Competition between co-dominant plants of the Serengeti plains depends on competitor identity,water, and urine

Kyllinga nervosa (Steud.) and Sporobolus kentrophyllus (K. Schum.) are co-dominant plants of the Serengeti short-grass plains, Tanzania. The plains are characterized by seasonal and sporadic rainfall and currently support in excess of 1.5 million migratory ungulates. The interactive effect of simulated bovine urine and water availability were tested on the competitive interactions of these species in the laboratory. Sporobolus kentrophyllus was a superior competitor to K. nervosa over the tested treatment levels with respect to growth and reproductive effort. Sporobolus kentrophyllus exhibited rapid growth in response to urine addition, leading to a significant species × urine interaction while reduced growth by K. nervosa in response to low water availability explained the significant species × water interaction and is likely explained by K. nervosa's shallow root system. Kyllinga nervosa, however, appears to be more tolerant of low nitrogen conditions based on its similar growth with and without the urine treatment. The effect of intraspecific competition on total biomass was similar for S. kentrophyllus and K. nervosa. Competition resulted in increased size differences (asymmetry) for K. nervosa and for the interspecific competition treatments compared to the size differences observed for plants grown individually (in absence of competition).Total reproductive biomass was reduced most by competition with S. kentrophyllus, irrespective of target species. The water treatment did not influence reproduction while the urine treatment significantly increased reproductive biomass and interacted with target species, competitor species, and yielded a three-way urine × target × competitor species interaction.Results suggest that codominance of these two species in the Serengeti is regulated by water availability, nitrogen input from grazers, and local neighbor identity.     

Estimation of the genome size of blue-green algae from DNA renaturation rates

The molecular weight of the genomes of the blue-green algaeAnacystis nidulans andAnabaena cylindrica have been estimated as 2.27×10⁹ and 2.47×10⁹ daltons respectively from the renaturation kinetics of DNA. Thus the genomes of these organisms are similar in size to that ofEscherichia coli K-12, (2.40×10⁹ daltons) measured by the same technique. No evidence was obtained of repeated sequences in the DNA of the two blue-green algae.     

Unexpectedly low UV-sensitivity in a bird,the budgerigar

Photoreceptor adaptation ensures appropriate visual responses during changing light conditions and contributes to colour constancy. We used behavioural tests to compare UV-sensitivity of budgerigars after adaptation to UV-rich and UV-poor backgrounds. In the latter case, we found lower UV-sensitivity than expected, which could be the result of photon-shot noise corrupting cone signal robustness or nonlinear background adaptation. We suggest that nonlinear adaptation may be necessary for allowing cones to discriminate UV-rich signals, such as bird plumage colours, against UV-poor natural backgrounds.     

Ecological and genetic data indicate recovery of the endangered coral Acropora palmata in Los Roques, Southern Caribbean

The rapid decline of Acropora cervicornis and Acropora palmata has often been linked with coral reef deterioration in the Caribbean; yet, it remains controversial whether these species are currently recovering or still declining. In this study, the status of ten populations of A. palmata in Los Roques National Park (LRNP), Venezuela is presented. Six of these populations showed signs of recovery. Ten 80 m² belt-transects were surveyed at each of the ten reef sites. Within belt-transects, each colony was measured (maximum diameter and height) and its status (healthy, diseased or injured) was recorded. Populations in recovery were defined by a dominance of small to medium-sized colonies in densities >1 colony per 10 m², together with 75% undamaged colonies, a low prevalence of diseases (<10%), and a low density of predators (0.25 snails per colony). Based on allozyme analysis of seven polymorphic loci in four populations (N = 30), a moderate to high-genetic connectivity among these populations (F _ST = 0.048) was found with a predominance of sexual over asexual reproduction (N* : N = 1; N _go : N = 0.93–1). Both ecological and molecular data support a good prognosis for the recovery of this species in Los Roques.     

Development of a new protein labeling system to map subunits and domains of macromolecular complexes for electron microscopy

