Use Of Null Models Research Articles

A Critical Evaluation of Network Approaches for Studying Species Interactions

Ecological networks of species interactions are popular and provide powerful analytical tools for understanding variation in community structure and ecosystem functioning. However, network analyses and commonly used metrics such as nestedness and connectance have also attracted criticism. One major concern is that observed patterns are misinterpreted as niche properties such as specialization, whereas they may instead merely reflect variation in sampling, abundance, and/or diversity. As a result, studies potentially draw flawed conclusions about ecological function, stability, or coextinction risks. We highlight potential biases in analyzing and interpreting species-interaction networks and review the solutions available to overcome them, among which we particularly recommend the use of null models that account for species abundances. We show why considering variation across species and networks is important for understanding species interactions and their consequences. Network analyses can advance knowledge on the principles of species interactions but only when judiciously applied.

Generating spatially realistic environmental null models with the shift‐&‐rotate approach helps evaluate false positives in species distribution modelling

Abstract To circumvent reporting spurious correlations, species distribution models often explicitly account for spatial autocorrelation, for example by including spatially structured random effects. The validity of statistical inference derived from such models has been tested by simulations using null environmental predictors that do not have any causal dependency with the response. Such null environmental predictors can be obtained by permutations of the original predictors or by simulating spatial structures resembling the original predictors. In such approaches, it is important that the permuted or simulated predictors reflect the nature of spatial variation present in the original predictors. Here we present a novel approach for generating realistic null predictors by a shift‐&‐rotate (S&R) approach: we extract environmental variables after randomly translating and rotating the sampling area within a window of defined environmental layers. In this way, the null environmental variables have fully realistic spatial variation and covariation, but no relationship to the response variable. We implement the S&R approach to three main R‐functions and demonstrate with a simulation study how they can be used to untangle causal versus non‐causal relationships within species distribution modelling. These methods allow us to quantify the predictive power attributed within the models due to non‐causal correlations generated by the realistic structure of the environmental covariates. In our case study, we identify when a model incorrectly estimates parameter values, yet still has high predictive power due to the structured nature of the predictor variables. The use of null models is imperative in ecological modelling for testing the accuracy of statistical inference in complex ecological systems and the choice of these null models is far from trivial. Here we provide R functions for generating spatially realistic null models to use in species distribution modelling as well as other spatially explicit fields such as landscape genetics.

Using null models and species traits to optimize phytoplankton monitoring: An application across oceans and ecosystems

Phytoplankton assemblages are privileged descriptors of the ecological status of marine ecosystems regularly included in routine monitoring programmes. The high spatial and temporal variability of phytoplankton and the intrinsic difficulties of species identifications, however, combine in making reiterate assessments of this component of marine biota particularly demanding. Coarse levels of taxonomic resolution (e.g., genus, family) or morpho-functional categories have been proposed to reduce identification efforts or to ease the analysis of phytoplankton assemblages for monitoring purposes, although with contrasting outcomes. A major issue is that, in the absence of control for the loss of information associated to these alternative approaches, their application may lead to poor representations of genuine spatial and/or temporal patterns of assemblages in relation to natural and anthropogenic sources of variation. We provided a new approach to reduce the efforts required to analyse phytoplankton assemblages that integrate morpho-functional classification of phytoplankton with the use of null models to estimate the consequent loss of information on species-level community patterns. Null models for information loss were built by randomly grouping the original species variables into a progressively decreasing number of groups, in order to identify the minimum number of aggregate variables needed to detect community patters as at species level. Aggregate variables were then defined as morpho-functional groups, by grouping species on the basis of a combination of morpho-functional traits, including general taxonomy, cell size, shape, elongation and complexity. We applied the approach to six case studies investigating the response of phytoplankton assemblages from marine and transitional water ecosystems under different environmental settings in areas spanning the world’s ocean, including coral atolls, mangroves, estuaries, coastal lagoons and inlets. The approach allowed obtaining parsimonious sets of morpho-functional groups, which were suitable to detect changes in phytoplankton assemblage structure as at species level in all case studies. Trait-based approaches to phytoplankton research and monitoring are crucial to shed light on processes underlying phytoplankton community assembly and dynamics in the face of global change. In this perspective, our framework incorporates cost-effectiveness, instances from traditional monitoring programmes aiming at the detection of community patterns, and the current need for a deeper understanding of functional responses of phytoplankton to environmental drivers.

