this method on the early choice of the best common bean (Phaseolus vulgaris) lines. Fifty-one F(2:4) progenies were produced from a cross between the CVIII8511 x RP-26 lines. A randomized block design was used with 20 replications and one-plant field plots. Character data on plant architecture and grain yield were obtained and then the sum of the standardized variables was estimated for simultaneous selection of both traits. Analysis was carried out by mixed models (BLUP) and the least squares method to compare different selection strategies, like mass selection, stratified mass selection and between and within progeny selection. The progenies selected by BLUP were assessed in advanced generations, always selecting the greatest and smallest sum of the standardized variables. Analyses by the least squares method and BLUP procedure ranked the progenies in the same way. The coincidence of the individuals identified by BLUP and between and within progeny selection was high and of the greatest magnitude when BLUP was compared with mass selection. Although BLUP is the best estimator of genotypic value, its efficiency in the response to long term selection is not different from any of the other methods, because it is also unable to predict the future effect of the progenies x environments interaction. It was inferred that selection success will always depend on the most accurate possible progeny assessment and using alternatives to reduce the progenies x environments interaction effect.     

Elevational species shifts in a warmer climate are overestimated when based on weather station data

Strong topographic variation interacting with low stature alpine vegetation creates a multitude of micro-habitats poorly represented by common 2 m above the ground meteorological measurements (weather station data). However, the extent to which the actual habitat temperatures in alpine landscapes deviate from meteorological data at different spatial scales has rarely been quantified. In this study, we assessed thermal surface and soil conditions across topographically rich alpine landscapes by thermal imagery and miniature data loggers from regional (2-km²) to plot (1-m²) scale. The data were used to quantify the effects of spatial sampling resolution on current micro-habitat distributions and habitat loss due to climate warming scenarios. Soil temperatures showed substantial variation among slopes (2–3 K) dependent on slope exposure, within slopes (3–4 K) due to micro-topography and within 1-m² plots (1 K) as a result of plant cover effects. A reduction of spatial sampling resolution from 1 × 1 m to 100 × 100 m leads to an underestimation of current habitat diversity by 25% and predicts a six-times higher habitat loss in a 2-K warming scenario. Our results demonstrate that weather station data are unable to reflect the complex thermal patterns of aerodynamically decoupled alpine vegetation at the investigated scales. Thus, the use of interpolated weather station data to describe alpine life conditions without considering the micro-topographically induced thermal mosaic might lead to misinterpretation and inaccurate prediction.     

Changes in the understory of Canadian southern boreal forest after fire

Abstract. We investigated changes in the composition and abundance of understory species after fire in the southern boreal forest around Lake Duparquet, Québec. Ten plots of 100 m² were sampled in each of eight sites varying in post-fire age from 26 to 230 yr, with 20 1-m² quadrats in each of these 80 plots. Variation in the understory was described by DCA ordination and interpreted as a regeneration succession series. Thickness of the organic layers, stand age and canopy composition were all correlated with vegetational change. This change was not constant throughout succession; some old sites showed an increase in the diversity and abundance of certain pioneer species. This was partly related to openings in the canopy resulting from a major outbreak of spruce budworm, which affected sites dominated by Abies balsamea. The ordinations were performed on both the 100-m² plots and the 1-m² quadrats. Heterogeneity within sites was larger at the 1-m² scale and there was a great deal of overlap in the position of the quadrats in ordination space. At the smaller scale of analysis, stand age and thickness of the organic layers were not correlated with the changes observed in the understory.