Several gene fusion technologies have been successfully applied to label particular subunits or domains within macromolecular complexes to enable positional mapping of electron microscopy (EM) density maps, but exogenous fusion of a protein domain into the target polypeptide can cause unwanted structural and functional outcomes. Fab fragments from antibodies can be used as labeling reagents during EM visualization without gene manipulation of the target protein, but this method requires a panel of high-affinity antibodies that recognize a wide variety of epitopes. Linear peptide tags and their anti-tag antibodies can be used but they have a limited mapping ability as their placement is usually limited to the terminal regions of a protein. The PA dodecapeptide epitope tag (GVAMPGAEDDVV), forms a tight β-turn in the antigen binding pocket of its antibody (NZ-1). This capability allows for insertion of the PA tag into various surface-exposed loops within a multi-domain cell adhesion receptor, α_IIbβ₃ integrin. We confirmed that the purified PA-tagged integrin ectodomain fragments can form a stable complex with NZ-1 Fab. Negative stain EM of the various integrin-NZ-1 complexes revealed that a majority of the particles exhibited a clear density corresponding to the NZ-1 Fab; and the positions of the bound Fab were in good agreement with the predicted location of the inserted PA tag. The high-affinity and insertion-compatibility of the PA tag system allowed us to develop a new EM labeling methodology applicable to proteins for which good antibodies are not available.     

Modeling aggregation and growth processes in an algal population model: analysis and computations

 Aggregation, the formation of large particles through multiple collision of smaller ones is a highly visible phenomena in oceanic waters which can control material flux to the deep sea. Oceanic aggregates more than 1 cm in diameter have been observed and are frequently described to consist of phytoplankton cells as well as other organic matter such as fecel pellets and mucus nets from pteropods. Division of live phytoplankton cells within an aggregate can also increase the size of aggregate (assuming some daughter cells stay in the aggregate) and hence could be a significant factor in speeding up the formation process of larger aggregate. Due to the difficulty of modeling cell division within aggregates, few efforts have been made in this direction. In this paper, we propose a size structured approach that includes growth of aggregate size due to both cell division and aggregation. We first examine some basic mathematical issues associated with the development of a numerical simulation of the resulting algal aggregation model. The numerical algorithm is then used to examine the basic model behavior and present a comparison between aggregate distribution with and without division in aggregates. Results indicate that the inclusion of a growth term in aggregates, due to cell division, results in higher densities of larger aggregates; hence it has the impact to speed clearance of organic matter from the surface layer of the ocean. Received 1 July 1994; received in revised form 23 February 1996     

Pollination Biology of the Exotic Rattleweed Crotalaria retusa L. (Fabaceae) in NE Brazil1

The rattleweed Crotalaria retusa was introduced in Brazil from Africa, and combines a series of characters that have ensured its establishment in NE Brazil. We focused on its reproductive biology and pollinator behavior to explain its reproductive success. We performed manual pollination and germination experiments, and monitored the behavior of C. retusa's main pollinators in monospecific plots, and in mixed plots where C. retusa occurred together with two congeners, Crotalaria pallida and Crotalaria lanceolata. Crotalaria retusa is self‐compatible and capable of automatic selfing. Inbreeding depression was expressed at the level of percent seed germination, but not seed set. Few insects visited the inflorescences. Legitimate pollinators were two large carpenter bees, Xylocopa frontalis and Xylocopa grisescens which, together, accounted for more than 90 percent of the visits. The former foraged on C. retusa exclusively and has low pollen spread potential. The latter flew longer distances between plants and visited fewer flowers per inflorescence, potentially increasing the extent of pollen carryover, but at the risk of increasing heterospecific pollen transfer, because it visits other Crotalaria species during the same foraging bout. The different foraging strategies, allied to morphological disadvantages represented by pollen overlap on X. grisescens' body, may partially explain the much lower seed germination observed in C. pallida and C. lanceolata. These results are consistent with the hypothesis that a reduction in flower constancy may significantly depress viable seed set by increasing the chances of self‐pollination.     

Statistical analysis of unlabeled point sets: comparing molecules in chemoinformatics

We consider Bayesian methodology for comparing two or more unlabeled point sets. Application of the technique to a set of steroid molecules illustrates its potential utility involving the comparison of molecules in chemoinformatics and bioinformatics. We initially match a pair of molecules, where one molecule is regarded as random and the other fixed. A type of mixture model is proposed for the point set coordinates, and the parameters of the distribution are a labeling matrix (indicating which pairs of points match) and a concentration parameter. An important property of the likelihood is that it is invariant under rotations and translations of the data. Bayesian inference for the parameters is carried out using Markov chain Monte Carlo simulation, and it is demonstrated that the procedure works well on the steroid data. The posterior distribution is difficult to simulate from, due to multiple local modes, and we also use additional data (partial charges on atoms) to help with this task. An approximation is considered for speeding up the simulation algorithm, and the approximating fast algorithm leads to essentially identical inference to that under the exact method for our data. Extensions to multiple molecule alignment are also introduced, and an algorithm is described which also works well on the steroid data set. After all the steroid molecules have been matched, exploratory data analysis is carried out to examine which molecules are similar. Also, further Bayesian inference for the multiple alignment problem is considered.