Comparative analysis of four medicinal floras: Phylogenetic methods to identify cross‐cultural patterns

Societal Impact StatementPlants are living repositories of pharmacologically active chemicals and help to meet society's health care needs directly, or by providing natural products for drug development. We describe phylogenetic approaches to compare medicinal floras from different cultures in distinct regions of the world, and consider how these findings can improve knowledge of how plants have been selected for medical purposes. Greater insight into how people have selected plants for medicinal use will benefit healthcare and drug discovery strategies, and ultimately contribute to the future health and well‐being of society.Summary Four medicinal floras were compared using phylogenetic methods, to test whether there are shared patterns in medical plant use at the level of the whole medicinal floras, or for specific therapeutic applications. Checklists of the native plants and medicinal plants of Oman were compiled, and analyzed alongside existing checklists for Nepal, the Cape of South Africa and New Zealand. We reconstructed a plant phylogeny at generic level for Oman, and a new, more inclusive phylogeny to represent the genera found in all four local floras. Methods from community phylogenetics were used to identify clustering and overdispersion of the plants used. The impacts of using local or more inclusive phylogenies and different null model selections were explored. We found that Omani medicinal plant use emphasizes the same deep lineages of flowering plants as the other three medicinal floras, most strongly when comparing Omani and Nepalese medicinal plants. Drivers of this similarity might be floristic composition, opportunity for exchange of knowledge and shared beliefs in the causation of illness. Phylogenetic patterns among therapeutic applications are cross‐predictive within and between cultures, and must be interpreted with care since inappropriate use of null models can result in spurious similarity. High levels of cross‐predictivity suggest that targeting plants used for specific therapeutic applications to identify specific bioactives may have limited value. We outline the questions that might be addressed using a global phylogeny and medicinal plant checklists, suggest the best methods for future studies and propose how findings might be interpreted.

The use and limitations of null-model-based hypothesis testing

In this article I give a critical evaluation of the use and limitations of null-model-based hypothesis testing as a research strategy in the biological sciences. According to this strategy, the null model based on a randomization procedure provides an appropriate null hypothesis stating that the existence of a pattern is the result of random processes or can be expected by chance alone, and proponents of other hypotheses should first try to reject this null hypothesis in order to demonstrate their own hypotheses. Using as an example the controversy over the use of null hypotheses and null models in species co-occurrence studies, I argue that null-model-based hypothesis testing fails to work as a proper analog to traditional statistical null-hypothesis testing as used in well-controlled experimental research, and that the random process hypothesis should not be privileged as a null hypothesis. Instead, the possible use of the null model resides in its role of providing a way to challenge scientists’ commonsense judgments about how a seemingly unusual pattern could have come to be. Despite this possible use, null-model-based hypothesis testing still carries certain limitations, and it should not be regarded as an obligation for biologists who are interested in explaining patterns in nature to first conduct such a test before pursuing their own hypotheses.

Improving Species Distribution Modelling of freshwater invasive species for management applications.

Freshwater ecosystems rank among the most endangered ecosystems in the world and are under increasing threat from aquatic invasive species (AIS). Understanding the range expansion of AIS is key for mitigating their impacts. Most approaches rely on Species Distribution Models (SDMs) to predict the expansion of AIS, using mainly environmental variables, yet ignore the role of human activities in favouring the introduction and range expansion of AIS. In this study, we use five SDM algorithms (independently and in ensemble) and two accuracy measures (TSS, AUC), combined with a null modelling approach, to assess the predictive performance of the models and to quantify which predictors (environmental and anthropogenic from the native and introduced regions) best explain the distribution of nine freshwater invasive species (including fish, arthropods, molluscs, amphibians and reptiles) in a large island (Great Britain), and which species characteristics affect model performance. Our results show that the distribution of invasive species is difficult to predict by SDMs, even in cases when TSS and AUC model accuracy values are high. Our study strongly advocates the use of null models for testing SDMs performance and the inclusion of information from the native area and a variety of both human-related and environmental predictors for a more accurate modelling of the range expansion of AIS. Otherwise, models that only include climatic variables, or rely only on standard accuracy measures or a single algorithm, might result in mismanagement of AIS.

