Climate change induced uncertainties in future spatial patterns of conservation-related outcomes make it difficult to implement standard conservation planning paradigms. A recent study translates Markowitz's risk diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However this method is information intensive and requires a large number of climate scenarios for carrying out fine-resolution conservation planning. We develop an iterative portfolio analysis technique that enables conservation agents to allocate scarce conservation resources across a desired level of sub-regions in a planning landscape in the absence of sufficient number of climate scenarios. We use a case study of the Prairie Pothole Region to show that lack of sufficient future climate information prevents a conservation agent from attaining the most efficient risk-return conservation outcomes. Our study highlights that the difference in expected conservation returns can be as large as 30% between conservation planning with limited climate change information and full climate change information, even when using the most efficient iterative approach. However, our iterative approach enables a decision maker to do finer-resolution portfolio allocation with limited available climate change forecasts in a manner that obtains the best possible risk-return combinations. We illustrate that a conservation agent can reduce the expected loss in conservation outcomes owing to limited climate change information by 17% by using our recommended iterative approach compared to other approaches. This article is protected by copyright. All rights reserved.