On the use of random graphs as null model of large connected networks

Addressing topological properties of real-world networks requires the use of null models, of which the most common are random Erdős-Rényi graphs with the same number of nodes and links than the network under study. Yet, these latter graphs are completely structure agnostic, and can therefore be disconnected. In this study we analyse the bias introduced by the use of such null models when evaluating the topology of networks that are connected by construction, as is the case of transportation systems. By using large sets of synthetic and real-world networks, we show that metrics like the average shortest path length are consistently overestimated, while others, like the diameter, are underestimated. We further propose an efficient algorithm for creating large connected random networks, which outperforms the naïve strategy of creating Erdős-Rényi graphs until a connected one is obtained. We finally discuss the bias introduced by the use of a Z-Score when the underlying metrics are not normally distributed.

Movement patterns of a commercially important, free-ranging marine invertebrate in the vicinity of a bait source

BackgroundCatch per unit effort is a cost-effective index of abundance and fishing effort, and an integral part of many fisheries stock assessments. Trap fisheries data are often generated using non-standardised methodology and the information to improve the accuracy of estimates is not always available due to current ecological knowledge gaps. Despite its economic importance, the European lobster Homarus gammarus has been relatively understudied compared to the closely related H. americanus. Previous studies investigating behaviour of Homarus spp. in relation to bait sources have been undertaken in aquariums or mesocosms rather than on free-ranging lobsters in the field. This study uses fine-scale acoustic telemetry data, and a null model approach to investigate free-ranging H. gammarus behaviour and movement in relation to baited commercial traps.ResultsThe distribution of lobsters {textit{n}} = 11 was largely similar in the presence and absence of traps. The time spent within 20 m of a trap ranged from 3 min to 16 h 55 min ({textit{n}} = 27), and the distance at which lobsters began approaching a trap varied considerably (5.40 m to 125 m, {textit{n}} = 22); the mean distances were larger than calculated by previous studies. A fifth of trap approaches resulted in movement against the current indicating a potential olfactory response to a bait plume. A pre-existing non-random association with a trap location may increase the time spent near the trap and reduce the minimum distance between the lobster and the trap.ConclusionsThis is the first study to assess the movement patterns of free-ranging H. gammarus in relation to a bait source. The larger approach distances in this study were likely due to the unrestricted ranging behaviour of the tagged lobsters. Aquarium and mesocosm studies provide greater experimental control, but may restrict movement and underestimate the area of bait influence. The use of null models to infer movement patterns of free-ranging lobsters has many advantages over aquarium-based studies. These include better highlighting of individual variability in behaviour, and the potential to elucidate the effects of bait plumes on catchability. Wider application of this approach can be used to improve estimates of catch and stock assessments.

Use of null models to explain crustacean zooplankton assemblages in North Patagonian lakes with presence or absence of mixotrophic ciliates (38°S, Chile)

Zooplankton assemblages in Northern Patagonian lakes are characterized by a low species richness and a marked dominance of calanoid copepods. The aim of the present study was to do a null model analysis to explain the composition of the zooplankton assemblages in two North Patagonian lakes. The first aspect to which null model analysis was applied was species co-occurrence, and there the model indicates that the species associations found are not random. The second aspect was niche sharing, and that analysis denotes that the species do not share niches. The third aspect tested was size overlap, and the model there denotes that the species have no size overlap. The results obtained indicate that the sites are relatively homogeneous, which would explain the random effect in species co-ocurrence, whereas the absence of niche sharing is due to the presence of different energetic resources at both sites investigated, which would separate the niche of each species from those of other faunistic elements. Finally, the third application of the null model analysis demonstrates that there is no competition among the species reported upon herein.

Island biology and the consequences of interspecific interactions

Island biology and the consequences of interspecific interactions

Foraging guild structure and niche characteristics of waterbirds in an epicontinental lake in Mexico

AbstractBackgroundIt was suggested that ecological patterns can be used to infer the nature of ecological processes (i.e., competition) that structure communities. Analysis of patterns of resource partitioning under the classical niche paradigm (competitive niche differentiation in exploiting limited resources) has traditionally been used to understand the structure of communities. On the contrary, neutral theory states that patterns result from neutral processes such as stochasticity and dispersal abilities. Thus, if any ecological process gives rise to a characteristic ecological pattern, the comparative study of patterns with appropriate neutral models may reveal the magnitude of that process. In this study, we analyzed patterns of resource utilization of a waterbird community in Lake Acuitlapilco, an epicontinental lake in central Mexico. In February 2011 to January 2012, we recorded foraging behaviors of waterbird species in two niche dimensions or axes: feeding technique and foraging habitat. The pattern of resource utilization was characterized by niche breath and niche overlap.ResultsResults showed that waterbird species in Lake Acuitlapilco were specialists in resource utilization patterns and therefore were vulnerable to fluctuations in resources, particularly feeding habitat. Niche overlaps were generally largest among species belonging to the same guild. To test competition as an ecological process that plays a role in the community structure, observed niche overlaps were compared with niche overlaps generated with null models of communities in the absence of competition using the RA4 randomization algorithm. Habitat and observed bidimensional overlaps were higher than those of randomly generated communities.ConclusionsOur study suggested that other processes can be used to predict resource utilization patterns instead of competition alone, as suggested by neutral theory. Future studies analyzing the mechanisms that structure waterbird communities should include the use of null models to support their conclusions.

Overlap and resource sharing in coteries of fruit-eating birds

Abstract:A range of species eating the same fruit suggests that niche overlap can occur, along with potential competition among them. To test if the overlap in the coterie of fruit-eating birds is larger than would be expected by chance, we performed a comparison with coteries generated from the use of null models. The study was carried out in an area of savanna woodland of 127 ha in Uberlândia city, Brazil. Four individuals of five zoochorous plant species were selected and 60 h of focal observation was performed on each species. We recorded species of birds that consumed fruits and the quantity of fruit removed. We used an index of Proportional Similarity (PS) between each pair of plant species, using the relative proportion of fruit taken by each bird species of each plant. The mean value of observed PS was compared with the mean PS generated from randomizations. Thirty-six bird species were recorded eating fruits in the selected plant species. The mean overlap observed (PS = 0.183) was significantly higher (P = 0.032) than the mean overlap generated by the null models (PS = 0.123). This pattern suggests that competition is not an important factor in the formation of the coteries and there is sharing of resources. The abundance of fruits offered, especially in the rainy season, and the relatively low number of frugivorous species may be factors explaining the low influence of interactions and therefore the overlap between coteries.

The use of null models and partial least squares approach path modelling (PLS-PM) for investigating risk factors influencing post-weaning mortality in indoor pig farms

Although post-weaning mortality (PWM) in pig farming is mainly due to the effect of pathogens, farm type or swine management are also directly or indirectly involved. In this work, we used null models and the partial least squares approach (PLS) to structural equation modelling, also known as PLS path modelling (PLS-PM), to explore whether farm type, swine management and pathogens, including porcine circovirus type 2, swine influenza virus, porcine reproductive and respiratory syndrome virus and Aujeszky's disease virus, directly or indirectly influenced PWM in 42 Spanish indoor pig farms. The null model analysis revealed that contact with multiple combinations of viruses could occur by chance. On the other hand, PLS-PM showed that farm characteristics do not influence virus infections, and thus neither farm type nor associated management practices shaped PWM due to pathogens. Accordingly, preventive programmes aimed at controlling PWM in intensive farming should prioritize the control of major pig pathogens.

Community mean traits as additional indicators to monitor effects of land-use intensity on grassland plant diversity

Semi-natural grasslands, biodiversity hotspots in Central-Europe, suffer from the cessation of traditional land-use. Amount and intensity of these changes challenge current monitoring frameworks typically based on classic indicators such as selected target species or diversity indices. Indicators based on plant functional traits provide an interesting extension since they reflect ecological strategies at individual and ecological processes at community levels. They typically show convergent responses to gradients of land-use intensity over scales and regions, are more directly related to environmental drivers than diversity components themselves and enable detecting directional changes in whole community dynamics. However, probably due to their labor- and cost intensive assessment in the field, they have been rarely applied as indicators so far. Here we suggest overcoming these limitations by calculating indicators with plant traits derived from online accessible databases. Aiming to provide a minimal trait set to monitor effects of land-use intensification on plant diversity we investigated relationships between 12 community mean traits, 2 diversity indices and 6 predictors of land-use intensity within grassland communities of 3 different regions in Germany (part of the German ‘Biodiversity Exploratory’ research network). By standardization of traits and diversity measures, use of null models and linear mixed models we confirmed (i) strong links between functional community composition and plant diversity, (ii) that traits are closely related to land-use intensity, and (iii) that functional indicators are equally, or even more sensitive to land-use intensity than traditional diversity indices. The deduced trait set consisted of 5 traits, i.e., specific leaf area (SLA), leaf dry matter content (LDMC), seed release height, leaf distribution, and onset of flowering. These database derived traits enable the early detection of changes in community structure indicative for future diversity loss. As an addition to current monitoring measures they allow to better link environmental drivers to processes controlling community dynamics.

Symposium summary — organizer’s perspective: Biogeography and ecology: two lenses in one telescope

news and update ISSN 1948‐6596 symposium summary — organizer’s perspective Biogeography and ecology: two lenses in one telescope A symposium at the 5th International Biogeography Society Conference – Heraklion, Greece, 7– 11 January 2011 Biogeography and ecology had common roots in natural history but have been largely separate dis‐ ciplines for decades, as evidenced by their distinct journals and professional societies. A dichotomous key to the disciplines might separate biogeography and modern ecology as explicitly historical and ahistorical, respectively (McIntosh 1985, Lomolino et al. 2010). In addition, experimental ecology has necessarily focused on local‐scale processes and patterns that operate over relatively short time intervals, whereas biogeography has typically fo‐ cused on processes and patterns that operate over long time intervals and larger spatial scales. Thus, biogeography and ecology may be considered at first glance to be very different views of nature. In spite of their divergent histories, biogeog‐ raphy and ecology are increasingly converging on intermediate spatial and temporal scales, as evi‐ denced by theoretical and empirical research on metapopulations, metacommunities, regional communities, and evolutionary ecology (e.g. Rick‐ lefs and Schluter 1993, Hanski and Gaggioti 2004, Holyoak et al. 2005, Emerson and Gillespie 2008, Ricklefs 2007, 2008, Cavender‐Bares et al. 2009). This convergence has resulted from the matura‐ tion and extension of each discipline and from in‐ creasing attention to global climate change and its effects at regional scales. As the temporal and spa‐ tial scales of biogeographical and ecological con‐ cepts increasingly overlap, the two disciplines risk developing separate conceptual imagery, jargon, and expectations for the same natural phenom‐ ena. If biogeography and ecology are to inform the conservation and management of nature amidst the simultaneous pressures of 7‐plus billion people and global climate change, these disciplines must speak the same language to talk about common concepts. To extend the visual metaphor of the Symposium title, the two lenses of biogeography and ecology need to be aligned to form one tele‐ scope through which we receive clear and accurate conceptual images of the natural world and human impacts. As part of the 5 th International Biogeography Society meeting in Crete (7–11 January 2011), a symposium was convened entitled “Biogeography and ecology: Two lenses in one telescope”. Speak‐ ers were organized in pairs: one ecologist and one biogeographer were each assigned to a topic and asked to converse with each other in advance of the Symposium. After an introduction by David Jenkins outlining the background of the Sympo‐ sium, four topics relevant to both disciplines were addressed by the eight speakers; niche, compara‐ tive ecology/macro‐ecology, community assembly, and diversity. Jonathan Chase addressed core issues with a summary of ecological niche concepts and sug‐ gested that divergent ecological and biogeographic views of niche might be regarded as ‘MacArthur's Paradox’ (Robert MacArthur contributed mightily to both ecological niche and island biogeography theory). Dr. Chase also explained more recent ex‐ tensions of ecological niche research, including neutral theory and the use of null models to distin‐ guish niche‐based and stochastic processes driving community structure. John Wiens then considered the niche concept at biogeographic scales (e.g. species ranges), and noted that abiotic tolerances have been prominent in biogeography while biotic interactions remain relatively unstudied as drivers of large‐scale distribution. Dr. Wiens also argued that biogeography should incorporate species' ecology and niche into explanations for species distributions. Phylogeny is explicit in much of biogeogra‐ phy, but not often in ecology. However, Robert Poulin emphasized the benefit of a phylogenetic context and consideration of ecological traits (e.g. niche breadth) to modern comparative ecology. Dr. Poulin’s research on parasites highlighted the intersection between ecology and biogeography when he described the interaction of host specific‐ ity, life cycle, and host mobility as factors affecting frontiers of biogeography 3.1, 2011 — © 2011 the authors; journal compilation © 2011 The International Biogeography Society

Temporal turnover in the composition of tropical tree communities: functional determinism and phylogenetic stochasticity

The degree to which turnover in biological communities is structured by deterministic or stochastic factors and the identities of influential deterministic factors are fundamental, yet unresolved, questions in ecology. Answers to these questions are particularly important for projecting the fate of forests with diverse disturbance histories worldwide. To uncover the processes governing turnover we use species-level molecular phylogenies and functional trait data sets for two long-term tropical forest plots with contrasting disturbance histories: one forest is older-growth, and one was recently disturbed. Having both phylogenetic and functional information further allows us to parse out the deterministic influences of different ecological filters. With the use of null models we find that compositional turnover was random with respect to phylogeny on average, but highly nonrandom with respect to measured functional traits. Furthermore, as predicted by a deterministic assembly process, the older-growth and disturbed forests were characterized by less than and greater than expected functional turnover, respectively. These results suggest that the abiotic environment, which changes due to succession in the disturbed forest, strongly governs the temporal dynamics of disturbed and undisturbed tropical forests. Predicting future changes in the composition of disturbed and undisturbed forests may therefore be tractable when using a functional-trait-based approach.

Significance testing in ecological null models

In the past decade, the use of null models has become widespread in the testing of ecological theory. Along with increasing usage, null models have also become more complex particularly with regard to tests of significance. Despite the complexity, there are essentially only two distinct ways in which tests of significance are conducted. Direct tests derive a p value directly from the null distribution of a test statistic, as the proportion of the distribution more extreme than the observed value of the test statistic. Indirect tests compare an observed value of a parameter to a null distribution by conducting an additional analysis such as a chi-square test, Kolmogorov–Smirnov test, or regression, although in many cases, this additional step is not necessary. Many kinds of indirect tests require that the null distribution is normal whereas direct tests carry no assumptions about the form of the null distribution. Therefore, when assumptions are violated, indirect tests may have higher type I and II error rates than their counterpart direct tests. A review of 108 null model papers revealed that direct tests were used in 56.5% of studies and indirect tests used in 45.5%. A few studies used both types of test. In general, the randomization algorithms used in most null models should produce normal null distributions, but this could not be confirmed because most studies did not present any description of the null distribution. Researchers should be aware of the differences between direct and indirect tests so as to better use, communicate, and evaluate null models. In many cases, direct tests should be favored for their simplicity and parsimony.

Use of Null Models to Explain Crustacean Zooplankton Assemblages in Northern Patagonian Lakes (Chile) with and Without Mixotrophic Ciliates

AbstractThe zooplankton assemblages in deep, mostly oligotrophic northern Patagonian lakes are characterized by a low species number and a marked dominance of calanoid copepods, as well as often by the presence of large mixotrophic ciliates (Stentor). In the present study, data collected in field work on four northern Patagonian lakes were analysed using co-occurrence of null models, with the aim to determine potential regulating factors for the observed crustacean and mixotrophic ciliate assemblages, using a presence-absence matrix. The null model uses species co-occurrence, and the basis of this model is that the species associations observed are random. The results revealed the absence of regulating factors and indicate that the sites are relatively homogeneous, with low species numbers, and similar plankton assemblages at all study sites. This finding coincides with similar descriptions for zooplankton assemblages in other Chilean Patagonian lakes.

Calculations on the back of a climate envelope: Addressing the geography of species distributions

Climate envelope modeling is an approach that identifies association between species distribution and climate, an association that often is strong at broader spatial scales. Beale et al. (1) discuss limitations of climate envelope modeling and propose use of null models to test relationships between species distributions and climate. Their null models maintain the prevalence of observations and spatial structure of species data while altering the geographic location of the distribution. Other qualities of geographic distributions and variability demonstrate a need for improved understanding and management of geographic concepts in climate envelope modeling.

The use of null models to explain crustacean zooplankton associations in shallow water bodies of the Magellan region, Chile

Southern Patagonia is characterized by the presence of numerous shallow ponds with variable trophic and conductivity conditions, and a relatively high species richness of Crustacea. In the present study, published information and data collected in field work on shallow ponds in the Magellan region was reviewed and analysed using co-occurrence of null models, with the aim to determine potential random factors as regulators on crustacean zooplankton assemblages, using a presence-absence matrix. The results of C-score analysis revealed the existence of non-random effects mainly in data collected in 1989-1990 for Torres del Paine National Park, and in data on coastal shallow ponds close to Punta Arenas, collected in October 2006. A different situation is reported for shallow ponds located in other zones of the Magellan region, including also some in the Torres del Paine National Park collected in October 2001, and for shallow ponds close to Porvenir on Tierra del Fuego Island, collected in April 2007. The existence of non-random effects was probably due to markedly different zooplankton assemblages, assumed to be caused mainly by the conductivity gradient and trophic level. Random effects can probably be explained by the condition that a few species occur practically at all localities studied, in many of which species richness is very low. This obviously means the variability in species composition is very limited, yielding similar zooplankton assemblages in the many ponds sampled. Ecological and biogeographical topics are also discussed. La zona sur de la Patagonia se caracteriza por la presencia de numerosas lagunas poco profundas, con diferentes condiciones troficas y de conductividad y relativamente alta riqueza de especies. En el presente estudio se considero informacion publicada y datos colectados en trabajos de campo en la region de Magallanes, esta informacion fue analizada sobre la base de modelos nulos de co-ocurrencia, con el objetivo de determinar potenciales efectos aleatorios en la composicion de los ensambles de crustaceos zooplanctonicos, usando una matriz de presencia y ausencia. Los resultados del factor C-score, revelaron la no existencia de efectos aleatorios principalmente en datos colectados para el Parque Nacional Torres del Paine en 1989-1990, y lagunas costeras cercanas a Punta Arenas en Octubre de 2006. Una situacion diferente se reporto en lagunas superficiales en diferentes lagunas de la region de Magallanes, incluido el Parque Nacional Torres del Paine colectados en Octubre de 2001, y lagunas superficiales cercanas a Porvenir en la Isla de Tierra del Fuego colectadas en Abril de 2007. La ausencia de efectos aleatorios se debio probablemente al gradiente de conductividad y de condiciones troficas. Mientras que la existencia de efectos aleatorios, se debio probablemente a pocas especies que se encontraron en practicamente todos las localidades estudiadas, muchas de las cuales tuvieron bajo numero de especies, esto obviamente significa que la variabilidad en composicion de especies es limitada, obteniendose similares patrones en las asociaciones de especies zooplanctonicas en los sitios estudiados. Se discutieron aspectos ecologicos y biogeograficos en el presente estudio.